/**
|
* @license
|
* Copyright 2022 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
(function (global, factory) {
|
typeof exports === 'object' && typeof module !== 'undefined' ? factory(exports, require('@tensorflow/tfjs-core'), require('path'), require('fs'), require('worker_threads'), require('perf_hooks'), require('os')) :
|
typeof define === 'function' && define.amd ? define(['exports', '@tensorflow/tfjs-core', 'path', 'fs', 'worker_threads', 'perf_hooks', 'os'], factory) :
|
(global = global || self, factory((global.tf = global.tf || {}, global.tf.wasm = global.tf.wasm || {}), global.tf, global.path, global.fs, global.worker_threads, global.perf_hooks, global.os));
|
}(this, (function (exports, tfjsCore, path, fs, worker_threads, perf_hooks, os) { 'use strict';
|
|
path = path && Object.prototype.hasOwnProperty.call(path, 'default') ? path['default'] : path;
|
fs = fs && Object.prototype.hasOwnProperty.call(fs, 'default') ? fs['default'] : fs;
|
worker_threads = worker_threads && Object.prototype.hasOwnProperty.call(worker_threads, 'default') ? worker_threads['default'] : worker_threads;
|
perf_hooks = perf_hooks && Object.prototype.hasOwnProperty.call(perf_hooks, 'default') ? perf_hooks['default'] : perf_hooks;
|
os = os && Object.prototype.hasOwnProperty.call(os, 'default') ? os['default'] : os;
|
|
/**
|
* @license
|
* Copyright 2019 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
// This enum must align with the enum defined in cc/backend.h.
|
var CppDType;
|
(function (CppDType) {
|
CppDType[CppDType["float32"] = 0] = "float32";
|
CppDType[CppDType["int32"] = 1] = "int32";
|
CppDType[CppDType["bool"] = 2] = "bool";
|
CppDType[CppDType["string"] = 3] = "string";
|
CppDType[CppDType["complex64"] = 4] = "complex64";
|
})(CppDType || (CppDType = {}));
|
// Must match enum in cc/fusable_activations.h.
|
var FusableActivation;
|
(function (FusableActivation) {
|
FusableActivation[FusableActivation["linear"] = 0] = "linear";
|
FusableActivation[FusableActivation["relu"] = 1] = "relu";
|
FusableActivation[FusableActivation["relu6"] = 2] = "relu6";
|
FusableActivation[FusableActivation["prelu"] = 3] = "prelu";
|
FusableActivation[FusableActivation["leakyrelu"] = 4] = "leakyrelu";
|
FusableActivation[FusableActivation["sigmoid"] = 5] = "sigmoid";
|
FusableActivation[FusableActivation["elu"] = 6] = "elu";
|
})(FusableActivation || (FusableActivation = {}));
|
|
/**
|
* @license
|
* Copyright 2019 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var wasmFusedMatMul;
|
function setup(backend) {
|
wasmFusedMatMul = backend.wasm.cwrap(tfjsCore._FusedMatMul, null /* void */, [
|
'number',
|
'array',
|
'number',
|
'number',
|
'array',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number' // out_id
|
]);
|
}
|
function fusedBatchMatMul(args) {
|
var inputs = args.inputs, backend = args.backend, attrs = args.attrs;
|
var a = inputs.a, b = inputs.b, bias = inputs.bias, preluActivationWeights = inputs.preluActivationWeights;
|
if (a.dtype !== 'float32' || b.dtype !== 'float32') {
|
throw new Error("_FusedMatMul for non non-float32 tensors not yet supported.");
|
}
|
var transposeA = attrs.transposeA, transposeB = attrs.transposeB, activation = attrs.activation, leakyreluAlpha = attrs.leakyreluAlpha;
|
var aId = backend.dataIdMap.get(a.dataId).id;
|
var bId = backend.dataIdMap.get(b.dataId).id;
|
var biasId = 0;
|
if (bias != null) {
|
var biasData = backend.dataIdMap.get(bias.dataId);
|
if (biasData.shape.length !== 1) {
|
throw new Error("_FusedMatMul only supports rank-1 bias but got " +
|
("rank " + biasData.shape.length + "."));
|
}
|
biasId = biasData.id;
|
}
|
var preluActivationWeightsId = preluActivationWeights == null ?
|
0 :
|
backend.dataIdMap.get(preluActivationWeights.dataId).id;
|
var fusedActivation = FusableActivation[activation];
|
if (fusedActivation == null) {
|
throw new Error(activation + " activation not yet supported for FusedConv2D " +
|
"in the wasm backend.");
|
}
|
var leftDim = transposeA ? a.shape[2] : a.shape[1];
|
var rightDim = transposeB ? b.shape[1] : b.shape[2];
|
var batchDims = tfjsCore.broadcast_util.assertAndGetBroadcastShape(a.shape.slice(0, -2), b.shape.slice(0, -2));
|
var out = backend.makeOutput(batchDims.concat([leftDim, rightDim]), a.dtype);
|
var outId = backend.dataIdMap.get(out.dataId).id;
|
var aShapeBytes = new Uint8Array(new Int32Array(a.shape).buffer);
|
var bShapeBytes = new Uint8Array(new Int32Array(b.shape).buffer);
|
wasmFusedMatMul(aId, aShapeBytes, a.shape.length, bId, bShapeBytes, b.shape.length, transposeA, transposeB, fusedActivation, biasId, preluActivationWeightsId, leakyreluAlpha || 0, outId);
|
return out;
|
}
|
var _fusedMatMulConfig = {
|
kernelName: tfjsCore._FusedMatMul,
|
backendName: 'wasm',
|
setupFunc: setup,
|
kernelFunc: fusedBatchMatMul
|
};
|
|
/**
|
* @license
|
* Copyright 2019 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
function createUnaryKernelConfig(kernelName, outType) {
|
var wasmFunc;
|
function setupFunc(backend) {
|
wasmFunc = backend.wasm.cwrap(kernelName, null /* void */, [
|
'number',
|
'number',
|
'number',
|
]);
|
}
|
function kernelFunc(args) {
|
var backend = args.backend, x = args.inputs.x;
|
var xId = backend.dataIdMap.get(x.dataId).id;
|
var out = backend.makeOutput(x.shape, outType || x.dtype);
|
var outId = backend.dataIdMap.get(out.dataId).id;
|
// Short-circuit zero-sized tensors.
|
if (tfjsCore.util.sizeFromShape(out.shape) === 0) {
|
return out;
|
}
|
wasmFunc(xId, CppDType[x.dtype], outId);
|
return out;
|
}
|
return { kernelName: kernelName, backendName: 'wasm', setupFunc: setupFunc, kernelFunc: kernelFunc };
|
}
|
|
/**
|
* @license
|
* Copyright 2019 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var absConfig = createUnaryKernelConfig(tfjsCore.Abs);
|
|
/**
|
* @license
|
* Copyright 2019 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
function createBinaryKernelConfig(kernelName, supportsFullBroadcast, dtype) {
|
var wasmFunc;
|
function setupFunc(backend) {
|
wasmFunc = backend.wasm.cwrap(kernelName, null /* void */, [
|
'number',
|
'array',
|
'number',
|
'number',
|
'array',
|
'number',
|
'number',
|
'number' // out_id
|
]);
|
}
|
function kernelFunc(args) {
|
var backend = args.backend, inputs = args.inputs;
|
var a = inputs.a, b = inputs.b;
|
var aId = backend.dataIdMap.get(a.dataId).id;
|
var bId = backend.dataIdMap.get(b.dataId).id;
|
var outputType = dtype != null ? dtype : a.dtype;
|
var newShape = tfjsCore.backend_util.assertAndGetBroadcastShape(a.shape, b.shape);
|
var out = backend.makeOutput(newShape, outputType);
|
// Short-circuit zero-sized tensors.
|
if (tfjsCore.util.sizeFromShape(newShape) === 0) {
|
return out;
|
}
|
var aShapeBytes = new Uint8Array(new Int32Array(a.shape).buffer);
|
var bShapeBytes = new Uint8Array(new Int32Array(b.shape).buffer);
|
var outId = backend.dataIdMap.get(out.dataId).id;
|
var kernelFunc = function () { return wasmFunc(aId, aShapeBytes, a.shape.length, bId, bShapeBytes, b.shape.length, CppDType[a.dtype], outId); };
|
kernelFunc();
|
return out;
|
}
|
return { kernelName: kernelName, backendName: 'wasm', setupFunc: setupFunc, kernelFunc: kernelFunc };
|
}
|
|
/**
|
* @license
|
* Copyright 2019 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var addConfig = createBinaryKernelConfig(tfjsCore.Add);
|
|
/**
|
* @license
|
* Copyright 2019 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var wasmFunc;
|
function setupFunc(backend) {
|
wasmFunc = backend.wasm.cwrap(tfjsCore.AddN, null /* void */, [
|
'array',
|
'number',
|
'number',
|
'number',
|
]);
|
}
|
function addn(args) {
|
var inputs = args.inputs, backend = args.backend;
|
var out = backend.makeOutput(inputs[0].shape, inputs[0].dtype);
|
// Short-circuit zero-sized tensors.
|
if (tfjsCore.util.sizeFromShape(out.shape) === 0) {
|
return out;
|
}
|
var inputIds = inputs.map(function (x) { return backend.dataIdMap.get(x.dataId).id; });
|
var inputIdsBytes = new Uint8Array(new Int32Array(inputIds).buffer);
|
var outId = backend.dataIdMap.get(out.dataId).id;
|
wasmFunc(inputIdsBytes, inputIds.length, CppDType[out.dtype], outId);
|
return out;
|
}
|
var addNConfig = {
|
kernelName: tfjsCore.AddN,
|
backendName: 'wasm',
|
setupFunc: setupFunc,
|
kernelFunc: addn,
|
};
|
|
/**
|
* @license
|
* Copyright 2020 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
function identity(args) {
|
var x = args.inputs.x, backend = args.backend;
|
var out = backend.makeOutput(x.shape, x.dtype);
|
var inVals = backend.typedArrayFromHeap(x);
|
var outVals = backend.typedArrayFromHeap(out);
|
outVals.set(inVals);
|
return out;
|
}
|
var identityConfig = {
|
kernelName: tfjsCore.Identity,
|
backendName: 'wasm',
|
kernelFunc: identity,
|
};
|
|
/**
|
* @license
|
* Copyright 2019 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var wasmTranspose;
|
function setup$1(backend) {
|
wasmTranspose = backend.wasm.cwrap(tfjsCore.Transpose, null /* void */, [
|
'number',
|
'array',
|
'number',
|
'number',
|
'number',
|
'array',
|
'number',
|
]);
|
}
|
function transpose(args) {
|
var inputs = args.inputs, backend = args.backend, attrs = args.attrs;
|
// Reduce any dimensions with size one. Lower-rank transpose kernel performs
|
// better due to simpler memory access pattern.
|
var _a = removeOneSizeDims(inputs.x.shape, attrs.perm), reducedShape = _a[0], perm = _a[1];
|
var permIsNoOp = true;
|
for (var i = 0; i < perm.length; i++) {
|
if (perm[i] !== i) {
|
permIsNoOp = false;
|
}
|
}
|
var outShape = computeOutShape(inputs.x.shape, attrs.perm);
|
var x = {
|
dataId: inputs.x.dataId,
|
shape: reducedShape,
|
dtype: inputs.x.dtype
|
};
|
if (permIsNoOp) {
|
var cloned = identity({ inputs: inputs, backend: backend });
|
cloned.shape = outShape;
|
return cloned;
|
}
|
var out = backend.makeOutput(outShape, x.dtype);
|
var xId = backend.dataIdMap.get(x.dataId).id;
|
var outId = backend.dataIdMap.get(out.dataId).id;
|
var permBytes = new Uint8Array(new Int32Array(perm).buffer);
|
var xShapeBytes = new Uint8Array(new Int32Array(x.shape).buffer);
|
wasmTranspose(xId, xShapeBytes, x.shape.length, CppDType[x.dtype], outId, permBytes, perm.length);
|
return out;
|
}
|
function computeOutShape(inShape, perm) {
|
var outShape = new Array(inShape.length);
|
for (var i = 0; i < outShape.length; i++) {
|
outShape[i] = inShape[perm[i]];
|
}
|
return outShape;
|
}
|
function removeOneSizeDims(shape, perm) {
|
var newShape = [];
|
var newPerm = [];
|
for (var i = 0; i < shape.length; ++i) {
|
if (shape[i] !== 1) {
|
newShape.push(shape[i]);
|
}
|
if (shape[perm[i]] !== 1) {
|
newPerm.push(perm[i]);
|
}
|
}
|
for (var i = 0; i < newPerm.length; ++i) {
|
var minValIdx = -1;
|
for (var j = 0; j < newPerm.length; ++j) {
|
if (newPerm[j] >= i &&
|
(minValIdx === -1 || newPerm[minValIdx] > newPerm[j])) {
|
minValIdx = j;
|
}
|
}
|
newPerm[minValIdx] = i;
|
}
|
return [newShape, newPerm];
|
}
|
var transposeConfig = {
|
kernelName: tfjsCore.Transpose,
|
backendName: 'wasm',
|
kernelFunc: transpose,
|
setupFunc: setup$1,
|
};
|
|
/**
|
* @license
|
* Copyright 2020 Google Inc. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
/**
|
* Compute permutation axes and do a transpose if necessary.
|
*
|
* Used by reduction ops.
|
* @param x input TensorInfo
|
* @param axis reduction axes
|
* @param backend wasm backend instance
|
*/
|
function permuteAxesAndTranspose(x, axis, backend) {
|
var xShape = x.shape;
|
var xRank = x.shape.length;
|
var originalAxes = tfjsCore.util.parseAxisParam(axis, xShape);
|
var axes = originalAxes;
|
var permutedAxes = tfjsCore.backend_util.getAxesPermutation(axes, xRank);
|
var xTransposed = null;
|
var inputWasTransposed = false;
|
if (permutedAxes != null) {
|
var newShape = new Array(xRank);
|
for (var i = 0; i < newShape.length; i++) {
|
newShape[i] = xShape[permutedAxes[i]];
|
}
|
axes = tfjsCore.backend_util.getInnerMostAxes(axes.length, xRank);
|
xTransposed =
|
transpose({ inputs: { x: x }, attrs: { perm: permutedAxes }, backend: backend });
|
var xId = backend.dataIdMap.get(x.dataId).id;
|
var transposedId = backend.dataIdMap.get(xTransposed.dataId).id;
|
if (transposedId !== xId) {
|
inputWasTransposed = true;
|
}
|
}
|
return { transposed: xTransposed, originalAxes: originalAxes, axes: axes, inputWasTransposed: inputWasTransposed };
|
}
|
|
/**
|
* @license
|
* Copyright 2021 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var wasmAll;
|
function setup$2(backend) {
|
wasmAll = backend.wasm.cwrap(tfjsCore.All, null /*void*/, ['number, number, number']);
|
}
|
function all(args) {
|
var backend = args.backend, inputs = args.inputs, attrs = args.attrs;
|
var axis = attrs.axis, keepDims = attrs.keepDims;
|
var x = inputs.x;
|
var xId = backend.dataIdMap.get(x.dataId).id;
|
var inputId = xId;
|
var input = x;
|
var _a = permuteAxesAndTranspose(x, axis, backend), transposed = _a.transposed, axes = _a.axes, originalAxes = _a.originalAxes, inputWasTransposed = _a.inputWasTransposed;
|
if (inputWasTransposed) {
|
var transposedId = backend.dataIdMap.get(transposed.dataId).id;
|
input = transposed;
|
inputId = transposedId;
|
}
|
var inputRank = input.shape.length;
|
tfjsCore.backend_util.assertAxesAreInnerMostDims('all', axes, inputRank);
|
var _b = tfjsCore.backend_util.computeOutAndReduceShapes(input.shape, axes), outShape = _b[0], reduceShape = _b[1];
|
var reduceSize = tfjsCore.util.sizeFromShape(reduceShape);
|
var out = backend.makeOutput(outShape, x.dtype);
|
if (tfjsCore.util.sizeFromShape(input.shape) !== 0) {
|
var outId = backend.dataIdMap.get(out.dataId).id;
|
wasmAll(inputId, reduceSize, outId);
|
}
|
if (inputWasTransposed) {
|
// dispose of the transposed tensor.
|
backend.disposeData(transposed.dataId);
|
}
|
if (keepDims) {
|
// reshape
|
var newShape = tfjsCore.backend_util.expandShapeToKeepDim(out.shape, originalAxes);
|
out.shape = newShape;
|
}
|
return out;
|
}
|
var allConfig = {
|
kernelName: tfjsCore.All,
|
backendName: 'wasm',
|
setupFunc: setup$2,
|
kernelFunc: all
|
};
|
|
/**
|
* @license
|
* Copyright 2021 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var wasmAny;
|
function setup$3(backend) {
|
wasmAny = backend.wasm.cwrap(tfjsCore.Any, null /*void*/, ['number, number, number']);
|
}
|
function any(args) {
|
var backend = args.backend, inputs = args.inputs, attrs = args.attrs;
|
var axis = attrs.axis, keepDims = attrs.keepDims;
|
var x = inputs.x;
|
var xId = backend.dataIdMap.get(x.dataId).id;
|
var inputId = xId;
|
var input = x;
|
var _a = permuteAxesAndTranspose(x, axis, backend), transposed = _a.transposed, axes = _a.axes, originalAxes = _a.originalAxes, inputWasTransposed = _a.inputWasTransposed;
|
if (inputWasTransposed) {
|
var transposedId = backend.dataIdMap.get(transposed.dataId).id;
|
input = transposed;
|
inputId = transposedId;
|
}
|
var inputRank = input.shape.length;
|
tfjsCore.backend_util.assertAxesAreInnerMostDims('any', axes, inputRank);
|
var _b = tfjsCore.backend_util.computeOutAndReduceShapes(input.shape, axes), outShape = _b[0], reduceShape = _b[1];
|
var reduceSize = tfjsCore.util.sizeFromShape(reduceShape);
|
var out = backend.makeOutput(outShape, x.dtype);
|
if (tfjsCore.util.sizeFromShape(input.shape) !== 0) {
|
var outId = backend.dataIdMap.get(out.dataId).id;
|
wasmAny(inputId, reduceSize, outId);
|
}
|
if (inputWasTransposed) {
|
// dispose of the transposed tensor.
|
backend.disposeData(transposed.dataId);
|
}
|
if (keepDims) {
|
// reshape
|
var newShape = tfjsCore.backend_util.expandShapeToKeepDim(out.shape, originalAxes);
|
out.shape = newShape;
|
}
|
return out;
|
}
|
var anyConfig = {
|
kernelName: tfjsCore.Any,
|
backendName: 'wasm',
|
setupFunc: setup$3,
|
kernelFunc: any
|
};
|
|
/**
|
* @license
|
* Copyright 2019 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var wasmFunc$1;
|
function setup$4(backend) {
|
wasmFunc$1 = backend.wasm.cwrap(tfjsCore.ArgMax, null /* void */, [
|
'number',
|
'number',
|
'number',
|
'number',
|
'number' // out_id
|
]);
|
}
|
function argmax(args) {
|
var backend = args.backend, inputs = args.inputs, attrs = args.attrs;
|
var axis = attrs.axis;
|
var x = inputs.x;
|
var xId = backend.dataIdMap.get(x.dataId).id;
|
var inputId = xId;
|
var input = x;
|
var _a = permuteAxesAndTranspose(x, axis, backend), transposed = _a.transposed, axes = _a.axes, inputWasTransposed = _a.inputWasTransposed;
|
if (inputWasTransposed) {
|
var transposedId = backend.dataIdMap.get(transposed.dataId).id;
|
if (transposedId !== xId) {
|
// transpose was not a no-op. We will need to dispose of this
|
// once we are done.
|
input = transposed;
|
inputId = transposedId;
|
}
|
}
|
var outShape = input.shape.slice(0, -1);
|
var out = backend.makeOutput(outShape, 'int32');
|
var outId = backend.dataIdMap.get(out.dataId).id;
|
var outerSize = tfjsCore.util.sizeFromShape(out.shape);
|
var innerSize = input.shape[axes[0]];
|
wasmFunc$1(inputId, CppDType[input.dtype], outerSize, innerSize, outId);
|
if (inputWasTransposed) {
|
// dispose of the transposed tensor.
|
backend.disposeData(transposed.dataId);
|
}
|
return out;
|
}
|
var argMaxConfig = {
|
kernelName: tfjsCore.ArgMax,
|
backendName: 'wasm',
|
kernelFunc: argmax,
|
setupFunc: setup$4
|
};
|
|
/**
|
* @license
|
* Copyright 2019 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var wasmAvgPool;
|
function setup$5(backend) {
|
wasmAvgPool = backend.wasm.cwrap(tfjsCore.AvgPool, null /* void */, [
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
]);
|
}
|
function avgPool(args) {
|
var inputs = args.inputs, attrs = args.attrs, backend = args.backend;
|
var x = inputs.x;
|
var xId = backend.dataIdMap.get(x.dataId).id;
|
var filterSize = attrs.filterSize, strides = attrs.strides, pad = attrs.pad, dimRoundingMode = attrs.dimRoundingMode;
|
var convInfo = tfjsCore.backend_util.computePool2DInfo(x.shape, filterSize, strides, 1 /* dilations */, pad, dimRoundingMode);
|
var filterHeight = convInfo.filterHeight;
|
var filterWidth = convInfo.filterWidth;
|
var padTop = convInfo.padInfo.top;
|
var padRight = convInfo.padInfo.right;
|
var padBottom = convInfo.padInfo.bottom;
|
var padLeft = convInfo.padInfo.left;
|
var strideHeight = convInfo.strideHeight;
|
var strideWidth = convInfo.strideWidth;
|
var channels = convInfo.inChannels;
|
if (convInfo.dataFormat !== 'channelsLast') {
|
throw new Error("wasm backend does not support dataFormat:'" +
|
(convInfo.dataFormat + "'. Please use 'channelsLast'."));
|
}
|
if (convInfo.dilationWidth !== 1 || convInfo.dilationHeight !== 1) {
|
throw new Error("was backend only supports average pooling with dilation = [1, 1], " +
|
("got [" + convInfo.dilationHeight + ", " + convInfo.dilationWidth + "]."));
|
}
|
var out = backend.makeOutput(convInfo.outShape, 'float32');
|
var outId = backend.dataIdMap.get(out.dataId).id;
|
wasmAvgPool(xId, x.shape[0], x.shape[1], x.shape[2], filterHeight, filterWidth, padTop, padRight, padBottom, padLeft, strideHeight, strideWidth, channels, outId);
|
return out;
|
}
|
var avgPoolConfig = {
|
kernelName: tfjsCore.AvgPool,
|
backendName: 'wasm',
|
setupFunc: setup$5,
|
kernelFunc: avgPool
|
};
|
|
/**
|
* @license
|
* Copyright 2019 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
function reshape(args) {
|
var inputs = args.inputs, attrs = args.attrs;
|
var x = inputs.x;
|
var shape = attrs.shape;
|
var xSize = tfjsCore.util.sizeFromShape(x.shape);
|
var $shape = tfjsCore.util.inferFromImplicitShape(shape, xSize);
|
tfjsCore.util.assert(xSize === tfjsCore.util.sizeFromShape($shape), function () { return "new shape: " + $shape + ", old shape: " + x.shape + ". New shape and old " +
|
"shape must have the same number of elements."; });
|
// Backend needs to track refCount for the dataId for reshape op
|
args.backend.incRef(x.dataId);
|
return { dataId: x.dataId, shape: $shape, dtype: x.dtype };
|
}
|
var reshapeConfig = {
|
kernelName: tfjsCore.Reshape,
|
backendName: 'wasm',
|
kernelFunc: reshape
|
};
|
|
/**
|
* @license
|
* Copyright 2019 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var wasmBatchMatMul;
|
function setup$6(backend) {
|
wasmBatchMatMul = backend.wasm.cwrap(tfjsCore.BatchMatMul, null /* void */, [
|
'number',
|
'array',
|
'number',
|
'number',
|
'array',
|
'number',
|
'number',
|
'number',
|
'number' // out_id
|
]);
|
}
|
function batchMatMul(args) {
|
var inputs = args.inputs, backend = args.backend, attrs = args.attrs;
|
var a = inputs.a, b = inputs.b;
|
var transposeA = attrs.transposeA, transposeB = attrs.transposeB;
|
if (a.dtype !== 'float32' || b.dtype !== 'float32') {
|
throw new Error("BatchMatMul for non non-float32 tensors not yet supported.");
|
}
|
var aRank = a.shape.length;
|
var bRank = b.shape.length;
|
var innerShapeA = transposeA ? a.shape[aRank - 2] : a.shape[aRank - 1];
|
var innerShapeB = transposeB ? b.shape[bRank - 1] : b.shape[bRank - 2];
|
var outerShapeA = transposeA ? a.shape[aRank - 1] : a.shape[aRank - 2];
|
var outerShapeB = transposeB ? b.shape[bRank - 2] : b.shape[bRank - 1];
|
var outerDimsA = a.shape.slice(0, -2);
|
var outerDimsB = b.shape.slice(0, -2);
|
var batchDimA = tfjsCore.util.sizeFromShape(outerDimsA);
|
var batchDimB = tfjsCore.util.sizeFromShape(outerDimsB);
|
var outShapeOuterDims = tfjsCore.broadcast_util.assertAndGetBroadcastShape(a.shape.slice(0, -2), b.shape.slice(0, -2));
|
var outShape = outShapeOuterDims.concat([outerShapeA, outerShapeB]);
|
tfjsCore.util.assert(innerShapeA === innerShapeB, function () { return "Error in matMul: inner shapes (" + innerShapeA + ") and (" +
|
(innerShapeB + ") of Tensors with shapes " + a.shape + " and ") +
|
(b.shape + " and transposeA=" + transposeA) +
|
(" and transposeB=" + transposeB + " must match."); });
|
var a3dShape = transposeA ? [batchDimA, innerShapeA, outerShapeA] :
|
[batchDimA, outerShapeA, innerShapeA];
|
var b3dShape = transposeB ? [batchDimB, outerShapeB, innerShapeB] :
|
[batchDimB, innerShapeB, outerShapeB];
|
// The rest of the implementation is designed to operate on rank-3 tensors
|
var a3d = reshape({ inputs: { x: a }, backend: backend, attrs: { shape: a3dShape } });
|
var b3d = reshape({ inputs: { x: b }, backend: backend, attrs: { shape: b3dShape } });
|
var a3dId = backend.dataIdMap.get(a3d.dataId).id;
|
var b3dId = backend.dataIdMap.get(b3d.dataId).id;
|
var leftDim = transposeA ? a3d.shape[2] : a3d.shape[1];
|
var rightDim = transposeB ? b3d.shape[1] : b3d.shape[2];
|
var batchDim = Math.max(batchDimA, batchDimB);
|
var out = backend.makeOutput([batchDim, leftDim, rightDim], a3d.dtype);
|
var outId = backend.dataIdMap.get(out.dataId).id;
|
var aShapeBytes = new Uint8Array(new Int32Array(a3d.shape).buffer);
|
var bShapeBytes = new Uint8Array(new Int32Array(b3d.shape).buffer);
|
wasmBatchMatMul(a3dId, aShapeBytes, a3d.shape.length, b3dId, bShapeBytes, b3d.shape.length, transposeA, transposeB, outId);
|
backend.disposeData(a3d.dataId);
|
backend.disposeData(b3d.dataId);
|
out.shape = outShape;
|
return out;
|
}
|
var batchMatMulConfig = {
|
kernelName: tfjsCore.BatchMatMul,
|
backendName: 'wasm',
|
setupFunc: setup$6,
|
kernelFunc: batchMatMul
|
};
|
|
/**
|
* @license
|
* Copyright 2020 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
function concatImpl(inputs, outShape, dtype, simplyConcat) {
|
const outVals = tfjsCore.util.getArrayFromDType(dtype, tfjsCore.util.sizeFromShape(outShape));
|
if (simplyConcat && dtype !== 'string') {
|
// Use built-in TypedArray.set() method for speed.
|
let offset = 0;
|
inputs.forEach(input => {
|
const size = tfjsCore.util.sizeFromShape(input.shape);
|
outVals.set(input.vals, offset);
|
offset += size;
|
});
|
}
|
else {
|
let colOffset = 0;
|
inputs.forEach(input => {
|
const decodedData = dtype === 'string' ?
|
tfjsCore.backend_util.fromUint8ToStringArray(input.vals) :
|
input.vals;
|
let tIdx = 0;
|
for (let row = 0; row < input.shape[0]; ++row) {
|
const resIdx = row * outShape[1] + colOffset;
|
for (let col = 0; col < input.shape[1]; ++col) {
|
outVals[resIdx + col] = decodedData[tIdx++];
|
}
|
}
|
colOffset += input.shape[1];
|
});
|
}
|
return outVals;
|
}
|
|
/**
|
* @license
|
* Copyright 2020 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
function rangeImpl(start, stop, step, dtype) {
|
const sameStartStop = start === stop;
|
const increasingRangeNegativeStep = start < stop && step < 0;
|
const decreasingRangePositiveStep = stop < start && step > 1;
|
if (sameStartStop || increasingRangeNegativeStep ||
|
decreasingRangePositiveStep) {
|
return tfjsCore.util.makeZerosTypedArray(0, dtype);
|
}
|
const numElements = Math.abs(Math.ceil((stop - start) / step));
|
const values = tfjsCore.util.makeZerosTypedArray(numElements, dtype);
|
if (stop < start && step === 1) {
|
// Auto adjust the step's sign if it hasn't been set
|
// (or was set to 1)
|
step = -1;
|
}
|
values[0] = start;
|
for (let i = 1; i < values.length; i++) {
|
values[i] = values[i - 1] + step;
|
}
|
return values;
|
}
|
|
/**
|
* @license
|
* Copyright 2020 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
function sliceImpl(vals, begin, size, shape, dtype) {
|
const isContinous = tfjsCore.slice_util.isSliceContinous(shape, begin, size);
|
const length = tfjsCore.util.sizeFromShape(size);
|
const xStrides = tfjsCore.util.computeStrides(shape);
|
if (isContinous) {
|
const flatOffset = tfjsCore.slice_util.computeFlatOffset(begin, xStrides);
|
if (dtype === 'string') {
|
return vals.slice(flatOffset, flatOffset + length);
|
}
|
return vals.subarray(flatOffset, flatOffset + length);
|
}
|
const decodedData = dtype === 'string' ?
|
tfjsCore.backend_util.fromUint8ToStringArray(vals) :
|
vals;
|
const inBuf = tfjsCore.buffer(shape, dtype, decodedData);
|
const outBuf = tfjsCore.buffer(size, dtype);
|
for (let i = 0; i < outBuf.size; ++i) {
|
const outLoc = outBuf.indexToLoc(i);
|
const inLoc = outLoc.map((idx, j) => idx + begin[j]);
|
outBuf.set(inBuf.get(...inLoc), ...outLoc);
|
}
|
if (dtype === 'string') {
|
return tfjsCore.backend_util.fromStringArrayToUint8(outBuf.values);
|
}
|
return outBuf.values;
|
}
|
|
/**
|
* @license
|
* Copyright 2019 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
function slice(args) {
|
var x = args.inputs.x, _a = args.attrs, begin = _a.begin, size = _a.size, backend = args.backend;
|
var _b = tfjsCore.slice_util.parseSliceParams(x, begin, size), begin_ = _b[0], size_ = _b[1];
|
var isContinous = tfjsCore.slice_util.isSliceContinous(x.shape, begin_, size_);
|
var xVals = backend.readSync(x.dataId);
|
var out = backend.makeOutput(size_, x.dtype);
|
var xStrides = tfjsCore.util.computeStrides(x.shape);
|
var outData = backend.dataIdMap.get(out.dataId);
|
if (isContinous) {
|
var flatOffset = tfjsCore.slice_util.computeFlatOffset(begin_, xStrides);
|
if (x.dtype === 'string') {
|
outData.stringBytes =
|
xVals
|
.slice(flatOffset, flatOffset + tfjsCore.util.sizeFromShape(size_));
|
}
|
else {
|
var outVals_1 = backend.typedArrayFromHeap(out);
|
outVals_1.set(xVals
|
.subarray(flatOffset, flatOffset + tfjsCore.util.sizeFromShape(size_)));
|
}
|
return out;
|
}
|
if (x.dtype === 'string') {
|
var res = sliceImpl(xVals, begin_, size_, x.shape, x.dtype);
|
outData.stringBytes = res;
|
return out;
|
}
|
var outVals = backend.typedArrayFromHeap(out);
|
var rank = x.shape.length;
|
if (rank === 2) {
|
slice2d(xVals, xStrides[0], outVals, begin_, size_);
|
}
|
else if (rank === 3) {
|
slice3d(xVals, xStrides[0], xStrides[1], outVals, begin_, size_);
|
}
|
else if (rank === 4) {
|
slice4d(xVals, xStrides[0], xStrides[1], xStrides[2], outVals, begin_, size_);
|
}
|
else {
|
var res = sliceImpl(xVals, begin_, size_, x.shape, x.dtype);
|
outVals.set(res);
|
}
|
return out;
|
}
|
function slice2d(xVals, xStride, outVals, begin, size) {
|
var outOffset = 0;
|
var beginI = begin[0];
|
var beginJ = begin[1];
|
var endI = beginI + size[0];
|
for (var i = beginI; i < endI; i++) {
|
var xOffset = i * xStride + beginJ;
|
outVals.set(xVals.subarray(xOffset, xOffset + size[1]), outOffset);
|
outOffset += size[1];
|
}
|
}
|
function slice3d(xVals, xStride1, xStride2, outVals, begin, size) {
|
var outOffset = 0;
|
var beginI = begin[0];
|
var beginJ = begin[1];
|
var beginK = begin[2];
|
var endI = beginI + size[0];
|
var endJ = beginJ + size[1];
|
for (var i = beginI; i < endI; i++) {
|
for (var j = beginJ; j < endJ; j++) {
|
var xOffset = i * xStride1 + j * xStride2 + beginK;
|
outVals.set(xVals.subarray(xOffset, xOffset + size[2]), outOffset);
|
outOffset += size[2];
|
}
|
}
|
}
|
function slice4d(xVals, xStride1, xStride2, xStride3, outVals, begin, size) {
|
var outOffset = 0;
|
var beginI = begin[0];
|
var beginJ = begin[1];
|
var beginK = begin[2];
|
var endI = beginI + size[0];
|
var endJ = beginJ + size[1];
|
var endK = beginK + size[2];
|
var beginL = begin[3];
|
for (var i = beginI; i < endI; i++) {
|
for (var j = beginJ; j < endJ; j++) {
|
for (var k = beginK; k < endK; k++) {
|
var xOffset = i * xStride1 + j * xStride2 + k * xStride3 + beginL;
|
outVals.set(xVals.subarray(xOffset, xOffset + size[3]), outOffset);
|
outOffset += size[3];
|
}
|
}
|
}
|
}
|
var sliceConfig = {
|
kernelName: tfjsCore.Slice,
|
backendName: 'wasm',
|
kernelFunc: slice,
|
};
|
|
/**
|
* @license
|
* Copyright 2021 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
function batchToSpaceND(args) {
|
var inputs = args.inputs, backend = args.backend, attrs = args.attrs;
|
var x = inputs.x;
|
var blockShape = attrs.blockShape, crops = attrs.crops;
|
var prod = blockShape.reduce(function (a, b) { return a * b; });
|
var reshaped = tfjsCore.backend_util.getReshaped(x.shape, blockShape, prod);
|
var permuted = tfjsCore.backend_util.getPermuted(reshaped.length, blockShape.length);
|
var reshapedPermuted = tfjsCore.backend_util.getReshapedPermuted(x.shape, blockShape, prod);
|
var sliceBeginCoords = tfjsCore.backend_util.getSliceBeginCoords(crops, blockShape.length);
|
var sliceSize = tfjsCore.backend_util.getSliceSize(reshapedPermuted, crops, blockShape.length);
|
var xReshaped = reshape({ inputs: { x: x }, backend: backend, attrs: { shape: reshaped } });
|
var xTransposed = transpose({ inputs: { x: xReshaped }, backend: backend, attrs: { perm: permuted } });
|
var xTransposedReshaped = reshape({ inputs: { x: xTransposed }, backend: backend, attrs: { shape: reshapedPermuted } });
|
var result = slice({
|
inputs: { x: xTransposedReshaped },
|
backend: backend,
|
attrs: { begin: sliceBeginCoords, size: sliceSize }
|
});
|
backend.disposeData(xReshaped.dataId);
|
backend.disposeData(xTransposed.dataId);
|
backend.disposeData(xReshaped.dataId);
|
return result;
|
}
|
var batchToSpaceNDConfig = {
|
kernelName: tfjsCore.BatchToSpaceND,
|
backendName: 'wasm',
|
kernelFunc: batchToSpaceND
|
};
|
|
/**
|
* @license
|
* Copyright 2019 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
function cast(args) {
|
var x = args.inputs.x, dtype = args.attrs.dtype, backend = args.backend;
|
var out = backend.makeOutput(x.shape, dtype);
|
var inVals = backend.typedArrayFromHeap(x);
|
var outVals = backend.typedArrayFromHeap(out);
|
outVals.set(inVals);
|
return out;
|
}
|
var castConfig = {
|
kernelName: tfjsCore.Cast,
|
backendName: 'wasm',
|
kernelFunc: cast,
|
};
|
|
/**
|
* @license
|
* Copyright 2021 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var ceilConfig = createUnaryKernelConfig(tfjsCore.Ceil);
|
|
/**
|
* @license
|
* Copyright 2019 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var wasmClip;
|
function setup$7(backend) {
|
wasmClip = backend.wasm.cwrap(tfjsCore.ClipByValue, null /* void */, [
|
'number',
|
'number',
|
'number',
|
'number' // out_id
|
]);
|
}
|
function clip(args) {
|
var inputs = args.inputs, backend = args.backend, attrs = args.attrs;
|
var x = inputs.x;
|
var clipValueMin = attrs.clipValueMin, clipValueMax = attrs.clipValueMax;
|
var xId = backend.dataIdMap.get(x.dataId).id;
|
var out = backend.makeOutput(x.shape, x.dtype);
|
var outId = backend.dataIdMap.get(out.dataId).id;
|
wasmClip(xId, clipValueMin, clipValueMax, outId);
|
return out;
|
}
|
var clipByValueConfig = {
|
kernelName: tfjsCore.ClipByValue,
|
backendName: 'wasm',
|
setupFunc: setup$7,
|
kernelFunc: clip
|
};
|
|
/**
|
* @license
|
* Copyright 2019 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
function concat(args) {
|
var inputs = args.inputs, backend = args.backend;
|
var axis = tfjsCore.util.parseAxisParam(args.attrs.axis, inputs[0].shape)[0];
|
var outShape = tfjsCore.backend_util.computeOutShape(inputs.map(function (t) { return t.shape; }), axis);
|
// Keep only non-empty tensors (ignore tensors with 0 in their shape).
|
var $inputs = inputs.filter(function (t) { return tfjsCore.util.sizeFromShape(t.shape) > 0; });
|
if ($inputs.length === 1) {
|
return identity({ inputs: { x: $inputs[0] }, backend: backend });
|
}
|
var out = backend.makeOutput(outShape, inputs[0].dtype);
|
if (tfjsCore.util.sizeFromShape(outShape) === 0) {
|
return out;
|
}
|
var shapes = $inputs.map(function (t) { return t.shape; });
|
tfjsCore.backend_util.assertParamsConsistent(shapes, axis);
|
if ($inputs[0].dtype === 'string') {
|
// Any concat of n-dimensional tensors across any axis can be reduced to
|
// a concatenation of two-dimensional tensors across the axis 1 by first
|
// partitioning the axes of the original tensors into those less than the
|
// axis to be concatenated and the rest. Then reshape the tensors
|
// into a two-dimensional tensor by collapsing these two sets of axes and
|
// concatenate the resulting matrices across the axis 1, finally reshaping
|
// the result to have the proper shape.
|
var inputs2D = $inputs.map(function (t) {
|
var innerSize = tfjsCore.util.sizeFromShape(t.shape.slice(axis));
|
var shape = [-1, innerSize];
|
return reshape({ inputs: { x: t }, backend: backend, attrs: { shape: shape } });
|
});
|
var inputsValShapes = inputs2D.map(function (t) {
|
return { vals: backend.readSync(t.dataId), shape: t.shape };
|
});
|
// Concats 2d tensors along axis=1.
|
outShape =
|
tfjsCore.backend_util.computeOutShape(inputs2D.map(function (t) { return t.shape; }), 1 /* axis */);
|
var simplyConcat = inputs2D[0].shape[0] === 1;
|
var outVals_1 = concatImpl(inputsValShapes, outShape, inputs[0].dtype, simplyConcat);
|
var finalOutShape = tfjsCore.backend_util.computeOutShape($inputs.map(function (t) { return t.shape; }), axis);
|
out.shape = finalOutShape;
|
var outData = backend.dataIdMap.get(out.dataId);
|
outData.stringBytes = tfjsCore.backend_util.fromStringArrayToUint8(outVals_1);
|
inputs2D.forEach(function (t) { return backend.disposeData(t.dataId); });
|
return out;
|
}
|
var batchDim = tfjsCore.util.sizeFromShape($inputs[0].shape.slice(0, axis));
|
var sumInnerDims = 0;
|
var innerDims = $inputs.map(function (input) {
|
var innerDim = tfjsCore.util.sizeFromShape(input.shape.slice(axis));
|
sumInnerDims += innerDim;
|
return innerDim;
|
});
|
var inVals = $inputs.map(function (input) { return backend.typedArrayFromHeap(input); });
|
var outVals = backend.typedArrayFromHeap(out);
|
for (var b = 0; b < batchDim; b++) {
|
var outOffset = b * sumInnerDims;
|
for (var i = 0; i < inVals.length; i++) {
|
var innerDim = innerDims[i];
|
var inOffset = b * innerDim;
|
var vals = inVals[i].subarray(inOffset, inOffset + innerDim);
|
outVals.set(vals, outOffset);
|
outOffset += innerDim;
|
}
|
}
|
return out;
|
}
|
var concatConfig = {
|
kernelName: tfjsCore.Concat,
|
backendName: 'wasm',
|
kernelFunc: concat,
|
};
|
|
/**
|
* @license
|
* Copyright 2019 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var wasmConv2d;
|
function setup$8(backend) {
|
wasmConv2d = backend.wasm.cwrap(tfjsCore.Conv2D, null /* void */, [
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
]);
|
}
|
function conv2d(args) {
|
var inputs = args.inputs, attrs = args.attrs, backend = args.backend;
|
var x = inputs.x, filter = inputs.filter;
|
var xId = backend.dataIdMap.get(x.dataId).id;
|
var filterId = backend.dataIdMap.get(filter.dataId).id;
|
var strides = attrs.strides, dilations = attrs.dilations, pad = attrs.pad, dimRoundingMode = attrs.dimRoundingMode, dataFormat = attrs.dataFormat;
|
var $dataFormat = tfjsCore.backend_util.convertConv2DDataFormat(dataFormat);
|
var convInfo = tfjsCore.backend_util.computeConv2DInfo(x.shape, filter.shape, strides, dilations, pad, dimRoundingMode, false, $dataFormat);
|
var filterHeight = convInfo.filterHeight;
|
var filterWidth = convInfo.filterWidth;
|
var padTop = convInfo.padInfo.top;
|
var padRight = convInfo.padInfo.right;
|
var padBottom = convInfo.padInfo.bottom;
|
var padLeft = convInfo.padInfo.left;
|
var dilationHeight = convInfo.dilationHeight;
|
var dilationWidth = convInfo.dilationWidth;
|
var strideHeight = convInfo.strideHeight;
|
var strideWidth = convInfo.strideWidth;
|
var inputChannels = convInfo.inChannels;
|
var outputChannels = convInfo.outChannels;
|
var isSamePad = convInfo.padInfo.type === 'SAME' ? 1 : 0;
|
if (convInfo.dataFormat !== 'channelsLast') {
|
throw new Error("wasm backend Conv2D does not support dataFormat:'" +
|
(convInfo.dataFormat + "'. Please use 'channelsLast'."));
|
}
|
var out = backend.makeOutput(convInfo.outShape, 'float32');
|
var outId = backend.dataIdMap.get(out.dataId).id;
|
wasmConv2d(xId, x.shape[0], x.shape[1], x.shape[2], filterId, filterHeight, filterWidth, padTop, padRight, padBottom, padLeft, isSamePad, dilationHeight, dilationWidth, strideHeight, strideWidth, inputChannels, outputChannels, outId);
|
return out;
|
}
|
var conv2DConfig = {
|
kernelName: tfjsCore.Conv2D,
|
backendName: 'wasm',
|
setupFunc: setup$8,
|
kernelFunc: conv2d
|
};
|
|
/**
|
* @license
|
* Copyright 2020 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var wasmConv2DBackpropInput;
|
function setup$9(backend) {
|
wasmConv2DBackpropInput = backend.wasm.cwrap(tfjsCore.Conv2DBackpropInput, null, [
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
]);
|
}
|
function conv2DBackpropInput(args) {
|
var backend = args.backend, inputs = args.inputs, attrs = args.attrs;
|
var dy = inputs.dy, filter = inputs.filter;
|
var strides = attrs.strides, pad = attrs.pad, dataFormat = attrs.dataFormat, dimRoundingMode = attrs.dimRoundingMode, inputShape = attrs.inputShape;
|
var dilations = 1;
|
var $dataFormat = tfjsCore.backend_util.convertConv2DDataFormat(dataFormat);
|
var convInfo = tfjsCore.backend_util.computeConv2DInfo(inputShape, filter.shape, strides, dilations, pad, dimRoundingMode, false /* depthwise */, $dataFormat);
|
var batchSize = convInfo.batchSize, filterHeight = convInfo.filterHeight, filterWidth = convInfo.filterWidth, inChannels = convInfo.inChannels, inHeight = convInfo.inHeight, inWidth = convInfo.inWidth, outChannels = convInfo.outChannels, outHeight = convInfo.outHeight, outWidth = convInfo.outWidth, strideHeight = convInfo.strideHeight, strideWidth = convInfo.strideWidth;
|
var topPad = filterHeight - 1 - convInfo.padInfo.top;
|
var leftPad = filterWidth - 1 - convInfo.padInfo.left;
|
var isChannelsLast = convInfo.dataFormat === 'channelsLast';
|
var dxStrides = tfjsCore.util.computeStrides(convInfo.inShape);
|
var dyStrides = tfjsCore.util.computeStrides(dy.shape);
|
var _a = tfjsCore.util.computeStrides(filter.shape), fltS0 = _a[0], fltS1 = _a[1], fltS2 = _a[2];
|
var xBatchStride = dxStrides[0];
|
var xRowStride = isChannelsLast ? dxStrides[1] : dxStrides[2];
|
var xColStride = isChannelsLast ? dxStrides[2] : 1;
|
var xChannelStride = isChannelsLast ? 1 : dxStrides[1];
|
var yBatchStride = dyStrides[0];
|
var yRowStride = isChannelsLast ? dyStrides[1] : dyStrides[2];
|
var yColStride = isChannelsLast ? dyStrides[2] : 1;
|
var yChannelStride = isChannelsLast ? 1 : dyStrides[1];
|
var out = backend.makeOutput(convInfo.inShape, 'float32');
|
var outId = backend.dataIdMap.get(out.dataId).id;
|
var dyId = backend.dataIdMap.get(dy.dataId).id;
|
var filterId = backend.dataIdMap.get(filter.dataId).id;
|
wasmConv2DBackpropInput(dyId, filterId, batchSize, filterHeight, filterWidth, inHeight, inWidth, inChannels, outHeight, outWidth, outChannels, strideHeight, strideWidth, topPad, leftPad, fltS0, fltS1, fltS2, xBatchStride, xRowStride, xColStride, xChannelStride, yBatchStride, yRowStride, yColStride, yChannelStride, outId);
|
return out;
|
}
|
var conv2DBackpropInputConfig = {
|
kernelName: tfjsCore.Conv2DBackpropInput,
|
backendName: 'wasm',
|
setupFunc: setup$9,
|
kernelFunc: conv2DBackpropInput
|
};
|
|
/**
|
* @license
|
* Copyright 2019 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var cosConfig = createUnaryKernelConfig(tfjsCore.Cos);
|
|
/**
|
* @license
|
* Copyright 2021 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var coshConfig = createUnaryKernelConfig(tfjsCore.Cosh);
|
|
/**
|
* @license
|
* Copyright 2019 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
// Must match enum in CropAndResize.cc
|
var InterpolationMethod;
|
(function (InterpolationMethod) {
|
InterpolationMethod[InterpolationMethod["bilinear"] = 0] = "bilinear";
|
InterpolationMethod[InterpolationMethod["nearest"] = 1] = "nearest";
|
})(InterpolationMethod || (InterpolationMethod = {}));
|
var wasmCropAndResize;
|
function setup$a(backend) {
|
wasmCropAndResize = backend.wasm.cwrap(tfjsCore.CropAndResize, null /*void*/, [
|
'number',
|
'number',
|
'number',
|
'number',
|
'array',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number' // out id
|
]);
|
}
|
function cropAndResize(args) {
|
var backend = args.backend, inputs = args.inputs, attrs = args.attrs;
|
var method = attrs.method, extrapolationValue = attrs.extrapolationValue, cropSize = attrs.cropSize;
|
var image = inputs.image, boxes = inputs.boxes, boxInd = inputs.boxInd;
|
var numBoxes = boxes.shape[0];
|
var _a = cropSize, cropHeight = _a[0], cropWidth = _a[1];
|
var outShape = [numBoxes, cropHeight, cropWidth, image.shape[3]];
|
var imagesData = backend.dataIdMap.get(image.dataId);
|
var castedData;
|
if (image.dtype !== 'float32') {
|
castedData = cast({ backend: backend, inputs: { x: image }, attrs: { dtype: 'float32' } });
|
imagesData = backend.dataIdMap.get(castedData.dataId);
|
}
|
var imagesId = imagesData.id;
|
var boxesId = backend.dataIdMap.get(boxes.dataId).id;
|
var boxIndId = backend.dataIdMap.get(boxInd.dataId).id;
|
var out = backend.makeOutput(outShape, 'float32');
|
var outId = backend.dataIdMap.get(out.dataId).id;
|
var imagesShapeBytes = new Uint8Array(new Int32Array(image.shape).buffer);
|
wasmCropAndResize(imagesId, boxesId, boxIndId, numBoxes, imagesShapeBytes, cropHeight, cropWidth, InterpolationMethod[method], extrapolationValue, outId);
|
if (castedData != null) {
|
backend.disposeData(castedData.dataId);
|
}
|
return out;
|
}
|
var cropAndResizeConfig = {
|
kernelName: tfjsCore.CropAndResize,
|
backendName: 'wasm',
|
setupFunc: setup$a,
|
kernelFunc: cropAndResize
|
};
|
|
/**
|
* @license
|
* Copyright 2022 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var wasmCumprod;
|
function setup$b(backend) {
|
wasmCumprod = backend.wasm.cwrap(tfjsCore.Cumprod, null /* void */, [
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number' // dtype
|
]);
|
}
|
function cumprod(args) {
|
var inputs = args.inputs, backend = args.backend, attrs = args.attrs;
|
var x = inputs.x;
|
var axis = attrs.axis, exclusive = attrs.exclusive, reverse = attrs.reverse;
|
var xRank = x.shape.length;
|
tfjsCore.util.assert(x.dtype === 'float32' || x.dtype === 'int32', function () { return "cumprod does not support " + x.dtype + " tensors in the WASM backend"; });
|
// permute required axis to inner most axis
|
var permutation = tfjsCore.backend_util.getAxesPermutation([axis], xRank);
|
var permutedX = x;
|
if (permutation !== null) {
|
permutedX = transpose({ inputs: { x: x }, attrs: { perm: permutation }, backend: backend });
|
}
|
var permutedAxis = tfjsCore.backend_util.getInnerMostAxes(1, xRank)[0];
|
tfjsCore.backend_util.assertAxesAreInnerMostDims('cumprod', [permutedAxis], xRank);
|
var permutedOut = backend.makeOutput(permutedX.shape, permutedX.dtype);
|
var finalDim = permutedX.shape[permutedAxis];
|
var permutedXId = backend.dataIdMap.get(permutedX.dataId).id;
|
var permutedOutId = backend.dataIdMap.get(permutedOut.dataId).id;
|
wasmCumprod(permutedXId, exclusive ? 1 : 0, reverse ? 1 : 0, finalDim, permutedOutId, CppDType[x.dtype]);
|
// transpose data back if permuted
|
var out = permutedOut;
|
if (permutation !== null) {
|
var undoPermutation = tfjsCore.backend_util.getUndoAxesPermutation(permutation);
|
out = transpose({ inputs: { x: permutedOut }, attrs: { perm: undoPermutation }, backend: backend });
|
backend.disposeData(permutedX.dataId);
|
backend.disposeData(permutedOut.dataId);
|
}
|
return out;
|
}
|
var cumprodConfig = {
|
kernelName: tfjsCore.Cumprod,
|
backendName: 'wasm',
|
setupFunc: setup$b,
|
kernelFunc: cumprod
|
};
|
|
/**
|
* @license
|
* Copyright 2020 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var wasmCumsum;
|
function setup$c(backend) {
|
wasmCumsum = backend.wasm.cwrap(tfjsCore.Cumsum, null /* void */, [
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number' // dtype
|
]);
|
}
|
function cumsum(args) {
|
var inputs = args.inputs, backend = args.backend, attrs = args.attrs;
|
var x = inputs.x;
|
var axis = attrs.axis, exclusive = attrs.exclusive, reverse = attrs.reverse;
|
var xRank = x.shape.length;
|
tfjsCore.util.assert(x.dtype === 'float32' || x.dtype === 'int32', function () { return "cumsum does not support " + x.dtype + " tensors in the WASM backend"; });
|
// permute required axis to inner most axis
|
var permutation = tfjsCore.backend_util.getAxesPermutation([axis], xRank);
|
var permutedX = x;
|
if (permutation !== null) {
|
permutedX = transpose({ inputs: { x: x }, attrs: { perm: permutation }, backend: backend });
|
}
|
var permutedAxis = tfjsCore.backend_util.getInnerMostAxes(1, xRank)[0];
|
tfjsCore.backend_util.assertAxesAreInnerMostDims('cumsum', [permutedAxis], xRank);
|
var permutedOut = backend.makeOutput(permutedX.shape, permutedX.dtype);
|
var finalDim = permutedX.shape[permutedAxis];
|
var permutedXId = backend.dataIdMap.get(permutedX.dataId).id;
|
var permutedOutId = backend.dataIdMap.get(permutedOut.dataId).id;
|
wasmCumsum(permutedXId, exclusive ? 1 : 0, reverse ? 1 : 0, finalDim, permutedOutId, CppDType[x.dtype]);
|
// transpose data back if permuted
|
var out = permutedOut;
|
if (permutation !== null) {
|
var undoPermutation = tfjsCore.backend_util.getUndoAxesPermutation(permutation);
|
out = transpose({ inputs: { x: permutedOut }, attrs: { perm: undoPermutation }, backend: backend });
|
backend.disposeData(permutedX.dataId);
|
backend.disposeData(permutedOut.dataId);
|
}
|
return out;
|
}
|
var cumsumConfig = {
|
kernelName: tfjsCore.Cumsum,
|
backendName: 'wasm',
|
setupFunc: setup$c,
|
kernelFunc: cumsum
|
};
|
|
/**
|
* @license
|
* Copyright 2019 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var wasmDepthToSpace;
|
function setup$d(backend) {
|
wasmDepthToSpace = backend.wasm.cwrap(tfjsCore.DepthToSpace, null /*void*/, [
|
'number',
|
'number',
|
'number',
|
'array',
|
'number',
|
'array',
|
'array',
|
'number',
|
'number',
|
]);
|
}
|
function depthToSpace(args) {
|
var backend = args.backend, inputs = args.inputs, attrs = args.attrs;
|
var x = inputs.x;
|
var blockSize = attrs.blockSize, dataFormat = attrs.dataFormat;
|
var batchSize = x.shape[0];
|
var inputHeight = (dataFormat === 'NHWC') ? x.shape[1] : x.shape[2];
|
var inputWidth = (dataFormat === 'NHWC') ? x.shape[2] : x.shape[3];
|
var inputDepth = (dataFormat === 'NHWC') ? x.shape[3] : x.shape[1];
|
var outputHeight = inputHeight * blockSize;
|
var outputWidth = inputWidth * blockSize;
|
var outputDepth = inputDepth / (blockSize * blockSize);
|
var outputShape = (dataFormat === 'NHWC') ?
|
[batchSize, outputHeight, outputWidth, outputDepth] :
|
[batchSize, outputDepth, outputHeight, outputWidth];
|
var out = backend.makeOutput(outputShape, 'float32');
|
var xData = backend.dataIdMap.get(x.dataId);
|
var xId = xData.id;
|
var xStridesBytes = new Uint8Array(new Int32Array(tfjsCore.util.computeStrides(x.shape)).buffer);
|
var outputShapeBytes = new Uint8Array(new Int32Array(outputShape).buffer);
|
var outStridesBytes = new Uint8Array(new Int32Array(tfjsCore.util.computeStrides(outputShape)).buffer);
|
var outId = backend.dataIdMap.get(out.dataId).id;
|
var channelsLast = dataFormat === 'NHWC' ? 1 : 0;
|
wasmDepthToSpace(xId, blockSize, channelsLast, xStridesBytes, x.shape.length - 1, outputShapeBytes, outStridesBytes, outputShape.length, outId);
|
return out;
|
}
|
var depthToSpaceConfig = {
|
kernelName: tfjsCore.DepthToSpace,
|
backendName: 'wasm',
|
setupFunc: setup$d,
|
kernelFunc: depthToSpace
|
};
|
|
/**
|
* @license
|
* Copyright 2019 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var wasmDepthwiseConv2d;
|
function setup$e(backend) {
|
wasmDepthwiseConv2d =
|
backend.wasm.cwrap(tfjsCore.DepthwiseConv2dNative, null /* void */, [
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
]);
|
}
|
function depthwiseConv2d(args) {
|
var inputs = args.inputs, attrs = args.attrs, backend = args.backend;
|
var x = inputs.x, filter = inputs.filter;
|
var xId = backend.dataIdMap.get(x.dataId).id;
|
var filterId = backend.dataIdMap.get(filter.dataId).id;
|
var strides = attrs.strides, dilations = attrs.dilations, pad = attrs.pad, dimRoundingMode = attrs.dimRoundingMode;
|
var $dilations = dilations == null ? [1, 1] : dilations;
|
var convInfo = tfjsCore.backend_util.computeConv2DInfo(x.shape, filter.shape, strides, $dilations, pad, dimRoundingMode, true /* depthwise */);
|
var filterHeight = convInfo.filterHeight;
|
var filterWidth = convInfo.filterWidth;
|
var padTop = convInfo.padInfo.top;
|
var padRight = convInfo.padInfo.right;
|
var padBottom = convInfo.padInfo.bottom;
|
var padLeft = convInfo.padInfo.left;
|
var dilationHeight = convInfo.dilationHeight;
|
var dilationWidth = convInfo.dilationWidth;
|
var strideHeight = convInfo.strideHeight;
|
var strideWidth = convInfo.strideWidth;
|
var inputChannels = convInfo.inChannels;
|
var outputChannels = convInfo.outChannels;
|
var isSamePad = convInfo.padInfo.type === 'SAME' ? 1 : 0;
|
if (convInfo.dataFormat !== 'channelsLast') {
|
throw new Error("wasm backend DepthwiseConv2dNative does not support dataFormat:'" +
|
(convInfo.dataFormat + "'. Please use 'channelsLast'."));
|
}
|
var out = backend.makeOutput(convInfo.outShape, 'float32');
|
var outId = backend.dataIdMap.get(out.dataId).id;
|
wasmDepthwiseConv2d(xId, x.shape[0], x.shape[1], x.shape[2], filterId, filterHeight, filterWidth, padTop, padRight, padBottom, padLeft, isSamePad, dilationHeight, dilationWidth, strideHeight, strideWidth, inputChannels, outputChannels, outId);
|
return out;
|
}
|
var depthwiseConv2dNativeConfig = {
|
kernelName: tfjsCore.DepthwiseConv2dNative,
|
backendName: 'wasm',
|
setupFunc: setup$e,
|
kernelFunc: depthwiseConv2d
|
};
|
|
/**
|
* @license
|
* Copyright 2021 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var eluConfig = createUnaryKernelConfig(tfjsCore.Elu);
|
|
/**
|
* @license
|
* Copyright 2020 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var supportsFullBroadcast = false;
|
var equalConfig = createBinaryKernelConfig(tfjsCore.Equal, supportsFullBroadcast, 'bool');
|
|
/**
|
* @license
|
* Copyright 2019 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var expConfig = createUnaryKernelConfig(tfjsCore.Exp, 'float32');
|
|
/**
|
* @license
|
* Copyright 2019 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
function expandDims(args) {
|
var inputs = args.inputs, attrs = args.attrs, backend = args.backend;
|
var input = inputs.input;
|
var dim = attrs.dim;
|
var inputRank = input.shape.length;
|
var newShape = input.shape.slice();
|
var $dim = dim;
|
if (dim < 0) {
|
// Negative value is counted from the tail of rank.
|
tfjsCore.util.assert(-(inputRank + 1) <= dim, function () { return "Axis must be in the interval [" + -(inputRank + 1) + ", " + inputRank + "]"; });
|
$dim = inputRank + dim + 1;
|
}
|
newShape.splice($dim, 0, 1);
|
return reshape({ inputs: { x: input }, backend: backend, attrs: { shape: newShape } });
|
}
|
var expandDimsConfig = {
|
kernelName: tfjsCore.ExpandDims,
|
backendName: 'wasm',
|
kernelFunc: expandDims,
|
};
|
|
/**
|
* @license
|
* Copyright 2020 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
function fill(args) {
|
var _a = args.attrs, shape = _a.shape, value = _a.value, dtype = _a.dtype, backend = args.backend;
|
var out = backend.makeOutput(shape, dtype);
|
var outVals = backend.typedArrayFromHeap(out);
|
outVals.fill(value);
|
return out;
|
}
|
var fillConfig = {
|
kernelName: tfjsCore.Fill,
|
backendName: 'wasm',
|
kernelFunc: fill,
|
};
|
|
/**
|
* @license
|
* Copyright 2019 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var wasmFlipLeftRight;
|
function setup$f(backend) {
|
wasmFlipLeftRight = backend.wasm.cwrap(tfjsCore.FlipLeftRight, null /* void */, [
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
]);
|
}
|
function flipLeftRight(args) {
|
var inputs = args.inputs, backend = args.backend;
|
var image = inputs.image;
|
var out = backend.makeOutput(image.shape, image.dtype);
|
var imageId = backend.dataIdMap.get(image.dataId).id;
|
var outId = backend.dataIdMap.get(out.dataId).id;
|
var _a = image.shape, batch = _a[0], imageHeight = _a[1], imageWidth = _a[2], numChannels = _a[3];
|
wasmFlipLeftRight(imageId, batch, imageHeight, imageWidth, numChannels, outId);
|
return out;
|
}
|
var flipLeftRightConfig = {
|
kernelName: tfjsCore.FlipLeftRight,
|
backendName: 'wasm',
|
kernelFunc: flipLeftRight,
|
setupFunc: setup$f
|
};
|
|
/**
|
* @license
|
* Copyright 2020 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var floorConfig = createUnaryKernelConfig(tfjsCore.Floor);
|
|
/**
|
* @license
|
* Copyright 2019 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var floorDivConfig = createBinaryKernelConfig(tfjsCore.FloorDiv);
|
|
/**
|
* @license
|
* Copyright 2019 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var wasmBatchNorm;
|
function setup$g(backend) {
|
wasmBatchNorm = backend.wasm.cwrap(tfjsCore.FusedBatchNorm, null /* void */, ['number', 'number', 'number', 'number', 'number', 'number', 'number']);
|
}
|
function fusedBatchNorm(args) {
|
var backend = args.backend, inputs = args.inputs, attrs = args.attrs;
|
var varianceEpsilon = attrs.varianceEpsilon;
|
var x = inputs.x, mean = inputs.mean, variance = inputs.variance, offset = inputs.offset, scale = inputs.scale;
|
var xId = backend.dataIdMap.get(x.dataId).id;
|
var meanId = backend.dataIdMap.get(mean.dataId).id;
|
var varianceId = backend.dataIdMap.get(variance.dataId).id;
|
var offsetId = offset != null ? backend.dataIdMap.get(offset.dataId).id : 0;
|
var scaleId = scale != null ? backend.dataIdMap.get(scale.dataId).id : 0;
|
var out = backend.makeOutput(x.shape, x.dtype);
|
// Short-circuit zero-sized tensors.
|
if (tfjsCore.util.sizeFromShape(x.shape) === 0) {
|
return out;
|
}
|
var outId = backend.dataIdMap.get(out.dataId).id;
|
wasmBatchNorm(xId, meanId, varianceId, offsetId, scaleId, varianceEpsilon, outId);
|
return out;
|
}
|
var fusedBatchNormConfig = {
|
kernelName: tfjsCore.FusedBatchNorm,
|
backendName: 'wasm',
|
setupFunc: setup$g,
|
kernelFunc: fusedBatchNorm
|
};
|
|
/**
|
* @license
|
* Copyright 2019 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var wasmFusedConv2d;
|
function setup$h(backend) {
|
wasmFusedConv2d = backend.wasm.cwrap(tfjsCore.FusedConv2D, null /* void */, [
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
]);
|
}
|
function fusedConv2d(args) {
|
var inputs = args.inputs, attrs = args.attrs, backend = args.backend;
|
var x = inputs.x, filter = inputs.filter, bias = inputs.bias, preluActivationWeights = inputs.preluActivationWeights;
|
var strides = attrs.strides, pad = attrs.pad, dilations = attrs.dilations, dataFormat = attrs.dataFormat, dimRoundingMode = attrs.dimRoundingMode, activation = attrs.activation, leakyreluAlpha = attrs.leakyreluAlpha;
|
var convInfo = tfjsCore.backend_util.computeConv2DInfo(x.shape, filter.shape, strides, dilations, pad, dimRoundingMode);
|
var fusedActivation = FusableActivation[activation];
|
if (fusedActivation == null) {
|
throw new Error(activation + " activation not yet supported for FusedConv2D " +
|
"in the wasm backend.");
|
}
|
var xId = backend.dataIdMap.get(x.dataId).id;
|
var filterId = backend.dataIdMap.get(filter.dataId).id;
|
var outputChannels = convInfo.outChannels;
|
var biasId = 0;
|
if (bias != null) {
|
var biasData = backend.dataIdMap.get(bias.dataId);
|
if (biasData.shape.length !== 1) {
|
throw new Error("FusedConv2D only supports rank-1 bias but got " +
|
("rank " + biasData.shape.length + "."));
|
}
|
if (biasData.shape[0] !== outputChannels) {
|
throw new Error("FusedConv2D bias shape (" + biasData.shape + ") does not " +
|
("match the number of output channels (" + outputChannels + ")"));
|
}
|
biasId = biasData.id;
|
}
|
var filterHeight = convInfo.filterHeight;
|
var filterWidth = convInfo.filterWidth;
|
var padTop = convInfo.padInfo.top;
|
var padRight = convInfo.padInfo.right;
|
var padBottom = convInfo.padInfo.bottom;
|
var padLeft = convInfo.padInfo.left;
|
var dilationHeight = convInfo.dilationHeight;
|
var dilationWidth = convInfo.dilationWidth;
|
var strideHeight = convInfo.strideHeight;
|
var strideWidth = convInfo.strideWidth;
|
var inputChannels = convInfo.inChannels;
|
var isSamePad = convInfo.padInfo.type === 'SAME' ? 1 : 0;
|
var batchSize = convInfo.batchSize;
|
var inHeight = convInfo.inHeight;
|
var inWidth = convInfo.inWidth;
|
if (dataFormat !== 'NHWC') {
|
throw new Error("wasm backend FusedConv2D does not support dataFormat:'" +
|
(dataFormat + "'. Please use 'NHWC'."));
|
}
|
var out = backend.makeOutput(convInfo.outShape, 'float32');
|
var outId = backend.dataIdMap.get(out.dataId).id;
|
var preluActivationWeightsId = preluActivationWeights == null ?
|
0 :
|
backend.dataIdMap.get(preluActivationWeights.dataId).id;
|
wasmFusedConv2d(xId, batchSize, inHeight, inWidth, filterId, filterHeight, filterWidth, biasId, padTop, padRight, padBottom, padLeft, isSamePad, dilationHeight, dilationWidth, strideHeight, strideWidth, inputChannels, outputChannels, fusedActivation, preluActivationWeightsId, leakyreluAlpha || 0, outId);
|
return out;
|
}
|
var fusedConv2DConfig = {
|
kernelName: tfjsCore.FusedConv2D,
|
backendName: 'wasm',
|
setupFunc: setup$h,
|
kernelFunc: fusedConv2d
|
};
|
|
/**
|
* @license
|
* Copyright 2019 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var wasmFusedDepthwiseConv2d;
|
function setup$i(backend) {
|
wasmFusedDepthwiseConv2d =
|
backend.wasm.cwrap(tfjsCore.FusedDepthwiseConv2D, null /* void */, [
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
]);
|
}
|
function fusedDepthwiseConv2d(args) {
|
var inputs = args.inputs, attrs = args.attrs, backend = args.backend;
|
var x = inputs.x, filter = inputs.filter, bias = inputs.bias, preluActivationWeights = inputs.preluActivationWeights;
|
var strides = attrs.strides, pad = attrs.pad, dilations = attrs.dilations, dataFormat = attrs.dataFormat, dimRoundingMode = attrs.dimRoundingMode, activation = attrs.activation, leakyreluAlpha = attrs.leakyreluAlpha;
|
var convInfo = tfjsCore.backend_util.computeConv2DInfo(x.shape, filter.shape, strides, dilations, pad, dimRoundingMode, true /* depthwise */);
|
var fusedActivation = FusableActivation[activation];
|
if (fusedActivation == null) {
|
throw new Error(activation + " activation not yet supported for FusedDepthwiseConv2D " +
|
"in the wasm backend.");
|
}
|
var xId = backend.dataIdMap.get(x.dataId).id;
|
var filterId = backend.dataIdMap.get(filter.dataId).id;
|
var outputChannels = convInfo.outChannels;
|
var biasId = 0;
|
if (bias != null) {
|
var biasData = backend.dataIdMap.get(bias.dataId);
|
if (biasData.shape.length !== 1) {
|
throw new Error("FusedDepthwiseConv2D only supports rank-1 bias but got " +
|
("rank " + biasData.shape.length + "."));
|
}
|
if (biasData.shape[0] !== outputChannels) {
|
throw new Error("FusedDepthwiseConv2D bias shape (" + biasData.shape + ") does not " +
|
("match the number of output channels (" + outputChannels + ")"));
|
}
|
biasId = biasData.id;
|
}
|
var filterHeight = convInfo.filterHeight;
|
var filterWidth = convInfo.filterWidth;
|
var padTop = convInfo.padInfo.top;
|
var padRight = convInfo.padInfo.right;
|
var padBottom = convInfo.padInfo.bottom;
|
var padLeft = convInfo.padInfo.left;
|
var dilationHeight = convInfo.dilationHeight;
|
var dilationWidth = convInfo.dilationWidth;
|
var strideHeight = convInfo.strideHeight;
|
var strideWidth = convInfo.strideWidth;
|
var inputChannels = convInfo.inChannels;
|
var isSamePad = convInfo.padInfo.type === 'SAME' ? 1 : 0;
|
var batchSize = convInfo.batchSize;
|
var inHeight = convInfo.inHeight;
|
var inWidth = convInfo.inWidth;
|
if (dataFormat !== 'NHWC') {
|
throw new Error("wasm backend FusedDepthwiseConv2D does not support dataFormat:'" +
|
(dataFormat + "'. Please use 'NHWC'."));
|
}
|
var out = backend.makeOutput(convInfo.outShape, 'float32');
|
var outId = backend.dataIdMap.get(out.dataId).id;
|
var preluActivationWeightsId = preluActivationWeights == null ?
|
0 :
|
backend.dataIdMap.get(preluActivationWeights.dataId).id;
|
wasmFusedDepthwiseConv2d(xId, batchSize, inHeight, inWidth, filterId, filterHeight, filterWidth, biasId, padTop, padRight, padBottom, padLeft, isSamePad, dilationHeight, dilationWidth, strideHeight, strideWidth, inputChannels, outputChannels, fusedActivation, preluActivationWeightsId, leakyreluAlpha || 0, outId);
|
return out;
|
}
|
var fusedDepthwiseConv2DConfig = {
|
kernelName: tfjsCore.FusedDepthwiseConv2D,
|
backendName: 'wasm',
|
setupFunc: setup$i,
|
kernelFunc: fusedDepthwiseConv2d
|
};
|
|
/**
|
* @license
|
* Copyright 2019 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var wasmGatherNd;
|
function setup$j(backend) {
|
wasmGatherNd = backend.wasm.cwrap(tfjsCore.GatherNd, null /*void*/, [
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'array',
|
'number' // outId
|
]);
|
}
|
function gatherNd(args) {
|
var backend = args.backend, inputs = args.inputs;
|
var params = inputs.params, indices = inputs.indices;
|
var _a = tfjsCore.gather_util.prepareAndValidate(params, indices), resultShape = _a[0], numSlices = _a[1], sliceSize = _a[2], strides = _a[3];
|
var out = backend.makeOutput(resultShape, params.dtype);
|
if (numSlices === 0) {
|
return out;
|
}
|
var indicesShape = indices.shape;
|
var sliceRank = indicesShape[indicesShape.length - 1];
|
var xData = backend.dataIdMap.get(params.dataId);
|
var xId = xData.id;
|
var indicesData = backend.dataIdMap.get(indices.dataId);
|
var indicesId = indicesData.id;
|
var stridesBytes = new Uint8Array(new Int32Array(strides).buffer);
|
var outId = backend.dataIdMap.get(out.dataId).id;
|
wasmGatherNd(xId, CppDType[params.dtype], indicesId, numSlices, sliceRank, sliceSize, stridesBytes, outId);
|
return out;
|
}
|
var gatherNdConfig = {
|
kernelName: tfjsCore.GatherNd,
|
backendName: 'wasm',
|
setupFunc: setup$j,
|
kernelFunc: gatherNd
|
};
|
|
/**
|
* @license
|
* Copyright 2019 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var wasmGather;
|
function setup$k(backend) {
|
wasmGather = backend.wasm.cwrap('Gather', null /*void*/, [
|
'number',
|
'number',
|
'array',
|
'number',
|
'number',
|
'number',
|
'array',
|
'number' // outId
|
]);
|
}
|
function gatherV2(args) {
|
var backend = args.backend, inputs = args.inputs, attrs = args.attrs;
|
var x = inputs.x, indices = inputs.indices;
|
var axis = attrs.axis, batchDims = attrs.batchDims;
|
// Throw error when any index is out of bound.
|
var parsedAxis = tfjsCore.util.parseAxisParam(axis, x.shape)[0];
|
var indicesVals = backend.readSync(indices.dataId);
|
var axisDim = x.shape[parsedAxis];
|
var _loop_1 = function (i) {
|
var index = indicesVals[i];
|
tfjsCore.util.assert(index <= axisDim - 1 && index >= 0, function () {
|
return "GatherV2: the index value " + index + " is not in [0, " + (axisDim - 1) + "]";
|
});
|
};
|
for (var i = 0; i < indicesVals.length; ++i) {
|
_loop_1(i);
|
}
|
var shapeInfo = tfjsCore.backend_util.segment_util.collectGatherOpShapeInfo(x, indices, parsedAxis, batchDims);
|
var flattenX = reshape({
|
inputs: { x: x },
|
attrs: {
|
shape: [
|
shapeInfo.batchSize, shapeInfo.outerSize, shapeInfo.dimSize,
|
shapeInfo.sliceSize
|
]
|
},
|
backend: backend
|
});
|
var indicesSize = tfjsCore.util.sizeFromShape(indices.shape);
|
var flattenIndex = reshape({
|
inputs: { x: indices },
|
attrs: { shape: [shapeInfo.batchSize, indicesSize / shapeInfo.batchSize] },
|
backend: backend
|
});
|
var flattenOutputShape = [
|
shapeInfo.batchSize, shapeInfo.outerSize, indicesSize / shapeInfo.batchSize,
|
shapeInfo.sliceSize
|
];
|
var out = backend.makeOutput(flattenOutputShape, x.dtype);
|
if (tfjsCore.util.sizeFromShape(x.shape) === 0) {
|
return out;
|
}
|
var stridesSize = flattenX.shape.length - 1;
|
var xData = backend.dataIdMap.get(flattenX.dataId);
|
var xId = xData.id;
|
var indicesData = backend.dataIdMap.get(flattenIndex.dataId);
|
var indicesId = indicesData.id;
|
var outId = backend.dataIdMap.get(out.dataId).id;
|
var xStridesBytes = new Uint8Array(new Int32Array(tfjsCore.util.computeStrides(flattenX.shape)).buffer);
|
var outStridesBytes = new Uint8Array(new Int32Array(tfjsCore.util.computeStrides(flattenOutputShape)).buffer);
|
wasmGather(xId, CppDType[x.dtype], xStridesBytes, stridesSize, indicesId, shapeInfo.batchSize, outStridesBytes, outId);
|
backend.disposeData(flattenX.dataId);
|
backend.disposeData(flattenIndex.dataId);
|
// reshape
|
out.shape = shapeInfo.outputShape;
|
return out;
|
}
|
var gatherV2Config = {
|
kernelName: tfjsCore.GatherV2,
|
backendName: 'wasm',
|
setupFunc: setup$k,
|
kernelFunc: gatherV2
|
};
|
|
/**
|
* @license
|
* Copyright 2019 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var supportsFullBroadcast$1 = false;
|
var greaterConfig = createBinaryKernelConfig(tfjsCore.Greater, supportsFullBroadcast$1, 'bool');
|
|
/**
|
* @license
|
* Copyright 2019 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var supportsFullBroadcast$2 = false;
|
var greaterEqualConfig = createBinaryKernelConfig(tfjsCore.GreaterEqual, supportsFullBroadcast$2, 'bool');
|
|
/**
|
* @license
|
* Copyright 2019 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var wasmFunc$2;
|
function setupFunc$1(backend) {
|
wasmFunc$2 = backend.wasm.cwrap(tfjsCore.LeakyRelu, null /* void */, [
|
'number',
|
'number',
|
'number',
|
'number',
|
]);
|
}
|
function leakyRelu(args) {
|
var x = args.inputs.x, alpha = args.attrs.alpha, backend = args.backend;
|
var xId = backend.dataIdMap.get(x.dataId).id;
|
// According to TF API, LeakyRelu returns float32 when input is either float32
|
// or int32.
|
var out = backend.makeOutput(x.shape, 'float32');
|
if (tfjsCore.util.sizeFromShape(x.shape) !== 0) {
|
var outId = backend.dataIdMap.get(out.dataId).id;
|
wasmFunc$2(xId, CppDType[x.dtype], alpha, outId);
|
}
|
return out;
|
}
|
var leakyReluConfig = {
|
kernelName: tfjsCore.LeakyRelu,
|
backendName: 'wasm',
|
setupFunc: setupFunc$1,
|
kernelFunc: leakyRelu,
|
};
|
|
/**
|
* @license
|
* Copyright 2019 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var supportsFullBroadcast$3 = false;
|
var lessConfig = createBinaryKernelConfig(tfjsCore.Less, supportsFullBroadcast$3, 'bool');
|
|
/**
|
* @license
|
* Copyright 2019 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var supportsFullBroadcast$4 = false;
|
var lessEqualConfig = createBinaryKernelConfig(tfjsCore.LessEqual, supportsFullBroadcast$4, 'bool');
|
|
/**
|
* @license
|
* Copyright 2019 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var logConfig = createUnaryKernelConfig(tfjsCore.Log);
|
|
/**
|
* @license
|
* Copyright 2019 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var supportsFullBroadcast$5 = false;
|
var logicalAndConfig = createBinaryKernelConfig(tfjsCore.LogicalAnd, supportsFullBroadcast$5, 'bool');
|
|
/**
|
* @license
|
* Copyright 2019 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var wasmMax;
|
function setup$l(backend) {
|
wasmMax = backend.wasm.cwrap(tfjsCore.Max, null /*void*/, [
|
'number',
|
'number',
|
'number',
|
'number',
|
]);
|
}
|
function max(args) {
|
var backend = args.backend, inputs = args.inputs, attrs = args.attrs;
|
var axis = attrs.reductionIndices, keepDims = attrs.keepDims;
|
var x = inputs.x;
|
var xId = backend.dataIdMap.get(x.dataId).id;
|
var inputId = xId;
|
var input = x;
|
var _a = permuteAxesAndTranspose(x, axis, backend), transposed = _a.transposed, axes = _a.axes, originalAxes = _a.originalAxes, inputWasTransposed = _a.inputWasTransposed;
|
if (inputWasTransposed) {
|
var transposedId = backend.dataIdMap.get(transposed.dataId).id;
|
input = transposed;
|
inputId = transposedId;
|
}
|
var inputRank = input.shape.length;
|
tfjsCore.backend_util.assertAxesAreInnerMostDims('max', axes, inputRank);
|
var _b = tfjsCore.backend_util.computeOutAndReduceShapes(input.shape, axes), outShape = _b[0], reduceShape = _b[1];
|
var reduceSize = tfjsCore.util.sizeFromShape(reduceShape);
|
var out = backend.makeOutput(outShape, x.dtype);
|
if (tfjsCore.util.sizeFromShape(input.shape) !== 0) {
|
var outId = backend.dataIdMap.get(out.dataId).id;
|
wasmMax(inputId, CppDType[x.dtype], reduceSize, outId);
|
}
|
if (inputWasTransposed) {
|
// dispose of the transposed tensor.
|
backend.disposeData(transposed.dataId);
|
}
|
if (keepDims) {
|
// reshape
|
var newShape = tfjsCore.backend_util.expandShapeToKeepDim(out.shape, originalAxes);
|
out.shape = newShape;
|
}
|
return out;
|
}
|
var maxConfig = {
|
kernelName: tfjsCore.Max,
|
backendName: 'wasm',
|
setupFunc: setup$l,
|
kernelFunc: max
|
};
|
|
/**
|
* @license
|
* Copyright 2019 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var maximumConfig = createBinaryKernelConfig(tfjsCore.Maximum);
|
|
/**
|
* @license
|
* Copyright 2019 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var wasmMaxPool;
|
function setup$m(backend) {
|
wasmMaxPool = backend.wasm.cwrap(tfjsCore.MaxPool, null /* void */, [
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
]);
|
}
|
function maxPool(args) {
|
var inputs = args.inputs, attrs = args.attrs, backend = args.backend;
|
var x = inputs.x;
|
var xId = backend.dataIdMap.get(x.dataId).id;
|
// TF API supports int32 input. CPU and WebGL backend also support int32
|
// input. WASM backend doesn't support it because it uses xnnpack which only
|
// supports float32.
|
//
|
// Add the following assert only for the WASM backend instead of at core op
|
// level.
|
//
|
// TODO: add support for int32 input.
|
tfjsCore.util.assert(x.dtype === 'float32', function () {
|
return "Error in MaxPool: only float32 input is supported. Got " + x.dtype + ".";
|
});
|
var filterSize = attrs.filterSize, strides = attrs.strides, pad = attrs.pad, dimRoundingMode = attrs.dimRoundingMode;
|
var convInfo = tfjsCore.backend_util.computePool2DInfo(x.shape, filterSize, strides, 1 /* dilations */, pad, dimRoundingMode);
|
var filterHeight = convInfo.filterHeight;
|
var filterWidth = convInfo.filterWidth;
|
var padTop = convInfo.padInfo.top;
|
var padRight = convInfo.padInfo.right;
|
var padBottom = convInfo.padInfo.bottom;
|
var padLeft = convInfo.padInfo.left;
|
var dilationHeight = convInfo.dilationHeight;
|
var dilationWidth = convInfo.dilationWidth;
|
var strideHeight = convInfo.strideHeight;
|
var strideWidth = convInfo.strideWidth;
|
var inputChannels = convInfo.inChannels;
|
var outputChannels = convInfo.outChannels;
|
if (convInfo.dataFormat !== 'channelsLast') {
|
throw new Error("wasm backend does not support dataFormat:'" +
|
(convInfo.dataFormat + "'. Please use 'channelsLast'."));
|
}
|
var out = backend.makeOutput(convInfo.outShape, 'float32');
|
var outId = backend.dataIdMap.get(out.dataId).id;
|
wasmMaxPool(xId, x.shape[0], x.shape[1], x.shape[2], filterHeight, filterWidth, padTop, padRight, padBottom, padLeft, dilationHeight, dilationWidth, strideHeight, strideWidth, inputChannels, outputChannels, outId);
|
return out;
|
}
|
var maxPoolConfig = {
|
kernelName: tfjsCore.MaxPool,
|
backendName: 'wasm',
|
setupFunc: setup$m,
|
kernelFunc: maxPool
|
};
|
|
/**
|
* @license
|
* Copyright 2020 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var wasmMean;
|
function setup$n(backend) {
|
wasmMean =
|
backend.wasm.cwrap(tfjsCore.Mean, null /*void*/, ['number, number, number']);
|
}
|
function mean(args) {
|
var backend = args.backend, inputs = args.inputs, attrs = args.attrs;
|
var axis = attrs.axis, keepDims = attrs.keepDims;
|
var x = inputs.x;
|
var xId = backend.dataIdMap.get(x.dataId).id;
|
var inputId = xId;
|
var input = x;
|
var _a = permuteAxesAndTranspose(x, axis, backend), transposed = _a.transposed, axes = _a.axes, originalAxes = _a.originalAxes, inputWasTransposed = _a.inputWasTransposed;
|
var reductionAxes = axes;
|
if (inputWasTransposed) {
|
var transposedId = backend.dataIdMap.get(transposed.dataId).id;
|
if (transposedId !== xId) {
|
// transpose was not a no-op. We will need to dispose of this
|
// once we are done.
|
input = transposed;
|
inputId = transposedId;
|
reductionAxes = tfjsCore.backend_util.getInnerMostAxes(reductionAxes.length, input.shape.length);
|
}
|
}
|
tfjsCore.backend_util.assertAxesAreInnerMostDims('mean', reductionAxes, input.shape.length);
|
var _b = tfjsCore.backend_util.computeOutAndReduceShapes(input.shape, reductionAxes), outShape = _b[0], reduceShape = _b[1];
|
var reduceSize = tfjsCore.util.sizeFromShape(reduceShape);
|
var castedInput = input;
|
if (input.dtype !== 'float32') {
|
castedInput =
|
cast({ backend: backend, inputs: { x: input }, attrs: { dtype: 'float32' } });
|
inputId = backend.dataIdMap.get(castedInput.dataId).id;
|
}
|
var out = backend.makeOutput(outShape, 'float32');
|
if (tfjsCore.util.sizeFromShape(input.shape) !== 0) {
|
var outId = backend.dataIdMap.get(out.dataId).id;
|
wasmMean(inputId, reduceSize, outId);
|
}
|
if (inputWasTransposed) {
|
// dispose of the transposed tensor.
|
backend.disposeData(transposed.dataId);
|
}
|
if (keepDims) {
|
// reshape
|
var newShape = tfjsCore.backend_util.expandShapeToKeepDim(out.shape, originalAxes);
|
out.shape = newShape;
|
}
|
if (input.dtype !== 'float32') {
|
backend.disposeData(castedInput.dataId);
|
}
|
return out;
|
}
|
var meanConfig = {
|
kernelName: tfjsCore.Mean,
|
backendName: 'wasm',
|
setupFunc: setup$n,
|
kernelFunc: mean
|
};
|
|
/**
|
* @license
|
* Copyright 2019 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var wasmMin;
|
function setup$o(backend) {
|
wasmMin = backend.wasm.cwrap(tfjsCore.Min, null /*void*/, [
|
'number',
|
'number',
|
'number',
|
'number',
|
]);
|
}
|
function min(args) {
|
var backend = args.backend, inputs = args.inputs, attrs = args.attrs;
|
var axis = attrs.axis, keepDims = attrs.keepDims;
|
var x = inputs.x;
|
var xId = backend.dataIdMap.get(x.dataId).id;
|
var inputId = xId;
|
var input = x;
|
var _a = permuteAxesAndTranspose(x, axis, backend), transposed = _a.transposed, axes = _a.axes, originalAxes = _a.originalAxes, inputWasTransposed = _a.inputWasTransposed;
|
if (inputWasTransposed) {
|
var transposedId = backend.dataIdMap.get(transposed.dataId).id;
|
if (transposedId !== xId) {
|
// transpose was not a no-op. We will need to dispose of this
|
// once we are done.
|
input = transposed;
|
inputId = transposedId;
|
}
|
}
|
var inputRank = input.shape.length;
|
tfjsCore.backend_util.assertAxesAreInnerMostDims('min', axes, inputRank);
|
var _b = tfjsCore.backend_util.computeOutAndReduceShapes(input.shape, axes), outShape = _b[0], reduceShape = _b[1];
|
var reduceSize = tfjsCore.util.sizeFromShape(reduceShape);
|
var out = backend.makeOutput(outShape, input.dtype);
|
if (tfjsCore.util.sizeFromShape(input.shape) !== 0) {
|
var outId = backend.dataIdMap.get(out.dataId).id;
|
wasmMin(inputId, CppDType[x.dtype], reduceSize, outId);
|
}
|
if (inputWasTransposed) {
|
// dispose of the transposed tensor.
|
backend.disposeData(transposed.dataId);
|
}
|
if (keepDims) {
|
// reshape
|
var newShape = tfjsCore.backend_util.expandShapeToKeepDim(out.shape, originalAxes);
|
out.shape = newShape;
|
}
|
return out;
|
}
|
var minConfig = {
|
kernelName: tfjsCore.Min,
|
backendName: 'wasm',
|
setupFunc: setup$o,
|
kernelFunc: min
|
};
|
|
/**
|
* @license
|
* Copyright 2019 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var minimumConfig = createBinaryKernelConfig(tfjsCore.Minimum);
|
|
/**
|
* @license
|
* Copyright 2021 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
// Must match enum in MirrorPad.cc
|
var MirrorPaddingMode;
|
(function (MirrorPaddingMode) {
|
MirrorPaddingMode[MirrorPaddingMode["reflect"] = 0] = "reflect";
|
MirrorPaddingMode[MirrorPaddingMode["symmetric"] = 1] = "symmetric";
|
})(MirrorPaddingMode || (MirrorPaddingMode = {}));
|
var wasmMirrorPad;
|
function setup$p(backend) {
|
wasmMirrorPad = backend.wasm.cwrap(tfjsCore.MirrorPad, null /* void */, [
|
'number',
|
'array',
|
'number',
|
'number',
|
'array',
|
'array',
|
'number',
|
'number',
|
]);
|
}
|
function mirrorPad(args) {
|
var x = args.inputs.x, backend = args.backend, _a = args.attrs, paddings = _a.paddings, mode = _a.mode;
|
var outShape = paddings.map(function (p, i) { return p[0] /* beforePad */ + x.shape[i] + p[1]; } /* afterPad */);
|
var xId = backend.dataIdMap.get(x.dataId).id;
|
var out = backend.makeOutput(outShape, x.dtype);
|
var outId = backend.dataIdMap.get(out.dataId).id;
|
var xShapeBytes = new Uint8Array(new Int32Array(x.shape).buffer);
|
var prePaddingsFlat = paddings.map(function (padTuple) { return padTuple[0]; });
|
var postPaddingsFlat = paddings.map(function (padTuple) { return padTuple[1]; });
|
var prePaddingsBytes = new Uint8Array(new Int32Array(prePaddingsFlat).buffer);
|
var postPaddingsBytes = new Uint8Array(new Int32Array(postPaddingsFlat).buffer);
|
wasmMirrorPad(xId, xShapeBytes, x.shape.length, CppDType[x.dtype], prePaddingsBytes, postPaddingsBytes, MirrorPaddingMode[mode], outId);
|
return out;
|
}
|
var mirrorPadConfig = {
|
kernelName: tfjsCore.MirrorPad,
|
backendName: 'wasm',
|
kernelFunc: mirrorPad,
|
setupFunc: setup$p
|
};
|
|
/**
|
* @license
|
* Copyright 2019 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var multiplyConfig = createBinaryKernelConfig(tfjsCore.Multiply);
|
|
/**
|
* @license
|
* Copyright 2020 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var negConfig = createUnaryKernelConfig(tfjsCore.Neg);
|
|
/**
|
* @license
|
* Copyright 2019 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
/**
|
* Parse the result of the c++ method, which has the shape equivalent to
|
* `Result`.
|
*/
|
function parseResultStruct(backend, resOffset) {
|
var result = new Int32Array(backend.wasm.HEAPU8.buffer, resOffset, 4);
|
var pSelectedIndices = result[0];
|
var selectedSize = result[1];
|
var pSelectedScores = result[2];
|
var pValidOutputs = result[3];
|
// Since the result was allocated on the heap, we have to delete it.
|
backend.wasm._free(resOffset);
|
return { pSelectedIndices: pSelectedIndices, selectedSize: selectedSize, pSelectedScores: pSelectedScores, pValidOutputs: pValidOutputs };
|
}
|
|
/**
|
* @license
|
* Copyright 2019 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var wasmFunc$3;
|
function setup$q(backend) {
|
wasmFunc$3 = backend.wasm.cwrap(tfjsCore.NonMaxSuppressionV3, 'number', // Result*
|
[
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
]);
|
}
|
function kernelFunc(args) {
|
var backend = args.backend, inputs = args.inputs, attrs = args.attrs;
|
var iouThreshold = attrs.iouThreshold, maxOutputSize = attrs.maxOutputSize, scoreThreshold = attrs.scoreThreshold;
|
var boxes = inputs.boxes, scores = inputs.scores;
|
var boxesId = backend.dataIdMap.get(boxes.dataId).id;
|
var scoresId = backend.dataIdMap.get(scores.dataId).id;
|
var resOffset = wasmFunc$3(boxesId, scoresId, maxOutputSize, iouThreshold, scoreThreshold);
|
var _a = parseResultStruct(backend, resOffset), pSelectedIndices = _a.pSelectedIndices, selectedSize = _a.selectedSize, pSelectedScores = _a.pSelectedScores, pValidOutputs = _a.pValidOutputs;
|
// Since we are not using scores for V3, we have to delete it from the heap.
|
backend.wasm._free(pSelectedScores);
|
backend.wasm._free(pValidOutputs);
|
var selectedIndicesTensor = backend.makeOutput([selectedSize], 'int32', pSelectedIndices);
|
return selectedIndicesTensor;
|
}
|
var nonMaxSuppressionV3Config = {
|
kernelName: tfjsCore.NonMaxSuppressionV3,
|
backendName: 'wasm',
|
setupFunc: setup$q,
|
kernelFunc: kernelFunc,
|
};
|
|
/**
|
* @license
|
* Copyright 2020 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var wasmFunc$4;
|
function setup$r(backend) {
|
wasmFunc$4 = backend.wasm.cwrap(tfjsCore.NonMaxSuppressionV4, 'number', // Result*
|
[
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'bool',
|
]);
|
}
|
function nonMaxSuppressionV4(args) {
|
var backend = args.backend, inputs = args.inputs, attrs = args.attrs;
|
var iouThreshold = attrs.iouThreshold, maxOutputSize = attrs.maxOutputSize, scoreThreshold = attrs.scoreThreshold, padToMaxOutputSize = attrs.padToMaxOutputSize;
|
var boxes = inputs.boxes, scores = inputs.scores;
|
var boxesId = backend.dataIdMap.get(boxes.dataId).id;
|
var scoresId = backend.dataIdMap.get(scores.dataId).id;
|
var resOffset = wasmFunc$4(boxesId, scoresId, maxOutputSize, iouThreshold, scoreThreshold, padToMaxOutputSize);
|
var _a = parseResultStruct(backend, resOffset), pSelectedIndices = _a.pSelectedIndices, selectedSize = _a.selectedSize, pSelectedScores = _a.pSelectedScores, pValidOutputs = _a.pValidOutputs;
|
// Since we are not using scores for V4, we have to delete it from the heap.
|
backend.wasm._free(pSelectedScores);
|
var selectedIndicesTensor = backend.makeOutput([selectedSize], 'int32', pSelectedIndices);
|
var validOutputsTensor = backend.makeOutput([], 'int32', pValidOutputs);
|
return [selectedIndicesTensor, validOutputsTensor];
|
}
|
var nonMaxSuppressionV4Config = {
|
kernelName: tfjsCore.NonMaxSuppressionV4,
|
backendName: 'wasm',
|
setupFunc: setup$r,
|
kernelFunc: nonMaxSuppressionV4,
|
};
|
|
/**
|
* @license
|
* Copyright 2019 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var wasmFunc$5;
|
function setup$s(backend) {
|
wasmFunc$5 = backend.wasm.cwrap(tfjsCore.NonMaxSuppressionV5, 'number', // Result*
|
[
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
]);
|
}
|
function kernelFunc$1(args) {
|
var backend = args.backend, inputs = args.inputs, attrs = args.attrs;
|
var iouThreshold = attrs.iouThreshold, maxOutputSize = attrs.maxOutputSize, scoreThreshold = attrs.scoreThreshold, softNmsSigma = attrs.softNmsSigma;
|
var boxes = inputs.boxes, scores = inputs.scores;
|
var boxesId = backend.dataIdMap.get(boxes.dataId).id;
|
var scoresId = backend.dataIdMap.get(scores.dataId).id;
|
var resOffset = wasmFunc$5(boxesId, scoresId, maxOutputSize, iouThreshold, scoreThreshold, softNmsSigma);
|
var _a = parseResultStruct(backend, resOffset), pSelectedIndices = _a.pSelectedIndices, selectedSize = _a.selectedSize, pSelectedScores = _a.pSelectedScores, pValidOutputs = _a.pValidOutputs;
|
// Since we are not using validOutputs for V5, we have to delete it from the
|
// heap.
|
backend.wasm._free(pValidOutputs);
|
var selectedIndicesTensor = backend.makeOutput([selectedSize], 'int32', pSelectedIndices);
|
var selectedScoresTensor = backend.makeOutput([selectedSize], 'float32', pSelectedScores);
|
return [selectedIndicesTensor, selectedScoresTensor];
|
}
|
var nonMaxSuppressionV5Config = {
|
kernelName: tfjsCore.NonMaxSuppressionV5,
|
backendName: 'wasm',
|
setupFunc: setup$s,
|
kernelFunc: kernelFunc$1,
|
};
|
|
/**
|
* @license
|
* Copyright 2020 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var supportsFullBroadcast$6 = false;
|
var notEqualConfig = createBinaryKernelConfig(tfjsCore.NotEqual, supportsFullBroadcast$6, 'bool');
|
|
/**
|
* @license
|
* Copyright 2020 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var wasmOneHot;
|
function setup$t(backend) {
|
wasmOneHot = backend.wasm.cwrap(tfjsCore.OneHot, null /* void */, [
|
'number',
|
'number',
|
'number',
|
'number',
|
'number' // out_id
|
]);
|
}
|
function oneHot(args) {
|
var inputs = args.inputs, backend = args.backend, attrs = args.attrs;
|
var indices = inputs.indices;
|
var depth = attrs.depth, onValue = attrs.onValue, offValue = attrs.offValue;
|
var out = backend.makeOutput(indices.shape.concat([depth]), 'int32');
|
var outId = backend.dataIdMap.get(out.dataId).id;
|
var indicesData = backend.dataIdMap.get(indices.dataId);
|
var indicesId = indicesData.id;
|
wasmOneHot(indicesId, depth, onValue, offValue, outId);
|
return out;
|
}
|
var oneHotConfig = {
|
kernelName: tfjsCore.OneHot,
|
backendName: 'wasm',
|
setupFunc: setup$t,
|
kernelFunc: oneHot,
|
};
|
|
/**
|
* @license
|
* Copyright 2020 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
function onesLike(args) {
|
var x = args.inputs.x, backend = args.backend;
|
var out = backend.makeOutput(x.shape, x.dtype);
|
var outVals = backend.typedArrayFromHeap(out);
|
outVals.fill(1);
|
return out;
|
}
|
var onesLikeConfig = {
|
kernelName: tfjsCore.OnesLike,
|
backendName: 'wasm',
|
kernelFunc: onesLike,
|
};
|
|
/**
|
* @license
|
* Copyright 2020 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
function pack(args) {
|
var inputs = args.inputs, backend = args.backend, attrs = args.attrs;
|
var axis = attrs.axis;
|
if (inputs.length === 1) {
|
return expandDims({ inputs: { input: inputs[0] }, backend: backend, attrs: { dim: axis } });
|
}
|
var shape = inputs[0].shape;
|
var dtype = inputs[0].dtype;
|
inputs.forEach(function (t) {
|
tfjsCore.util.assertShapesMatch(shape, t.shape, 'All tensors passed to stack must have matching shapes');
|
tfjsCore.util.assert(dtype === t.dtype, function () { return 'All tensors passed to stack must have matching dtypes'; });
|
});
|
var intermediateTensorInfos = [];
|
var expandedTensors = inputs.map(function (t) {
|
var expandedT = expandDims({ inputs: { input: t }, backend: backend, attrs: { dim: axis } });
|
intermediateTensorInfos.push(expandedT);
|
return expandedT;
|
});
|
var result = concat({ inputs: expandedTensors, backend: backend, attrs: { axis: axis } });
|
intermediateTensorInfos.forEach(function (t) { return backend.disposeData(t.dataId); });
|
return result;
|
}
|
var packConfig = {
|
kernelName: tfjsCore.Pack,
|
backendName: 'wasm',
|
kernelFunc: pack
|
};
|
|
/**
|
* @license
|
* Copyright 2019 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var wasmPadV2;
|
function setup$u(backend) {
|
wasmPadV2 = backend.wasm.cwrap(tfjsCore.PadV2, null /* void */, [
|
'number',
|
'array',
|
'number',
|
'number',
|
'array',
|
'array',
|
'number',
|
'number',
|
]);
|
}
|
function pad(args) {
|
var x = args.inputs.x, backend = args.backend, _a = args.attrs, paddings = _a.paddings, constantValue = _a.constantValue;
|
var outShape = paddings.map(function (p, i) { return p[0] /* beforePad */ + x.shape[i] + p[1]; } /* afterPad */);
|
if (tfjsCore.util.sizeFromShape(x.shape) === 0) {
|
// Short-circuit the computation, since x doesn't have value, only
|
// the shape is used to compute output shape to pad.
|
return fill({
|
backend: backend,
|
attrs: { shape: outShape, value: constantValue, dtype: x.dtype }
|
});
|
}
|
var xId = backend.dataIdMap.get(x.dataId).id;
|
var out = backend.makeOutput(outShape, x.dtype);
|
var outTensorData = backend.dataIdMap.get(out.dataId);
|
var outId = outTensorData.id;
|
var xShapeBytes = new Uint8Array(new Int32Array(x.shape).buffer);
|
var prePaddingsFlat = paddings.map(function (padTuple) { return padTuple[0]; });
|
var postPaddingsFlat = paddings.map(function (padTuple) { return padTuple[1]; });
|
var prePaddingsBytes = new Uint8Array(new Int32Array(prePaddingsFlat).buffer);
|
var postPaddingsBytes = new Uint8Array(new Int32Array(postPaddingsFlat).buffer);
|
wasmPadV2(xId, xShapeBytes, x.shape.length, CppDType[x.dtype], prePaddingsBytes, postPaddingsBytes, constantValue, outId);
|
return out;
|
}
|
var padV2Config = {
|
kernelName: tfjsCore.PadV2,
|
backendName: 'wasm',
|
kernelFunc: pad,
|
setupFunc: setup$u
|
};
|
|
/**
|
* @license
|
* Copyright 2019 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var powConfig = createBinaryKernelConfig(tfjsCore.Pow);
|
|
/**
|
* @license
|
* Copyright 2019 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var wasmPrelu;
|
function setup$v(backend) {
|
wasmPrelu = backend.wasm.cwrap(tfjsCore.Prelu, null /* void */, [
|
'number',
|
'number',
|
'number' // out_id
|
]);
|
}
|
function prelu(args) {
|
var inputs = args.inputs, backend = args.backend;
|
var x = inputs.x, alpha = inputs.alpha;
|
var xId = backend.dataIdMap.get(x.dataId).id;
|
var weightsId = backend.dataIdMap.get(alpha.dataId).id;
|
var inputId = xId;
|
var input = x;
|
var castedInput = input;
|
if (input.dtype !== 'float32') {
|
castedInput = cast({ backend: backend, inputs: { x: x }, attrs: { dtype: 'float32' } });
|
inputId = backend.dataIdMap.get(castedInput.dataId).id;
|
}
|
var out = backend.makeOutput(x.shape, 'float32');
|
var outId = backend.dataIdMap.get(out.dataId).id;
|
wasmPrelu(inputId, weightsId, outId);
|
if (input.dtype !== 'float32') {
|
backend.disposeData(castedInput.dataId);
|
}
|
return out;
|
}
|
var preluConfig = {
|
kernelName: tfjsCore.Prelu,
|
backendName: 'wasm',
|
setupFunc: setup$v,
|
kernelFunc: prelu
|
};
|
|
/**
|
* @license
|
* Copyright 2020 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var wasmProd;
|
function setup$w(backend) {
|
wasmProd = backend.wasm.cwrap(tfjsCore.Prod, null /*void*/, [
|
'number',
|
'number',
|
'number',
|
'number'
|
]);
|
}
|
function prod(args) {
|
var backend = args.backend, inputs = args.inputs, attrs = args.attrs;
|
var axis = attrs.axis, keepDims = attrs.keepDims;
|
var x = inputs.x;
|
var xId = backend.dataIdMap.get(x.dataId).id;
|
var inputId = xId;
|
var input = x;
|
var _a = permuteAxesAndTranspose(x, axis, backend), transposed = _a.transposed, axes = _a.axes, originalAxes = _a.originalAxes, inputWasTransposed = _a.inputWasTransposed;
|
var reductionAxes = axes;
|
if (inputWasTransposed) {
|
var transposedId = backend.dataIdMap.get(transposed.dataId).id;
|
if (transposedId !== xId) {
|
// transpose was not a no-op. We will need to dispose of this
|
// once we are done.
|
input = transposed;
|
inputId = transposedId;
|
reductionAxes = tfjsCore.backend_util.getInnerMostAxes(reductionAxes.length, input.shape.length);
|
}
|
}
|
tfjsCore.backend_util.assertAxesAreInnerMostDims('prod', reductionAxes, input.shape.length);
|
var _b = tfjsCore.backend_util.computeOutAndReduceShapes(input.shape, reductionAxes), outShape = _b[0], reduceShape = _b[1];
|
var reduceSize = tfjsCore.util.sizeFromShape(reduceShape);
|
var out = backend.makeOutput(outShape, input.dtype);
|
if (tfjsCore.util.sizeFromShape(input.shape) !== 0) {
|
var outId = backend.dataIdMap.get(out.dataId).id;
|
wasmProd(inputId, reduceSize, CppDType[out.dtype], outId);
|
}
|
if (inputWasTransposed) {
|
// dispose of the transposed tensor.
|
backend.disposeData(transposed.dataId);
|
}
|
if (keepDims) {
|
// reshape
|
var newShape = tfjsCore.backend_util.expandShapeToKeepDim(out.shape, originalAxes);
|
out.shape = newShape;
|
}
|
return out;
|
}
|
var prodConfig = {
|
kernelName: tfjsCore.Prod,
|
backendName: 'wasm',
|
setupFunc: setup$w,
|
kernelFunc: prod
|
};
|
|
/**
|
* @license
|
* Copyright 2020 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var range = function (args) {
|
var backend = args.backend, attrs = args.attrs;
|
var start = attrs.start, stop = attrs.stop, step = attrs.step, dtype = attrs.dtype;
|
var values = rangeImpl(start, stop, step, dtype);
|
var out = backend.makeOutput([values.length], dtype);
|
var outVals = backend.typedArrayFromHeap(out);
|
outVals.set(values);
|
return out;
|
};
|
var rangeConfig = {
|
kernelName: tfjsCore.Range,
|
backendName: 'wasm',
|
kernelFunc: range
|
};
|
|
/**
|
* @license
|
* Copyright 2019 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var realDivConfig = createBinaryKernelConfig(tfjsCore.RealDiv);
|
|
/**
|
* @license
|
* Copyright 2019 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var reluConfig = createUnaryKernelConfig(tfjsCore.Relu);
|
|
/**
|
* @license
|
* Copyright 2019 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var relu6Config = createUnaryKernelConfig(tfjsCore.Relu6);
|
|
/**
|
* @license
|
* Copyright 2019 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var wasmResizeBilinear;
|
function setup$x(backend) {
|
wasmResizeBilinear = backend.wasm.cwrap(tfjsCore.ResizeBilinear, null /*void*/, [
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number' // outId
|
]);
|
}
|
function resizeBilinear(args) {
|
var backend = args.backend, inputs = args.inputs, attrs = args.attrs;
|
var images = inputs.images;
|
var alignCorners = attrs.alignCorners, halfPixelCenters = attrs.halfPixelCenters, size = attrs.size;
|
var newHeight = size[0], newWidth = size[1];
|
var _a = images.shape, batch = _a[0], oldHeight = _a[1], oldWidth = _a[2], numChannels = _a[3];
|
var outShape = [batch, newHeight, newWidth, numChannels];
|
var xData = backend.dataIdMap.get(images.dataId);
|
var castedData;
|
if (xData.dtype !== 'float32') {
|
castedData =
|
cast({ backend: backend, inputs: { x: images }, attrs: { dtype: 'float32' } });
|
xData = backend.dataIdMap.get(castedData.dataId);
|
}
|
var xId = xData.id;
|
var out = backend.makeOutput(outShape, 'float32');
|
if (tfjsCore.util.sizeFromShape(images.shape) === 0) {
|
return out;
|
}
|
var outId = backend.dataIdMap.get(out.dataId).id;
|
wasmResizeBilinear(xId, batch, oldHeight, oldWidth, numChannels, newHeight, newWidth, alignCorners ? 1 : 0, halfPixelCenters ? 1 : 0, outId);
|
if (castedData != null) {
|
backend.disposeData(castedData.dataId);
|
}
|
return out;
|
}
|
var resizeBilinearConfig = {
|
kernelName: tfjsCore.ResizeBilinear,
|
backendName: 'wasm',
|
setupFunc: setup$x,
|
kernelFunc: resizeBilinear
|
};
|
|
/**
|
* @license
|
* Copyright 2020 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var wasmReverse;
|
function setup$y(backend) {
|
wasmReverse = backend.wasm.cwrap(tfjsCore.Reverse, null, [
|
'number',
|
'array',
|
'number',
|
'array',
|
'number',
|
'number' // out_id
|
]);
|
}
|
function reverse(args) {
|
var inputs = args.inputs, backend = args.backend, attrs = args.attrs;
|
var x = inputs.x;
|
var dims = attrs.dims;
|
var axes = tfjsCore.util.parseAxisParam(dims, x.shape);
|
if (x.shape.length === 0) {
|
return identity({ inputs: { x: x }, backend: backend });
|
}
|
var out = backend.makeOutput(x.shape, x.dtype);
|
var xId = backend.dataIdMap.get(x.dataId).id;
|
var outId = backend.dataIdMap.get(out.dataId).id;
|
var axesBytes = new Uint8Array(new Int32Array(axes).buffer);
|
var outShapeBytes = new Uint8Array(new Int32Array(x.shape).buffer);
|
wasmReverse(xId, axesBytes, axes.length, outShapeBytes, x.shape.length, outId);
|
var reshaped = reshape({ inputs: { x: out }, attrs: { shape: x.shape }, backend: backend });
|
backend.disposeData(out.dataId);
|
return reshaped;
|
}
|
var reverseConfig = {
|
kernelName: tfjsCore.Reverse,
|
backendName: 'wasm',
|
kernelFunc: reverse,
|
setupFunc: setup$y
|
};
|
|
/**
|
* @license
|
* Copyright 2019 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var wasmRotate;
|
function setup$z(backend) {
|
wasmRotate = backend.wasm.cwrap(tfjsCore.RotateWithOffset, null /* void */, [
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'array',
|
'number',
|
'number',
|
]);
|
}
|
function rotateWithOffset(args) {
|
var inputs = args.inputs, backend = args.backend, attrs = args.attrs;
|
var image = inputs.image;
|
var radians = attrs.radians, fillValue = attrs.fillValue, center = attrs.center;
|
var out = backend.makeOutput(image.shape, image.dtype);
|
var imageId = backend.dataIdMap.get(image.dataId).id;
|
var outId = backend.dataIdMap.get(out.dataId).id;
|
var _a = image.shape, batch = _a[0], imageHeight = _a[1], imageWidth = _a[2], numChannels = _a[3];
|
var _b = tfjsCore.backend_util.getImageCenter(center, imageHeight, imageWidth), centerX = _b[0], centerY = _b[1];
|
var fillIsBlack = fillValue === 0;
|
var fullOpacityValue = 255;
|
var fillValues = typeof fillValue === 'number' ?
|
[fillValue, fillValue, fillValue, fillIsBlack ? 0 : fullOpacityValue] : fillValue.concat([fullOpacityValue]);
|
var fillBytes = new Uint8Array(new Int32Array(fillValues).buffer);
|
wasmRotate(imageId, batch, imageHeight, imageWidth, numChannels, radians, centerX, centerY, fillBytes, fillValues.length, outId);
|
return out;
|
}
|
var rotateWithOffsetConfig = {
|
kernelName: tfjsCore.RotateWithOffset,
|
backendName: 'wasm',
|
kernelFunc: rotateWithOffset,
|
setupFunc: setup$z
|
};
|
|
/**
|
* @license
|
* Copyright 2021 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var roundConfig = createUnaryKernelConfig(tfjsCore.Round);
|
|
/**
|
* @license
|
* Copyright 2019 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var rsqrtConfig = createUnaryKernelConfig(tfjsCore.Rsqrt);
|
|
/**
|
* @license
|
* Copyright 2019 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var wasmScatterNd;
|
function setup$A(backend) {
|
wasmScatterNd = backend.wasm.cwrap(tfjsCore.ScatterNd, null /*void*/, [
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'array',
|
'number',
|
'number' // outId
|
]);
|
}
|
function scatterNd(args) {
|
var backend = args.backend, inputs = args.inputs, attrs = args.attrs;
|
var indices = inputs.indices, updates = inputs.updates;
|
var shape = attrs.shape;
|
var out = backend.makeOutput(shape, updates.dtype);
|
if (tfjsCore.util.sizeFromShape(shape) === 0) {
|
return out;
|
}
|
var _a = tfjsCore.scatter_util.calculateShapes(updates, indices, shape), sliceRank = _a.sliceRank, numUpdates = _a.numUpdates, sliceSize = _a.sliceSize, strides = _a.strides, outputSize = _a.outputSize;
|
var indicesData = backend.dataIdMap.get(indices.dataId);
|
var indicesId = indicesData.id;
|
var updatesData = backend.dataIdMap.get(updates.dataId);
|
var updatesId = updatesData.id;
|
var stridesBytes = new Uint8Array(new Int32Array(strides).buffer);
|
var outId = backend.dataIdMap.get(out.dataId).id;
|
wasmScatterNd(indicesId, updatesId, CppDType[updates.dtype], sliceRank, numUpdates, sliceSize, stridesBytes, outputSize, outId);
|
return out;
|
}
|
var scatterNdConfig = {
|
kernelName: tfjsCore.ScatterNd,
|
backendName: 'wasm',
|
setupFunc: setup$A,
|
kernelFunc: scatterNd
|
};
|
|
/**
|
* @license
|
* Copyright 2020 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var wasmSelect;
|
function setup$B(backend) {
|
wasmSelect = backend.wasm.cwrap('SelectV2', null, [
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
]);
|
}
|
function select(args) {
|
var inputs = args.inputs, backend = args.backend;
|
var condition = inputs.condition, t = inputs.t, e = inputs.e;
|
var conditionId = backend.dataIdMap.get(condition.dataId).id;
|
var tId = backend.dataIdMap.get(t.dataId).id;
|
var eId = backend.dataIdMap.get(e.dataId).id;
|
var out = backend.makeOutput(t.shape, t.dtype);
|
var outId = backend.dataIdMap.get(out.dataId).id;
|
var cRank = condition.shape.length;
|
var tRank = t.shape.length;
|
var offset = cRank === 0 || cRank > 1 || tRank === 1 ?
|
1 :
|
tfjsCore.util.sizeFromShape(t.shape.slice(1));
|
wasmSelect(conditionId, tId, eId, offset, outId);
|
return out;
|
}
|
var selectConfig = {
|
kernelName: tfjsCore.Select,
|
backendName: 'wasm',
|
kernelFunc: select,
|
setupFunc: setup$B
|
};
|
|
/**
|
* @license
|
* Copyright 2019 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var wasmFunc$6;
|
function setup$C(backend) {
|
wasmFunc$6 = backend.wasm.cwrap(tfjsCore.Sigmoid, null /* void */, ['number', 'number']);
|
}
|
function sigmoid(args) {
|
var backend = args.backend, x = args.inputs.x;
|
var xId = backend.dataIdMap.get(x.dataId).id;
|
var out = backend.makeOutput(x.shape, x.dtype);
|
var outId = backend.dataIdMap.get(out.dataId).id;
|
// Short-circuit zero-sized tensors.
|
if (tfjsCore.util.sizeFromShape(out.shape) === 0) {
|
return out;
|
}
|
wasmFunc$6(xId, outId);
|
return out;
|
}
|
var sigmoidConfig = {
|
kernelName: 'Sigmoid',
|
backendName: 'wasm',
|
setupFunc: setup$C,
|
kernelFunc: sigmoid
|
};
|
|
/**
|
* @license
|
* Copyright 2019 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var sinConfig = createUnaryKernelConfig(tfjsCore.Sin);
|
|
/**
|
* @license
|
* Copyright 2020 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var wasmFunc$7;
|
function setup$D(backend) {
|
wasmFunc$7 = backend.wasm.cwrap(tfjsCore.Softmax, null /* void */, [
|
'number',
|
'number',
|
'number',
|
'number' // batch
|
]);
|
}
|
function softmax(args) {
|
var backend = args.backend, logits = args.inputs.logits, dim = args.attrs.dim;
|
var xId = backend.dataIdMap.get(logits.dataId).id;
|
var out = backend.makeOutput(logits.shape, logits.dtype);
|
var outId = backend.dataIdMap.get(out.dataId).id;
|
var channels = logits.shape[dim];
|
var batch = tfjsCore.util.sizeFromShape(logits.shape) / channels;
|
// Short-circuit zero-sized tensors.
|
if (tfjsCore.util.sizeFromShape(out.shape) === 0) {
|
return out;
|
}
|
wasmFunc$7(xId, outId, channels, batch);
|
return out;
|
}
|
var softmaxConfig = {
|
kernelName: tfjsCore.Softmax,
|
backendName: 'wasm',
|
setupFunc: setup$D,
|
kernelFunc: softmax
|
};
|
|
/**
|
* @license
|
* Copyright 2021 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
function spaceToBatchND(args) {
|
var inputs = args.inputs, backend = args.backend, attrs = args.attrs;
|
var x = inputs.x;
|
var blockShape = attrs.blockShape, paddings = attrs.paddings;
|
var prod = tfjsCore.util.sizeFromShape(blockShape);
|
var completePaddings = [[0, 0]];
|
completePaddings.push.apply(completePaddings, paddings);
|
for (var i = 1 + blockShape.length; i < x.shape.length; ++i) {
|
completePaddings.push([0, 0]);
|
}
|
var paddedX = padV2Config.kernelFunc({
|
inputs: { x: x },
|
backend: backend,
|
attrs: { paddings: completePaddings, constantValue: 0 }
|
});
|
var reshapedPaddedShape = tfjsCore.backend_util.getReshaped(paddedX.shape, blockShape, prod, false);
|
var permutedReshapedPaddedPermutation = tfjsCore.backend_util.getPermuted(reshapedPaddedShape.length, blockShape.length, false);
|
var flattenShape = tfjsCore.backend_util.getReshapedPermuted(paddedX.shape, blockShape, prod, false);
|
var reshapeInputs = { x: paddedX };
|
var reshapeAttrs = { shape: reshapedPaddedShape };
|
var paddedXReshaped = reshape({ inputs: reshapeInputs, backend: backend, attrs: reshapeAttrs });
|
var transposeInputs = { x: paddedXReshaped };
|
var transposeAttrs = { perm: permutedReshapedPaddedPermutation };
|
var paddedXT = transpose({ inputs: transposeInputs, backend: backend, attrs: transposeAttrs });
|
var resultReshapeInputs = { x: paddedXT };
|
var resultReshapeAttrs = { shape: flattenShape };
|
var result = reshape({ inputs: resultReshapeInputs, backend: backend, attrs: resultReshapeAttrs });
|
backend.disposeData(paddedX.dataId);
|
backend.disposeData(paddedXReshaped.dataId);
|
backend.disposeData(paddedXT.dataId);
|
return result;
|
}
|
var spaceToBatchNDConfig = {
|
kernelName: tfjsCore.SpaceToBatchND,
|
backendName: 'wasm',
|
kernelFunc: spaceToBatchND
|
};
|
|
/**
|
* @license
|
* Copyright 2021 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var wasmSparseFillEmptyRows;
|
function setup$E(backend) {
|
wasmSparseFillEmptyRows =
|
backend.wasm.cwrap('SparseFillEmptyRows', 'number', [
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
]);
|
}
|
function sparseFillEmptyRows(args) {
|
var backend = args.backend, inputs = args.inputs;
|
var indices = inputs.indices, values = inputs.values, denseShape = inputs.denseShape, defaultValue = inputs.defaultValue;
|
var indicesCount = indices.shape[0];
|
var rank = indices.shape[1];
|
var denseRows = backend.readSync(denseShape.dataId)[0];
|
// Set output size to maximum possible and resize later (actual result
|
// might be smaller).
|
var maxOutputIndicesShape = [indicesCount + denseRows, rank];
|
var indicesId = backend.dataIdMap.get(indices.dataId).id;
|
var valuesId = backend.dataIdMap.get(values.dataId).id;
|
var defaultValueId = backend.dataIdMap.get(defaultValue.dataId).id;
|
var outputIndices = backend.makeOutput(maxOutputIndicesShape, indices.dtype);
|
var outputIndicesId = backend.dataIdMap.get(outputIndices.dataId).id;
|
var outputValues = backend.makeOutput(maxOutputIndicesShape.slice(0, 1), values.dtype);
|
var outputValuesId = backend.dataIdMap.get(outputValues.dataId).id;
|
var emptyRowIndicator = backend.makeOutput([denseRows], 'bool');
|
var emptyRowIndicatorId = backend.dataIdMap.get(emptyRowIndicator.dataId).id;
|
var reverseIndexMap = backend.makeOutput([indicesCount], indices.dtype);
|
var reverseIndexMapId = backend.dataIdMap.get(reverseIndexMap.dataId).id;
|
var exceptionValues = backend.makeOutput([4], 'int32');
|
var exceptionValuesId = backend.dataIdMap.get(exceptionValues.dataId).id;
|
var outputRows = wasmSparseFillEmptyRows(indicesId, valuesId, CppDType[values.dtype], indicesCount, denseRows, rank, defaultValueId, outputIndicesId, outputValuesId, emptyRowIndicatorId, reverseIndexMapId, exceptionValuesId);
|
var exceptionValuesArray = backend.readSync(exceptionValues.dataId);
|
var exceptionMessage;
|
switch (exceptionValuesArray[0]) {
|
case 1: {
|
exceptionMessage =
|
tfjsCore.backend_util.getSparseFillEmptyRowsIndicesDenseShapeMismatch(exceptionValuesArray[1]);
|
break;
|
}
|
case 2: {
|
exceptionMessage =
|
tfjsCore.backend_util.getSparseFillEmptyRowsNegativeIndexErrorMessage(exceptionValuesArray[1], exceptionValuesArray[2]);
|
break;
|
}
|
case 3:
|
exceptionMessage =
|
tfjsCore.backend_util.getSparseFillEmptyRowsOutOfRangeIndexErrorMessage(exceptionValuesArray[1], exceptionValuesArray[2], exceptionValuesArray[3]);
|
break;
|
default:
|
exceptionMessage = '';
|
}
|
backend.disposeData(exceptionValues.dataId);
|
if (exceptionMessage) {
|
backend.disposeData(outputIndices.dataId);
|
backend.disposeData(outputValues.dataId);
|
backend.disposeData(emptyRowIndicator.dataId);
|
backend.disposeData(reverseIndexMap.dataId);
|
throw new Error(exceptionMessage);
|
}
|
var resizedIndices = outputIndices;
|
var resizedValues = outputValues;
|
// Overestimated output size.
|
if (outputRows !== maxOutputIndicesShape[0]) {
|
resizedIndices = slice({
|
inputs: { x: outputIndices },
|
attrs: { begin: 0, size: [outputRows, rank] },
|
backend: backend
|
});
|
resizedValues = slice({
|
inputs: { x: outputValues },
|
attrs: { begin: 0, size: outputRows },
|
backend: backend
|
});
|
backend.disposeData(outputIndices.dataId);
|
backend.disposeData(outputValues.dataId);
|
}
|
return [resizedIndices, resizedValues, emptyRowIndicator, reverseIndexMap];
|
}
|
var sparseFillEmptyRowsConfig = {
|
kernelName: tfjsCore.SparseFillEmptyRows,
|
backendName: 'wasm',
|
setupFunc: setup$E,
|
kernelFunc: sparseFillEmptyRows
|
};
|
|
/**
|
* @license
|
* Copyright 2021 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var wasmSparseReshape;
|
function setup$F(backend) {
|
wasmSparseReshape = backend.wasm.cwrap(tfjsCore.SparseReshape, null /*void*/, [
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
]);
|
}
|
function sparseReshape(args) {
|
var backend = args.backend, inputs = args.inputs;
|
var inputIndices = inputs.inputIndices, inputShape = inputs.inputShape, newShape = inputs.newShape;
|
if (inputIndices.shape.length !== 2) {
|
throw new Error("Input indices should be a matrix but received shape\n " + inputIndices.shape);
|
}
|
if (inputShape.shape.length !== 1) {
|
throw new Error("Input shape should be a vector but received shape\n " + inputShape.shape);
|
}
|
if (newShape.shape.length !== 1) {
|
throw new Error("Target shape should be a vector but received shape " + newShape.shape);
|
}
|
var inputIndicesId = backend.dataIdMap.get(inputIndices.dataId).id;
|
var inputShapeId = backend.dataIdMap.get(inputShape.dataId).id;
|
var newShapeId = backend.dataIdMap.get(newShape.dataId).id;
|
var nnz = inputIndices.shape[0];
|
var outputRank = tfjsCore.util.sizeFromShape(newShape.shape);
|
var newIndices = backend.makeOutput([nnz, outputRank], inputIndices.dtype);
|
var newIndicesId = backend.dataIdMap.get(newIndices.dataId).id;
|
var outputShape = backend.makeOutput([outputRank], newShape.dtype);
|
var outputShapeId = backend.dataIdMap.get(outputShape.dataId).id;
|
var exceptionValues = backend.makeOutput([3], 'int32');
|
var exceptionValuesId = backend.dataIdMap.get(exceptionValues.dataId).id;
|
wasmSparseReshape(inputIndicesId, inputShapeId, newShapeId, nnz, newIndicesId, outputShapeId, exceptionValuesId);
|
var exceptionValuesArray = backend.readSync(exceptionValues.dataId);
|
var exceptionMessage;
|
switch (exceptionValuesArray[0]) {
|
case 0: {
|
exceptionMessage =
|
tfjsCore.backend_util.getSparseReshapeMultipleNegativeOneOutputDimErrorMessage(exceptionValuesArray[1], exceptionValuesArray[2]);
|
break;
|
}
|
case 1: {
|
exceptionMessage =
|
tfjsCore.backend_util.getSparseReshapeNegativeOutputDimErrorMessage(exceptionValuesArray[1], exceptionValuesArray[2]);
|
break;
|
}
|
case 2:
|
exceptionMessage =
|
tfjsCore.backend_util.getSparseReshapeEmptyTensorZeroOutputDimErrorMessage();
|
break;
|
case 3: {
|
var inputShapeValues = Array.from(backend.readSync(inputShape.dataId)), outputShapeValues = Array.from(backend.readSync(outputShape.dataId));
|
exceptionMessage =
|
tfjsCore.backend_util.getSparseReshapeInputOutputMultipleErrorMessage(inputShapeValues, outputShapeValues);
|
break;
|
}
|
case 4: {
|
var inputShapeValues = Array.from(backend.readSync(inputShape.dataId)), outputShapeValues = Array.from(backend.readSync(outputShape.dataId));
|
exceptionMessage =
|
tfjsCore.backend_util.getSparseReshapeInputOutputMismatchErrorMessage(inputShapeValues, outputShapeValues);
|
break;
|
}
|
default:
|
exceptionMessage = '';
|
}
|
backend.disposeData(exceptionValues.dataId);
|
if (exceptionMessage) {
|
backend.disposeData(newIndices.dataId);
|
backend.disposeData(outputShape.dataId);
|
throw new Error(exceptionMessage);
|
}
|
return [newIndices, outputShape];
|
}
|
var sparseReshapeConfig = {
|
kernelName: tfjsCore.SparseReshape,
|
backendName: 'wasm',
|
setupFunc: setup$F,
|
kernelFunc: sparseReshape
|
};
|
|
/**
|
* @license
|
* Copyright 2021 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var wasmSparseSegmentReduction;
|
function setup$G(backend) {
|
wasmSparseSegmentReduction =
|
backend.wasm.cwrap('SparseSegmentReduction', null /*void*/, [
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
]);
|
}
|
function sparseSegmentReduction(args, isMean) {
|
var backend = args.backend, inputs = args.inputs;
|
var data = inputs.data, indices = inputs.indices, segmentIds = inputs.segmentIds;
|
var numIndices = indices.shape[0];
|
var segmentIdsBack = backend.readSync(segmentIds.dataId, numIndices - 1, numIndices)[0];
|
var lastSegmentIdPlusOne = numIndices > 0 ? segmentIdsBack + 1 : 0;
|
var outputRows = lastSegmentIdPlusOne;
|
if (outputRows < 0) {
|
throw (new Error(tfjsCore.backend_util
|
.getSparseSegmentReductionNegativeSegmentIdsErrorMessage()));
|
}
|
var outputShape = data.shape.slice();
|
outputShape[0] = outputRows;
|
var dataId = backend.dataIdMap.get(data.dataId).id;
|
var indicesId = backend.dataIdMap.get(indices.dataId).id;
|
var segmentIdsId = backend.dataIdMap.get(segmentIds.dataId).id;
|
var output = backend.makeOutput(outputShape, data.dtype);
|
var outputId = backend.dataIdMap.get(output.dataId).id;
|
var exceptionValues = backend.makeOutput([4], 'int32');
|
var exceptionValuesId = backend.dataIdMap.get(exceptionValues.dataId).id;
|
wasmSparseSegmentReduction(dataId, CppDType[data.dtype], data.shape[0], indicesId, segmentIdsId, outputId, exceptionValuesId, isMean, 0);
|
var exceptionValuesArray = backend.readSync(exceptionValues.dataId);
|
var exceptionMessage;
|
switch (exceptionValuesArray[0]) {
|
case 0: {
|
exceptionMessage =
|
tfjsCore.backend_util
|
.getSparseSegmentReductionNegativeSegmentIdsErrorMessage();
|
break;
|
}
|
case 1: {
|
exceptionMessage =
|
tfjsCore.backend_util
|
.getSparseSegmentReductionNonIncreasingSegmentIdsErrorMessage();
|
break;
|
}
|
case 2:
|
exceptionMessage =
|
tfjsCore.backend_util.getSparseSegmentReductionSegmentIdOutOfRangeErrorMessage(exceptionValuesArray[1], exceptionValuesArray[2]);
|
break;
|
case 3:
|
exceptionMessage =
|
tfjsCore.backend_util.getSparseSegmentReductionIndicesOutOfRangeErrorMessage(exceptionValuesArray[1], exceptionValuesArray[2], exceptionValuesArray[3]);
|
break;
|
default:
|
exceptionMessage = '';
|
}
|
backend.disposeData(exceptionValues.dataId);
|
if (exceptionMessage) {
|
backend.disposeData(output.dataId);
|
throw new Error(exceptionMessage);
|
}
|
return output;
|
}
|
|
/**
|
* @license
|
* Copyright 2021 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
function sparseSegmentMean(args) {
|
return sparseSegmentReduction(args, true);
|
}
|
var sparseSegmentMeanConfig = {
|
kernelName: tfjsCore.SparseSegmentMean,
|
backendName: 'wasm',
|
setupFunc: setup$G,
|
kernelFunc: sparseSegmentMean
|
};
|
|
/**
|
* @license
|
* Copyright 2021 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
function sparseSegmentSum(args) {
|
return sparseSegmentReduction(args, false);
|
}
|
var sparseSegmentSumConfig = {
|
kernelName: tfjsCore.SparseSegmentSum,
|
backendName: 'wasm',
|
setupFunc: setup$G,
|
kernelFunc: sparseSegmentSum
|
};
|
|
/**
|
* @license
|
* Copyright 2020 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
function splitV(args) {
|
var inputs = args.inputs, attrs = args.attrs, backend = args.backend;
|
var x = inputs.x;
|
var numOrSizeSplits = attrs.numOrSizeSplits, axis = attrs.axis;
|
var $axis = tfjsCore.util.parseAxisParam(axis, x.shape)[0];
|
var splitSizes = tfjsCore.backend_util.prepareSplitSize(x, numOrSizeSplits, $axis);
|
var begin = new Array(x.shape.length).fill(0);
|
var size = x.shape.slice();
|
return splitSizes.map(function (s) {
|
var xSliceSize = size.slice();
|
xSliceSize[$axis] = s;
|
var xSlice = slice({ inputs: { x: x }, attrs: { begin: begin, size: xSliceSize }, backend: backend });
|
begin[$axis] += s;
|
return xSlice;
|
});
|
}
|
var splitVConfig = {
|
kernelName: tfjsCore.SplitV,
|
backendName: 'wasm',
|
kernelFunc: splitV
|
};
|
|
/**
|
* @license
|
* Copyright 2020 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var sqrtConfig = createUnaryKernelConfig(tfjsCore.Sqrt);
|
|
/**
|
* @license
|
* Copyright 2019 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var squareConfig = createUnaryKernelConfig(tfjsCore.Square);
|
|
/**
|
* @license
|
* Copyright 2019 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var squaredDifferenceConfig = createBinaryKernelConfig(tfjsCore.SquaredDifference);
|
|
/**
|
* @license
|
* Copyright 2020 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var wasmStep;
|
function setup$H(backend) {
|
wasmStep = backend.wasm.cwrap(tfjsCore.Step, null /*void*/, [
|
'number',
|
'number',
|
'number',
|
'number',
|
]);
|
}
|
function step(args) {
|
var backend = args.backend, inputs = args.inputs, attrs = args.attrs;
|
var alpha = attrs.alpha;
|
var x = inputs.x;
|
var xId = backend.dataIdMap.get(x.dataId).id;
|
var out = backend.makeOutput(x.shape, x.dtype);
|
var outId = backend.dataIdMap.get(out.dataId).id;
|
wasmStep(xId, alpha, CppDType[x.dtype], outId);
|
return out;
|
}
|
var stepConfig = {
|
kernelName: tfjsCore.Step,
|
backendName: 'wasm',
|
setupFunc: setup$H,
|
kernelFunc: step
|
};
|
|
/**
|
* @license
|
* Copyright 2021 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var wasmStridedSlice;
|
function setup$I(backend) {
|
wasmStridedSlice = backend.wasm.cwrap(tfjsCore.StridedSlice, null /*void*/, [
|
'number',
|
'array',
|
'number',
|
'array',
|
'array',
|
'array',
|
'array',
|
'array',
|
'number',
|
'number',
|
]);
|
}
|
function stridedSlice(args) {
|
var backend = args.backend, inputs = args.inputs, attrs = args.attrs;
|
var x = inputs.x;
|
var begin = attrs.begin, end = attrs.end, strides = attrs.strides, beginMask = attrs.beginMask, endMask = attrs.endMask, ellipsisMask = attrs.ellipsisMask, newAxisMask = attrs.newAxisMask, shrinkAxisMask = attrs.shrinkAxisMask;
|
var _a = tfjsCore.slice_util.sliceInfo(x.shape, begin, end, strides, beginMask, endMask, ellipsisMask, newAxisMask, shrinkAxisMask), finalShapeSparse = _a.finalShapeSparse, finalShape = _a.finalShape, isIdentity = _a.isIdentity, sliceDim0 = _a.sliceDim0, isSimpleSlice = _a.isSimpleSlice, $begin = _a.begin, $end = _a.end, $strides = _a.strides;
|
var result;
|
if (isIdentity) {
|
// Optimization #1, slice is a no-op plus reshape
|
result = reshape({ inputs: { x: x }, backend: backend, attrs: { shape: finalShape } });
|
}
|
else if (sliceDim0 || isSimpleSlice) {
|
// Optimization #2, slice is memory contiguous (only occurs in dim 0)
|
tfjsCore.util.assert(x.shape.length >= 1, function () { return "Input must have rank at least 1, got: " + x.shape.length; });
|
var size = tfjsCore.slice_util.computeOutShape($begin, $end, $strides);
|
// To tolerate begin[0] > end[0] (a 0-output slice), we min(begin, end).
|
var sliced = slice({ inputs: { x: x }, backend: backend, attrs: { begin: $begin, size: size } });
|
result =
|
reshape({ inputs: { x: sliced }, backend: backend, attrs: { shape: finalShape } });
|
backend.disposeData(sliced.dataId);
|
}
|
else {
|
var out = backend.makeOutput(finalShapeSparse, 'float32');
|
var xId = backend.dataIdMap.get(x.dataId).id;
|
var xStridesBytes = new Uint8Array(new Int32Array(tfjsCore.util.computeStrides(x.shape)).buffer);
|
var beginBytes = new Uint8Array(new Int32Array($begin).buffer);
|
var endBytes = new Uint8Array(new Int32Array($end).buffer);
|
var stridesBytes = new Uint8Array(new Int32Array($strides).buffer);
|
var outputShapeBytes = new Uint8Array(new Int32Array(finalShapeSparse).buffer);
|
var outStridesBytes = new Uint8Array(new Int32Array(tfjsCore.util.computeStrides(finalShapeSparse)).buffer);
|
var outId = backend.dataIdMap.get(out.dataId).id;
|
wasmStridedSlice(xId, xStridesBytes, x.shape.length, beginBytes, endBytes, stridesBytes, outputShapeBytes, outStridesBytes, finalShapeSparse.length, outId);
|
result = reshape({ inputs: { x: out }, backend: backend, attrs: { shape: finalShape } });
|
backend.disposeData(out.dataId);
|
}
|
return result;
|
}
|
var stridedSliceConfig = {
|
kernelName: tfjsCore.StridedSlice,
|
backendName: 'wasm',
|
setupFunc: setup$I,
|
kernelFunc: stridedSlice
|
};
|
|
/**
|
* @license
|
* Copyright 2019 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var subConfig = createBinaryKernelConfig(tfjsCore.Sub);
|
|
/**
|
* @license
|
* Copyright 2019 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var wasmSum;
|
function setup$J(backend) {
|
wasmSum = backend.wasm.cwrap(tfjsCore.Sum, null /*void*/, [
|
'number',
|
'number',
|
'number',
|
'number',
|
]);
|
}
|
function sum(args) {
|
var backend = args.backend, inputs = args.inputs, attrs = args.attrs;
|
var axis = attrs.axis, keepDims = attrs.keepDims;
|
var x = inputs.x;
|
var xId = backend.dataIdMap.get(x.dataId).id;
|
var inputId = xId;
|
var input = x;
|
var _a = permuteAxesAndTranspose(x, axis, backend), transposed = _a.transposed, axes = _a.axes, originalAxes = _a.originalAxes, inputWasTransposed = _a.inputWasTransposed;
|
var reductionAxes = axes;
|
if (inputWasTransposed) {
|
var transposedId = backend.dataIdMap.get(transposed.dataId).id;
|
if (transposedId !== xId) {
|
// transpose was not a no-op. We will need to dispose of this
|
// once we are done.
|
input = transposed;
|
inputId = transposedId;
|
reductionAxes = tfjsCore.backend_util.getInnerMostAxes(reductionAxes.length, input.shape.length);
|
}
|
}
|
tfjsCore.backend_util.assertAxesAreInnerMostDims('sum', reductionAxes, input.shape.length);
|
var _b = tfjsCore.backend_util.computeOutAndReduceShapes(input.shape, reductionAxes), outShape = _b[0], reduceShape = _b[1];
|
var reduceSize = tfjsCore.util.sizeFromShape(reduceShape);
|
var out = backend.makeOutput(outShape, input.dtype);
|
if (tfjsCore.util.sizeFromShape(input.shape) !== 0) {
|
var outId = backend.dataIdMap.get(out.dataId).id;
|
wasmSum(inputId, reduceSize, CppDType[out.dtype], outId);
|
}
|
if (inputWasTransposed) {
|
// dispose of the transposed tensor.
|
backend.disposeData(transposed.dataId);
|
}
|
if (keepDims) {
|
// reshape
|
var newShape = tfjsCore.backend_util.expandShapeToKeepDim(out.shape, originalAxes);
|
out.shape = newShape;
|
}
|
return out;
|
}
|
var sumConfig = {
|
kernelName: tfjsCore.Sum,
|
backendName: 'wasm',
|
setupFunc: setup$J,
|
kernelFunc: sum
|
};
|
|
/**
|
* @license
|
* Copyright 2021 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var tanConfig = createUnaryKernelConfig(tfjsCore.Tan);
|
|
/**
|
* @license
|
* Copyright 2019 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var tanhConfig = createUnaryKernelConfig(tfjsCore.Tanh);
|
|
/**
|
* @license
|
* Copyright 2019 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var wasmTile;
|
function setup$K(backend) {
|
wasmTile = backend.wasm.cwrap(tfjsCore.Tile, null /* void */, [
|
'number',
|
'array',
|
'number',
|
'array',
|
'number',
|
'number' // out_id
|
]);
|
}
|
function tile(args) {
|
var inputs = args.inputs, backend = args.backend, attrs = args.attrs;
|
var x = inputs.x;
|
var xId = backend.dataIdMap.get(x.dataId).id;
|
var reps = attrs.reps;
|
var newShape = new Array(x.shape.length);
|
for (var i = 0; i < newShape.length; i++) {
|
newShape[i] = x.shape[i] * reps[i];
|
}
|
var xShapeBytes = new Uint8Array(new Int32Array(x.shape).buffer);
|
var newShapeBytes = new Uint8Array(new Int32Array(newShape).buffer);
|
var out = backend.makeOutput(newShape, x.dtype);
|
var outId = backend.dataIdMap.get(out.dataId).id;
|
wasmTile(xId, xShapeBytes, x.shape.length, newShapeBytes, newShape.length, CppDType[out.dtype], outId);
|
return out;
|
}
|
var tileConfig = {
|
kernelName: tfjsCore.Tile,
|
backendName: 'wasm',
|
setupFunc: setup$K,
|
kernelFunc: tile
|
};
|
|
/**
|
* @license
|
* Copyright 2020 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var wasmTopK;
|
function setup$L(backend) {
|
wasmTopK = backend.wasm.cwrap(tfjsCore.TopK, null /* void */, [
|
'number',
|
'array',
|
'number',
|
'number',
|
'number',
|
'bool',
|
'number',
|
'number',
|
]);
|
}
|
var topk = function (_a) {
|
var inputs = _a.inputs, backend = _a.backend, attrs = _a.attrs;
|
var x = inputs.x;
|
var k = attrs.k, sorted = attrs.sorted;
|
var xId = backend.dataIdMap.get(x.dataId).id;
|
var xShapeBytes = new Uint8Array(new Int32Array(x.shape).buffer);
|
var outputShape = x.shape.slice();
|
outputShape[outputShape.length - 1] = k;
|
var outValues = backend.makeOutput(outputShape, x.dtype);
|
var outValuesId = backend.dataIdMap.get(outValues.dataId).id;
|
var outIndices = backend.makeOutput(outputShape, 'int32');
|
var outIndicesId = backend.dataIdMap.get(outIndices.dataId).id;
|
wasmTopK(xId, xShapeBytes, x.shape.length, CppDType[x.dtype], k, sorted, outValuesId, outIndicesId);
|
return [outValues, outIndices];
|
};
|
var topKConfig = {
|
kernelName: tfjsCore.TopK,
|
backendName: 'wasm',
|
setupFunc: setup$L,
|
kernelFunc: topk,
|
};
|
|
/**
|
* @license
|
* Copyright 2021 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var wasmTransform;
|
function setup$M(backend) {
|
wasmTransform = backend.wasm.cwrap(tfjsCore.Transform, null /*void*/, [
|
'number',
|
'number',
|
'bool',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number',
|
'array',
|
'number',
|
'number',
|
'number',
|
'number',
|
'number' // outId
|
]);
|
}
|
function transform(args) {
|
var backend = args.backend, inputs = args.inputs, attrs = args.attrs;
|
var image = inputs.image, transforms = inputs.transforms;
|
var interpolation = attrs.interpolation, fillMode = attrs.fillMode, fillValue = attrs.fillValue, outputShape = attrs.outputShape;
|
var _a = image.shape, batch = _a[0], imageHeight = _a[1], imageWidth = _a[2], numChannels = _a[3];
|
var _b = outputShape != null ? outputShape : [imageHeight, imageWidth], outHeight = _b[0], outWidth = _b[1];
|
var outShape = [batch, outHeight, outWidth,
|
numChannels];
|
var strides = new Uint8Array(new Int32Array(tfjsCore.util.computeStrides(image.shape)).buffer);
|
var out = backend.makeOutput(outShape, image.dtype);
|
var outId = backend.dataIdMap.get(out.dataId).id;
|
var imageData = backend.dataIdMap.get(image.dataId);
|
var imageId = imageData.id;
|
var transformsData = backend.dataIdMap.get(transforms.dataId);
|
var transformsId = transformsData.id;
|
var interpolationModeId = interpolation === 'nearest' ? 1 : 2;
|
var fillModeId;
|
switch (fillMode) {
|
case 'constant':
|
fillModeId = 1;
|
break;
|
case 'reflect':
|
fillModeId = 2;
|
break;
|
case 'wrap':
|
fillModeId = 3;
|
break;
|
case 'nearest':
|
fillModeId = 4;
|
break;
|
default:
|
fillModeId = 1;
|
break;
|
}
|
wasmTransform(imageId, transformsId, (transforms.shape[0] > 1), batch, outHeight, outWidth, numChannels, imageWidth, imageHeight, strides, image.shape.length - 1, interpolationModeId, fillModeId, fillValue, outId);
|
return out;
|
}
|
var transformConfig = {
|
kernelName: tfjsCore.Transform,
|
backendName: 'wasm',
|
setupFunc: setup$M,
|
kernelFunc: transform
|
};
|
|
/**
|
* @license
|
* Copyright 2019 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
function unpack(args) {
|
var inputs = args.inputs, backend = args.backend, attrs = args.attrs;
|
var value = inputs.value;
|
var axis = attrs.axis;
|
if (axis < 0) {
|
axis += value.shape.length;
|
}
|
var numOutputs = value.shape[axis];
|
var rank = value.shape.length;
|
var outShape = new Array(rank - 1);
|
var outIndex = 0;
|
for (var i = 0; i < rank; i++) {
|
if (i !== axis) {
|
outShape[outIndex++] = value.shape[i];
|
}
|
}
|
var outs = new Array(numOutputs);
|
var begin = new Array(rank).fill(0);
|
var size = value.shape.slice();
|
size[axis] = 1;
|
for (var i = 0; i < outs.length; i++) {
|
begin[axis] = i;
|
outs[i] = slice({ inputs: { x: value }, attrs: { begin: begin, size: size }, backend: backend });
|
}
|
return outs.map(function (_a) {
|
var dataId = _a.dataId, dtype = _a.dtype;
|
return ({ dataId: dataId, dtype: dtype, shape: outShape });
|
});
|
}
|
var unpackConfig = {
|
kernelName: tfjsCore.Unpack,
|
backendName: 'wasm',
|
kernelFunc: unpack,
|
};
|
|
/**
|
* @license
|
* Copyright 2020 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
function zerosLike(args) {
|
var x = args.inputs.x, backend = args.backend;
|
var out = backend.makeOutput(x.shape, x.dtype);
|
var outVals = backend.typedArrayFromHeap(out);
|
outVals.fill(0);
|
return out;
|
}
|
var zerosLikeConfig = {
|
kernelName: tfjsCore.ZerosLike,
|
backendName: 'wasm',
|
kernelFunc: zerosLike,
|
};
|
|
/**
|
* @license
|
* Copyright 2020 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
// List all kernel configs here
|
var kernelConfigs = [
|
_fusedMatMulConfig,
|
absConfig,
|
addConfig,
|
addNConfig,
|
allConfig,
|
anyConfig,
|
argMaxConfig,
|
avgPoolConfig,
|
batchMatMulConfig,
|
batchToSpaceNDConfig,
|
castConfig,
|
ceilConfig,
|
clipByValueConfig,
|
concatConfig,
|
conv2DConfig,
|
conv2DBackpropInputConfig,
|
cosConfig,
|
coshConfig,
|
cropAndResizeConfig,
|
cumprodConfig,
|
cumsumConfig,
|
depthToSpaceConfig,
|
depthwiseConv2dNativeConfig,
|
eluConfig,
|
equalConfig,
|
expConfig,
|
expandDimsConfig,
|
fillConfig,
|
flipLeftRightConfig,
|
floorConfig,
|
floorDivConfig,
|
fusedBatchNormConfig,
|
fusedConv2DConfig,
|
fusedDepthwiseConv2DConfig,
|
gatherNdConfig,
|
gatherV2Config,
|
greaterConfig,
|
greaterEqualConfig,
|
identityConfig,
|
leakyReluConfig,
|
lessConfig,
|
lessEqualConfig,
|
logConfig,
|
logicalAndConfig,
|
maxConfig,
|
maximumConfig,
|
maxPoolConfig,
|
meanConfig,
|
minConfig,
|
minimumConfig,
|
mirrorPadConfig,
|
multiplyConfig,
|
negConfig,
|
nonMaxSuppressionV3Config,
|
nonMaxSuppressionV4Config,
|
nonMaxSuppressionV5Config,
|
notEqualConfig,
|
oneHotConfig,
|
onesLikeConfig,
|
packConfig,
|
padV2Config,
|
powConfig,
|
preluConfig,
|
prodConfig,
|
rangeConfig,
|
realDivConfig,
|
reluConfig,
|
relu6Config,
|
reshapeConfig,
|
resizeBilinearConfig,
|
reverseConfig,
|
rotateWithOffsetConfig,
|
roundConfig,
|
rsqrtConfig,
|
scatterNdConfig,
|
selectConfig,
|
sigmoidConfig,
|
sinConfig,
|
sliceConfig,
|
softmaxConfig,
|
spaceToBatchNDConfig,
|
sparseFillEmptyRowsConfig,
|
sparseReshapeConfig,
|
sparseSegmentMeanConfig,
|
sparseSegmentSumConfig,
|
splitVConfig,
|
sqrtConfig,
|
squareConfig,
|
squaredDifferenceConfig,
|
stepConfig,
|
stridedSliceConfig,
|
subConfig,
|
sumConfig,
|
tanConfig,
|
tanhConfig,
|
tileConfig,
|
topKConfig,
|
transformConfig,
|
transposeConfig,
|
unpackConfig,
|
zerosLikeConfig
|
];
|
for (var _i = 0, kernelConfigs_1 = kernelConfigs; _i < kernelConfigs_1.length; _i++) {
|
var kernelConfig = kernelConfigs_1[_i];
|
tfjsCore.registerKernel(kernelConfig);
|
}
|
|
/*! *****************************************************************************
|
Copyright (c) Microsoft Corporation.
|
|
Permission to use, copy, modify, and/or distribute this software for any
|
purpose with or without fee is hereby granted.
|
|
THE SOFTWARE IS PROVIDED "AS IS" AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH
|
REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY
|
AND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT,
|
INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM
|
LOSS OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR
|
OTHER TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR
|
PERFORMANCE OF THIS SOFTWARE.
|
***************************************************************************** */
|
/* global Reflect, Promise */
|
|
var extendStatics = function(d, b) {
|
extendStatics = Object.setPrototypeOf ||
|
({ __proto__: [] } instanceof Array && function (d, b) { d.__proto__ = b; }) ||
|
function (d, b) { for (var p in b) if (b.hasOwnProperty(p)) d[p] = b[p]; };
|
return extendStatics(d, b);
|
};
|
|
function __extends(d, b) {
|
extendStatics(d, b);
|
function __() { this.constructor = d; }
|
d.prototype = b === null ? Object.create(b) : (__.prototype = b.prototype, new __());
|
}
|
|
function __awaiter(thisArg, _arguments, P, generator) {
|
function adopt(value) { return value instanceof P ? value : new P(function (resolve) { resolve(value); }); }
|
return new (P || (P = Promise))(function (resolve, reject) {
|
function fulfilled(value) { try { step(generator.next(value)); } catch (e) { reject(e); } }
|
function rejected(value) { try { step(generator["throw"](value)); } catch (e) { reject(e); } }
|
function step(result) { result.done ? resolve(result.value) : adopt(result.value).then(fulfilled, rejected); }
|
step((generator = generator.apply(thisArg, _arguments || [])).next());
|
});
|
}
|
|
function __generator(thisArg, body) {
|
var _ = { label: 0, sent: function() { if (t[0] & 1) throw t[1]; return t[1]; }, trys: [], ops: [] }, f, y, t, g;
|
return g = { next: verb(0), "throw": verb(1), "return": verb(2) }, typeof Symbol === "function" && (g[Symbol.iterator] = function() { return this; }), g;
|
function verb(n) { return function (v) { return step([n, v]); }; }
|
function step(op) {
|
if (f) throw new TypeError("Generator is already executing.");
|
while (_) try {
|
if (f = 1, y && (t = op[0] & 2 ? y["return"] : op[0] ? y["throw"] || ((t = y["return"]) && t.call(y), 0) : y.next) && !(t = t.call(y, op[1])).done) return t;
|
if (y = 0, t) op = [op[0] & 2, t.value];
|
switch (op[0]) {
|
case 0: case 1: t = op; break;
|
case 4: _.label++; return { value: op[1], done: false };
|
case 5: _.label++; y = op[1]; op = [0]; continue;
|
case 7: op = _.ops.pop(); _.trys.pop(); continue;
|
default:
|
if (!(t = _.trys, t = t.length > 0 && t[t.length - 1]) && (op[0] === 6 || op[0] === 2)) { _ = 0; continue; }
|
if (op[0] === 3 && (!t || (op[1] > t[0] && op[1] < t[3]))) { _.label = op[1]; break; }
|
if (op[0] === 6 && _.label < t[1]) { _.label = t[1]; t = op; break; }
|
if (t && _.label < t[2]) { _.label = t[2]; _.ops.push(op); break; }
|
if (t[2]) _.ops.pop();
|
_.trys.pop(); continue;
|
}
|
op = body.call(thisArg, _);
|
} catch (e) { op = [6, e]; y = 0; } finally { f = t = 0; }
|
if (op[0] & 5) throw op[1]; return { value: op[0] ? op[1] : void 0, done: true };
|
}
|
}
|
|
/**
|
* @license
|
* Copyright 2020 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var _this = undefined;
|
var ENV = tfjsCore.env();
|
/**
|
* True if SIMD is supported.
|
*/
|
// From: https://github.com/GoogleChromeLabs/wasm-feature-detect
|
ENV.registerFlag(
|
// This typed array passed in to WebAssembly.validate is WebAssembly binary
|
// code. In this case it is a small program that contains SIMD
|
// instructions.
|
'WASM_HAS_SIMD_SUPPORT', function () { return __awaiter(_this, void 0, void 0, function () {
|
return __generator(this, function (_a) {
|
return [2 /*return*/, WebAssembly.validate(new Uint8Array([
|
0, 97, 115, 109, 1, 0, 0, 0, 1, 4, 1, 96, 0, 0, 3,
|
2, 1, 0, 10, 9, 1, 7, 0, 65, 0, 253, 15, 26, 11
|
]))];
|
});
|
}); });
|
/**
|
* True if threads are supported.
|
*/
|
// From: https://github.com/GoogleChromeLabs/wasm-feature-detect
|
ENV.registerFlag('WASM_HAS_MULTITHREAD_SUPPORT', function () { return __awaiter(_this, void 0, void 0, function () {
|
return __generator(this, function (_a) {
|
// TODO(annxingyuan): Enable node support once this is resolved:
|
// https://github.com/tensorflow/tfjs/issues/3830
|
if (ENV.get('IS_NODE')) {
|
return [2 /*return*/, false];
|
}
|
try {
|
// Test for transferability of SABs (needed for Firefox)
|
// https://groups.google.com/forum/#!msg/mozilla.dev.platform/IHkBZlHETpA/dwsMNchWEQAJ
|
new MessageChannel().port1.postMessage(new SharedArrayBuffer(1));
|
// This typed array is a WebAssembly program containing threaded
|
// instructions.
|
return [2 /*return*/, WebAssembly.validate(new Uint8Array([
|
0, 97, 115, 109, 1, 0, 0, 0, 1, 4, 1, 96, 0, 0, 3, 2, 1, 0, 5,
|
4, 1, 3, 1, 1, 10, 11, 1, 9, 0, 65, 0, 254, 16, 2, 0, 26, 11
|
]))];
|
}
|
catch (e) {
|
return [2 /*return*/, false];
|
}
|
return [2 /*return*/];
|
});
|
}); });
|
|
var commonjsGlobal = typeof globalThis !== 'undefined' ? globalThis : typeof window !== 'undefined' ? window : typeof global !== 'undefined' ? global : typeof self !== 'undefined' ? self : {};
|
|
function createCommonjsModule(fn, module) {
|
return module = { exports: {} }, fn(module, module.exports), module.exports;
|
}
|
|
var tfjsBackendWasmThreadedSimd = createCommonjsModule(function (module, exports) {
|
var WasmBackendModuleThreadedSimd = (() => {
|
var _scriptDir = typeof document !== 'undefined' && document.currentScript ? document.currentScript.src : undefined;
|
if (typeof __filename !== 'undefined') _scriptDir = _scriptDir || __filename;
|
return (
|
function(WasmBackendModuleThreadedSimd) {
|
WasmBackendModuleThreadedSimd = WasmBackendModuleThreadedSimd || {};
|
|
function GROWABLE_HEAP_I8(){if(wasmMemory.buffer!=buffer){updateGlobalBufferAndViews(wasmMemory.buffer);}return HEAP8}function GROWABLE_HEAP_U8(){if(wasmMemory.buffer!=buffer){updateGlobalBufferAndViews(wasmMemory.buffer);}return HEAPU8}function GROWABLE_HEAP_I32(){if(wasmMemory.buffer!=buffer){updateGlobalBufferAndViews(wasmMemory.buffer);}return HEAP32}function GROWABLE_HEAP_F64(){if(wasmMemory.buffer!=buffer){updateGlobalBufferAndViews(wasmMemory.buffer);}return HEAPF64}var Module=typeof WasmBackendModuleThreadedSimd!=="undefined"?WasmBackendModuleThreadedSimd:{};var readyPromiseResolve,readyPromiseReject;Module["ready"]=new Promise(function(resolve,reject){readyPromiseResolve=resolve;readyPromiseReject=reject;});var beforeListeners;if(typeof process!=="undefined"&&process.listeners){beforeListeners={uncaughtException:process.listeners("uncaughtException"),unhandledRejection:process.listeners("unhandledRejection")};}var moduleOverrides=Object.assign({},Module);var arguments_=[];var thisProgram="./this.program";var quit_=(status,toThrow)=>{throw toThrow};var ENVIRONMENT_IS_WEB=typeof window==="object";var ENVIRONMENT_IS_WORKER=typeof importScripts==="function";var ENVIRONMENT_IS_NODE=typeof process==="object"&&typeof process.versions==="object"&&typeof process.versions.node==="string";var ENVIRONMENT_IS_PTHREAD=Module["ENVIRONMENT_IS_PTHREAD"]||false;var scriptDirectory="";function locateFile(path){if(Module["locateFile"]){return Module["locateFile"](path,scriptDirectory)}return scriptDirectory+path}var read_,readAsync,readBinary;function logExceptionOnExit(e){if(e instanceof ExitStatus)return;let toLog=e;err("exiting due to exception: "+toLog);}var fs$1;var nodePath;var requireNodeFS;if(ENVIRONMENT_IS_NODE){if(ENVIRONMENT_IS_WORKER){scriptDirectory=path.dirname(scriptDirectory)+"/";}else {scriptDirectory=__dirname+"/";}requireNodeFS=(()=>{if(!nodePath){fs$1=fs;nodePath=path;}});read_=function shell_read(filename,binary){requireNodeFS();filename=nodePath["normalize"](filename);return fs$1.readFileSync(filename,binary?undefined:"utf8")};readBinary=(filename=>{var ret=read_(filename,true);if(!ret.buffer){ret=new Uint8Array(ret);}return ret});readAsync=((filename,onload,onerror)=>{requireNodeFS();filename=nodePath["normalize"](filename);fs$1.readFile(filename,function(err,data){if(err)onerror(err);else onload(data.buffer);});});if(process["argv"].length>1){thisProgram=process["argv"][1].replace(/\\/g,"/");}arguments_=process["argv"].slice(2);process["on"]("uncaughtException",function(ex){if(!(ex instanceof ExitStatus)){throw ex}});process["on"]("unhandledRejection",function(reason){throw reason});quit_=((status,toThrow)=>{if(keepRuntimeAlive()){process["exitCode"]=status;throw toThrow}logExceptionOnExit(toThrow);process["exit"](status);});Module["inspect"]=function(){return "[Emscripten Module object]"};let nodeWorkerThreads;try{nodeWorkerThreads=worker_threads;}catch(e){console.error('The "worker_threads" module is not supported in this node.js build - perhaps a newer version is needed?');throw e}commonjsGlobal.Worker=nodeWorkerThreads.Worker;}else if(ENVIRONMENT_IS_WEB||ENVIRONMENT_IS_WORKER){if(ENVIRONMENT_IS_WORKER){scriptDirectory=self.location.href;}else if(typeof document!=="undefined"&&document.currentScript){scriptDirectory=document.currentScript.src;}if(typeof _scriptDir !== "undefined" && _scriptDir){scriptDirectory=_scriptDir;}if(scriptDirectory.indexOf("blob:")!==0){scriptDirectory=scriptDirectory.substr(0,scriptDirectory.replace(/[?#].*/,"").lastIndexOf("/")+1);}else {scriptDirectory="";}if(!ENVIRONMENT_IS_NODE){read_=(url=>{var xhr=new XMLHttpRequest;xhr.open("GET",url,false);xhr.send(null);return xhr.responseText});if(ENVIRONMENT_IS_WORKER){readBinary=(url=>{var xhr=new XMLHttpRequest;xhr.open("GET",url,false);xhr.responseType="arraybuffer";xhr.send(null);return new Uint8Array(xhr.response)});}readAsync=((url,onload,onerror)=>{var xhr=new XMLHttpRequest;xhr.open("GET",url,true);xhr.responseType="arraybuffer";xhr.onload=(()=>{if(xhr.status==200||xhr.status==0&&xhr.response){onload(xhr.response);return}onerror();});xhr.onerror=onerror;xhr.send(null);});}}if(ENVIRONMENT_IS_NODE){if(typeof performance==="undefined"){commonjsGlobal.performance=perf_hooks.performance;}}var defaultPrint=console.log.bind(console);var defaultPrintErr=console.warn.bind(console);if(ENVIRONMENT_IS_NODE){requireNodeFS();defaultPrint=(str=>fs$1.writeSync(1,str+"\n"));defaultPrintErr=(str=>fs$1.writeSync(2,str+"\n"));}var out=Module["print"]||defaultPrint;var err=Module["printErr"]||defaultPrintErr;Object.assign(Module,moduleOverrides);moduleOverrides=null;if(Module["arguments"])arguments_=Module["arguments"];if(Module["thisProgram"])thisProgram=Module["thisProgram"];if(Module["quit"])quit_=Module["quit"];function warnOnce(text){if(!warnOnce.shown)warnOnce.shown={};if(!warnOnce.shown[text]){warnOnce.shown[text]=1;err(text);}}var wasmBinary;if(Module["wasmBinary"])wasmBinary=Module["wasmBinary"];var noExitRuntime=Module["noExitRuntime"]||true;if(typeof WebAssembly!=="object"){abort("no native wasm support detected");}var wasmMemory;var wasmModule;var ABORT=false;var EXITSTATUS;function getCFunc(ident){var func=Module["_"+ident];return func}function ccall(ident,returnType,argTypes,args,opts){var toC={"string":function(str){var ret=0;if(str!==null&&str!==undefined&&str!==0){var len=(str.length<<2)+1;ret=stackAlloc(len);stringToUTF8(str,ret,len);}return ret},"array":function(arr){var ret=stackAlloc(arr.length);writeArrayToMemory(arr,ret);return ret}};function convertReturnValue(ret){if(returnType==="string")return UTF8ToString(ret);if(returnType==="boolean")return Boolean(ret);return ret}var func=getCFunc(ident);var cArgs=[];var stack=0;if(args){for(var i=0;i<args.length;i++){var converter=toC[argTypes[i]];if(converter){if(stack===0)stack=stackSave();cArgs[i]=converter(args[i]);}else {cArgs[i]=args[i];}}}var ret=func.apply(null,cArgs);function onDone(ret){if(stack!==0)stackRestore(stack);return convertReturnValue(ret)}ret=onDone(ret);return ret}function cwrap(ident,returnType,argTypes,opts){argTypes=argTypes||[];var numericArgs=argTypes.every(function(type){return type==="number"});var numericRet=returnType!=="string";if(numericRet&&numericArgs&&!opts){return getCFunc(ident)}return function(){return ccall(ident,returnType,argTypes,arguments)}}function TextDecoderWrapper(encoding){var textDecoder=new TextDecoder(encoding);this.decode=(data=>{if(data.buffer instanceof SharedArrayBuffer){data=new Uint8Array(data);}return textDecoder.decode.call(textDecoder,data)});}var UTF8Decoder=typeof TextDecoder!=="undefined"?new TextDecoderWrapper("utf8"):undefined;function UTF8ArrayToString(heap,idx,maxBytesToRead){var endIdx=idx+maxBytesToRead;var endPtr=idx;while(heap[endPtr]&&!(endPtr>=endIdx))++endPtr;if(endPtr-idx>16&&heap.subarray&&UTF8Decoder){return UTF8Decoder.decode(heap.subarray(idx,endPtr))}else {var str="";while(idx<endPtr){var u0=heap[idx++];if(!(u0&128)){str+=String.fromCharCode(u0);continue}var u1=heap[idx++]&63;if((u0&224)==192){str+=String.fromCharCode((u0&31)<<6|u1);continue}var u2=heap[idx++]&63;if((u0&240)==224){u0=(u0&15)<<12|u1<<6|u2;}else {u0=(u0&7)<<18|u1<<12|u2<<6|heap[idx++]&63;}if(u0<65536){str+=String.fromCharCode(u0);}else {var ch=u0-65536;str+=String.fromCharCode(55296|ch>>10,56320|ch&1023);}}}return str}function UTF8ToString(ptr,maxBytesToRead){return ptr?UTF8ArrayToString(GROWABLE_HEAP_U8(),ptr,maxBytesToRead):""}function stringToUTF8Array(str,heap,outIdx,maxBytesToWrite){if(!(maxBytesToWrite>0))return 0;var startIdx=outIdx;var endIdx=outIdx+maxBytesToWrite-1;for(var i=0;i<str.length;++i){var u=str.charCodeAt(i);if(u>=55296&&u<=57343){var u1=str.charCodeAt(++i);u=65536+((u&1023)<<10)|u1&1023;}if(u<=127){if(outIdx>=endIdx)break;heap[outIdx++]=u;}else if(u<=2047){if(outIdx+1>=endIdx)break;heap[outIdx++]=192|u>>6;heap[outIdx++]=128|u&63;}else if(u<=65535){if(outIdx+2>=endIdx)break;heap[outIdx++]=224|u>>12;heap[outIdx++]=128|u>>6&63;heap[outIdx++]=128|u&63;}else {if(outIdx+3>=endIdx)break;heap[outIdx++]=240|u>>18;heap[outIdx++]=128|u>>12&63;heap[outIdx++]=128|u>>6&63;heap[outIdx++]=128|u&63;}}heap[outIdx]=0;return outIdx-startIdx}function stringToUTF8(str,outPtr,maxBytesToWrite){return stringToUTF8Array(str,GROWABLE_HEAP_U8(),outPtr,maxBytesToWrite)}function lengthBytesUTF8(str){var len=0;for(var i=0;i<str.length;++i){var u=str.charCodeAt(i);if(u>=55296&&u<=57343)u=65536+((u&1023)<<10)|str.charCodeAt(++i)&1023;if(u<=127)++len;else if(u<=2047)len+=2;else if(u<=65535)len+=3;else len+=4;}return len}var UTF16Decoder=typeof TextDecoder!=="undefined"?new TextDecoderWrapper("utf-16le"):undefined;function writeArrayToMemory(array,buffer){GROWABLE_HEAP_I8().set(array,buffer);}function alignUp(x,multiple){if(x%multiple>0){x+=multiple-x%multiple;}return x}var buffer,HEAP8,HEAPU8,HEAP16,HEAPU16,HEAP32,HEAPU32,HEAPF32,HEAPF64;if(ENVIRONMENT_IS_PTHREAD){buffer=Module["buffer"];}function updateGlobalBufferAndViews(buf){buffer=buf;Module["HEAP8"]=HEAP8=new Int8Array(buf);Module["HEAP16"]=HEAP16=new Int16Array(buf);Module["HEAP32"]=HEAP32=new Int32Array(buf);Module["HEAPU8"]=HEAPU8=new Uint8Array(buf);Module["HEAPU16"]=HEAPU16=new Uint16Array(buf);Module["HEAPU32"]=HEAPU32=new Uint32Array(buf);Module["HEAPF32"]=HEAPF32=new Float32Array(buf);Module["HEAPF64"]=HEAPF64=new Float64Array(buf);}var INITIAL_MEMORY=Module["INITIAL_MEMORY"]||16777216;if(ENVIRONMENT_IS_PTHREAD){wasmMemory=Module["wasmMemory"];buffer=Module["buffer"];}else {if(Module["wasmMemory"]){wasmMemory=Module["wasmMemory"];}else {wasmMemory=new WebAssembly.Memory({"initial":INITIAL_MEMORY/65536,"maximum":2147483648/65536,"shared":true});if(!(wasmMemory.buffer instanceof SharedArrayBuffer)){err("requested a shared WebAssembly.Memory but the returned buffer is not a SharedArrayBuffer, indicating that while the browser has SharedArrayBuffer it does not have WebAssembly threads support - you may need to set a flag");if(ENVIRONMENT_IS_NODE){console.log("(on node you may need: --experimental-wasm-threads --experimental-wasm-bulk-memory and also use a recent version)");}throw Error("bad memory")}}}if(wasmMemory){buffer=wasmMemory.buffer;}INITIAL_MEMORY=buffer.byteLength;updateGlobalBufferAndViews(buffer);var wasmTable;var __ATPRERUN__=[];var __ATINIT__=[];var __ATPOSTRUN__=[];var runtimeKeepaliveCounter=0;function keepRuntimeAlive(){return noExitRuntime||runtimeKeepaliveCounter>0}function preRun(){if(Module["preRun"]){if(typeof Module["preRun"]=="function")Module["preRun"]=[Module["preRun"]];while(Module["preRun"].length){addOnPreRun(Module["preRun"].shift());}}callRuntimeCallbacks(__ATPRERUN__);}function initRuntime(){if(ENVIRONMENT_IS_PTHREAD)return;callRuntimeCallbacks(__ATINIT__);}function exitRuntime(){if(ENVIRONMENT_IS_PTHREAD)return;PThread.terminateAllThreads();}function postRun(){if(ENVIRONMENT_IS_PTHREAD)return;if(Module["postRun"]){if(typeof Module["postRun"]=="function")Module["postRun"]=[Module["postRun"]];while(Module["postRun"].length){addOnPostRun(Module["postRun"].shift());}}callRuntimeCallbacks(__ATPOSTRUN__);}function addOnPreRun(cb){__ATPRERUN__.unshift(cb);}function addOnInit(cb){__ATINIT__.unshift(cb);}function addOnPostRun(cb){__ATPOSTRUN__.unshift(cb);}var runDependencies=0;var dependenciesFulfilled=null;function addRunDependency(id){runDependencies++;if(Module["monitorRunDependencies"]){Module["monitorRunDependencies"](runDependencies);}}function removeRunDependency(id){runDependencies--;if(Module["monitorRunDependencies"]){Module["monitorRunDependencies"](runDependencies);}if(runDependencies==0){if(dependenciesFulfilled){var callback=dependenciesFulfilled;dependenciesFulfilled=null;callback();}}}Module["preloadedImages"]={};Module["preloadedAudios"]={};function abort(what){if(ENVIRONMENT_IS_PTHREAD){postMessage({"cmd":"onAbort","arg":what});}else {if(Module["onAbort"]){Module["onAbort"](what);}}what="Aborted("+what+")";err(what);ABORT=true;EXITSTATUS=1;what+=". Build with -s ASSERTIONS=1 for more info.";var e=new WebAssembly.RuntimeError(what);readyPromiseReject(e);throw e}var dataURIPrefix="data:application/octet-stream;base64,";function isDataURI(filename){return filename.startsWith(dataURIPrefix)}function isFileURI(filename){return filename.startsWith("file://")}var wasmBinaryFile;wasmBinaryFile="tfjs-backend-wasm-threaded-simd.wasm";if(!isDataURI(wasmBinaryFile)){wasmBinaryFile=locateFile(wasmBinaryFile);}function getBinary(file){try{if(file==wasmBinaryFile&&wasmBinary){return new Uint8Array(wasmBinary)}if(readBinary){return readBinary(file)}else {throw "both async and sync fetching of the wasm failed"}}catch(err){abort(err);}}function getBinaryPromise(){if(!wasmBinary&&(ENVIRONMENT_IS_WEB||ENVIRONMENT_IS_WORKER)){if(typeof fetch==="function"&&!isFileURI(wasmBinaryFile)){return fetch(wasmBinaryFile,{credentials:"same-origin"}).then(function(response){if(!response["ok"]){throw "failed to load wasm binary file at '"+wasmBinaryFile+"'"}return response["arrayBuffer"]()}).catch(function(){return getBinary(wasmBinaryFile)})}else {if(readAsync){return new Promise(function(resolve,reject){readAsync(wasmBinaryFile,function(response){resolve(new Uint8Array(response));},reject);})}}}return Promise.resolve().then(function(){return getBinary(wasmBinaryFile)})}function createWasm(){var info={"env":asmLibraryArg,"wasi_snapshot_preview1":asmLibraryArg};function receiveInstance(instance,module){var exports=instance.exports;Module["asm"]=exports;registerTlsInit(Module["asm"]["emscripten_tls_init"]);wasmTable=Module["asm"]["__indirect_function_table"];addOnInit(Module["asm"]["__wasm_call_ctors"]);wasmModule=module;if(!ENVIRONMENT_IS_PTHREAD){var numWorkersToLoad=PThread.unusedWorkers.length;PThread.unusedWorkers.forEach(function(w){PThread.loadWasmModuleToWorker(w,function(){if(!--numWorkersToLoad)removeRunDependency();});});}}if(!ENVIRONMENT_IS_PTHREAD){addRunDependency();}function receiveInstantiationResult(result){receiveInstance(result["instance"],result["module"]);}function instantiateArrayBuffer(receiver){return getBinaryPromise().then(function(binary){return WebAssembly.instantiate(binary,info)}).then(function(instance){return instance}).then(receiver,function(reason){err("failed to asynchronously prepare wasm: "+reason);abort(reason);})}function instantiateAsync(){if(!wasmBinary&&typeof WebAssembly.instantiateStreaming==="function"&&!isDataURI(wasmBinaryFile)&&!isFileURI(wasmBinaryFile)&&typeof fetch==="function"){return fetch(wasmBinaryFile,{credentials:"same-origin"}).then(function(response){var result=WebAssembly.instantiateStreaming(response,info);return result.then(receiveInstantiationResult,function(reason){err("wasm streaming compile failed: "+reason);err("falling back to ArrayBuffer instantiation");return instantiateArrayBuffer(receiveInstantiationResult)})})}else {return instantiateArrayBuffer(receiveInstantiationResult)}}if(Module["instantiateWasm"]){try{var exports=Module["instantiateWasm"](info,receiveInstance);return exports}catch(e){err("Module.instantiateWasm callback failed with error: "+e);return false}}instantiateAsync().catch(readyPromiseReject);return {}}var ASM_CONSTS={};function callRuntimeCallbacks(callbacks){while(callbacks.length>0){var callback=callbacks.shift();if(typeof callback=="function"){callback(Module);continue}var func=callback.func;if(typeof func==="number"){if(callback.arg===undefined){getWasmTableEntry(func)();}else {getWasmTableEntry(func)(callback.arg);}}else {func(callback.arg===undefined?null:callback.arg);}}}function withStackSave(f){var stack=stackSave();var ret=f();stackRestore(stack);return ret}function killThread(pthread_ptr){GROWABLE_HEAP_I32()[pthread_ptr>>2]=0;var pthread=PThread.pthreads[pthread_ptr];delete PThread.pthreads[pthread_ptr];pthread.worker.terminate();__emscripten_thread_free_data(pthread_ptr);PThread.runningWorkers.splice(PThread.runningWorkers.indexOf(pthread.worker),1);pthread.worker.pthread=undefined;}function cancelThread(pthread_ptr){var pthread=PThread.pthreads[pthread_ptr];pthread.worker.postMessage({"cmd":"cancel"});}function cleanupThread(pthread_ptr){var pthread=PThread.pthreads[pthread_ptr];if(pthread){GROWABLE_HEAP_I32()[pthread_ptr>>2]=0;var worker=pthread.worker;PThread.returnWorkerToPool(worker);}}function _exit(status){exit(status);}function handleException(e){if(e instanceof ExitStatus||e=="unwind"){return EXITSTATUS}quit_(1,e);}var PThread={unusedWorkers:[],runningWorkers:[],tlsInitFunctions:[],init:function(){if(ENVIRONMENT_IS_PTHREAD){PThread.initWorker();}else {PThread.initMainThread();}},initMainThread:function(){var pthreadPoolSize=8;for(var i=0;i<pthreadPoolSize;++i){PThread.allocateUnusedWorker();}},initWorker:function(){noExitRuntime=false;},pthreads:{},setExitStatus:function(status){EXITSTATUS=status;},terminateAllThreads:function(){for(var t in PThread.pthreads){var pthread=PThread.pthreads[t];if(pthread&&pthread.worker){PThread.returnWorkerToPool(pthread.worker);}}for(var i=0;i<PThread.unusedWorkers.length;++i){var worker=PThread.unusedWorkers[i];worker.terminate();}PThread.unusedWorkers=[];},returnWorkerToPool:function(worker){PThread.runWithoutMainThreadQueuedCalls(function(){delete PThread.pthreads[worker.pthread.threadInfoStruct];PThread.unusedWorkers.push(worker);PThread.runningWorkers.splice(PThread.runningWorkers.indexOf(worker),1);__emscripten_thread_free_data(worker.pthread.threadInfoStruct);worker.pthread=undefined;});},runWithoutMainThreadQueuedCalls:function(func){GROWABLE_HEAP_I32()[__emscripten_allow_main_runtime_queued_calls>>2]=0;try{func();}finally{GROWABLE_HEAP_I32()[__emscripten_allow_main_runtime_queued_calls>>2]=1;}},receiveObjectTransfer:function(data){},threadInit:function(){for(var i in PThread.tlsInitFunctions){PThread.tlsInitFunctions[i]();}},loadWasmModuleToWorker:function(worker,onFinishedLoading){worker.onmessage=(e=>{var d=e["data"];var cmd=d["cmd"];if(worker.pthread)PThread.currentProxiedOperationCallerThread=worker.pthread.threadInfoStruct;if(d["targetThread"]&&d["targetThread"]!=_pthread_self()){var thread=PThread.pthreads[d.targetThread];if(thread){thread.worker.postMessage(d,d["transferList"]);}else {err('Internal error! Worker sent a message "'+cmd+'" to target pthread '+d["targetThread"]+", but that thread no longer exists!");}PThread.currentProxiedOperationCallerThread=undefined;return}if(cmd==="processQueuedMainThreadWork"){_emscripten_main_thread_process_queued_calls();}else if(cmd==="spawnThread"){spawnThread(d);}else if(cmd==="cleanupThread"){cleanupThread(d["thread"]);}else if(cmd==="killThread"){killThread(d["thread"]);}else if(cmd==="cancelThread"){cancelThread(d["thread"]);}else if(cmd==="loaded"){worker.loaded=true;if(onFinishedLoading)onFinishedLoading(worker);if(worker.runPthread){worker.runPthread();delete worker.runPthread;}}else if(cmd==="print"){out("Thread "+d["threadId"]+": "+d["text"]);}else if(cmd==="printErr"){err("Thread "+d["threadId"]+": "+d["text"]);}else if(cmd==="alert"){alert("Thread "+d["threadId"]+": "+d["text"]);}else if(d.target==="setimmediate"){worker.postMessage(d);}else if(cmd==="onAbort"){if(Module["onAbort"]){Module["onAbort"](d["arg"]);}}else {err("worker sent an unknown command "+cmd);}PThread.currentProxiedOperationCallerThread=undefined;});worker.onerror=(e=>{var message="worker sent an error!";err(message+" "+e.filename+":"+e.lineno+": "+e.message);throw e});if(ENVIRONMENT_IS_NODE){worker.on("message",function(data){worker.onmessage({data:data});});worker.on("error",function(e){worker.onerror(e);});worker.on("detachedExit",function(){});}worker.postMessage({"cmd":"load","urlOrBlob":Module["mainScriptUrlOrBlob"]||_scriptDir,"wasmMemory":wasmMemory,"wasmModule":wasmModule});},allocateUnusedWorker:function(){var pthreadMainJs=locateFile("tfjs-backend-wasm-threaded-simd.worker.js");PThread.unusedWorkers.push(new Worker(pthreadMainJs));},getNewWorker:function(){if(PThread.unusedWorkers.length==0){PThread.allocateUnusedWorker();PThread.loadWasmModuleToWorker(PThread.unusedWorkers[0]);}return PThread.unusedWorkers.pop()}};function establishStackSpace(){var pthread_ptr=_pthread_self();var stackTop=GROWABLE_HEAP_I32()[pthread_ptr+44>>2];var stackSize=GROWABLE_HEAP_I32()[pthread_ptr+48>>2];var stackMax=stackTop-stackSize;_emscripten_stack_set_limits(stackTop,stackMax);stackRestore(stackTop);}Module["establishStackSpace"]=establishStackSpace;function exitOnMainThread(returnCode){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(1,0,returnCode);try{_exit(returnCode);}catch(e){handleException(e);}}var wasmTableMirror=[];function getWasmTableEntry(funcPtr){var func=wasmTableMirror[funcPtr];if(!func){if(funcPtr>=wasmTableMirror.length)wasmTableMirror.length=funcPtr+1;wasmTableMirror[funcPtr]=func=wasmTable.get(funcPtr);}return func}function invokeEntryPoint(ptr,arg){return getWasmTableEntry(ptr)(arg)}Module["invokeEntryPoint"]=invokeEntryPoint;function registerTlsInit(tlsInitFunc,moduleExports,metadata){PThread.tlsInitFunctions.push(tlsInitFunc);}var _emscripten_get_now;if(ENVIRONMENT_IS_NODE){_emscripten_get_now=(()=>{var t=process["hrtime"]();return t[0]*1e3+t[1]/1e6});}else if(ENVIRONMENT_IS_PTHREAD){_emscripten_get_now=(()=>performance.now()-Module["__performance_now_clock_drift"]);}else _emscripten_get_now=(()=>performance.now());var _emscripten_get_now_is_monotonic=true;function setErrNo(value){GROWABLE_HEAP_I32()[___errno_location()>>2]=value;return value}function _clock_gettime(clk_id,tp){var now;if(clk_id===0){now=Date.now();}else if((clk_id===1||clk_id===4)&&_emscripten_get_now_is_monotonic){now=_emscripten_get_now();}else {setErrNo(28);return -1}GROWABLE_HEAP_I32()[tp>>2]=now/1e3|0;GROWABLE_HEAP_I32()[tp+4>>2]=now%1e3*1e3*1e3|0;return 0}function ___clock_gettime(a0,a1){return _clock_gettime(a0,a1)}function ___emscripten_init_main_thread_js(tb){__emscripten_thread_init(tb,!ENVIRONMENT_IS_WORKER,1,!ENVIRONMENT_IS_WEB);PThread.threadInit();}function ___emscripten_thread_cleanup(thread){if(!ENVIRONMENT_IS_PTHREAD)cleanupThread(thread);else postMessage({"cmd":"cleanupThread","thread":thread});}function spawnThread(threadParams){var worker=PThread.getNewWorker();if(!worker){return 6}PThread.runningWorkers.push(worker);var pthread=PThread.pthreads[threadParams.pthread_ptr]={worker:worker,threadInfoStruct:threadParams.pthread_ptr};worker.pthread=pthread;var msg={"cmd":"run","start_routine":threadParams.startRoutine,"arg":threadParams.arg,"threadInfoStruct":threadParams.pthread_ptr};worker.runPthread=(()=>{msg.time=performance.now();worker.postMessage(msg,threadParams.transferList);});if(worker.loaded){worker.runPthread();delete worker.runPthread;}return 0}function ___pthread_create_js(pthread_ptr,attr,start_routine,arg){if(typeof SharedArrayBuffer==="undefined"){err("Current environment does not support SharedArrayBuffer, pthreads are not available!");return 6}var transferList=[];var error=0;if(ENVIRONMENT_IS_PTHREAD&&(transferList.length===0||error)){return _emscripten_sync_run_in_main_thread_4(687865856,pthread_ptr,attr,start_routine,arg)}var threadParams={startRoutine:start_routine,pthread_ptr:pthread_ptr,arg:arg,transferList:transferList};if(ENVIRONMENT_IS_PTHREAD){threadParams.cmd="spawnThread";postMessage(threadParams,transferList);return 0}return spawnThread(threadParams)}function __emscripten_default_pthread_stack_size(){return 2097152}function __emscripten_notify_thread_queue(targetThreadId,mainThreadId){if(targetThreadId==mainThreadId){postMessage({"cmd":"processQueuedMainThreadWork"});}else if(ENVIRONMENT_IS_PTHREAD){postMessage({"targetThread":targetThreadId,"cmd":"processThreadQueue"});}else {var pthread=PThread.pthreads[targetThreadId];var worker=pthread&&pthread.worker;if(!worker){return}worker.postMessage({"cmd":"processThreadQueue"});}return 1}function _abort(){abort("");}function _emscripten_check_blocking_allowed(){if(ENVIRONMENT_IS_NODE)return;if(ENVIRONMENT_IS_WORKER)return;warnOnce("Blocking on the main thread is very dangerous, see https://emscripten.org/docs/porting/pthreads.html#blocking-on-the-main-browser-thread");}function _emscripten_get_heap_max(){return 2147483648}function _emscripten_memcpy_big(dest,src,num){GROWABLE_HEAP_U8().copyWithin(dest,src,src+num);}function _emscripten_num_logical_cores(){if(ENVIRONMENT_IS_NODE)return os.cpus().length;return navigator["hardwareConcurrency"]}function _emscripten_proxy_to_main_thread_js(index,sync){var numCallArgs=arguments.length-2;var outerArgs=arguments;return withStackSave(function(){var serializedNumCallArgs=numCallArgs;var args=stackAlloc(serializedNumCallArgs*8);var b=args>>3;for(var i=0;i<numCallArgs;i++){var arg=outerArgs[2+i];GROWABLE_HEAP_F64()[b+i]=arg;}return _emscripten_run_in_main_runtime_thread_js(index,serializedNumCallArgs,args,sync)})}var _emscripten_receive_on_main_thread_js_callArgs=[];function _emscripten_receive_on_main_thread_js(index,numCallArgs,args){_emscripten_receive_on_main_thread_js_callArgs.length=numCallArgs;var b=args>>3;for(var i=0;i<numCallArgs;i++){_emscripten_receive_on_main_thread_js_callArgs[i]=GROWABLE_HEAP_F64()[b+i];}var isEmAsmConst=index<0;var func=!isEmAsmConst?proxiedFunctionTable[index]:ASM_CONSTS[-index-1];return func.apply(null,_emscripten_receive_on_main_thread_js_callArgs)}function emscripten_realloc_buffer(size){try{wasmMemory.grow(size-buffer.byteLength+65535>>>16);updateGlobalBufferAndViews(wasmMemory.buffer);return 1}catch(e){}}function _emscripten_resize_heap(requestedSize){var oldSize=GROWABLE_HEAP_U8().length;requestedSize=requestedSize>>>0;if(requestedSize<=oldSize){return false}var maxHeapSize=_emscripten_get_heap_max();if(requestedSize>maxHeapSize){return false}for(var cutDown=1;cutDown<=4;cutDown*=2){var overGrownHeapSize=oldSize*(1+.2/cutDown);overGrownHeapSize=Math.min(overGrownHeapSize,requestedSize+100663296);var newSize=Math.min(maxHeapSize,alignUp(Math.max(requestedSize,overGrownHeapSize),65536));var replacement=emscripten_realloc_buffer(newSize);if(replacement){return true}}return false}var JSEvents={inEventHandler:0,removeAllEventListeners:function(){for(var i=JSEvents.eventHandlers.length-1;i>=0;--i){JSEvents._removeHandler(i);}JSEvents.eventHandlers=[];JSEvents.deferredCalls=[];},registerRemoveEventListeners:function(){if(!JSEvents.removeEventListenersRegistered){JSEvents.removeEventListenersRegistered=true;}},deferredCalls:[],deferCall:function(targetFunction,precedence,argsList){function arraysHaveEqualContent(arrA,arrB){if(arrA.length!=arrB.length)return false;for(var i in arrA){if(arrA[i]!=arrB[i])return false}return true}for(var i in JSEvents.deferredCalls){var call=JSEvents.deferredCalls[i];if(call.targetFunction==targetFunction&&arraysHaveEqualContent(call.argsList,argsList)){return}}JSEvents.deferredCalls.push({targetFunction:targetFunction,precedence:precedence,argsList:argsList});JSEvents.deferredCalls.sort(function(x,y){return x.precedence<y.precedence});},removeDeferredCalls:function(targetFunction){for(var i=0;i<JSEvents.deferredCalls.length;++i){if(JSEvents.deferredCalls[i].targetFunction==targetFunction){JSEvents.deferredCalls.splice(i,1);--i;}}},canPerformEventHandlerRequests:function(){return JSEvents.inEventHandler&&JSEvents.currentEventHandler.allowsDeferredCalls},runDeferredCalls:function(){if(!JSEvents.canPerformEventHandlerRequests()){return}for(var i=0;i<JSEvents.deferredCalls.length;++i){var call=JSEvents.deferredCalls[i];JSEvents.deferredCalls.splice(i,1);--i;call.targetFunction.apply(null,call.argsList);}},eventHandlers:[],removeAllHandlersOnTarget:function(target,eventTypeString){for(var i=0;i<JSEvents.eventHandlers.length;++i){if(JSEvents.eventHandlers[i].target==target&&(!eventTypeString||eventTypeString==JSEvents.eventHandlers[i].eventTypeString)){JSEvents._removeHandler(i--);}}},_removeHandler:function(i){var h=JSEvents.eventHandlers[i];h.target.removeEventListener(h.eventTypeString,h.eventListenerFunc,h.useCapture);JSEvents.eventHandlers.splice(i,1);},registerOrRemoveHandler:function(eventHandler){var jsEventHandler=function jsEventHandler(event){++JSEvents.inEventHandler;JSEvents.currentEventHandler=eventHandler;JSEvents.runDeferredCalls();eventHandler.handlerFunc(event);JSEvents.runDeferredCalls();--JSEvents.inEventHandler;};if(eventHandler.callbackfunc){eventHandler.eventListenerFunc=jsEventHandler;eventHandler.target.addEventListener(eventHandler.eventTypeString,jsEventHandler,eventHandler.useCapture);JSEvents.eventHandlers.push(eventHandler);JSEvents.registerRemoveEventListeners();}else {for(var 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(_Relu=Module["_Relu"]=Module["asm"]["Relu"]).apply(null,arguments)};var _Relu6=Module["_Relu6"]=function(){return (_Relu6=Module["_Relu6"]=Module["asm"]["Relu6"]).apply(null,arguments)};var _ResizeBilinear=Module["_ResizeBilinear"]=function(){return (_ResizeBilinear=Module["_ResizeBilinear"]=Module["asm"]["ResizeBilinear"]).apply(null,arguments)};var _Reverse=Module["_Reverse"]=function(){return (_Reverse=Module["_Reverse"]=Module["asm"]["Reverse"]).apply(null,arguments)};var _RotateWithOffset=Module["_RotateWithOffset"]=function(){return (_RotateWithOffset=Module["_RotateWithOffset"]=Module["asm"]["RotateWithOffset"]).apply(null,arguments)};var _Round=Module["_Round"]=function(){return (_Round=Module["_Round"]=Module["asm"]["Round"]).apply(null,arguments)};var _Rsqrt=Module["_Rsqrt"]=function(){return (_Rsqrt=Module["_Rsqrt"]=Module["asm"]["Rsqrt"]).apply(null,arguments)};var _ScatterNd=Module["_ScatterNd"]=function(){return (_ScatterNd=Module["_ScatterNd"]=Module["asm"]["ScatterNd"]).apply(null,arguments)};var _SelectV2=Module["_SelectV2"]=function(){return (_SelectV2=Module["_SelectV2"]=Module["asm"]["SelectV2"]).apply(null,arguments)};var _Sigmoid=Module["_Sigmoid"]=function(){return (_Sigmoid=Module["_Sigmoid"]=Module["asm"]["Sigmoid"]).apply(null,arguments)};var _Sin=Module["_Sin"]=function(){return (_Sin=Module["_Sin"]=Module["asm"]["Sin"]).apply(null,arguments)};var _Softmax=Module["_Softmax"]=function(){return (_Softmax=Module["_Softmax"]=Module["asm"]["Softmax"]).apply(null,arguments)};var _SparseFillEmptyRows=Module["_SparseFillEmptyRows"]=function(){return (_SparseFillEmptyRows=Module["_SparseFillEmptyRows"]=Module["asm"]["SparseFillEmptyRows"]).apply(null,arguments)};var _SparseReshape=Module["_SparseReshape"]=function(){return (_SparseReshape=Module["_SparseReshape"]=Module["asm"]["SparseReshape"]).apply(null,arguments)};var _SparseSegmentReduction=Module["_SparseSegmentReduction"]=function(){return (_SparseSegmentReduction=Module["_SparseSegmentReduction"]=Module["asm"]["SparseSegmentReduction"]).apply(null,arguments)};var _Sqrt=Module["_Sqrt"]=function(){return (_Sqrt=Module["_Sqrt"]=Module["asm"]["Sqrt"]).apply(null,arguments)};var _Square=Module["_Square"]=function(){return (_Square=Module["_Square"]=Module["asm"]["Square"]).apply(null,arguments)};var _SquaredDifference=Module["_SquaredDifference"]=function(){return (_SquaredDifference=Module["_SquaredDifference"]=Module["asm"]["SquaredDifference"]).apply(null,arguments)};var _Step=Module["_Step"]=function(){return (_Step=Module["_Step"]=Module["asm"]["Step"]).apply(null,arguments)};var _StridedSlice=Module["_StridedSlice"]=function(){return (_StridedSlice=Module["_StridedSlice"]=Module["asm"]["StridedSlice"]).apply(null,arguments)};var _Sub=Module["_Sub"]=function(){return (_Sub=Module["_Sub"]=Module["asm"]["Sub"]).apply(null,arguments)};var _Sum=Module["_Sum"]=function(){return (_Sum=Module["_Sum"]=Module["asm"]["Sum"]).apply(null,arguments)};var _Tan=Module["_Tan"]=function(){return (_Tan=Module["_Tan"]=Module["asm"]["Tan"]).apply(null,arguments)};var _Tanh=Module["_Tanh"]=function(){return (_Tanh=Module["_Tanh"]=Module["asm"]["Tanh"]).apply(null,arguments)};var _Tile=Module["_Tile"]=function(){return (_Tile=Module["_Tile"]=Module["asm"]["Tile"]).apply(null,arguments)};var _TopK=Module["_TopK"]=function(){return (_TopK=Module["_TopK"]=Module["asm"]["TopK"]).apply(null,arguments)};var _Transform=Module["_Transform"]=function(){return (_Transform=Module["_Transform"]=Module["asm"]["Transform"]).apply(null,arguments)};var _Transpose=Module["_Transpose"]=function(){return (_Transpose=Module["_Transpose"]=Module["asm"]["Transpose"]).apply(null,arguments)};var __FusedMatMul=Module["__FusedMatMul"]=function(){return (__FusedMatMul=Module["__FusedMatMul"]=Module["asm"]["_FusedMatMul"]).apply(null,arguments)};var _malloc=Module["_malloc"]=function(){return (_malloc=Module["_malloc"]=Module["asm"]["malloc"]).apply(null,arguments)};var _free=Module["_free"]=function(){return (_free=Module["_free"]=Module["asm"]["free"]).apply(null,arguments)};var _emscripten_tls_init=Module["_emscripten_tls_init"]=function(){return (_emscripten_tls_init=Module["_emscripten_tls_init"]=Module["asm"]["emscripten_tls_init"]).apply(null,arguments)};var ___errno_location=Module["___errno_location"]=function(){return (___errno_location=Module["___errno_location"]=Module["asm"]["__errno_location"]).apply(null,arguments)};var _pthread_self=Module["_pthread_self"]=function(){return (_pthread_self=Module["_pthread_self"]=Module["asm"]["pthread_self"]).apply(null,arguments)};var _emscripten_main_thread_process_queued_calls=Module["_emscripten_main_thread_process_queued_calls"]=function(){return (_emscripten_main_thread_process_queued_calls=Module["_emscripten_main_thread_process_queued_calls"]=Module["asm"]["emscripten_main_thread_process_queued_calls"]).apply(null,arguments)};var __emscripten_thread_crashed=Module["__emscripten_thread_crashed"]=function(){return (__emscripten_thread_crashed=Module["__emscripten_thread_crashed"]=Module["asm"]["_emscripten_thread_crashed"]).apply(null,arguments)};var __emscripten_thread_init=Module["__emscripten_thread_init"]=function(){return (__emscripten_thread_init=Module["__emscripten_thread_init"]=Module["asm"]["_emscripten_thread_init"]).apply(null,arguments)};var _emscripten_current_thread_process_queued_calls=Module["_emscripten_current_thread_process_queued_calls"]=function(){return (_emscripten_current_thread_process_queued_calls=Module["_emscripten_current_thread_process_queued_calls"]=Module["asm"]["emscripten_current_thread_process_queued_calls"]).apply(null,arguments)};var _emscripten_main_browser_thread_id=Module["_emscripten_main_browser_thread_id"]=function(){return (_emscripten_main_browser_thread_id=Module["_emscripten_main_browser_thread_id"]=Module["asm"]["emscripten_main_browser_thread_id"]).apply(null,arguments)};var _emscripten_sync_run_in_main_thread_2=Module["_emscripten_sync_run_in_main_thread_2"]=function(){return (_emscripten_sync_run_in_main_thread_2=Module["_emscripten_sync_run_in_main_thread_2"]=Module["asm"]["emscripten_sync_run_in_main_thread_2"]).apply(null,arguments)};var _emscripten_sync_run_in_main_thread_4=Module["_emscripten_sync_run_in_main_thread_4"]=function(){return (_emscripten_sync_run_in_main_thread_4=Module["_emscripten_sync_run_in_main_thread_4"]=Module["asm"]["emscripten_sync_run_in_main_thread_4"]).apply(null,arguments)};var _emscripten_run_in_main_runtime_thread_js=Module["_emscripten_run_in_main_runtime_thread_js"]=function(){return (_emscripten_run_in_main_runtime_thread_js=Module["_emscripten_run_in_main_runtime_thread_js"]=Module["asm"]["emscripten_run_in_main_runtime_thread_js"]).apply(null,arguments)};var _emscripten_dispatch_to_thread_=Module["_emscripten_dispatch_to_thread_"]=function(){return (_emscripten_dispatch_to_thread_=Module["_emscripten_dispatch_to_thread_"]=Module["asm"]["emscripten_dispatch_to_thread_"]).apply(null,arguments)};var __emscripten_thread_free_data=Module["__emscripten_thread_free_data"]=function(){return (__emscripten_thread_free_data=Module["__emscripten_thread_free_data"]=Module["asm"]["_emscripten_thread_free_data"]).apply(null,arguments)};var __emscripten_thread_exit=Module["__emscripten_thread_exit"]=function(){return (__emscripten_thread_exit=Module["__emscripten_thread_exit"]=Module["asm"]["_emscripten_thread_exit"]).apply(null,arguments)};var _memalign=Module["_memalign"]=function(){return (_memalign=Module["_memalign"]=Module["asm"]["memalign"]).apply(null,arguments)};var _emscripten_stack_set_limits=Module["_emscripten_stack_set_limits"]=function(){return (_emscripten_stack_set_limits=Module["_emscripten_stack_set_limits"]=Module["asm"]["emscripten_stack_set_limits"]).apply(null,arguments)};var stackSave=Module["stackSave"]=function(){return (stackSave=Module["stackSave"]=Module["asm"]["stackSave"]).apply(null,arguments)};var stackRestore=Module["stackRestore"]=function(){return (stackRestore=Module["stackRestore"]=Module["asm"]["stackRestore"]).apply(null,arguments)};var stackAlloc=Module["stackAlloc"]=function(){return (stackAlloc=Module["stackAlloc"]=Module["asm"]["stackAlloc"]).apply(null,arguments)};var dynCall_iijjiiii=Module["dynCall_iijjiiii"]=function(){return (dynCall_iijjiiii=Module["dynCall_iijjiiii"]=Module["asm"]["dynCall_iijjiiii"]).apply(null,arguments)};var dynCall_jiji=Module["dynCall_jiji"]=function(){return (dynCall_jiji=Module["dynCall_jiji"]=Module["asm"]["dynCall_jiji"]).apply(null,arguments)};var __emscripten_allow_main_runtime_queued_calls=Module["__emscripten_allow_main_runtime_queued_calls"]=21464;Module["cwrap"]=cwrap;Module["keepRuntimeAlive"]=keepRuntimeAlive;Module["PThread"]=PThread;Module["PThread"]=PThread;Module["wasmMemory"]=wasmMemory;Module["ExitStatus"]=ExitStatus;var calledRun;function ExitStatus(status){this.name="ExitStatus";this.message="Program terminated with exit("+status+")";this.status=status;}dependenciesFulfilled=function runCaller(){if(!calledRun)run();if(!calledRun)dependenciesFulfilled=runCaller;};function run(args){if(runDependencies>0){return}if(ENVIRONMENT_IS_PTHREAD){readyPromiseResolve(Module);initRuntime();postMessage({"cmd":"loaded"});return}preRun();if(runDependencies>0){return}function doRun(){if(calledRun)return;calledRun=true;Module["calledRun"]=true;if(ABORT)return;initRuntime();readyPromiseResolve(Module);if(Module["onRuntimeInitialized"])Module["onRuntimeInitialized"]();postRun();}if(Module["setStatus"]){Module["setStatus"]("Running...");setTimeout(function(){setTimeout(function(){Module["setStatus"]("");},1);doRun();},1);}else {doRun();}}Module["run"]=run;function exit(status,implicit){EXITSTATUS=status;if(!implicit){if(ENVIRONMENT_IS_PTHREAD){exitOnMainThread(status);throw "unwind"}}if(keepRuntimeAlive());else {exitRuntime();}procExit(status);}function procExit(code){EXITSTATUS=code;if(!keepRuntimeAlive()){PThread.terminateAllThreads();if(Module["onExit"])Module["onExit"](code);ABORT=true;}quit_(code,new ExitStatus(code));}if(Module["preInit"]){if(typeof Module["preInit"]=="function")Module["preInit"]=[Module["preInit"]];while(Module["preInit"].length>0){Module["preInit"].pop()();}}run();var listenersAdded;if(beforeListeners){listenersAdded={uncaughtException:process.listeners("uncaughtException").filter(function(listener){return !beforeListeners.uncaughtException.indexOf(listener)>-1}),unhandledRejection:process.listeners("unhandledRejection").filter(function(listener){return !beforeListeners.unhandledRejection.indexOf(listener)>-1})};}var actualModule;if(typeof WasmBackendModule!=="undefined"){actualModule=WasmBackendModule;}else if(typeof WasmBackendModuleThreadedSimd!=="undefined"){actualModule=WasmBackendModuleThreadedSimd;}else {throw new Error("Could not find wasm module in post.js")}if(listenersAdded){var tmpDispose=actualModule["_dispose"];actualModule["_dispose"]=function(){tmpDispose();listenersAdded.uncaughtException.forEach(function(listener){process.removeListener("uncaughtException",listener);});listenersAdded.unhandledRejection.forEach(function(listener){process.removeListener("unhandledRejection",listener);});};}
|
|
|
return WasmBackendModuleThreadedSimd.ready
|
}
|
);
|
})();
|
module.exports = WasmBackendModuleThreadedSimd;
|
});
|
|
const wasmWorkerContents = '"use strict";var Module={};var ENVIRONMENT_IS_NODE=typeof process==="object"&&typeof process.versions==="object"&&typeof process.versions.node==="string";if(ENVIRONMENT_IS_NODE){var nodeWorkerThreads=require("worker_threads");var parentPort=nodeWorkerThreads.parentPort;parentPort.on("message",function(data){onmessage({data:data})});var fs=require("fs");Object.assign(global,{self:global,require:require,Module:Module,location:{href:__filename},Worker:nodeWorkerThreads.Worker,importScripts:function(f){(0,eval)(fs.readFileSync(f,"utf8"))},postMessage:function(msg){parentPort.postMessage(msg)},performance:global.performance||{now:function(){return Date.now()}}})}function threadPrintErr(){var text=Array.prototype.slice.call(arguments).join(" ");if(ENVIRONMENT_IS_NODE){fs.writeSync(2,text+"\n");return}console.error(text)}function threadAlert(){var text=Array.prototype.slice.call(arguments).join(" ");postMessage({cmd:"alert",text:text,threadId:Module["_pthread_self"]()})}var err=threadPrintErr;self.alert=threadAlert;Module["instantiateWasm"]=((info,receiveInstance)=>{var instance=new WebAssembly.Instance(Module["wasmModule"],info);receiveInstance(instance);Module["wasmModule"]=null;return instance.exports});self.onmessage=(e=>{try{if(e.data.cmd==="load"){Module["wasmModule"]=e.data.wasmModule;Module["wasmMemory"]=e.data.wasmMemory;Module["buffer"]=Module["wasmMemory"].buffer;Module["ENVIRONMENT_IS_PTHREAD"]=true;if(typeof e.data.urlOrBlob==="string"){importScripts(e.data.urlOrBlob)}else{var objectUrl=URL.createObjectURL(e.data.urlOrBlob);importScripts(objectUrl);URL.revokeObjectURL(objectUrl)}WasmBackendModuleThreadedSimd(Module).then(function(instance){Module=instance})}else if(e.data.cmd==="run"){Module["__performance_now_clock_drift"]=performance.now()-e.data.time;Module["__emscripten_thread_init"](e.data.threadInfoStruct,0,0,1);Module["establishStackSpace"]();Module["PThread"].receiveObjectTransfer(e.data);Module["PThread"].threadInit();try{var result=Module["invokeEntryPoint"](e.data.start_routine,e.data.arg);if(Module["keepRuntimeAlive"]()){Module["PThread"].setExitStatus(result)}else{Module["__emscripten_thread_exit"](result)}}catch(ex){if(ex!="unwind"){if(ex instanceof Module["ExitStatus"]){if(Module["keepRuntimeAlive"]()){}else{Module["__emscripten_thread_exit"](ex.status)}}else{throw ex}}}}else if(e.data.cmd==="cancel"){if(Module["_pthread_self"]()){Module["__emscripten_thread_exit"](-1)}}else if(e.data.target==="setimmediate"){}else if(e.data.cmd==="processThreadQueue"){if(Module["_pthread_self"]()){Module["_emscripten_current_thread_process_queued_calls"]()}}else if(e.data.cmd==="processProxyingQueue"){if(Module["_pthread_self"]()){Module["_emscripten_proxy_execute_queue"](e.data.queue)}}else{err("worker.js received unknown command "+e.data.cmd);err(e.data)}}catch(ex){err("worker.js onmessage() captured an uncaught exception: "+ex);if(ex&&ex.stack)err(ex.stack);if(Module["__emscripten_thread_crashed"]){Module["__emscripten_thread_crashed"]()}throw ex}});';
|
|
var tfjsBackendWasm = createCommonjsModule(function (module, exports) {
|
var WasmBackendModule = (() => {
|
var _scriptDir = typeof document !== 'undefined' && document.currentScript ? document.currentScript.src : undefined;
|
if (typeof __filename !== 'undefined') _scriptDir = _scriptDir || __filename;
|
return (
|
function(WasmBackendModule) {
|
WasmBackendModule = WasmBackendModule || {};
|
|
var Module=typeof WasmBackendModule!=="undefined"?WasmBackendModule:{};var readyPromiseResolve,readyPromiseReject;Module["ready"]=new Promise(function(resolve,reject){readyPromiseResolve=resolve;readyPromiseReject=reject;});var beforeListeners;if(typeof process!=="undefined"&&process.listeners){beforeListeners={uncaughtException:process.listeners("uncaughtException"),unhandledRejection:process.listeners("unhandledRejection")};}var moduleOverrides=Object.assign({},Module);var arguments_=[];var thisProgram="./this.program";var quit_=(status,toThrow)=>{throw toThrow};var ENVIRONMENT_IS_WEB=typeof window==="object";var ENVIRONMENT_IS_WORKER=typeof importScripts==="function";var ENVIRONMENT_IS_NODE=typeof process==="object"&&typeof process.versions==="object"&&typeof process.versions.node==="string";var scriptDirectory="";function locateFile(path){if(Module["locateFile"]){return Module["locateFile"](path,scriptDirectory)}return scriptDirectory+path}var read_,readAsync,readBinary;function logExceptionOnExit(e){if(e instanceof ExitStatus)return;let toLog=e;err("exiting due to exception: "+toLog);}var fs$1;var nodePath;var requireNodeFS;if(ENVIRONMENT_IS_NODE){if(ENVIRONMENT_IS_WORKER){scriptDirectory=path.dirname(scriptDirectory)+"/";}else {scriptDirectory=__dirname+"/";}requireNodeFS=(()=>{if(!nodePath){fs$1=fs;nodePath=path;}});read_=function shell_read(filename,binary){requireNodeFS();filename=nodePath["normalize"](filename);return fs$1.readFileSync(filename,binary?undefined:"utf8")};readBinary=(filename=>{var ret=read_(filename,true);if(!ret.buffer){ret=new Uint8Array(ret);}return ret});readAsync=((filename,onload,onerror)=>{requireNodeFS();filename=nodePath["normalize"](filename);fs$1.readFile(filename,function(err,data){if(err)onerror(err);else onload(data.buffer);});});if(process["argv"].length>1){thisProgram=process["argv"][1].replace(/\\/g,"/");}arguments_=process["argv"].slice(2);process["on"]("uncaughtException",function(ex){if(!(ex instanceof ExitStatus)){throw ex}});process["on"]("unhandledRejection",function(reason){throw reason});quit_=((status,toThrow)=>{if(keepRuntimeAlive()){process["exitCode"]=status;throw toThrow}logExceptionOnExit(toThrow);process["exit"](status);});Module["inspect"]=function(){return "[Emscripten Module object]"};}else if(ENVIRONMENT_IS_WEB||ENVIRONMENT_IS_WORKER){if(ENVIRONMENT_IS_WORKER){scriptDirectory=self.location.href;}else if(typeof document!=="undefined"&&document.currentScript){scriptDirectory=document.currentScript.src;}if(_scriptDir){scriptDirectory=_scriptDir;}if(scriptDirectory.indexOf("blob:")!==0){scriptDirectory=scriptDirectory.substr(0,scriptDirectory.replace(/[?#].*/,"").lastIndexOf("/")+1);}else {scriptDirectory="";}{read_=(url=>{var xhr=new XMLHttpRequest;xhr.open("GET",url,false);xhr.send(null);return xhr.responseText});if(ENVIRONMENT_IS_WORKER){readBinary=(url=>{var xhr=new XMLHttpRequest;xhr.open("GET",url,false);xhr.responseType="arraybuffer";xhr.send(null);return new Uint8Array(xhr.response)});}readAsync=((url,onload,onerror)=>{var xhr=new XMLHttpRequest;xhr.open("GET",url,true);xhr.responseType="arraybuffer";xhr.onload=(()=>{if(xhr.status==200||xhr.status==0&&xhr.response){onload(xhr.response);return}onerror();});xhr.onerror=onerror;xhr.send(null);});}}var out=Module["print"]||console.log.bind(console);var err=Module["printErr"]||console.warn.bind(console);Object.assign(Module,moduleOverrides);moduleOverrides=null;if(Module["arguments"])arguments_=Module["arguments"];if(Module["thisProgram"])thisProgram=Module["thisProgram"];if(Module["quit"])quit_=Module["quit"];var wasmBinary;if(Module["wasmBinary"])wasmBinary=Module["wasmBinary"];var noExitRuntime=Module["noExitRuntime"]||true;if(typeof WebAssembly!=="object"){abort("no native wasm support detected");}var wasmMemory;var ABORT=false;function getCFunc(ident){var func=Module["_"+ident];return func}function ccall(ident,returnType,argTypes,args,opts){var toC={"string":function(str){var ret=0;if(str!==null&&str!==undefined&&str!==0){var len=(str.length<<2)+1;ret=stackAlloc(len);stringToUTF8(str,ret,len);}return ret},"array":function(arr){var ret=stackAlloc(arr.length);writeArrayToMemory(arr,ret);return ret}};function convertReturnValue(ret){if(returnType==="string")return UTF8ToString(ret);if(returnType==="boolean")return Boolean(ret);return ret}var func=getCFunc(ident);var cArgs=[];var stack=0;if(args){for(var i=0;i<args.length;i++){var converter=toC[argTypes[i]];if(converter){if(stack===0)stack=stackSave();cArgs[i]=converter(args[i]);}else {cArgs[i]=args[i];}}}var ret=func.apply(null,cArgs);function onDone(ret){if(stack!==0)stackRestore(stack);return convertReturnValue(ret)}ret=onDone(ret);return ret}function cwrap(ident,returnType,argTypes,opts){argTypes=argTypes||[];var numericArgs=argTypes.every(function(type){return type==="number"});var numericRet=returnType!=="string";if(numericRet&&numericArgs&&!opts){return getCFunc(ident)}return function(){return ccall(ident,returnType,argTypes,arguments)}}var UTF8Decoder=typeof TextDecoder!=="undefined"?new TextDecoder("utf8"):undefined;function UTF8ArrayToString(heap,idx,maxBytesToRead){var endIdx=idx+maxBytesToRead;var endPtr=idx;while(heap[endPtr]&&!(endPtr>=endIdx))++endPtr;if(endPtr-idx>16&&heap.subarray&&UTF8Decoder){return UTF8Decoder.decode(heap.subarray(idx,endPtr))}else {var str="";while(idx<endPtr){var u0=heap[idx++];if(!(u0&128)){str+=String.fromCharCode(u0);continue}var u1=heap[idx++]&63;if((u0&224)==192){str+=String.fromCharCode((u0&31)<<6|u1);continue}var u2=heap[idx++]&63;if((u0&240)==224){u0=(u0&15)<<12|u1<<6|u2;}else {u0=(u0&7)<<18|u1<<12|u2<<6|heap[idx++]&63;}if(u0<65536){str+=String.fromCharCode(u0);}else {var ch=u0-65536;str+=String.fromCharCode(55296|ch>>10,56320|ch&1023);}}}return str}function UTF8ToString(ptr,maxBytesToRead){return ptr?UTF8ArrayToString(HEAPU8,ptr,maxBytesToRead):""}function stringToUTF8Array(str,heap,outIdx,maxBytesToWrite){if(!(maxBytesToWrite>0))return 0;var startIdx=outIdx;var endIdx=outIdx+maxBytesToWrite-1;for(var i=0;i<str.length;++i){var u=str.charCodeAt(i);if(u>=55296&&u<=57343){var u1=str.charCodeAt(++i);u=65536+((u&1023)<<10)|u1&1023;}if(u<=127){if(outIdx>=endIdx)break;heap[outIdx++]=u;}else if(u<=2047){if(outIdx+1>=endIdx)break;heap[outIdx++]=192|u>>6;heap[outIdx++]=128|u&63;}else if(u<=65535){if(outIdx+2>=endIdx)break;heap[outIdx++]=224|u>>12;heap[outIdx++]=128|u>>6&63;heap[outIdx++]=128|u&63;}else {if(outIdx+3>=endIdx)break;heap[outIdx++]=240|u>>18;heap[outIdx++]=128|u>>12&63;heap[outIdx++]=128|u>>6&63;heap[outIdx++]=128|u&63;}}heap[outIdx]=0;return outIdx-startIdx}function stringToUTF8(str,outPtr,maxBytesToWrite){return stringToUTF8Array(str,HEAPU8,outPtr,maxBytesToWrite)}var UTF16Decoder=typeof TextDecoder!=="undefined"?new TextDecoder("utf-16le"):undefined;function writeArrayToMemory(array,buffer){HEAP8.set(array,buffer);}function alignUp(x,multiple){if(x%multiple>0){x+=multiple-x%multiple;}return x}var buffer,HEAP8,HEAPU8,HEAP16,HEAPU16,HEAP32,HEAPU32,HEAPF32,HEAPF64;function updateGlobalBufferAndViews(buf){buffer=buf;Module["HEAP8"]=HEAP8=new Int8Array(buf);Module["HEAP16"]=HEAP16=new Int16Array(buf);Module["HEAP32"]=HEAP32=new Int32Array(buf);Module["HEAPU8"]=HEAPU8=new Uint8Array(buf);Module["HEAPU16"]=HEAPU16=new Uint16Array(buf);Module["HEAPU32"]=HEAPU32=new Uint32Array(buf);Module["HEAPF32"]=HEAPF32=new Float32Array(buf);Module["HEAPF64"]=HEAPF64=new Float64Array(buf);}var INITIAL_MEMORY=Module["INITIAL_MEMORY"]||16777216;var wasmTable;var __ATPRERUN__=[];var __ATINIT__=[];var __ATPOSTRUN__=[];var runtimeKeepaliveCounter=0;function keepRuntimeAlive(){return noExitRuntime||runtimeKeepaliveCounter>0}function preRun(){if(Module["preRun"]){if(typeof Module["preRun"]=="function")Module["preRun"]=[Module["preRun"]];while(Module["preRun"].length){addOnPreRun(Module["preRun"].shift());}}callRuntimeCallbacks(__ATPRERUN__);}function initRuntime(){callRuntimeCallbacks(__ATINIT__);}function postRun(){if(Module["postRun"]){if(typeof Module["postRun"]=="function")Module["postRun"]=[Module["postRun"]];while(Module["postRun"].length){addOnPostRun(Module["postRun"].shift());}}callRuntimeCallbacks(__ATPOSTRUN__);}function addOnPreRun(cb){__ATPRERUN__.unshift(cb);}function addOnInit(cb){__ATINIT__.unshift(cb);}function addOnPostRun(cb){__ATPOSTRUN__.unshift(cb);}var runDependencies=0;var dependenciesFulfilled=null;function addRunDependency(id){runDependencies++;if(Module["monitorRunDependencies"]){Module["monitorRunDependencies"](runDependencies);}}function removeRunDependency(id){runDependencies--;if(Module["monitorRunDependencies"]){Module["monitorRunDependencies"](runDependencies);}if(runDependencies==0){if(dependenciesFulfilled){var callback=dependenciesFulfilled;dependenciesFulfilled=null;callback();}}}Module["preloadedImages"]={};Module["preloadedAudios"]={};function abort(what){{if(Module["onAbort"]){Module["onAbort"](what);}}what="Aborted("+what+")";err(what);ABORT=true;what+=". Build with -s ASSERTIONS=1 for more info.";var e=new WebAssembly.RuntimeError(what);readyPromiseReject(e);throw e}var dataURIPrefix="data:application/octet-stream;base64,";function isDataURI(filename){return filename.startsWith(dataURIPrefix)}function isFileURI(filename){return filename.startsWith("file://")}var wasmBinaryFile;wasmBinaryFile="tfjs-backend-wasm.wasm";if(!isDataURI(wasmBinaryFile)){wasmBinaryFile=locateFile(wasmBinaryFile);}function getBinary(file){try{if(file==wasmBinaryFile&&wasmBinary){return new Uint8Array(wasmBinary)}if(readBinary){return readBinary(file)}else {throw "both async and sync fetching of the wasm failed"}}catch(err){abort(err);}}function getBinaryPromise(){if(!wasmBinary&&(ENVIRONMENT_IS_WEB||ENVIRONMENT_IS_WORKER)){if(typeof fetch==="function"&&!isFileURI(wasmBinaryFile)){return fetch(wasmBinaryFile,{credentials:"same-origin"}).then(function(response){if(!response["ok"]){throw "failed to load wasm binary file at '"+wasmBinaryFile+"'"}return response["arrayBuffer"]()}).catch(function(){return getBinary(wasmBinaryFile)})}else {if(readAsync){return new Promise(function(resolve,reject){readAsync(wasmBinaryFile,function(response){resolve(new Uint8Array(response));},reject);})}}}return Promise.resolve().then(function(){return getBinary(wasmBinaryFile)})}function createWasm(){var info={"env":asmLibraryArg,"wasi_snapshot_preview1":asmLibraryArg};function receiveInstance(instance,module){var exports=instance.exports;Module["asm"]=exports;wasmMemory=Module["asm"]["memory"];updateGlobalBufferAndViews(wasmMemory.buffer);wasmTable=Module["asm"]["__indirect_function_table"];addOnInit(Module["asm"]["__wasm_call_ctors"]);removeRunDependency();}addRunDependency();function receiveInstantiationResult(result){receiveInstance(result["instance"]);}function instantiateArrayBuffer(receiver){return getBinaryPromise().then(function(binary){return WebAssembly.instantiate(binary,info)}).then(function(instance){return instance}).then(receiver,function(reason){err("failed to asynchronously prepare wasm: "+reason);abort(reason);})}function instantiateAsync(){if(!wasmBinary&&typeof WebAssembly.instantiateStreaming==="function"&&!isDataURI(wasmBinaryFile)&&!isFileURI(wasmBinaryFile)&&typeof fetch==="function"){return fetch(wasmBinaryFile,{credentials:"same-origin"}).then(function(response){var result=WebAssembly.instantiateStreaming(response,info);return result.then(receiveInstantiationResult,function(reason){err("wasm streaming compile failed: "+reason);err("falling back to ArrayBuffer instantiation");return instantiateArrayBuffer(receiveInstantiationResult)})})}else {return instantiateArrayBuffer(receiveInstantiationResult)}}if(Module["instantiateWasm"]){try{var exports=Module["instantiateWasm"](info,receiveInstance);return exports}catch(e){err("Module.instantiateWasm callback failed with error: "+e);return false}}instantiateAsync().catch(readyPromiseReject);return {}}function callRuntimeCallbacks(callbacks){while(callbacks.length>0){var callback=callbacks.shift();if(typeof callback=="function"){callback(Module);continue}var func=callback.func;if(typeof func==="number"){if(callback.arg===undefined){getWasmTableEntry(func)();}else {getWasmTableEntry(func)(callback.arg);}}else {func(callback.arg===undefined?null:callback.arg);}}}var wasmTableMirror=[];function getWasmTableEntry(funcPtr){var func=wasmTableMirror[funcPtr];if(!func){if(funcPtr>=wasmTableMirror.length)wasmTableMirror.length=funcPtr+1;wasmTableMirror[funcPtr]=func=wasmTable.get(funcPtr);}return func}function _abort(){abort("");}function _emscripten_get_heap_max(){return 2147483648}function _emscripten_memcpy_big(dest,src,num){HEAPU8.copyWithin(dest,src,src+num);}function emscripten_realloc_buffer(size){try{wasmMemory.grow(size-buffer.byteLength+65535>>>16);updateGlobalBufferAndViews(wasmMemory.buffer);return 1}catch(e){}}function _emscripten_resize_heap(requestedSize){var oldSize=HEAPU8.length;requestedSize=requestedSize>>>0;var maxHeapSize=_emscripten_get_heap_max();if(requestedSize>maxHeapSize){return false}for(var cutDown=1;cutDown<=4;cutDown*=2){var overGrownHeapSize=oldSize*(1+.2/cutDown);overGrownHeapSize=Math.min(overGrownHeapSize,requestedSize+100663296);var newSize=Math.min(maxHeapSize,alignUp(Math.max(requestedSize,overGrownHeapSize),65536));var replacement=emscripten_realloc_buffer(newSize);if(replacement){return true}}return false}var SYSCALLS={mappings:{},buffers:[null,[],[]],printChar:function(stream,curr){var buffer=SYSCALLS.buffers[stream];if(curr===0||curr===10){(stream===1?out:err)(UTF8ArrayToString(buffer,0));buffer.length=0;}else {buffer.push(curr);}},varargs:undefined,get:function(){SYSCALLS.varargs+=4;var ret=HEAP32[SYSCALLS.varargs-4>>2];return ret},getStr:function(ptr){var ret=UTF8ToString(ptr);return ret},get64:function(low,high){return low}};function _fd_close(fd){return 0}function _fd_seek(fd,offset_low,offset_high,whence,newOffset){}function _fd_write(fd,iov,iovcnt,pnum){var num=0;for(var i=0;i<iovcnt;i++){var ptr=HEAP32[iov>>2];var len=HEAP32[iov+4>>2];iov+=8;for(var j=0;j<len;j++){SYSCALLS.printChar(fd,HEAPU8[ptr+j]);}num+=len;}HEAP32[pnum>>2]=num;return 0}function _setTempRet0(val){}var asmLibraryArg={"abort":_abort,"emscripten_get_heap_max":_emscripten_get_heap_max,"emscripten_memcpy_big":_emscripten_memcpy_big,"emscripten_resize_heap":_emscripten_resize_heap,"fd_close":_fd_close,"fd_seek":_fd_seek,"fd_write":_fd_write,"setTempRet0":_setTempRet0};var asm=createWasm();var ___wasm_call_ctors=Module["___wasm_call_ctors"]=function(){return (___wasm_call_ctors=Module["___wasm_call_ctors"]=Module["asm"]["__wasm_call_ctors"]).apply(null,arguments)};var _init=Module["_init"]=function(){return (_init=Module["_init"]=Module["asm"]["init"]).apply(null,arguments)};var _init_with_threads_count=Module["_init_with_threads_count"]=function(){return (_init_with_threads_count=Module["_init_with_threads_count"]=Module["asm"]["init_with_threads_count"]).apply(null,arguments)};var _get_threads_count=Module["_get_threads_count"]=function(){return (_get_threads_count=Module["_get_threads_count"]=Module["asm"]["get_threads_count"]).apply(null,arguments)};var _register_tensor=Module["_register_tensor"]=function(){return (_register_tensor=Module["_register_tensor"]=Module["asm"]["register_tensor"]).apply(null,arguments)};var _dispose_data=Module["_dispose_data"]=function(){return (_dispose_data=Module["_dispose_data"]=Module["asm"]["dispose_data"]).apply(null,arguments)};var _dispose=Module["_dispose"]=function(){return (_dispose=Module["_dispose"]=Module["asm"]["dispose"]).apply(null,arguments)};var _Abs=Module["_Abs"]=function(){return (_Abs=Module["_Abs"]=Module["asm"]["Abs"]).apply(null,arguments)};var _Add=Module["_Add"]=function(){return (_Add=Module["_Add"]=Module["asm"]["Add"]).apply(null,arguments)};var _AddN=Module["_AddN"]=function(){return (_AddN=Module["_AddN"]=Module["asm"]["AddN"]).apply(null,arguments)};var _All=Module["_All"]=function(){return (_All=Module["_All"]=Module["asm"]["All"]).apply(null,arguments)};var _Any=Module["_Any"]=function(){return (_Any=Module["_Any"]=Module["asm"]["Any"]).apply(null,arguments)};var _ArgMax=Module["_ArgMax"]=function(){return (_ArgMax=Module["_ArgMax"]=Module["asm"]["ArgMax"]).apply(null,arguments)};var _AvgPool=Module["_AvgPool"]=function(){return (_AvgPool=Module["_AvgPool"]=Module["asm"]["AvgPool"]).apply(null,arguments)};var _BatchMatMul=Module["_BatchMatMul"]=function(){return (_BatchMatMul=Module["_BatchMatMul"]=Module["asm"]["BatchMatMul"]).apply(null,arguments)};var _Ceil=Module["_Ceil"]=function(){return (_Ceil=Module["_Ceil"]=Module["asm"]["Ceil"]).apply(null,arguments)};var _ClipByValue=Module["_ClipByValue"]=function(){return (_ClipByValue=Module["_ClipByValue"]=Module["asm"]["ClipByValue"]).apply(null,arguments)};var _Conv2D=Module["_Conv2D"]=function(){return (_Conv2D=Module["_Conv2D"]=Module["asm"]["Conv2D"]).apply(null,arguments)};var _Conv2DBackpropInput=Module["_Conv2DBackpropInput"]=function(){return (_Conv2DBackpropInput=Module["_Conv2DBackpropInput"]=Module["asm"]["Conv2DBackpropInput"]).apply(null,arguments)};var _Cos=Module["_Cos"]=function(){return (_Cos=Module["_Cos"]=Module["asm"]["Cos"]).apply(null,arguments)};var _Cosh=Module["_Cosh"]=function(){return (_Cosh=Module["_Cosh"]=Module["asm"]["Cosh"]).apply(null,arguments)};var _CropAndResize=Module["_CropAndResize"]=function(){return (_CropAndResize=Module["_CropAndResize"]=Module["asm"]["CropAndResize"]).apply(null,arguments)};var _Cumprod=Module["_Cumprod"]=function(){return (_Cumprod=Module["_Cumprod"]=Module["asm"]["Cumprod"]).apply(null,arguments)};var _Cumsum=Module["_Cumsum"]=function(){return (_Cumsum=Module["_Cumsum"]=Module["asm"]["Cumsum"]).apply(null,arguments)};var _DepthToSpace=Module["_DepthToSpace"]=function(){return (_DepthToSpace=Module["_DepthToSpace"]=Module["asm"]["DepthToSpace"]).apply(null,arguments)};var _DepthwiseConv2dNative=Module["_DepthwiseConv2dNative"]=function(){return (_DepthwiseConv2dNative=Module["_DepthwiseConv2dNative"]=Module["asm"]["DepthwiseConv2dNative"]).apply(null,arguments)};var _Elu=Module["_Elu"]=function(){return (_Elu=Module["_Elu"]=Module["asm"]["Elu"]).apply(null,arguments)};var _Equal=Module["_Equal"]=function(){return (_Equal=Module["_Equal"]=Module["asm"]["Equal"]).apply(null,arguments)};var _Exp=Module["_Exp"]=function(){return (_Exp=Module["_Exp"]=Module["asm"]["Exp"]).apply(null,arguments)};var _FlipLeftRight=Module["_FlipLeftRight"]=function(){return (_FlipLeftRight=Module["_FlipLeftRight"]=Module["asm"]["FlipLeftRight"]).apply(null,arguments)};var _Floor=Module["_Floor"]=function(){return (_Floor=Module["_Floor"]=Module["asm"]["Floor"]).apply(null,arguments)};var _FloorDiv=Module["_FloorDiv"]=function(){return (_FloorDiv=Module["_FloorDiv"]=Module["asm"]["FloorDiv"]).apply(null,arguments)};var _FusedBatchNorm=Module["_FusedBatchNorm"]=function(){return (_FusedBatchNorm=Module["_FusedBatchNorm"]=Module["asm"]["FusedBatchNorm"]).apply(null,arguments)};var _FusedConv2D=Module["_FusedConv2D"]=function(){return (_FusedConv2D=Module["_FusedConv2D"]=Module["asm"]["FusedConv2D"]).apply(null,arguments)};var _FusedDepthwiseConv2D=Module["_FusedDepthwiseConv2D"]=function(){return (_FusedDepthwiseConv2D=Module["_FusedDepthwiseConv2D"]=Module["asm"]["FusedDepthwiseConv2D"]).apply(null,arguments)};var _Gather=Module["_Gather"]=function(){return (_Gather=Module["_Gather"]=Module["asm"]["Gather"]).apply(null,arguments)};var _GatherNd=Module["_GatherNd"]=function(){return (_GatherNd=Module["_GatherNd"]=Module["asm"]["GatherNd"]).apply(null,arguments)};var _Greater=Module["_Greater"]=function(){return (_Greater=Module["_Greater"]=Module["asm"]["Greater"]).apply(null,arguments)};var _GreaterEqual=Module["_GreaterEqual"]=function(){return (_GreaterEqual=Module["_GreaterEqual"]=Module["asm"]["GreaterEqual"]).apply(null,arguments)};var _LeakyRelu=Module["_LeakyRelu"]=function(){return (_LeakyRelu=Module["_LeakyRelu"]=Module["asm"]["LeakyRelu"]).apply(null,arguments)};var _Less=Module["_Less"]=function(){return (_Less=Module["_Less"]=Module["asm"]["Less"]).apply(null,arguments)};var _LessEqual=Module["_LessEqual"]=function(){return (_LessEqual=Module["_LessEqual"]=Module["asm"]["LessEqual"]).apply(null,arguments)};var _Log=Module["_Log"]=function(){return (_Log=Module["_Log"]=Module["asm"]["Log"]).apply(null,arguments)};var _LogicalAnd=Module["_LogicalAnd"]=function(){return (_LogicalAnd=Module["_LogicalAnd"]=Module["asm"]["LogicalAnd"]).apply(null,arguments)};var _Max=Module["_Max"]=function(){return (_Max=Module["_Max"]=Module["asm"]["Max"]).apply(null,arguments)};var _MaxPool=Module["_MaxPool"]=function(){return (_MaxPool=Module["_MaxPool"]=Module["asm"]["MaxPool"]).apply(null,arguments)};var _Maximum=Module["_Maximum"]=function(){return (_Maximum=Module["_Maximum"]=Module["asm"]["Maximum"]).apply(null,arguments)};var _Mean=Module["_Mean"]=function(){return (_Mean=Module["_Mean"]=Module["asm"]["Mean"]).apply(null,arguments)};var _Min=Module["_Min"]=function(){return (_Min=Module["_Min"]=Module["asm"]["Min"]).apply(null,arguments)};var _Minimum=Module["_Minimum"]=function(){return (_Minimum=Module["_Minimum"]=Module["asm"]["Minimum"]).apply(null,arguments)};var _MirrorPad=Module["_MirrorPad"]=function(){return (_MirrorPad=Module["_MirrorPad"]=Module["asm"]["MirrorPad"]).apply(null,arguments)};var _Multiply=Module["_Multiply"]=function(){return (_Multiply=Module["_Multiply"]=Module["asm"]["Multiply"]).apply(null,arguments)};var _Neg=Module["_Neg"]=function(){return (_Neg=Module["_Neg"]=Module["asm"]["Neg"]).apply(null,arguments)};var _NonMaxSuppressionV3=Module["_NonMaxSuppressionV3"]=function(){return (_NonMaxSuppressionV3=Module["_NonMaxSuppressionV3"]=Module["asm"]["NonMaxSuppressionV3"]).apply(null,arguments)};var _NonMaxSuppressionV4=Module["_NonMaxSuppressionV4"]=function(){return (_NonMaxSuppressionV4=Module["_NonMaxSuppressionV4"]=Module["asm"]["NonMaxSuppressionV4"]).apply(null,arguments)};var _NonMaxSuppressionV5=Module["_NonMaxSuppressionV5"]=function(){return (_NonMaxSuppressionV5=Module["_NonMaxSuppressionV5"]=Module["asm"]["NonMaxSuppressionV5"]).apply(null,arguments)};var _NotEqual=Module["_NotEqual"]=function(){return (_NotEqual=Module["_NotEqual"]=Module["asm"]["NotEqual"]).apply(null,arguments)};var _OneHot=Module["_OneHot"]=function(){return (_OneHot=Module["_OneHot"]=Module["asm"]["OneHot"]).apply(null,arguments)};var _PadV2=Module["_PadV2"]=function(){return (_PadV2=Module["_PadV2"]=Module["asm"]["PadV2"]).apply(null,arguments)};var _Pow=Module["_Pow"]=function(){return (_Pow=Module["_Pow"]=Module["asm"]["Pow"]).apply(null,arguments)};var _Prelu=Module["_Prelu"]=function(){return (_Prelu=Module["_Prelu"]=Module["asm"]["Prelu"]).apply(null,arguments)};var _Prod=Module["_Prod"]=function(){return (_Prod=Module["_Prod"]=Module["asm"]["Prod"]).apply(null,arguments)};var _RealDiv=Module["_RealDiv"]=function(){return (_RealDiv=Module["_RealDiv"]=Module["asm"]["RealDiv"]).apply(null,arguments)};var _Relu=Module["_Relu"]=function(){return (_Relu=Module["_Relu"]=Module["asm"]["Relu"]).apply(null,arguments)};var _Relu6=Module["_Relu6"]=function(){return (_Relu6=Module["_Relu6"]=Module["asm"]["Relu6"]).apply(null,arguments)};var _ResizeBilinear=Module["_ResizeBilinear"]=function(){return (_ResizeBilinear=Module["_ResizeBilinear"]=Module["asm"]["ResizeBilinear"]).apply(null,arguments)};var _Reverse=Module["_Reverse"]=function(){return (_Reverse=Module["_Reverse"]=Module["asm"]["Reverse"]).apply(null,arguments)};var _RotateWithOffset=Module["_RotateWithOffset"]=function(){return (_RotateWithOffset=Module["_RotateWithOffset"]=Module["asm"]["RotateWithOffset"]).apply(null,arguments)};var _Round=Module["_Round"]=function(){return (_Round=Module["_Round"]=Module["asm"]["Round"]).apply(null,arguments)};var _Rsqrt=Module["_Rsqrt"]=function(){return (_Rsqrt=Module["_Rsqrt"]=Module["asm"]["Rsqrt"]).apply(null,arguments)};var _ScatterNd=Module["_ScatterNd"]=function(){return (_ScatterNd=Module["_ScatterNd"]=Module["asm"]["ScatterNd"]).apply(null,arguments)};var _SelectV2=Module["_SelectV2"]=function(){return (_SelectV2=Module["_SelectV2"]=Module["asm"]["SelectV2"]).apply(null,arguments)};var _Sigmoid=Module["_Sigmoid"]=function(){return (_Sigmoid=Module["_Sigmoid"]=Module["asm"]["Sigmoid"]).apply(null,arguments)};var _Sin=Module["_Sin"]=function(){return (_Sin=Module["_Sin"]=Module["asm"]["Sin"]).apply(null,arguments)};var _Softmax=Module["_Softmax"]=function(){return (_Softmax=Module["_Softmax"]=Module["asm"]["Softmax"]).apply(null,arguments)};var _SparseFillEmptyRows=Module["_SparseFillEmptyRows"]=function(){return (_SparseFillEmptyRows=Module["_SparseFillEmptyRows"]=Module["asm"]["SparseFillEmptyRows"]).apply(null,arguments)};var _SparseReshape=Module["_SparseReshape"]=function(){return (_SparseReshape=Module["_SparseReshape"]=Module["asm"]["SparseReshape"]).apply(null,arguments)};var _SparseSegmentReduction=Module["_SparseSegmentReduction"]=function(){return (_SparseSegmentReduction=Module["_SparseSegmentReduction"]=Module["asm"]["SparseSegmentReduction"]).apply(null,arguments)};var _Sqrt=Module["_Sqrt"]=function(){return (_Sqrt=Module["_Sqrt"]=Module["asm"]["Sqrt"]).apply(null,arguments)};var _Square=Module["_Square"]=function(){return (_Square=Module["_Square"]=Module["asm"]["Square"]).apply(null,arguments)};var _SquaredDifference=Module["_SquaredDifference"]=function(){return (_SquaredDifference=Module["_SquaredDifference"]=Module["asm"]["SquaredDifference"]).apply(null,arguments)};var _Step=Module["_Step"]=function(){return (_Step=Module["_Step"]=Module["asm"]["Step"]).apply(null,arguments)};var _StridedSlice=Module["_StridedSlice"]=function(){return (_StridedSlice=Module["_StridedSlice"]=Module["asm"]["StridedSlice"]).apply(null,arguments)};var _Sub=Module["_Sub"]=function(){return (_Sub=Module["_Sub"]=Module["asm"]["Sub"]).apply(null,arguments)};var _Sum=Module["_Sum"]=function(){return (_Sum=Module["_Sum"]=Module["asm"]["Sum"]).apply(null,arguments)};var _Tan=Module["_Tan"]=function(){return (_Tan=Module["_Tan"]=Module["asm"]["Tan"]).apply(null,arguments)};var _Tanh=Module["_Tanh"]=function(){return (_Tanh=Module["_Tanh"]=Module["asm"]["Tanh"]).apply(null,arguments)};var _Tile=Module["_Tile"]=function(){return (_Tile=Module["_Tile"]=Module["asm"]["Tile"]).apply(null,arguments)};var _TopK=Module["_TopK"]=function(){return (_TopK=Module["_TopK"]=Module["asm"]["TopK"]).apply(null,arguments)};var _Transform=Module["_Transform"]=function(){return (_Transform=Module["_Transform"]=Module["asm"]["Transform"]).apply(null,arguments)};var _Transpose=Module["_Transpose"]=function(){return (_Transpose=Module["_Transpose"]=Module["asm"]["Transpose"]).apply(null,arguments)};var __FusedMatMul=Module["__FusedMatMul"]=function(){return (__FusedMatMul=Module["__FusedMatMul"]=Module["asm"]["_FusedMatMul"]).apply(null,arguments)};var _malloc=Module["_malloc"]=function(){return (_malloc=Module["_malloc"]=Module["asm"]["malloc"]).apply(null,arguments)};var _free=Module["_free"]=function(){return (_free=Module["_free"]=Module["asm"]["free"]).apply(null,arguments)};var ___errno_location=Module["___errno_location"]=function(){return (___errno_location=Module["___errno_location"]=Module["asm"]["__errno_location"]).apply(null,arguments)};var _emscripten_main_thread_process_queued_calls=Module["_emscripten_main_thread_process_queued_calls"]=function(){return (_emscripten_main_thread_process_queued_calls=Module["_emscripten_main_thread_process_queued_calls"]=Module["asm"]["emscripten_main_thread_process_queued_calls"]).apply(null,arguments)};var stackSave=Module["stackSave"]=function(){return (stackSave=Module["stackSave"]=Module["asm"]["stackSave"]).apply(null,arguments)};var stackRestore=Module["stackRestore"]=function(){return (stackRestore=Module["stackRestore"]=Module["asm"]["stackRestore"]).apply(null,arguments)};var stackAlloc=Module["stackAlloc"]=function(){return (stackAlloc=Module["stackAlloc"]=Module["asm"]["stackAlloc"]).apply(null,arguments)};var dynCall_iijjiiii=Module["dynCall_iijjiiii"]=function(){return (dynCall_iijjiiii=Module["dynCall_iijjiiii"]=Module["asm"]["dynCall_iijjiiii"]).apply(null,arguments)};var dynCall_jiji=Module["dynCall_jiji"]=function(){return (dynCall_jiji=Module["dynCall_jiji"]=Module["asm"]["dynCall_jiji"]).apply(null,arguments)};Module["cwrap"]=cwrap;var calledRun;function ExitStatus(status){this.name="ExitStatus";this.message="Program terminated with exit("+status+")";this.status=status;}dependenciesFulfilled=function runCaller(){if(!calledRun)run();if(!calledRun)dependenciesFulfilled=runCaller;};function run(args){if(runDependencies>0){return}preRun();if(runDependencies>0){return}function doRun(){if(calledRun)return;calledRun=true;Module["calledRun"]=true;if(ABORT)return;initRuntime();readyPromiseResolve(Module);if(Module["onRuntimeInitialized"])Module["onRuntimeInitialized"]();postRun();}if(Module["setStatus"]){Module["setStatus"]("Running...");setTimeout(function(){setTimeout(function(){Module["setStatus"]("");},1);doRun();},1);}else {doRun();}}Module["run"]=run;if(Module["preInit"]){if(typeof Module["preInit"]=="function")Module["preInit"]=[Module["preInit"]];while(Module["preInit"].length>0){Module["preInit"].pop()();}}run();var listenersAdded;if(beforeListeners){listenersAdded={uncaughtException:process.listeners("uncaughtException").filter(function(listener){return !beforeListeners.uncaughtException.indexOf(listener)>-1}),unhandledRejection:process.listeners("unhandledRejection").filter(function(listener){return !beforeListeners.unhandledRejection.indexOf(listener)>-1})};}var actualModule;if(typeof WasmBackendModule!=="undefined"){actualModule=WasmBackendModule;}else if(typeof WasmBackendModuleThreadedSimd!=="undefined"){actualModule=WasmBackendModuleThreadedSimd;}else {throw new Error("Could not find wasm module in post.js")}if(listenersAdded){var tmpDispose=actualModule["_dispose"];actualModule["_dispose"]=function(){tmpDispose();listenersAdded.uncaughtException.forEach(function(listener){process.removeListener("uncaughtException",listener);});listenersAdded.unhandledRejection.forEach(function(listener){process.removeListener("unhandledRejection",listener);});};}
|
|
|
return WasmBackendModule.ready
|
}
|
);
|
})();
|
module.exports = WasmBackendModule;
|
});
|
|
var BackendWasm = /** @class */ (function (_super) {
|
__extends(BackendWasm, _super);
|
function BackendWasm(wasm) {
|
var _this = _super.call(this) || this;
|
_this.wasm = wasm;
|
// 0 is reserved for null data ids.
|
_this.dataIdNextNumber = 1;
|
_this.wasm.tfjs.initWithThreadsCount(threadsCount);
|
actualThreadsCount = _this.wasm.tfjs.getThreadsCount();
|
_this.dataIdMap = new tfjsCore.DataStorage(_this, tfjsCore.engine());
|
return _this;
|
}
|
BackendWasm.prototype.write = function (values, shape, dtype) {
|
var dataId = { id: this.dataIdNextNumber++ };
|
this.move(dataId, values, shape, dtype, 1);
|
return dataId;
|
};
|
BackendWasm.prototype.numDataIds = function () {
|
return this.dataIdMap.numDataIds();
|
};
|
BackendWasm.prototype.time = function (f) {
|
return __awaiter(this, void 0, void 0, function () {
|
var start, kernelMs;
|
return __generator(this, function (_a) {
|
start = tfjsCore.util.now();
|
f();
|
kernelMs = tfjsCore.util.now() - start;
|
return [2 /*return*/, { kernelMs: kernelMs }];
|
});
|
});
|
};
|
BackendWasm.prototype.move = function (dataId, values, shape, dtype, refCount) {
|
var id = this.dataIdNextNumber++;
|
if (dtype === 'string') {
|
var stringBytes = values;
|
this.dataIdMap.set(dataId, { id: id, stringBytes: stringBytes, shape: shape, dtype: dtype, memoryOffset: null, refCount: refCount });
|
return;
|
}
|
var size = tfjsCore.util.sizeFromShape(shape);
|
var numBytes = size * tfjsCore.util.bytesPerElement(dtype);
|
var memoryOffset = this.wasm._malloc(numBytes);
|
this.dataIdMap.set(dataId, { id: id, memoryOffset: memoryOffset, shape: shape, dtype: dtype, refCount: refCount });
|
this.wasm.tfjs.registerTensor(id, size, memoryOffset);
|
if (values != null) {
|
this.wasm.HEAPU8.set(new Uint8Array(values.buffer, values.byteOffset, numBytes), memoryOffset);
|
}
|
};
|
BackendWasm.prototype.read = function (dataId) {
|
return __awaiter(this, void 0, void 0, function () {
|
return __generator(this, function (_a) {
|
return [2 /*return*/, this.readSync(dataId)];
|
});
|
});
|
};
|
BackendWasm.prototype.readSync = function (dataId, start, end) {
|
var _a = this.dataIdMap.get(dataId), memoryOffset = _a.memoryOffset, dtype = _a.dtype, shape = _a.shape, stringBytes = _a.stringBytes;
|
if (dtype === 'string') {
|
// Slice all elements.
|
if ((start == null || start === 0) &&
|
(end == null || end >= stringBytes.length)) {
|
return stringBytes;
|
}
|
return stringBytes.slice(start, end);
|
}
|
start = start || 0;
|
end = end || tfjsCore.util.sizeFromShape(shape);
|
var bytesPerElement = tfjsCore.util.bytesPerElement(dtype);
|
var bytes = this.wasm.HEAPU8.slice(memoryOffset + start * bytesPerElement, memoryOffset + end * bytesPerElement);
|
return typedArrayFromBuffer(bytes.buffer, dtype);
|
};
|
/**
|
* Dispose the memory if the dataId has 0 refCount. Return true if the memory
|
* is released, false otherwise.
|
* @param dataId
|
* @oaram force Optional, remove the data regardless of refCount
|
*/
|
BackendWasm.prototype.disposeData = function (dataId, force) {
|
if (force === void 0) { force = false; }
|
if (this.dataIdMap.has(dataId)) {
|
var data = this.dataIdMap.get(dataId);
|
data.refCount--;
|
if (!force && data.refCount > 0) {
|
return false;
|
}
|
this.wasm._free(data.memoryOffset);
|
this.wasm.tfjs.disposeData(data.id);
|
this.dataIdMap.delete(dataId);
|
}
|
return true;
|
};
|
/** Return refCount of a `TensorData`. */
|
BackendWasm.prototype.refCount = function (dataId) {
|
if (this.dataIdMap.has(dataId)) {
|
var tensorData = this.dataIdMap.get(dataId);
|
return tensorData.refCount;
|
}
|
return 0;
|
};
|
BackendWasm.prototype.incRef = function (dataId) {
|
var data = this.dataIdMap.get(dataId);
|
if (data != null) {
|
data.refCount++;
|
}
|
};
|
BackendWasm.prototype.floatPrecision = function () {
|
return 32;
|
};
|
// Returns the memory offset of a tensor. Useful for debugging and unit
|
// testing.
|
BackendWasm.prototype.getMemoryOffset = function (dataId) {
|
return this.dataIdMap.get(dataId).memoryOffset;
|
};
|
BackendWasm.prototype.dispose = function () {
|
this.wasm.tfjs.dispose();
|
if ('PThread' in this.wasm) {
|
this.wasm.PThread.terminateAllThreads();
|
}
|
this.wasm = null;
|
};
|
BackendWasm.prototype.memory = function () {
|
return { unreliable: false };
|
};
|
/**
|
* Make a tensor info for the output of an op. If `memoryOffset` is not
|
* present, this method allocates memory on the WASM heap. If `memoryOffset`
|
* is present, the memory was allocated elsewhere (in c++) and we just record
|
* the pointer where that memory lives.
|
*/
|
BackendWasm.prototype.makeOutput = function (shape, dtype, memoryOffset) {
|
var dataId;
|
if (memoryOffset == null) {
|
dataId = this.write(null /* values */, shape, dtype);
|
}
|
else {
|
var id = this.dataIdNextNumber++;
|
dataId = { id: id };
|
this.dataIdMap.set(dataId, { id: id, memoryOffset: memoryOffset, shape: shape, dtype: dtype, refCount: 1 });
|
var size = tfjsCore.util.sizeFromShape(shape);
|
this.wasm.tfjs.registerTensor(id, size, memoryOffset);
|
}
|
return { dataId: dataId, shape: shape, dtype: dtype };
|
};
|
BackendWasm.prototype.typedArrayFromHeap = function (_a) {
|
var shape = _a.shape, dtype = _a.dtype, dataId = _a.dataId;
|
var buffer = this.wasm.HEAPU8.buffer;
|
var memoryOffset = this.dataIdMap.get(dataId).memoryOffset;
|
var size = tfjsCore.util.sizeFromShape(shape);
|
switch (dtype) {
|
case 'float32':
|
return new Float32Array(buffer, memoryOffset, size);
|
case 'int32':
|
return new Int32Array(buffer, memoryOffset, size);
|
case 'bool':
|
return new Uint8Array(buffer, memoryOffset, size);
|
default:
|
throw new Error("Unknown dtype " + dtype);
|
}
|
};
|
return BackendWasm;
|
}(tfjsCore.KernelBackend));
|
function createInstantiateWasmFunc(path) {
|
// this will be replace by rollup plugin patchWechatWebAssembly in
|
// minprogram's output.
|
// tslint:disable-next-line:no-any
|
return function (imports, callback) {
|
tfjsCore.util.fetch(path, { credentials: 'same-origin' }).then(function (response) {
|
if (!response['ok']) {
|
imports.env.a("failed to load wasm binary file at '" + path + "'");
|
}
|
response.arrayBuffer().then(function (binary) {
|
WebAssembly.instantiate(binary, imports).then(function (output) {
|
callback(output.instance, output.module);
|
});
|
});
|
});
|
return {};
|
};
|
}
|
/**
|
* Returns the path of the WASM binary.
|
* @param simdSupported whether SIMD is supported
|
* @param threadsSupported whether multithreading is supported
|
* @param wasmModuleFolder the directory containing the WASM binaries.
|
*/
|
function getPathToWasmBinary(simdSupported, threadsSupported, wasmModuleFolder) {
|
if (wasmPath != null) {
|
// If wasmPath is defined, the user has supplied a full path to
|
// the vanilla .wasm binary.
|
return wasmPath;
|
}
|
var path = 'tfjs-backend-wasm.wasm';
|
if (simdSupported && threadsSupported) {
|
path = 'tfjs-backend-wasm-threaded-simd.wasm';
|
}
|
else if (simdSupported) {
|
path = 'tfjs-backend-wasm-simd.wasm';
|
}
|
if (wasmFileMap != null) {
|
if (wasmFileMap[path] != null) {
|
return wasmFileMap[path];
|
}
|
}
|
return wasmModuleFolder + path;
|
}
|
/**
|
* Initializes the wasm module and creates the js <--> wasm bridge.
|
*
|
* NOTE: We wrap the wasm module in a object with property 'wasm' instead of
|
* returning Promise<BackendWasmModule> to avoid freezing Chrome (last tested
|
* in Chrome 76).
|
*/
|
function init() {
|
return __awaiter(this, void 0, void 0, function () {
|
var _a, simdSupported, threadsSupported;
|
return __generator(this, function (_b) {
|
switch (_b.label) {
|
case 0: return [4 /*yield*/, Promise.all([
|
tfjsCore.env().getAsync('WASM_HAS_SIMD_SUPPORT'),
|
tfjsCore.env().getAsync('WASM_HAS_MULTITHREAD_SUPPORT')
|
])];
|
case 1:
|
_a = _b.sent(), simdSupported = _a[0], threadsSupported = _a[1];
|
return [2 /*return*/, new Promise(function (resolve, reject) {
|
var factoryConfig = {};
|
/**
|
* This function overrides the Emscripten module locateFile utility.
|
* @param path The relative path to the file that needs to be loaded.
|
* @param prefix The path to the main JavaScript file's directory.
|
*/
|
factoryConfig.locateFile = function (path, prefix) {
|
if (path.endsWith('.worker.js')) {
|
// Escape '\n' because Blob will turn it into a newline.
|
// There should be a setting for this, but 'endings: "native"' does
|
// not seem to work.
|
var response = wasmWorkerContents.replace(/\n/g, '\\n');
|
var blob = new Blob([response], { type: 'application/javascript' });
|
return URL.createObjectURL(blob);
|
}
|
if (path.endsWith('.wasm')) {
|
return getPathToWasmBinary(simdSupported, threadsSupported, wasmPathPrefix != null ? wasmPathPrefix : prefix);
|
}
|
return prefix + path;
|
};
|
// Use the instantiateWasm override when system fetch is not available.
|
// Reference:
|
// https://github.com/emscripten-core/emscripten/blob/2bca083cbbd5a4133db61fbd74d04f7feecfa907/tests/manual_wasm_instantiate.html#L170
|
if (customFetch) {
|
factoryConfig.instantiateWasm =
|
createInstantiateWasmFunc(getPathToWasmBinary(simdSupported, threadsSupported, wasmPathPrefix != null ? wasmPathPrefix : ''));
|
}
|
var initialized = false;
|
factoryConfig.onAbort = function () {
|
if (initialized) {
|
// Emscripten already called console.warn so no need to double log.
|
return;
|
}
|
if (initAborted) {
|
// Emscripten calls `onAbort` twice, resulting in double error
|
// messages.
|
return;
|
}
|
initAborted = true;
|
var rejectMsg = 'Make sure the server can serve the `.wasm` file relative to the ' +
|
'bundled js file. For more details see https://github.com/tensorflow/tfjs/blob/master/tfjs-backend-wasm/README.md#using-bundlers';
|
reject({ message: rejectMsg });
|
};
|
var wasm;
|
// If `wasmPath` has been defined we must initialize the vanilla module.
|
if (threadsSupported && simdSupported && wasmPath == null) {
|
factoryConfig.mainScriptUrlOrBlob = new Blob(["var WasmBackendModuleThreadedSimd = " +
|
tfjsBackendWasmThreadedSimd.toString()], { type: 'text/javascript' });
|
wasm = tfjsBackendWasmThreadedSimd(factoryConfig);
|
}
|
else {
|
// The wasmFactory works for both vanilla and SIMD binaries.
|
wasm = tfjsBackendWasm(factoryConfig);
|
}
|
// The WASM module has been successfully created by the factory.
|
// Any error will be caught by the onAbort callback defined above.
|
wasm.then(function (module) {
|
initialized = true;
|
initAborted = false;
|
var voidReturnType = null;
|
// Using the tfjs namespace to avoid conflict with emscripten's API.
|
module.tfjs = {
|
init: module.cwrap('init', null, []),
|
initWithThreadsCount: module.cwrap('init_with_threads_count', null, ['number']),
|
getThreadsCount: module.cwrap('get_threads_count', 'number', []),
|
registerTensor: module.cwrap('register_tensor', null, [
|
'number',
|
'number',
|
'number',
|
]),
|
disposeData: module.cwrap('dispose_data', voidReturnType, ['number']),
|
dispose: module.cwrap('dispose', voidReturnType, []),
|
};
|
resolve({ wasm: module });
|
});
|
})];
|
}
|
});
|
});
|
}
|
function typedArrayFromBuffer(buffer, dtype) {
|
switch (dtype) {
|
case 'float32':
|
return new Float32Array(buffer);
|
case 'int32':
|
return new Int32Array(buffer);
|
case 'bool':
|
return new Uint8Array(buffer);
|
default:
|
throw new Error("Unknown dtype " + dtype);
|
}
|
}
|
var wasmBinaryNames = [
|
'tfjs-backend-wasm.wasm', 'tfjs-backend-wasm-simd.wasm',
|
'tfjs-backend-wasm-threaded-simd.wasm'
|
];
|
var wasmPath = null;
|
var wasmPathPrefix = null;
|
var wasmFileMap = {};
|
var initAborted = false;
|
var customFetch = false;
|
/**
|
* @deprecated Use `setWasmPaths` instead.
|
* Sets the path to the `.wasm` file which will be fetched when the wasm
|
* backend is initialized. See
|
* https://github.com/tensorflow/tfjs/blob/master/tfjs-backend-wasm/README.md#using-bundlers
|
* for more details.
|
* @param path wasm file path or url
|
* @param usePlatformFetch optional boolean to use platform fetch to download
|
* the wasm file, default to false.
|
*
|
* @doc {heading: 'Environment', namespace: 'wasm'}
|
*/
|
function setWasmPath(path, usePlatformFetch) {
|
if (usePlatformFetch === void 0) { usePlatformFetch = false; }
|
tfjsCore.deprecationWarn('setWasmPath has been deprecated in favor of setWasmPaths and' +
|
' will be removed in a future release.');
|
if (initAborted) {
|
throw new Error('The WASM backend was already initialized. Make sure you call ' +
|
'`setWasmPath()` before you call `tf.setBackend()` or `tf.ready()`');
|
}
|
wasmPath = path;
|
customFetch = usePlatformFetch;
|
}
|
/**
|
* Configures the locations of the WASM binaries.
|
*
|
* ```js
|
* setWasmPaths({
|
* 'tfjs-backend-wasm.wasm': 'renamed.wasm',
|
* 'tfjs-backend-wasm-simd.wasm': 'renamed-simd.wasm',
|
* 'tfjs-backend-wasm-threaded-simd.wasm': 'renamed-threaded-simd.wasm'
|
* });
|
* tf.setBackend('wasm');
|
* ```
|
*
|
* @param prefixOrFileMap This can be either a string or object:
|
* - (string) The path to the directory where the WASM binaries are located.
|
* Note that this prefix will be used to load each binary (vanilla,
|
* SIMD-enabled, threading-enabled, etc.).
|
* - (object) Mapping from names of WASM binaries to custom
|
* full paths specifying the locations of those binaries. This is useful if
|
* your WASM binaries are not all located in the same directory, or if your
|
* WASM binaries have been renamed.
|
* @param usePlatformFetch optional boolean to use platform fetch to download
|
* the wasm file, default to false.
|
*
|
* @doc {heading: 'Environment', namespace: 'wasm'}
|
*/
|
function setWasmPaths(prefixOrFileMap, usePlatformFetch) {
|
if (usePlatformFetch === void 0) { usePlatformFetch = false; }
|
if (initAborted) {
|
throw new Error('The WASM backend was already initialized. Make sure you call ' +
|
'`setWasmPaths()` before you call `tf.setBackend()` or ' +
|
'`tf.ready()`');
|
}
|
if (typeof prefixOrFileMap === 'string') {
|
wasmPathPrefix = prefixOrFileMap;
|
}
|
else {
|
wasmFileMap = prefixOrFileMap;
|
var missingPaths = wasmBinaryNames.filter(function (name) { return wasmFileMap[name] == null; });
|
if (missingPaths.length > 0) {
|
throw new Error("There were no entries found for the following binaries: " +
|
(missingPaths.join(',') + ". Please either call setWasmPaths with a ") +
|
"map providing a path for each binary, or with a string indicating " +
|
"the directory where all the binaries can be found.");
|
}
|
}
|
customFetch = usePlatformFetch;
|
}
|
var threadsCount = -1;
|
var actualThreadsCount = -1;
|
/**
|
* Sets the number of threads that will be used by XNNPACK to create
|
* threadpool (default to the number of logical CPU cores).
|
*
|
* This must be called before calling `tf.setBackend('wasm')`.
|
*/
|
function setThreadsCount(numThreads) {
|
threadsCount = numThreads;
|
}
|
/**
|
* Gets the actual threads count that is used by XNNPACK.
|
*
|
* It is set after the backend is intialized.
|
*/
|
function getThreadsCount() {
|
if (actualThreadsCount === -1) {
|
throw new Error("WASM backend not initialized.");
|
}
|
return actualThreadsCount;
|
}
|
|
/** @license See the LICENSE file. */
|
// This code is auto-generated, do not modify this file!
|
var version = '3.16.0';
|
|
/**
|
* @license
|
* Copyright 2020 Google LLC. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
var _this$1 = undefined;
|
var WASM_PRIORITY = 2;
|
tfjsCore.registerBackend('wasm', function () { return __awaiter(_this$1, void 0, void 0, function () {
|
var wasm;
|
return __generator(this, function (_a) {
|
switch (_a.label) {
|
case 0: return [4 /*yield*/, init()];
|
case 1:
|
wasm = (_a.sent()).wasm;
|
return [2 /*return*/, new BackendWasm(wasm)];
|
}
|
});
|
}); }, WASM_PRIORITY);
|
|
exports.BackendWasm = BackendWasm;
|
exports.getThreadsCount = getThreadsCount;
|
exports.setThreadsCount = setThreadsCount;
|
exports.setWasmPath = setWasmPath;
|
exports.setWasmPaths = setWasmPaths;
|
exports.version_wasm = version;
|
|
Object.defineProperty(exports, '__esModule', { value: true });
|
|
})));
|
//# sourceMappingURL=tf-backend-wasm.js.map
|
