handsfree
Version:
A Face Pointer and Pose Estimator for interacting with pages, desktops, robots, and more via gestures
3,640 lines • 201 kB
JavaScript
/**
* @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 (global, factory) {
typeof exports === 'object' && typeof module !== 'undefined' ? factory(exports, require('@tensorflow/tfjs-core'), require('path'), require('fs')) :
typeof define === 'function' && define.amd ? define(['exports', '@tensorflow/tfjs-core', 'path', 'fs'], factory) :
(global = global || self, factory((global.tf = global.tf || {}, global.tf.wasm = global.tf.wasm || {}), global.tf, global.path, global.fs));
}(this, (function (exports, tfjsCore, path, fs) { 'use strict';
path = path && path.hasOwnProperty('default') ? path['default'] : path;
fs = fs && fs.hasOwnProperty('default') ? fs['default'] : fs;
/**
* @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 = {}));
/**
* @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.
* =============================================================================
*/
let wasmFusedMatMul;
function setup(backend) {
wasmFusedMatMul = backend.wasm.cwrap(tfjsCore._FusedMatMul, null /* void */, [
'number',
'array',
'number',
'number',
'array',
'number',
'number',
'number',
'number',
'number',
'number',
'number' // out_id
]);
}
function fusedBatchMatMul(args) {
const { inputs, backend, attrs } = args;
const { a, b, bias, preluActivationWeights } = inputs;
if (a.dtype !== 'float32' || b.dtype !== 'float32') {
throw new Error(`_FusedMatMul for non non-float32 tensors not yet supported.`);
}
const { transposeA, transposeB, activation } = attrs;
const aId = backend.dataIdMap.get(a.dataId).id;
const bId = backend.dataIdMap.get(b.dataId).id;
let biasId = 0;
if (bias != null) {
const biasData = backend.dataIdMap.get(bias.dataId);
if (biasData.shape.length !== 1) {
throw new Error(`_FusedMatMul only supports rank-1 bias but got ` +
`rank ${biasData.shape.length}.`);
}
biasId = biasData.id;
}
const preluActivationWeightsId = preluActivationWeights == null ?
0 :
backend.dataIdMap.get(preluActivationWeights.dataId).id;
const fusedActivation = FusableActivation[activation];
if (fusedActivation == null) {
throw new Error(`${activation} activation not yet supported for FusedConv2D ` +
`in the wasm backend.`);
}
const leftDim = transposeA ? a.shape[2] : a.shape[1];
const rightDim = transposeB ? b.shape[1] : b.shape[2];
const batchDim = a.shape[0];
const out = backend.makeOutput([batchDim, leftDim, rightDim], a.dtype);
const outId = backend.dataIdMap.get(out.dataId).id;
const aShapeBytes = new Uint8Array(new Int32Array(a.shape).buffer);
const bShapeBytes = new Uint8Array(new Int32Array(b.shape).buffer);
wasmFusedMatMul(aId, aShapeBytes, a.shape.length, bId, bShapeBytes, b.shape.length, transposeA, transposeB, fusedActivation, biasId, preluActivationWeightsId, outId);
return out;
}
const 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) {
let wasmFunc;
function setupFunc(backend) {
wasmFunc =
backend.wasm.cwrap(kernelName, null /* void */, ['number', 'number']);
}
function kernelFunc(args) {
const { backend, inputs: { x } } = args;
const xId = backend.dataIdMap.get(x.dataId).id;
const out = backend.makeOutput(x.shape, x.dtype);
const outId = backend.dataIdMap.get(out.dataId).id;
// Short-circuit zero-sized tensors.
if (tfjsCore.util.sizeFromShape(out.shape) === 0) {
return out;
}
wasmFunc(xId, outId);
return out;
}
return { kernelName, backendName: 'wasm', setupFunc, 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.
* =============================================================================
*/
const 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) {
let wasmFunc;
function setupFunc(backend) {
wasmFunc = backend.wasm.cwrap(kernelName, null /* void */, [
'number',
'array',
'number',
'number',
'array',
'number',
'number',
'number' // out_id
]);
}
function kernelFunc(args) {
const { backend, inputs } = args;
const { a, b } = inputs;
const aId = backend.dataIdMap.get(a.dataId).id;
const bId = backend.dataIdMap.get(b.dataId).id;
const outputType = dtype != null ? dtype : a.dtype;
const newShape = tfjsCore.backend_util.assertAndGetBroadcastShape(a.shape, b.shape);
const out = backend.makeOutput(newShape, outputType);
// Short-circuit zero-sized tensors.
if (tfjsCore.util.sizeFromShape(newShape) === 0) {
return out;
}
const aShapeBytes = new Uint8Array(new Int32Array(a.shape).buffer);
const bShapeBytes = new Uint8Array(new Int32Array(b.shape).buffer);
const outId = backend.dataIdMap.get(out.dataId).id;
const kernelFunc = () => wasmFunc(aId, aShapeBytes, a.shape.length, bId, bShapeBytes, b.shape.length, CppDType[a.dtype], outId);
// Currently only some float operations support full broadcast.
if (supportsFullBroadcast && a.dtype === 'float32') {
kernelFunc();
return out;
}
const aBroadcastDims = tfjsCore.backend_util.getBroadcastDims(a.shape, newShape);
const bBroadcastDims = tfjsCore.backend_util.getBroadcastDims(b.shape, newShape);
const loopsOverAllOfA = aBroadcastDims.every((v, i) => v === i);
const loopsOverAllOfB = bBroadcastDims.every((v, i) => v === i);
if (loopsOverAllOfA && loopsOverAllOfB) {
kernelFunc();
return out;
}
else {
throw new Error(`Broadcasting along outer dims is not yet ` +
`supported for ${a.dtype} ${kernelName}.`);
}
}
return { kernelName, backendName: 'wasm', setupFunc, 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.
* =============================================================================
*/
const supportsFullBroadcast = true;
const addConfig = createBinaryKernelConfig(tfjsCore.Add, supportsFullBroadcast);
/**
* @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.
* =============================================================================
*/
let wasmFunc;
function setupFunc(backend) {
wasmFunc = backend.wasm.cwrap(tfjsCore.AddN, null /* void */, [
'array',
'number',
'number',
'number',
]);
}
function addn(args) {
const { inputs, backend } = args;
const out = backend.makeOutput(inputs[0].shape, inputs[0].dtype);
// Short-circuit zero-sized tensors.
if (tfjsCore.util.sizeFromShape(out.shape) === 0) {
return out;
}
const inputIds = inputs.map(x => backend.dataIdMap.get(x.dataId).id);
const inputIdsBytes = new Uint8Array(new Int32Array(inputIds).buffer);
const outId = backend.dataIdMap.get(out.dataId).id;
wasmFunc(inputIdsBytes, inputIds.length, CppDType[out.dtype], outId);
return out;
}
const addNConfig = {
kernelName: tfjsCore.AddN,
backendName: 'wasm',
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) {
const { inputs: { x }, backend } = args;
const out = backend.makeOutput(x.shape, x.dtype);
const inVals = backend.typedArrayFromHeap(x);
const outVals = backend.typedArrayFromHeap(out);
outVals.set(inVals);
return out;
}
const 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.
* =============================================================================
*/
let wasmTranspose;
function setup$1(backend) {
wasmTranspose = backend.wasm.cwrap(tfjsCore.Transpose, null /* void */, [
'number',
'array',
'number',
'number',
'number',
'array',
'number',
]);
}
function transpose(args) {
const { inputs, backend, attrs } = args;
// Reduce any dimensions with size one. Lower-rank transpose kernel performs
// better due to simpler memory access pattern.
const [reducedShape, perm] = removeOneSizeDims(inputs.x.shape, attrs.perm);
let permIsNoOp = true;
for (let i = 0; i < perm.length; i++) {
if (perm[i] !== i) {
permIsNoOp = false;
}
}
const outShape = computeOutShape(inputs.x.shape, attrs.perm);
const x = {
dataId: inputs.x.dataId,
shape: reducedShape,
dtype: inputs.x.dtype
};
if (permIsNoOp) {
const cloned = identity({ inputs, backend });
cloned.shape = outShape;
return cloned;
}
const out = backend.makeOutput(outShape, x.dtype);
const xId = backend.dataIdMap.get(x.dataId).id;
const outId = backend.dataIdMap.get(out.dataId).id;
const permBytes = new Uint8Array(new Int32Array(perm).buffer);
const 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) {
const outShape = new Array(inShape.length);
for (let i = 0; i < outShape.length; i++) {
outShape[i] = inShape[perm[i]];
}
return outShape;
}
function removeOneSizeDims(shape, perm) {
const newShape = [];
const newPerm = [];
for (let i = 0; i < shape.length; ++i) {
if (shape[i] !== 1) {
newShape.push(shape[i]);
}
if (shape[perm[i]] !== 1) {
newPerm.push(perm[i]);
}
}
for (let i = 0; i < newPerm.length; ++i) {
let minValIdx = -1;
for (let j = 0; j < newPerm.length; ++j) {
if (newPerm[j] >= i &&
(minValIdx === -1 || newPerm[minValIdx] > newPerm[j])) {
minValIdx = j;
}
}
newPerm[minValIdx] = i;
}
return [newShape, newPerm];
}
const 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) {
const xShape = x.shape;
const xRank = x.shape.length;
const originalAxes = tfjsCore.util.parseAxisParam(axis, xShape);
let axes = originalAxes;
const permutedAxes = tfjsCore.backend_util.getAxesPermutation(axes, xRank);
let xTransposed = null;
let inputWasTransposed = false;
if (permutedAxes != null) {
const newShape = new Array(xRank);
for (let i = 0; i < newShape.length; i++) {
newShape[i] = xShape[permutedAxes[i]];
}
axes = tfjsCore.backend_util.getInnerMostAxes(axes.length, xRank);
xTransposed =
transpose({ inputs: { x }, attrs: { perm: permutedAxes }, backend });
const xId = backend.dataIdMap.get(x.dataId).id;
const transposedId = backend.dataIdMap.get(xTransposed.dataId).id;
if (transposedId !== xId) {
inputWasTransposed = true;
}
}
return { transposed: xTransposed, originalAxes, axes, inputWasTransposed };
}
/**
* @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.
* =============================================================================
*/
let wasmFunc$1;
function setup$2(backend) {
wasmFunc$1 = backend.wasm.cwrap(tfjsCore.ArgMax, null /* void */, [
'number',
'number',
'number',
'number',
'number' // out_id
]);
}
function argmax(args) {
const { backend, inputs, attrs } = args;
const { axis } = attrs;
const { x } = inputs;
const xId = backend.dataIdMap.get(x.dataId).id;
let inputId = xId;
let input = x;
const { transposed, axes, inputWasTransposed } = permuteAxesAndTranspose(x, axis, backend);
if (inputWasTransposed) {
const 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;
}
}
const outShape = input.shape.slice(0, -1);
const out = backend.makeOutput(outShape, 'int32');
const outId = backend.dataIdMap.get(out.dataId).id;
const outerSize = tfjsCore.util.sizeFromShape(out.shape);
const 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;
}
const argMaxConfig = {
kernelName: tfjsCore.ArgMax,
backendName: 'wasm',
kernelFunc: argmax,
setupFunc: setup$2
};
/**
* @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.
* =============================================================================
*/
let wasmAvgPool;
function setup$3(backend) {
wasmAvgPool = backend.wasm.cwrap(tfjsCore.AvgPool, null /* void */, [
'number',
'number',
'number',
'number',
'number',
'number',
'number',
'number',
'number',
'number',
'number',
'number',
'number',
'number',
]);
}
function avgPool(args) {
const { inputs, attrs, backend } = args;
const x = inputs.x;
const xId = backend.dataIdMap.get(x.dataId).id;
const { filterSize, strides, pad, dimRoundingMode } = attrs;
const convInfo = tfjsCore.backend_util.computePool2DInfo(x.shape, filterSize, strides, 1 /* dilations */, pad, dimRoundingMode);
const filterHeight = convInfo.filterHeight;
const filterWidth = convInfo.filterWidth;
const padTop = convInfo.padInfo.top;
const padRight = convInfo.padInfo.right;
const padBottom = convInfo.padInfo.bottom;
const padLeft = convInfo.padInfo.left;
const strideHeight = convInfo.strideHeight;
const strideWidth = convInfo.strideWidth;
const channels = convInfo.inChannels;
if (convInfo.dataFormat !== 'channelsLast') {
throw new Error(`wasm backend does not support dataFormat:'` +
`${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}].`);
}
const out = backend.makeOutput(convInfo.outShape, 'float32');
const 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;
}
const avgPoolConfig = {
kernelName: tfjsCore.AvgPool,
backendName: 'wasm',
setupFunc: setup$3,
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.
* =============================================================================
*/
let wasmBatchMatMul;
function setup$4(backend) {
wasmBatchMatMul = backend.wasm.cwrap(tfjsCore.BatchMatMul, null /* void */, [
'number',
'array',
'number',
'number',
'array',
'number',
'number',
'number',
'number' // out_id
]);
}
function batchMatMul(args) {
const { inputs, backend, attrs } = args;
const { a, b } = inputs;
if (a.dtype !== 'float32' || b.dtype !== 'float32') {
throw new Error(`BatchMatMul for non non-float32 tensors not yet supported.`);
}
const { transposeA, transposeB } = attrs;
const aId = backend.dataIdMap.get(a.dataId).id;
const bId = backend.dataIdMap.get(b.dataId).id;
const leftDim = transposeA ? a.shape[2] : a.shape[1];
const rightDim = transposeB ? b.shape[1] : b.shape[2];
const batchDim = a.shape[0];
const out = backend.makeOutput([batchDim, leftDim, rightDim], a.dtype);
const outId = backend.dataIdMap.get(out.dataId).id;
const aShapeBytes = new Uint8Array(new Int32Array(a.shape).buffer);
const bShapeBytes = new Uint8Array(new Int32Array(b.shape).buffer);
wasmBatchMatMul(aId, aShapeBytes, a.shape.length, bId, bShapeBytes, b.shape.length, transposeA, transposeB, outId);
return out;
}
const batchMatMulConfig = {
kernelName: tfjsCore.BatchMatMul,
backendName: 'wasm',
setupFunc: setup$4,
kernelFunc: batchMatMul
};
/**
* @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) {
const { inputs: { x }, attrs: { dtype }, backend } = args;
const out = backend.makeOutput(x.shape, dtype);
const inVals = backend.typedArrayFromHeap(x);
const outVals = backend.typedArrayFromHeap(out);
outVals.set(inVals);
return out;
}
const castConfig = {
kernelName: tfjsCore.Cast,
backendName: 'wasm',
kernelFunc: cast,
};
/**
* @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.
* =============================================================================
*/
let wasmClip;
function setup$5(backend) {
wasmClip = backend.wasm.cwrap(tfjsCore.ClipByValue, null /* void */, [
'number',
'number',
'number',
'number' // out_id
]);
}
function clip(args) {
const { inputs, backend, attrs } = args;
const { x } = inputs;
const { clipValueMin, clipValueMax } = attrs;
const xId = backend.dataIdMap.get(x.dataId).id;
const out = backend.makeOutput(x.shape, 'float32');
const outId = backend.dataIdMap.get(out.dataId).id;
wasmClip(xId, clipValueMin, clipValueMax, outId);
return out;
}
const clipByValueConfig = {
kernelName: tfjsCore.ClipByValue,
backendName: 'wasm',
setupFunc: setup$5,
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) {
const { inputs, backend } = args;
const axis = tfjsCore.util.parseAxisParam(args.attrs.axis, inputs[0].shape)[0];
const outShape = tfjsCore.backend_util.computeOutShape(inputs.map(t => t.shape), axis);
const out = backend.makeOutput(outShape, inputs[0].dtype);
const batchDim = tfjsCore.util.sizeFromShape(inputs[0].shape.slice(0, axis));
let sumInnerDims = 0;
const innerDims = inputs.map(input => {
const innerDim = tfjsCore.util.sizeFromShape(input.shape.slice(axis));
sumInnerDims += innerDim;
return innerDim;
});
const inVals = inputs.map(input => backend.typedArrayFromHeap(input));
const outVals = backend.typedArrayFromHeap(out);
for (let b = 0; b < batchDim; b++) {
let outOffset = b * sumInnerDims;
for (let i = 0; i < inVals.length; i++) {
const innerDim = innerDims[i];
const inOffset = b * innerDim;
const vals = inVals[i].subarray(inOffset, inOffset + innerDim);
outVals.set(vals, outOffset);
outOffset += innerDim;
}
}
return out;
}
const 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.
* =============================================================================
*/
let wasmConv2d;
function setup$6(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) {
const { inputs, attrs, backend } = args;
const { x, filter } = inputs;
const xId = backend.dataIdMap.get(x.dataId).id;
const filterId = backend.dataIdMap.get(filter.dataId).id;
const { strides, dilations, pad, dimRoundingMode, dataFormat } = attrs;
const $dataFormat = tfjsCore.backend_util.convertConv2DDataFormat(dataFormat);
const convInfo = tfjsCore.backend_util.computeConv2DInfo(x.shape, filter.shape, strides, dilations, pad, dimRoundingMode, false, $dataFormat);
const filterHeight = convInfo.filterHeight;
const filterWidth = convInfo.filterWidth;
const padTop = convInfo.padInfo.top;
const padRight = convInfo.padInfo.right;
const padBottom = convInfo.padInfo.bottom;
const padLeft = convInfo.padInfo.left;
const dilationHeight = convInfo.dilationHeight;
const dilationWidth = convInfo.dilationWidth;
const strideHeight = convInfo.strideHeight;
const strideWidth = convInfo.strideWidth;
const inputChannels = convInfo.inChannels;
const outputChannels = convInfo.outChannels;
const isSamePad = convInfo.padInfo.type === 'SAME' ? 1 : 0;
if (convInfo.dataFormat !== 'channelsLast') {
throw new Error(`wasm backend Conv2D does not support dataFormat:'` +
`${convInfo.dataFormat}'. Please use 'channelsLast'.`);
}
const out = backend.makeOutput(convInfo.outShape, 'float32');
const 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;
}
const conv2DConfig = {
kernelName: tfjsCore.Conv2D,
backendName: 'wasm',
setupFunc: setup$6,
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.
* =============================================================================
*/
let wasmConv2DBackpropInput;
function setup$7(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) {
const { backend, inputs, attrs } = args;
const { dy, filter } = inputs;
const { strides, pad, dataFormat, dimRoundingMode, inputShape } = attrs;
const dilations = 1;
const $dataFormat = tfjsCore.backend_util.convertConv2DDataFormat(dataFormat);
const convInfo = tfjsCore.backend_util.computeConv2DInfo(inputShape, filter.shape, strides, dilations, pad, dimRoundingMode, false /* depthwise */, $dataFormat);
const { batchSize, filterHeight, filterWidth, inChannels, inHeight, inWidth, outChannels, outHeight, outWidth, strideHeight, strideWidth } = convInfo;
const topPad = filterHeight - 1 - convInfo.padInfo.top;
const leftPad = filterWidth - 1 - convInfo.padInfo.left;
const isChannelsLast = convInfo.dataFormat === 'channelsLast';
const dxStrides = tfjsCore.util.computeStrides(convInfo.inShape);
const dyStrides = tfjsCore.util.computeStrides(dy.shape);
const [fltS0, fltS1, fltS2] = tfjsCore.util.computeStrides(filter.shape);
const xBatchStride = dxStrides[0];
const xRowStride = isChannelsLast ? dxStrides[1] : dxStrides[2];
const xColStride = isChannelsLast ? dxStrides[2] : 1;
const xChannelStride = isChannelsLast ? 1 : dxStrides[1];
const yBatchStride = dyStrides[0];
const yRowStride = isChannelsLast ? dyStrides[1] : dyStrides[2];
const yColStride = isChannelsLast ? dyStrides[2] : 1;
const yChannelStride = isChannelsLast ? 1 : dyStrides[1];
const out = backend.makeOutput(convInfo.inShape, 'float32');
const outId = backend.dataIdMap.get(out.dataId).id;
const dyId = backend.dataIdMap.get(dy.dataId).id;
const 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;
}
const conv2DBackpropInputConfig = {
kernelName: tfjsCore.Conv2DBackpropInput,
backendName: 'wasm',
setupFunc: setup$7,
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.
* =============================================================================
*/
const cosConfig = createUnaryKernelConfig(tfjsCore.Cos);
/**
* @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 = {}));
let wasmCropAndResize;
function setup$8(backend) {
wasmCropAndResize = backend.wasm.cwrap(tfjsCore.CropAndResize, null /*void*/, [
'number',
'number',
'number',
'number',
'array',
'number',
'number',
'number',
'number',
'number' // out id
]);
}
function cropAndResize(args) {
const { backend, inputs, attrs } = args;
const { method, extrapolationValue, cropSize } = attrs;
const { image, boxes, boxInd } = inputs;
const numBoxes = boxes.shape[0];
const [cropHeight, cropWidth] = cropSize;
const outShape = [numBoxes, cropHeight, cropWidth, image.shape[3]];
let imagesData = backend.dataIdMap.get(image.dataId);
let castedData;
if (image.dtype !== 'float32') {
castedData = cast({ backend, inputs: { x: image }, attrs: { dtype: 'float32' } });
imagesData = backend.dataIdMap.get(castedData.dataId);
}
const imagesId = imagesData.id;
const boxesId = backend.dataIdMap.get(boxes.dataId).id;
const boxIndId = backend.dataIdMap.get(boxInd.dataId).id;
const out = backend.makeOutput(outShape, 'float32');
const outId = backend.dataIdMap.get(out.dataId).id;
const 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;
}
const cropAndResizeConfig = {
kernelName: tfjsCore.CropAndResize,
backendName: 'wasm',
setupFunc: setup$8,
kernelFunc: cropAndResize
};
/**
* @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.
* =============================================================================
*/
let wasmDepthwiseConv2d;
function setup$9(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) {
const { inputs, attrs, backend } = args;
const { x, filter } = inputs;
const xId = backend.dataIdMap.get(x.dataId).id;
const filterId = backend.dataIdMap.get(filter.dataId).id;
const { strides, dilations, pad, dimRoundingMode } = attrs;
const $dilations = dilations == null ? [1, 1] : dilations;
const convInfo = tfjsCore.backend_util.computeConv2DInfo(x.shape, filter.shape, strides, $dilations, pad, dimRoundingMode, true /* depthwise */);
const filterHeight = convInfo.filterHeight;
const filterWidth = convInfo.filterWidth;
const padTop = convInfo.padInfo.top;
const padRight = convInfo.padInfo.right;
const padBottom = convInfo.padInfo.bottom;
const padLeft = convInfo.padInfo.left;
const dilationHeight = convInfo.dilationHeight;
const dilationWidth = convInfo.dilationWidth;
const strideHeight = convInfo.strideHeight;
const strideWidth = convInfo.strideWidth;
const inputChannels = convInfo.inChannels;
const outputChannels = convInfo.outChannels;
const isSamePad = convInfo.padInfo.type === 'SAME' ? 1 : 0;
if (convInfo.dataFormat !== 'channelsLast') {
throw new Error(`wasm backend DepthwiseConv2dNative does not support dataFormat:'` +
`${convInfo.dataFormat}'. Please use 'channelsLast'.`);
}
const out = backend.makeOutput(convInfo.outShape, 'float32');
const 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;
}
const depthwiseConv2DNativeConfig = {
kernelName: tfjsCore.DepthwiseConv2dNative,
backendName: 'wasm',
setupFunc: setup$9,
kernelFunc: depthwiseConv2d
};
/**
* @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.
* =============================================================================
*/
const supportsFullBroadcast$1 = true;
const divConfig = createBinaryKernelConfig(tfjsCore.Div, supportsFullBroadcast$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.
* =============================================================================
*/
const supportsFullBroadcast$2 = false;
const equalConfig = createBinaryKernelConfig(tfjsCore.Equal, 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.
* =============================================================================
*/
const expConfig = createUnaryKernelConfig(tfjsCore.Exp);
/**
* @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) {
const { attrs: { shape, value, dtype }, backend } = args;
const out = backend.makeOutput(shape, dtype);
const outVals = backend.typedArrayFromHeap(out);
outVals.fill(value);
return out;
}
const 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.
* =============================================================================
*/
const supportsFullBroadcast$3 = false;
const floorDivConfig = createBinaryKernelConfig(tfjsCore.FloorDiv, supportsFullBroadcast$3);
/**
* @license
* Copyright 2019 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
let wasmBatchNorm;
function setup$a(backend) {
wasmBatchNorm = backend.wasm.cwrap(tfjsCore.FusedBatchNorm, null /* void */, ['number', 'number', 'number', 'number', 'number', 'number', 'number']);
}
function fusedBatchNorm(args) {
const { backend, inputs, attrs } = args;
const { varianceEpsilon } = attrs;
const { x, mean, variance, offset, scale } = inputs;
const xId = backend.dataIdMap.get(x.dataId).id;
const meanId = backend.dataIdMap.get(mean.dataId).id;
const varianceId = backend.dataIdMap.get(variance.dataId).id;
const offsetId = offset != null ? backend.dataIdMap.get(offset.dataId).id : 0;
const scaleId = scale != null ? backend.dataIdMap.get(scale.dataId).id : 0;
const out = backend.makeOutput(x.shape, x.dtype);
// Short-circuit zero-sized tensors.
if (tfjsCore.util.sizeFromShape(x.shape) === 0) {
return out;
}
const outId = backend.dataIdMap.get(out.dataId).id;
wasmBatchNorm(xId, meanId, varianceId, offsetId, scaleId, varianceEpsilon, outId);
return out;
}
const fusedBatchNormConfig = {
kernelName: tfjsCore.FusedBatchNorm,
backendName: 'wasm',
setupFunc: setup$a,
kernelFunc: fusedBatchNorm
};
/**
* @license
* Copyright 2019 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
let wasmFusedConv2d;
function setup$b(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',
]);
}
function fusedConv2d(args) {
const { inputs, attrs, backend } = args;
const { x, filter, bias, preluActivationWeights } = inputs;
const { strides, pad, dilations, dataFormat, dimRoundingMode, activation } = attrs;
const convInfo = tfjsCore.backend_util.computeConv2DInfo(x.shape, filter.shape, strides, dilations, pad, dimRoundingMode);
const fusedActivation = FusableActivation[activation];
if (fusedActivation == null) {
throw new Error(`${activation} activation not yet supported for FusedConv2D ` +
`in the wasm backend.`);
}
const xId = backend.dataIdMap.get(x.dataId).id;
const filterId = backend.dataIdMap.get(filter.dataId).id;
const outputChannels = convInfo.outChannels;
let biasId = 0;
if (bias != null) {
const 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 (${outputChannels})`);
}
biasId = biasData.id;
}
const filterHeight = convInfo.filterHeight;
const filterWidth = convInfo.filterWidth;
const padTop = convInfo.padInfo.top;
const padRight = convInfo.padInfo.right;
const padBottom = convInfo.padInfo.bottom;
const padLeft = convInfo.padInfo.left;
const dilationHeight = convInfo.dilationHeight;
const dilationWidth = convInfo.dilationWidth;
const strideHeight = convInfo.strideHeight;
const strideWidth = convInfo.strideWidth;
const inputChannels = convInfo.inChannels;
const isSamePad = convInfo.padInfo.type === 'SAME' ? 1 : 0;
const batchSize = convInfo.batchSize;
const inHeight = convInfo.inHeight;
const inWidth = convInfo.inWidth;
if (dataFormat !== 'NHWC') {
throw new Error(`wasm backend FusedConv2D does not support dataFormat:'` +
`${dataFormat}'. Please use 'NHWC'.`);
}
const out = backend.makeOutput(convInfo.outShape, 'float32');
const outId = backend.dataIdMap.get(out.dataId).id;
const 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, outId);
return out;
}
const fusedConv2DConfig = {
kernelName: tfjsCore.FusedConv2D,
backendName: 'wasm',
setupFunc: setup$b,
kernelFunc: fusedConv2d
};
/**
* @license
* Copyright 2019 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
let wasmFusedDepthwiseConv2d;
function setup$c(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',
]);
}
function fusedDepthwiseConv2d(args) {
const { inputs, attrs, backend } = args;
const { x, filter, bias, preluActivationWeights } = inputs;
const { strides, pad, dilations, dataFormat, dimRoundingMode, activation } = attrs;
const convInfo = tfjsCore.backend_util.computeConv2DInfo(x.shape, filter.shape, strides, dilations, pad, dimRoundingMode, true /* depthwise */);
const fusedActivation = FusableActivation[activation];
if (fusedActivation == null) {
throw new Error(`${activation} activation not yet supported for FusedDepthwiseConv2D ` +
`in the wasm backend.`);
}
const xId = backend.dataIdMap.get(x.dataId).id;
const filterId = backend.dataIdMap.get(filter.dataId).id;
const outputChannels = convInfo.outChannels;
let biasId = 0;
if (bias != null) {
const 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 (${outputChannels})`);
}
biasId = biasData.id;
}
const filterHeight = convInfo.filterHeight;
const filterWidth = convInfo.filterWidth;
const padTop = convInfo.padInfo.top;
const padRight = convInfo.padInfo.right;
const padBottom = convInfo.padInfo.bottom;
const padLeft = convInfo.padInfo.left;
const dilationHeight = convInfo.dilationHeight;
const dilationWidth = convInfo.dilationWidth;
const strideHeight = convInfo.strideHeight;
const strideWidth = convInfo.strideWidth;
const inputChannels = convInfo.inChannels;
const isSamePad = convInfo.padInfo.type === 'SAME' ? 1 : 0;
const batchSize = convInfo.batchSize;
const inHeight = convInfo.inHeight;
const inWidth = convInfo.inWidth;
if (dataFormat !== 'NHWC') {
throw new Error(`wasm backend FusedDepthwiseConv2D does not support dataFormat:'` +
`${dataFormat}'. Please use 'NHWC'.`);
}
const out = backend.makeOutput(convInfo.outShape, 'float32');
const outId = backend.dataIdMap.get(out.dataId).id;
const 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, outId);
return out;
}
const fusedDepthwiseConv2DConfig = {
kernelName: tfjsCore.FusedDepthwiseConv2D,
backendName: 'wasm',
setupFunc: setup$c,
kernelFunc: fusedDepthwiseConv2d
};
/**
* @license
* Copyright 2019 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
let wasmGatherNd;
function setup$d(backend) {
wasmGatherNd = backend.wasm.cwrap(tfjsCore.GatherNd, null /*void*/, [
'number',
'number',
'number',
'number',
'number',
'number',
'array',
'number' // outId
]);
}
function gatherNd(args) {
const { backend, inputs } = args;
const { params, indices } = inputs;
const [resultShape, numSlices, sliceSize, strides] = tfjsCore.gather_util.prepareAndValidate(params, indices);
const out = backend.makeOutput(resultShape, params.dtype);
if (numSlices === 0) {
return out;
}
const indicesShape = indices.shape;
const sliceRank = indicesShape[indicesShape.length - 1];
const xData = backend.dataIdMap.get(params.dataId);
const xId = xData.id;
const indicesData = backend.dataIdMap.get(indices.dataId);
const indicesId = indicesData.id;
const stridesBytes = new Uint8Array(new Int32Array(strides).buffer);
const outId = backend.dataIdMap.get(out.dataId).id;
wasmGatherNd(xId, CppDType[params.dtype], indicesId, numSlices, sliceRank, sliceSize, stridesBytes, outId);
return out;
}
const gatherNdConfig = {
kernelName: tfjsCore.GatherNd,
backendName: 'wasm',
setupFunc: setup$d,
kernelFunc: gatherNd
};
/**
* @license
* Copyright 2019 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
let wasmGather;
function setup$e(backend) {
wasmGather = backend.wasm.cwrap('Gather', null /*void*/, [
'number',
'number',
'array',
'number',
'number',
'number',
'array',
'number' // outId
]);
}
function gatherV2(args) {
const { backend, inputs, attrs } = args;
const { x, indices } = inputs;
const { axis } = attrs;
const newShape = x.shape.slice();
newShape[axis] = tfjsCore.util.sizeFromShape(indices.shape);
const stridesSize = x.shape.length - 1;
const out = backend.makeOutput(newShape, x.dtype);
if (tfjsCore.util.sizeFromShape(x.shape) === 0) {
return out;
}
const xData = backend.dataIdMap.get(x.dataId);
const xId = xData.id;
const indicesData = backend.dataIdMap.get(indices.dataId);
const indicesId = indicesData.id;
const outId = backend.dataIdMap.get(out.dataId).id;
const xStridesBytes = new Uint8Array(new Int32Array(tfjsCore.util.computeStrides(x.shape)).buffer);
const outStridesBytes = new Uint8Array(new Int32Array(tfjsCore.util.computeStrides(newShape)).buffer);
wasmGather(xId, CppDType[x.dtype], xStridesBytes, stridesSize, indicesId, axis, outStridesBytes, outId);
// reshape
const parsedAxis = tfjsCore.util.parseAxisParam(axis, x.shape)[0];
const shapeInfo = tfjsCore.backend_util.segment_util.collectGatherOpShapeInfo(x, indices, parsedAxis);
out.shape = shapeInfo.outputShape;
return out;
}
const gatherV2Config = {
kernelName: tfjsCore.GatherV2,
backendName: 'wasm',
setupFunc: setup$e,
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.
* =============================================================================
*/
const supportsFullBroadcast$4 = false;
const greaterConfig = createBinaryKernelConfig(tfjsCore.Greater, 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.
* =============================================================================
*/
const supportsFullBroadcast$5 = false;
const greaterEqualConfig = createBinaryKernelConfig(tfjsCore.GreaterEqual, 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.
* =============================================================================
*/
const supportsFullBroadcast$6 = false;
const lessConfig = createBinaryKernelConfig(tfjsCore.Less, supportsFullBroadcast$6, '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.
* =============================================================================
*/
const supportsFullBroadcast$7 = false;
const lessEqualConfig = createBinaryKernelConfig(tfjsCore.LessEqual, supportsFullBroadcast$7, '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.
* =============================================================================
*/
const 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.
* =============================================================================
*/
const supportsFullBroadcast$8 = false;
const logicalAndConfig = createBinaryKernelConfig(tfjsCore.LogicalAnd, supportsFullBroadcast$8, 'bool');
/**
* @license
* Copyright 2019 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
let wasmMax;
function setup$f(backend) {
wasmMax = backend.wasm.cwrap(tfjsCore.Max, null /*void*/, ['number, number, number']);
}
function max(args) {
const { backend, inputs, attrs } = args;
const { reductionIndices: axis, keepDims } = attrs;
const { x } = inputs;
const xId = backend.dataIdMap.get(x.dataId).id;
let inputId = xId;
let input = x;
const { transposed, axes, originalAxes, inputWasTransposed } = permuteAxesAndTranspose(x, axis, backend);
if (inputWasTransposed) {
const transposedId = backend.dataIdMap.get(transposed.dataId).id;
input = transposed;
inputId = transposedId;
}
const inputRank = input.shape.length;
tfjsCore.backend_util.assertAxesAreInnerMostDims('max', axes, inputRank);
const [outShape, reduceShape] = tfjsCore.backend_util.computeOutAndReduceShapes(input.shape, axes);
const reduceSize = tfjsCore.util.sizeFromShape(reduceShape);
const out = backend.makeOutput(outShape, x.dtype);
if (tfjsCore.util.sizeFromShape(input.shape) !== 0) {
const outId = backend.dataIdMap.get(out.dataId).id;
wasmMax(inputId, reduceSize, outId);
}
if (inputWasTransposed) {
// dispose of the transposed tensor.
backend.disposeData(transposed.dataId);
}
if (keepDims) {
// reshape
const newShape = tfjsCore.backend_util.expandShapeToKeepDim(out.shape, originalAxes);
out.shape = newShape;
}
return out;
}
const maxConfig = {
kernelName: tfjsCore.Max,
backendName: 'wasm',
setupFunc: setup$f,
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.
* =============================================================================
*/
const supportsFullBroadcast$9 = false;
const maximumConfig = createBinaryKernelConfig(tfjsCore.Maximum, supportsFullBroadcast$9);
/**
* @license
* Copyright 2019 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
let wasmMaxPool;
function setup$g(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) {
const { inputs, attrs, backend } = args;
const x = inputs.x;
const xId = backend.dataIdMap.get(x.dataId).id;
const { filterSize, strides, pad, dimRoundingMode } = attrs;
const convInfo = tfjsCore.backend_util.computePool2DInfo(x.shape, filterSize, strides, 1 /* dilations */, pad, dimRoundingMode);
const filterHeight = convInfo.filterHeight;
const filterWidth = convInfo.filterWidth;
const padTop = convInfo.padInfo.top;
const padRight = convInfo.padInfo.right;
const padBottom = convInfo.padInfo.bottom;
const padLeft = convInfo.padInfo.left;
const dilationHeight = convInfo.dilationHeight;
const dilationWidth = convInfo.dilationWidth;
const strideHeight = convInfo.strideHeight;
const strideWidth = convInfo.strideWidth;
const inputChannels = convInfo.inChannels;
const outputChannels = convInfo.outChannels;
if (convInfo.dataFormat !== 'channelsLast') {
throw new Error(`wasm backend does not support dataFormat:'` +
`${convInfo.dataFormat}'. Please use 'channelsLast'.`);
}
const out = backend.makeOutput(convInfo.outShape, 'float32');
const outId = backend.dataIdMap.get(out.dataId).id;
wasmMaxPool(xId, x.shape[0], x.shape[1], x.shape[2], filterHeight, filterWidth, padTop, padRight, padBottom, padLeft, dilationHeight, dilationWidth, strideHeight, strideWidth, inputChannels, outputChannels, outId);
return out;
}
const maxPoolConfig = {
kernelName: tfjsCore.MaxPool,
backendName: 'wasm',
setupFunc: setup$g,
kernelFunc: maxPool
};
/**
* @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.
* =============================================================================
*/
let wasmMin;
function setup$h(backend) {
wasmMin = backend.wasm.cwrap(tfjsCore.Min, null /*void*/, ['number, number, number']);
}
function min(args) {
const { backend, inputs, attrs } = args;
const { axis, keepDims } = attrs;
const { x } = inputs;
const xId = backend.dataIdMap.get(x.dataId).id;
let inputId = xId;
let input = x;
const { transposed, axes, originalAxes, inputWasTransposed } = permuteAxesAndTranspose(x, axis, backend);
if (inputWasTransposed) {
const transposedId = backend.dataIdMap.get(transposed.dataId).id;
if (transposedId !== xId) {
// transpose was not a no-op. We will need to dispose of this
// once we are done.
input = transposed;
inputId = transposedId;
}
}
const inputRank = input.shape.length;
tfjsCore.backend_util.assertAxesAreInnerMostDims('min', axes, inputRank);
const [outShape, reduceShape] = tfjsCore.backend_util.computeOutAndReduceShapes(input.shape, axes);
const reduceSize = tfjsCore.util.sizeFromShape(reduceShape);
const out = backend.makeOutput(outShape, input.dtype);
if (tfjsCore.util.sizeFromShape(input.shape) !== 0) {
const outId = backend.dataIdMap.get(out.dataId).id;
wasmMin(inputId, reduceSize, outId);
}
if (inputWasTransposed) {
// dispose of the transposed tensor.
backend.disposeData(transposed.dataId);
}
if (keepDims) {
// reshape
const newShape = tfjsCore.backend_util.expandShapeToKeepDim(out.shape, originalAxes);
out.shape = newShape;
}
return out;
}
const minConfig = {
kernelName: tfjsCore.Min,
backendName: 'wasm',
setupFunc: setup$h,
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.
* =============================================================================
*/
const supportsFullBroadcast$a = false;
const minimumConfig = createBinaryKernelConfig(tfjsCore.Minimum, supportsFullBroadcast$a);
/**
* @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.
* =============================================================================
*/
const supportsFullBroadcast$b = true;
const multiplyConfig = createBinaryKernelConfig(tfjsCore.Multiply, supportsFullBroadcast$b);
/**
* @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.
* =============================================================================
*/
const negateConfig = createUnaryKernelConfig(tfjsCore.Negate);
/**
* @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) {
const result = new Int32Array(backend.wasm.HEAPU8.buffer, resOffset, 4);
const pSelectedIndices = result[0];
const selectedSize = result[1];
const pSelectedScores = result[2];
const pValidOutputs = result[3];
// Since the result was allocated on the heap, we have to delete it.
backend.wasm._free(resOffset);
return { pSelectedIndices, selectedSize, pSelectedScores, 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.
* =============================================================================
*/
let wasmFunc$2;
function setup$i(backend) {
wasmFunc$2 = backend.wasm.cwrap(tfjsCore.NonMaxSuppressionV3, 'number', // Result*
[
'number',
'number',
'number',
'number',
'number',
]);
}
function kernelFunc(args) {
const { backend, inputs, attrs } = args;
const { iouThreshold, maxOutputSize, scoreThreshold } = attrs;
const { boxes, scores } = inputs;
const boxesId = backend.dataIdMap.get(boxes.dataId).id;
const scoresId = backend.dataIdMap.get(scores.dataId).id;
const resOffset = wasmFunc$2(boxesId, scoresId, maxOutputSize, iouThreshold, scoreThreshold);
const { pSelectedIndices, selectedSize, pSelectedScores, pValidOutputs } = parseResultStruct(backend, resOffset);
// Since we are not using scores for V3, we have to delete it from the heap.
backend.wasm._free(pSelectedScores);
backend.wasm._free(pValidOutputs);
const selectedIndicesTensor = backend.makeOutput([selectedSize], 'int32', pSelectedIndices);
return selectedIndicesTensor;
}
const nonMaxSuppressionV3Config = {
kernelName: tfjsCore.NonMaxSuppressionV3,
backendName: 'wasm',
setupFunc: setup$i,
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.
* =============================================================================
*/
let wasmFunc$3;
function setup$j(backend) {
wasmFunc$3 = backend.wasm.cwrap(tfjsCore.NonMaxSuppressionV4, 'number', // Result*
[
'number',
'number',
'number',
'number',
'number',
'bool',
]);
}
function nonMaxSuppressionV4(args) {
const { backend, inputs, attrs } = args;
const { iouThreshold, maxOutputSize, scoreThreshold, padToMaxOutputSize } = attrs;
const { boxes, scores } = inputs;
const boxesId = backend.dataIdMap.get(boxes.dataId).id;
const scoresId = backend.dataIdMap.get(scores.dataId).id;
const resOffset = wasmFunc$3(boxesId, scoresId, maxOutputSize, iouThreshold, scoreThreshold, padToMaxOutputSize);
const { pSelectedIndices, selectedSize, pSelectedScores, pValidOutputs } = parseResultStruct(backend, resOffset);
// Since we are not using scores for V4, we have to delete it from the heap.
backend.wasm._free(pSelectedScores);
const selectedIndicesTensor = backend.makeOutput([selectedSize], 'int32', pSelectedIndices);
const validOutputsTensor = backend.makeOutput([], 'int32', pValidOutputs);
return [selectedIndicesTensor, validOutputsTensor];
}
const nonMaxSuppressionV4Config = {
kernelName: tfjsCore.NonMaxSuppressionV4,
backendName: 'wasm',
setupFunc: setup$j,
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.
* =============================================================================
*/
let wasmFunc$4;
function setup$k(backend) {
wasmFunc$4 = backend.wasm.cwrap(tfjsCore.NonMaxSuppressionV5, 'number', // Result*
[
'number',
'number',
'number',
'number',
'number',
'number',
]);
}
function kernelFunc$1(args) {
const { backend, inputs, attrs } = args;
const { iouThreshold, maxOutputSize, scoreThreshold, softNmsSigma } = attrs;
const { boxes, scores } = inputs;
const boxesId = backend.dataIdMap.get(boxes.dataId).id;
const scoresId = backend.dataIdMap.get(scores.dataId).id;
const resOffset = wasmFunc$4(boxesId, scoresId, maxOutputSize, iouThreshold, scoreThreshold, softNmsSigma);
const { pSelectedIndices, selectedSize, pSelectedScores, pValidOutputs } = parseResultStruct(backend, resOffset);
// Since we are not using validOutputs for V5, we have to delete it from the
// heap.
backend.wasm._free(pValidOutputs);
const selectedIndicesTensor = backend.makeOutput([selectedSize], 'int32', pSelectedIndices);
const selectedScoresTensor = backend.makeOutput([selectedSize], 'float32', pSelectedScores);
return [selectedIndicesTensor, selectedScoresTensor];
}
const nonMaxSuppressionV5Config = {
kernelName: tfjsCore.NonMaxSuppressionV5,
backendName: 'wasm',
setupFunc: setup$k,
kernelFunc: kernelFunc$1,
};
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
const supportsFullBroadcast$c = false;
const notEqualConfig = createBinaryKernelConfig(tfjsCore.NotEqual, supportsFullBroadcast$c, 'bool');
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
let wasmOneHot;
function setup$l(backend) {
wasmOneHot = backend.wasm.cwrap(tfjsCore.OneHot, null /* void */, [
'number',
'number',
'number',
'number',
'number' // out_id
]);
}
function oneHot(args) {
const { inputs, backend, attrs } = args;
const { indices } = inputs;
const { depth, onValue, offValue } = attrs;
const out = backend.makeOutput([...indices.shape, depth], 'int32');
const outId = backend.dataIdMap.get(out.dataId).id;
const indicesData = backend.dataIdMap.get(indices.dataId);
const indicesId = indicesData.id;
wasmOneHot(indicesId, depth, onValue, offValue, outId);
return out;
}
const oneHotConfig = {
kernelName: tfjsCore.OneHot,
backendName: 'wasm',
setupFunc: setup$l,
kernelFunc: oneHot,
};
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
function onesLike(args) {
const { inputs: { x }, backend } = args;
const out = backend.makeOutput(x.shape, x.dtype);
const outVals = backend.typedArrayFromHeap(out);
outVals.fill(1);
return out;
}
const onesLikeConfig = {
kernelName: tfjsCore.OnesLike,
backendName: 'wasm',
kernelFunc: onesLike,
};
/**
* @license
* Copyright 2019 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
let wasmPadV2;
function setup$m(backend) {
wasmPadV2 = backend.wasm.cwrap(tfjsCore.PadV2, null /* void */, [
'number',
'array',
'number',
'number',
'array',
'array',
'number',
'number',
]);
}
function pad(args) {
const { inputs: { x }, backend, attrs: { paddings, constantValue } } = args;
const outShape = paddings.map((p, i) => p[0] /* beforePad */ + x.shape[i] + p[1] /* afterPad */);
const xId = backend.dataIdMap.get(x.dataId).id;
const out = backend.makeOutput(outShape, x.dtype);
const outId = backend.dataIdMap.get(out.dataId).id;
const xShapeBytes = new Uint8Array(new Int32Array(x.shape).buffer);
const prePaddingsFlat = paddings.map(padTuple => padTuple[0]);
const postPaddingsFlat = paddings.map(padTuple => padTuple[1]);
const prePaddingsBytes = new Uint8Array(new Int32Array(prePaddingsFlat).buffer);
const postPaddingsBytes = new Uint8Array(new Int32Array(postPaddingsFlat).buffer);
wasmPadV2(xId, xShapeBytes, x.shape.length, CppDType[x.dtype], prePaddingsBytes, postPaddingsBytes, constantValue, outId);
return out;
}
const padV2Config = {
kernelName: tfjsCore.PadV2,
backendName: 'wasm',
kernelFunc: pad,
setupFunc: setup$m
};
/**
* @license
* Copyright 2019 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
const supportsFullBroadcast$d = false;
const powConfig = createBinaryKernelConfig(tfjsCore.Pow, supportsFullBroadcast$d);
/**
* @license
* Copyright 2019 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
let wasmPrelu;
function setup$n(backend) {
wasmPrelu = backend.wasm.cwrap(tfjsCore.Prelu, null /* void */, [
'number',
'number',
'number' // out_id
]);
}
function prelu(args) {
const { inputs, backend } = args;
const { x, alpha } = inputs;
const xId = backend.dataIdMap.get(x.dataId).id;
const weightsId = backend.dataIdMap.get(alpha.dataId).id;
const out = backend.makeOutput(x.shape, 'float32');
const outId = backend.dataIdMap.get(out.dataId).id;
wasmPrelu(xId, weightsId, outId);
return out;
}
const preluConfig = {
kernelName: tfjsCore.Prelu,
backendName: 'wasm',
setupFunc: setup$n,
kernelFunc: prelu
};
/**
* @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.
* =============================================================================
*/
const 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.
* =============================================================================
*/
const 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.
* =============================================================================
*/
function reshape(args) {
const { inputs, attrs } = args;
const { x } = inputs;
const { shape } = attrs;
return { dataId: x.dataId, shape, dtype: x.dtype };
}
const 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.
* =============================================================================
*/
let wasmResizeBilinear;
function setup$o(backend) {
wasmResizeBilinear = backend.wasm.cwrap(tfjsCore.ResizeBilinear, null /*void*/, [
'number',
'number',
'number',
'number',
'number',
'number',
'number',
'number',
'number' // outId
]);
}
function resizeBilinear(args) {
const { backend, inputs, attrs } = args;
const { images } = inputs;
const { alignCorners, size } = attrs;
const [newHeight, newWidth] = size;
const [batch, oldHeight, oldWidth, numChannels] = images.shape;
const outShape = [batch, newHeight, newWidth, numChannels];
let xData = backend.dataIdMap.get(images.dataId);
let castedData;
if (xData.dtype !== 'float32') {
castedData =
cast({ backend, inputs: { x: images }, attrs: { dtype: 'float32' } });
xData = backend.dataIdMap.get(castedData.dataId);
}
const xId = xData.id;
const out = backend.makeOutput(outShape, 'float32');
if (tfjsCore.util.sizeFromShape(images.shape) === 0) {
return out;
}
const outId = backend.dataIdMap.get(out.dataId).id;
wasmResizeBilinear(xId, batch, oldHeight, oldWidth, numChannels, newHeight, newWidth, alignCorners ? 1 : 0, outId);
if (castedData != null) {
backend.disposeData(castedData.dataId);
}
return out;
}
const resizeBilinearConfig = {
kernelName: tfjsCore.ResizeBilinear,
backendName: 'wasm',
setupFunc: setup$o,
kernelFunc: resizeBilinear
};
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
let wasmReverse;
function setup$p(backend) {
wasmReverse = backend.wasm.cwrap(tfjsCore.Reverse, null, [
'number',
'array',
'number',
'array',
'number',
'number' // out_id
]);
}
function reverse(args) {
const { inputs, backend, attrs } = args;
const { x } = inputs;
const { dims } = attrs;
const axes = tfjsCore.util.parseAxisParam(dims, x.shape);
if (x.shape.length === 0) {
return identity({ inputs: { x }, backend });
}
const out = backend.makeOutput(x.shape, x.dtype);
const xId = backend.dataIdMap.get(x.dataId).id;
const outId = backend.dataIdMap.get(out.dataId).id;
const axesBytes = new Uint8Array(new Int32Array(axes).buffer);
const outShapeBytes = new Uint8Array(new Int32Array(x.shape).buffer);
wasmReverse(xId, axesBytes, axes.length, outShapeBytes, x.shape.length, outId);
return reshape({ inputs: { x: out }, attrs: { shape: x.shape }, backend });
}
const reverseConfig = {
kernelName: tfjsCore.Reverse,
backendName: 'wasm',
kernelFunc: reverse,
setupFunc: setup$p
};
/**
* @license
* Copyright 2019 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
let wasmRotate;
function setup$q(backend) {
wasmRotate = backend.wasm.cwrap(tfjsCore.RotateWithOffset, null /* void */, [
'number',
'number',
'number',
'number',
'number',
'number',
'number',
'number',
'array',
'number',
'number',
]);
}
function rotateWithOffset(args) {
const { inputs, backend, attrs } = args;
const { image } = inputs;
const { radians, fillValue, center } = attrs;
const out = backend.makeOutput(image.shape, image.dtype);
const imageId = backend.dataIdMap.get(image.dataId).id;
const outId = backend.dataIdMap.get(out.dataId).id;
const [batch, imageHeight, imageWidth, numChannels] = image.shape;
const [centerX, centerY] = tfjsCore.backend_util.getImageCenter(center, imageHeight, imageWidth);
const fillIsBlack = fillValue === 0;
const fullOpacityValue = 255;
const fillValues = typeof fillValue === 'number' ?
[fillValue, fillValue, fillValue, fillIsBlack ? 0 : fullOpacityValue] :
[...fillValue, fullOpacityValue];
const fillBytes = new Uint8Array(new Int32Array(fillValues).buffer);
wasmRotate(imageId, batch, imageHeight, imageWidth, numChannels, radians, centerX, centerY, fillBytes, fillValues.length, outId);
return out;
}
const rotateWithOffsetConfig = {
kernelName: tfjsCore.RotateWithOffset,
backendName: 'wasm',
kernelFunc: rotateWithOffset,
setupFunc: setup$q
};
/**
* @license
* Copyright 2019 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
const rsqrtConfig = createUnaryKernelConfig(tfjsCore.Rsqrt);
/**
* @license
* Copyright 2019 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
let wasmScatterNd;
function setup$r(backend) {
wasmScatterNd = backend.wasm.cwrap(tfjsCore.ScatterNd, null /*void*/, [
'number',
'number',
'number',
'number',
'number',
'number',
'array',
'number',
'number' // outId
]);
}
function scatterNd(args) {
const { backend, inputs, attrs } = args;
const { indices, updates } = inputs;
const { shape } = attrs;
const out = backend.makeOutput(shape, updates.dtype);
if (tfjsCore.util.sizeFromShape(shape) === 0) {
return out;
}
const { sliceRank, numUpdates, sliceSize, strides, outputSize } = tfjsCore.scatter_util.calculateShapes(updates, indices, shape);
const indicesData = backend.dataIdMap.get(indices.dataId);
const indicesId = indicesData.id;
const updatesData = backend.dataIdMap.get(updates.dataId);
const updatesId = updatesData.id;
const stridesBytes = new Uint8Array(new Int32Array(strides).buffer);
const outId = backend.dataIdMap.get(out.dataId).id;
wasmScatterNd(indicesId, updatesId, CppDType[updates.dtype], sliceRank, numUpdates, sliceSize, stridesBytes, outputSize, outId);
return out;
}
const scatterNdConfig = {
kernelName: tfjsCore.ScatterNd,
backendName: 'wasm',
setupFunc: setup$r,
kernelFunc: scatterNd
};
/**
* @license
* Copyright 2020 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
let wasmSelect;
function setup$s(backend) {
wasmSelect = backend.wasm.cwrap(tfjsCore.SelectV2, null, [
'number',
'number',
'number',
'number',
'number',
]);
}
function select(args) {
const { inputs, backend } = args;
const { condition, t, e } = inputs;
const conditionId = backend.dataIdMap.get(condition.dataId).id;
const tId = backend.dataIdMap.get(t.dataId).id;
const eId = backend.dataIdMap.get(e.dataId).id;
const out = backend.makeOutput(t.shape, t.dtype);
const outId = backend.dataIdMap.get(out.dataId).id;
const cRank = condition.shape.length;
const tRank = t.shape.length;
const offset = cRank === 0 || cRank > 1 || tRank === 1 ?
1 :
tfjsCore.util.sizeFromShape(t.shape.slice(1));
wasmSelect(conditionId, tId, eId, offset, outId);
return out;
}
const selectV2Config = {
kernelName: tfjsCore.SelectV2,
backendName: 'wasm',
kernelFunc: select,
setupFunc: setup$s
};
/**
* @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.
* =============================================================================
*/
let wasmFunc$5;
function setup$t(backend) {
wasmFunc$5 = backend.wasm.cwrap(tfjsCore.Sigmoid, null /* void */, ['number', 'number']);
}
function sigmoid(args) {
const { backend, inputs: { x } } = args;
const xId = backend.dataIdMap.get(x.dataId).id;
const out = backend.makeOutput(x.shape, x.dtype);
const outId = backend.dataIdMap.get(out.dataId).id;
// Short-circuit zero-sized tensors.
if (tfjsCore.util.sizeFromShape(out.shape) === 0) {
return out;
}
wasmFunc$5(xId, outId);
return out;
}
const sigmoidConfig = {
kernelName: 'Sigmoid',
backendName: 'wasm',
setupFunc: setup$t,
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.
* =============================================================================
*/
const sinConfig = createUnaryKernelConfig(tfjsCore.Sin);
/**
* @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) {
const { inputs: { x }, attrs: { begin, size }, backend } = args;
const [begin_, size_] = tfjsCore.slice_util.parseSliceParams(x, begin, size);
const isContinous = tfjsCore.slice_util.isSliceContinous(x.shape, begin_, size_);
const xVals = backend.typedArrayFromHeap(x);
const out = backend.makeOutput(size_, x.dtype);
const outVals = backend.typedArrayFromHeap(out);
const xStrides = tfjsCore.util.computeStrides(x.shape);
if (isContinous) {
const flatOffset = tfjsCore.slice_util.computeFlatOffset(begin_, xStrides);
outVals.set(xVals.subarray(flatOffset, flatOffset + tfjsCore.util.sizeFromShape(size_)));
return out;
}
const 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 {
genericSliceSlow(xVals, x, outVals, begin_, size_);
}
return out;
}
function slice2d(xVals, xStride, outVals, begin, size) {
let outOffset = 0;
const beginI = begin[0];
const beginJ = begin[1];
const endI = beginI + size[0];
for (let i = beginI; i < endI; i++) {
const xOffset = i * xStride + beginJ;
outVals.set(xVals.subarray(xOffset, xOffset + size[1]), outOffset);
outOffset += size[1];
}
}
function slice3d(xVals, xStride1, xStride2, outVals, begin, size) {
let outOffset = 0;
const beginI = begin[0];
const beginJ = begin[1];
const beginK = begin[2];
const endI = beginI + size[0];
const endJ = beginJ + size[1];
for (let i = beginI; i < endI; i++) {
for (let j = beginJ; j < endJ; j++) {
const 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) {
let outOffset = 0;
const beginI = begin[0];
const beginJ = begin[1];
const beginK = begin[2];
const endI = beginI + size[0];
const endJ = beginJ + size[1];
const endK = beginK + size[2];
const beginL = begin[3];
for (let i = beginI; i < endI; i++) {
for (let j = beginJ; j < endJ; j++) {
for (let k = beginK; k < endK; k++) {
const xOffset = i * xStride1 + j * xStride2 + k * xStride3 + beginL;
outVals.set(xVals.subarray(xOffset, xOffset + size[3]), outOffset);
outOffset += size[3];
}
}
}
}
function genericSliceSlow(xVals, xInfo, outVals, begin, size) {
const outBuf = tfjsCore.buffer(size, xInfo.dtype, outVals);
const xBuf = tfjsCore.buffer(xInfo.shape, xInfo.dtype, xVals);
for (let i = 0; i < outBuf.size; ++i) {
const loc = outBuf.indexToLoc(i);
const xLoc = loc.map((idx, j) => idx + begin[j]);
outVals[i] = xBuf.get(...xLoc);
}
}
const sliceConfig = {
kernelName: tfjsCore.Slice,
backendName: 'wasm',
kernelFunc: slice,
};
/**
* @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.
* =============================================================================
*/
let wasmFunc$6;
function setup$u(backend) {
wasmFunc$6 = backend.wasm.cwrap(tfjsCore.Softmax, null /* void */, [
'number',
'number',
'number',
'number' // batch
]);
}
function softmax(args) {
const { backend, inputs: { logits }, attrs: { dim } } = args;
const xId = backend.dataIdMap.get(logits.dataId).id;
const out = backend.makeOutput(logits.shape, logits.dtype);
const outId = backend.dataIdMap.get(out.dataId).id;
const channels = logits.shape[dim];
const batch = tfjsCore.util.sizeFromShape(logits.shape) / channels;
// Short-circuit zero-sized tensors.
if (tfjsCore.util.sizeFromShape(out.shape) === 0) {
return out;
}
wasmFunc$6(xId, outId, channels, batch);
return out;
}
const softmaxConfig = {
kernelName: tfjsCore.Softmax,
backendName: 'wasm',
setupFunc: setup$u,
kernelFunc: softmax
};
/**
* @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 split(args) {
const { inputs, attrs, backend } = args;
const { x } = inputs;
const { numOrSizeSplits, axis } = attrs;
const $axis = tfjsCore.util.parseAxisParam(axis, x.shape)[0];
const splitSizes = tfjsCore.backend_util.prepareSplitSize(x, numOrSizeSplits, axis);
const begin = new Array(x.shape.length).fill(0);
const size = x.shape.slice();
return splitSizes.map(s => {
const xSliceSize = [...size];
xSliceSize[$axis] = s;
const xSlice = slice({ inputs: { x }, attrs: { begin, size: xSliceSize }, backend });
begin[$axis] += s;
return xSlice;
});
}
const splitVConfig = {
kernelName: tfjsCore.SplitV,
backendName: 'wasm',
kernelFunc: split
};
/**
* @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.
* =============================================================================
*/
const 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.
* =============================================================================
*/
const 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.
* =============================================================================
*/
const supportsFullBroadcast$e = true;
const subConfig = createBinaryKernelConfig(tfjsCore.Sub, supportsFullBroadcast$e);
/**
* @license
* Copyright 2019 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
let wasmSum;
function setup$v(backend) {
wasmSum = backend.wasm.cwrap(tfjsCore.Sum, null /*void*/, ['number, number, number']);
}
function sum(args) {
const { backend, inputs, attrs } = args;
const { axis, keepDims } = attrs;
const { x } = inputs;
const xId = backend.dataIdMap.get(x.dataId).id;
let inputId = xId;
let input = x;
const { transposed, axes, originalAxes, inputWasTransposed } = permuteAxesAndTranspose(x, axis, backend);
let reductionAxes = axes;
if (inputWasTransposed) {
const 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);
const [outShape, reduceShape] = tfjsCore.backend_util.computeOutAndReduceShapes(input.shape, reductionAxes);
const reduceSize = tfjsCore.util.sizeFromShape(reduceShape);
const out = backend.makeOutput(outShape, input.dtype);
if (tfjsCore.util.sizeFromShape(input.shape) !== 0) {
const outId = backend.dataIdMap.get(out.dataId).id;
wasmSum(inputId, reduceSize, outId);
}
if (inputWasTransposed) {
// dispose of the transposed tensor.
backend.disposeData(transposed.dataId);
}
if (keepDims) {
// reshape
const newShape = tfjsCore.backend_util.expandShapeToKeepDim(out.shape, originalAxes);
out.shape = newShape;
}
return out;
}
const sumConfig = {
kernelName: tfjsCore.Sum,
backendName: 'wasm',
setupFunc: setup$v,
kernelFunc: sum
};
/**
* @license
* Copyright 2019 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
const tanhConfig = createUnaryKernelConfig(tfjsCore.Tanh);
/**
* @license
* Copyright 2019 Google LLC. All Rights Reserved.
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* =============================================================================
*/
let wasmTile;
function setup$w(backend) {
wasmTile = backend.wasm.cwrap(tfjsCore.Tile, null /* void */, [
'number',
'array',
'number',
'array',
'number',
'number' // out_id
]);
}
function tile(args) {
const { inputs, backend, attrs } = args;
const { x } = inputs;
const xId = backend.dataIdMap.get(x.dataId).id;
const { reps } = attrs;
const newShape = new Array(x.shape.length);
for (let i = 0; i < newShape.length; i++) {
newShape[i] = x.shape[i] * reps[i];
}
const xShapeBytes = new Uint8Array(new Int32Array(x.shape).buffer);
const newShapeBytes = new Uint8Array(new Int32Array(newShape).buffer);
const out = backend.makeOutput(newShape, x.dtype);
const outId = backend.dataIdMap.get(out.dataId).id;
wasmTile(xId, xShapeBytes, x.shape.length, newShapeBytes, newShape.length, CppDType[out.dtype], outId);
return out;
}
const tileConfig = {
kernelName: tfjsCore.Tile,
backendName: 'wasm',
setupFunc: setup$w,
kernelFunc: tile
};
/**
* @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) {
const { inputs, backend, attrs } = args;
const { value } = inputs;
const { axis } = attrs;
const numOutputs = value.shape[axis];
const rank = value.shape.length;
const outShape = new Array(rank - 1);
let outIndex = 0;
for (let i = 0; i < rank; i++) {
if (i !== axis) {
outShape[outIndex++] = value.shape[i];
}
}
const outs = new Array(numOutputs);
const begin = new Array(rank).fill(0);
const size = value.shape.slice();
size[axis] = 1;
for (let i = 0; i < outs.length; i++) {
begin[axis] = i;
outs[i] = slice({ inputs: { x: value }, attrs: { begin, size }, backend });
}
return outs.map(({ dataId, dtype }) => ({ dataId, dtype, shape: outShape }));
}
const 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) {
const { inputs: { x }, backend } = args;
const out = backend.makeOutput(x.shape, x.dtype);
const outVals = backend.typedArrayFromHeap(out);
outVals.fill(0);
return out;
}
const 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
const kernelConfigs = [
absConfig,
addConfig,
addNConfig,
argMaxConfig,
avgPoolConfig,
batchMatMulConfig,
castConfig,
clipByValueConfig,
concatConfig,
conv2DConfig,
conv2DBackpropInputConfig,
cosConfig,
cropAndResizeConfig,
depthwiseConv2DNativeConfig,
divConfig,
equalConfig,
expConfig,
fillConfig,
floorDivConfig,
fusedMatMulConfig,
fusedBatchNormConfig,
fusedConv2DConfig,
fusedDepthwiseConv2DConfig,
gatherNdConfig,
gatherV2Config,
greaterConfig,
greaterEqualConfig,
identityConfig,
lessConfig,
lessEqualConfig,
logConfig,
logicalAndConfig,
maxConfig,
maximumConfig,
maxPoolConfig,
minConfig,
minimumConfig,
multiplyConfig,
negateConfig,
nonMaxSuppressionV3Config,
nonMaxSuppressionV4Config,
nonMaxSuppressionV5Config,
notEqualConfig,
oneHotConfig,
onesLikeConfig,
padV2Config,
powConfig,
preluConfig,
reluConfig,
relu6Config,
reshapeConfig,
resizeBilinearConfig,
reverseConfig,
rotateWithOffsetConfig,
rsqrtConfig,
scatterNdConfig,
selectV2Config,
sigmoidConfig,
sinConfig,
sliceConfig,
softmaxConfig,
splitVConfig,
sqrtConfig,
squareConfig,
subConfig,
sumConfig,
tanhConfig,
tileConfig,
transposeConfig,
unpackConfig,
zerosLikeConfig
];
for (const kernelConfig of kernelConfigs) {
tfjsCore.registerKernel(kernelConfig);
}
/**
* @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.
* =============================================================================
*/
const ENV = tfjsCore.env();
/**
* True if SIMD is supported.
*/
// From: https://github.com/GoogleChromeLabs/wasm-feature-detect
ENV.registerFlag('WASM_HAS_SIMD_SUPPORT', async () => 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
])));
function createCommonjsModule(fn, module) {
return module = { exports: {} }, fn(module, module.exports), module.exports;
}
var tfjsBackendWasmSimd = createCommonjsModule(function (module, exports) {
var WasmBackendModuleSimd = (function() {
var _scriptDir = typeof document !== 'undefined' && document.currentScript ? document.currentScript.src : undefined;
if (typeof __filename !== 'undefined') _scriptDir = _scriptDir || __filename;
return (
function(WasmBackendModuleSimd) {
WasmBackendModuleSimd = WasmBackendModuleSimd || {};
var Module=typeof WasmBackendModuleSimd!=="undefined"?WasmBackendModuleSimd:{};var moduleOverrides={};var key;for(key in Module){if(Module.hasOwnProperty(key)){moduleOverrides[key]=Module[key];}}var arguments_=[];var thisProgram="./this.program";var quit_=function(status,toThrow){throw toThrow};var ENVIRONMENT_IS_WEB=false;var ENVIRONMENT_IS_WORKER=false;var ENVIRONMENT_IS_NODE=false;var ENVIRONMENT_IS_SHELL=false;ENVIRONMENT_IS_WEB=typeof window==="object";ENVIRONMENT_IS_WORKER=typeof importScripts==="function";ENVIRONMENT_IS_NODE=typeof process==="object"&&typeof process.versions==="object"&&typeof process.versions.node==="string";ENVIRONMENT_IS_SHELL=!ENVIRONMENT_IS_WEB&&!ENVIRONMENT_IS_NODE&&!ENVIRONMENT_IS_WORKER;var scriptDirectory="";function locateFile(path){if(Module["locateFile"]){return Module["locateFile"](path,scriptDirectory)}return scriptDirectory+path}var read_,readBinary;var nodeFS;var nodePath;if(ENVIRONMENT_IS_NODE){if(ENVIRONMENT_IS_WORKER){scriptDirectory=path.dirname(scriptDirectory)+"/";}else{scriptDirectory=__dirname+"/";}read_=function shell_read(filename,binary){if(!nodeFS)nodeFS=fs;if(!nodePath)nodePath=path;filename=nodePath["normalize"](filename);return nodeFS["readFileSync"](filename,binary?null:"utf8")};readBinary=function readBinary(filename){var ret=read_(filename,true);if(!ret.buffer){ret=new Uint8Array(ret);}assert(ret.buffer);return ret};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",abort);quit_=function(status){process["exit"](status);};Module["inspect"]=function(){return "[Emscripten Module object]"};}else if(ENVIRONMENT_IS_SHELL){if(typeof read!="undefined"){read_=function shell_read(f){return read(f)};}readBinary=function readBinary(f){var data;if(typeof readbuffer==="function"){return new Uint8Array(readbuffer(f))}data=read(f,"binary");assert(typeof data==="object");return data};if(typeof scriptArgs!="undefined"){arguments_=scriptArgs;}else if(typeof arguments!="undefined"){arguments_=arguments;}if(typeof quit==="function"){quit_=function(status){quit(status);};}if(typeof print!=="undefined"){if(typeof console==="undefined")console={};console.log=print;console.warn=console.error=typeof printErr!=="undefined"?printErr:print;}}else if(ENVIRONMENT_IS_WEB||ENVIRONMENT_IS_WORKER){if(ENVIRONMENT_IS_WORKER){scriptDirectory=self.location.href;}else if(document.currentScript){scriptDirectory=document.currentScript.src;}if(_scriptDir){scriptDirectory=_scriptDir;}if(scriptDirectory.indexOf("blob:")!==0){scriptDirectory=scriptDirectory.substr(0,scriptDirectory.lastIndexOf("/")+1);}else{scriptDirectory="";}{read_=function shell_read(url){var xhr=new XMLHttpRequest;xhr.open("GET",url,false);xhr.send(null);return xhr.responseText};if(ENVIRONMENT_IS_WORKER){readBinary=function readBinary(url){var xhr=new XMLHttpRequest;xhr.open("GET",url,false);xhr.responseType="arraybuffer";xhr.send(null);return new Uint8Array(xhr.response)};}}}var out=Module["print"]||console.log.bind(console);var err=Module["printErr"]||console.warn.bind(console);for(key in moduleOverrides){if(moduleOverrides.hasOwnProperty(key)){Module[key]=moduleOverrides[key];}}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;if(Module["noExitRuntime"])noExitRuntime=Module["noExitRuntime"];if(typeof WebAssembly!=="object"){err("no native wasm support detected");}var wasmMemory;var wasmTable=new WebAssembly.Table({"initial":151,"maximum":151+0,"element":"anyfunc"});var ABORT=false;function assert(condition,text){if(!condition){abort("Assertion failed: "+text);}}function getCFunc(ident){var func=Module["_"+ident];assert(func,"Cannot call unknown function "+ident+", make sure it is exported");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);ret=convertReturnValue(ret);if(stack!==0)stackRestore(stack);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)}function writeArrayToMemory(array,buffer){HEAP8.set(array,buffer);}var WASM_PAGE_SIZE=65536;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 DYNAMIC_BASE=5254528,DYNAMICTOP_PTR=11488;var INITIAL_INITIAL_MEMORY=Module["INITIAL_MEMORY"]||16777216;if(Module["wasmMemory"]){wasmMemory=Module["wasmMemory"];}else{wasmMemory=new WebAssembly.Memory({"initial":INITIAL_INITIAL_MEMORY/WASM_PAGE_SIZE,"maximum":2147483648/WASM_PAGE_SIZE});}if(wasmMemory){buffer=wasmMemory.buffer;}INITIAL_INITIAL_MEMORY=buffer.byteLength;updateGlobalBufferAndViews(buffer);HEAP32[DYNAMICTOP_PTR>>2]=DYNAMIC_BASE;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){Module["dynCall_v"](func);}else{Module["dynCall_vi"](func,callback.arg);}}else{func(callback.arg===undefined?null:callback.arg);}}}var __ATPRERUN__=[];var __ATINIT__=[];var __ATMAIN__=[];var __ATPOSTRUN__=[];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 preMain(){callRuntimeCallbacks(__ATMAIN__);}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 addOnPostRun(cb){__ATPOSTRUN__.unshift(cb);}var Math_ceil=Math.ceil;var Math_floor=Math.floor;var runDependencies=0;var runDependencyWatcher=null;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(runDependencyWatcher!==null){clearInterval(runDependencyWatcher);runDependencyWatcher=null;}if(dependenciesFulfilled){var callback=dependenciesFulfilled;dependenciesFulfilled=null;callback();}}}Module["preloadedImages"]={};Module["preloadedAudios"]={};function abort(what){if(Module["onAbort"]){Module["onAbort"](what);}what+="";out(what);err(what);ABORT=true;what="abort("+what+"). Build with -s ASSERTIONS=1 for more info.";throw new WebAssembly.RuntimeError(what)}function hasPrefix(str,prefix){return String.prototype.startsWith?str.startsWith(prefix):str.indexOf(prefix)===0}var dataURIPrefix="data:application/octet-stream;base64,";function isDataURI(filename){return hasPrefix(filename,dataURIPrefix)}var fileURIPrefix="file://";function isFileURI(filename){return hasPrefix(filename,fileURIPrefix)}var wasmBinaryFile="tfjs-backend-wasm-simd.wasm";if(!isDataURI(wasmBinaryFile)){wasmBinaryFile=locateFile(wasmBinaryFile);}function getBinary(){try{if(wasmBinary){return new Uint8Array(wasmBinary)}if(readBinary){return readBinary(wasmBinaryFile)}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)&&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()})}return new Promise(function(resolve,reject){resolve(getBinary());})}function createWasm(){var info={"a":asmLibraryArg};function receiveInstance(instance,module){var exports=instance.exports;Module["asm"]=exports;removeRunDependency();}addRunDependency();function receiveInstantiatedSource(output){receiveInstance(output["instance"]);}function instantiateArrayBuffer(receiver){return getBinaryPromise().then(function(binary){return WebAssembly.instantiate(binary,info)}).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"){fetch(wasmBinaryFile,{credentials:"same-origin"}).then(function(response){var result=WebAssembly.instantiateStreaming(response,info);return result.then(receiveInstantiatedSource,function(reason){err("wasm streaming compile failed: "+reason);err("falling back to ArrayBuffer instantiation");instantiateArrayBuffer(receiveInstantiatedSource);})});}else{return instantiateArrayBuffer(receiveInstantiatedSource)}}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();return {}}__ATINIT__.push({func:function(){___wasm_call_ctors();}});function _abort(){abort();}function _emscripten_memcpy_big(dest,src,num){HEAPU8.copyWithin(dest,src,src+num);}function _emscripten_get_heap_size(){return HEAPU8.length}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){requestedSize=requestedSize>>>0;var oldSize=_emscripten_get_heap_size();var PAGE_MULTIPLE=65536;var maxHeapSize=2147483648;if(requestedSize>maxHeapSize){return false}var minHeapSize=16777216;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(minHeapSize,requestedSize,overGrownHeapSize),PAGE_MULTIPLE));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+i*8>>2];var len=HEAP32[iov+(i*8+4)>>2];for(var j=0;j<len;j++){SYSCALLS.printChar(fd,HEAPU8[ptr+j]);}num+=len;}HEAP32[pnum>>2]=num;return 0}function _roundf(d){d=+d;return d>=+0?+Math_floor(d+ +.5):+Math_ceil(d-+.5)}var asmLibraryArg={"a":_abort,"e":_emscripten_memcpy_big,"f":_emscripten_resize_heap,"g":_fd_close,"d":_fd_seek,"c":_fd_write,"memory":wasmMemory,"b":_roundf,"table":wasmTable};var asm=createWasm();Module["asm"]=asm;var ___wasm_call_ctors=Module["___wasm_call_ctors"]=function(){return (___wasm_call_ctors=Module["___wasm_call_ctors"]=Module["asm"]["h"]).apply(null,arguments)};var _init=Module["_init"]=function(){return (_init=Module["_init"]=Module["asm"]["i"]).apply(null,arguments)};var _register_tensor=Module["_register_tensor"]=function(){return (_register_tensor=Module["_register_tensor"]=Module["asm"]["j"]).apply(null,arguments)};var _dispose_data=Module["_dispose_data"]=function(){return (_dispose_data=Module["_dispose_data"]=Module["asm"]["k"]).apply(null,arguments)};var _dispose=Module["_dispose"]=function(){return (_dispose=Module["_dispose"]=Module["asm"]["l"]).apply(null,arguments)};var _Abs=Module["_Abs"]=function(){return (_Abs=Module["_Abs"]=Module["asm"]["m"]).apply(null,arguments)};var _Add=Module["_Add"]=function(){return (_Add=Module["_Add"]=Module["asm"]["n"]).apply(null,arguments)};var _AddN=Module["_AddN"]=function(){return (_AddN=Module["_AddN"]=Module["asm"]["o"]).apply(null,arguments)};var _ArgMax=Module["_ArgMax"]=function(){return (_ArgMax=Module["_ArgMax"]=Module["asm"]["p"]).apply(null,arguments)};var _AvgPool=Module["_AvgPool"]=function(){return (_AvgPool=Module["_AvgPool"]=Module["asm"]["q"]).apply(null,arguments)};var _BatchMatMul=Module["_BatchMatMul"]=function(){return (_BatchMatMul=Module["_BatchMatMul"]=Module["asm"]["r"]).apply(null,arguments)};var _ClipByValue=Module["_ClipByValue"]=function(){return (_ClipByValue=Module["_ClipByValue"]=Module["asm"]["s"]).apply(null,arguments)};var _Conv2D=Module["_Conv2D"]=function(){return (_Conv2D=Module["_Conv2D"]=Module["asm"]["t"]).apply(null,arguments)};var _Conv2DBackpropInput=Module["_Conv2DBackpropInput"]=function(){return (_Conv2DBackpropInput=Module["_Conv2DBackpropInput"]=Module["asm"]["u"]).apply(null,arguments)};var _Cos=Module["_Cos"]=function(){return (_Cos=Module["_Cos"]=Module["asm"]["v"]).apply(null,arguments)};var _CropAndResize=Module["_CropAndResize"]=function(){return (_CropAndResize=Module["_CropAndResize"]=Module["asm"]["w"]).apply(null,arguments)};var _DepthwiseConv2dNative=Module["_DepthwiseConv2dNative"]=function(){return (_DepthwiseConv2dNative=Module["_DepthwiseConv2dNative"]=Module["asm"]["x"]).apply(null,arguments)};var _Div=Module["_Div"]=function(){return (_Div=Module["_Div"]=Module["asm"]["y"]).apply(null,arguments)};var _Equal=Module["_Equal"]=function(){return (_Equal=Module["_Equal"]=Module["asm"]["z"]).apply(null,arguments)};var _Exp=Module["_Exp"]=function(){return (_Exp=Module["_Exp"]=Module["asm"]["A"]).apply(null,arguments)};var _FloorDiv=Module["_FloorDiv"]=function(){return (_FloorDiv=Module["_FloorDiv"]=Module["asm"]["B"]).apply(null,arguments)};var _FusedBatchNorm=Module["_FusedBatchNorm"]=function(){return (_FusedBatchNorm=Module["_FusedBatchNorm"]=Module["asm"]["C"]).apply(null,arguments)};var _FusedConv2D=Module["_FusedConv2D"]=function(){return (_FusedConv2D=Module["_FusedConv2D"]=Module["asm"]["D"]).apply(null,arguments)};var _FusedDepthwiseConv2D=Module["_FusedDepthwiseConv2D"]=function(){return (_FusedDepthwiseConv2D=Module["_FusedDepthwiseConv2D"]=Module["asm"]["E"]).apply(null,arguments)};var _Gather=Module["_Gather"]=function(){return (_Gather=Module["_Gather"]=Module["asm"]["F"]).apply(null,arguments)};var _GatherNd=Module["_GatherNd"]=function(){return (_GatherNd=Module["_GatherNd"]=Module["asm"]["G"]).apply(null,arguments)};var _Greater=Module["_Greater"]=function(){return (_Greater=Module["_Greater"]=Module["asm"]["H"]).apply(null,arguments)};var _GreaterEqual=Module["_GreaterEqual"]=function(){return (_GreaterEqual=Module["_GreaterEqual"]=Module["asm"]["I"]).apply(null,arguments)};var _Less=Module["_Less"]=function(){return (_Less=Module["_Less"]=Module["asm"]["J"]).apply(null,arguments)};var _LessEqual=Module["_LessEqual"]=function(){return (_LessEqual=Module["_LessEqual"]=Module["asm"]["K"]).apply(null,arguments)};var _Log=Module["_Log"]=function(){return (_Log=Module["_Log"]=Module["asm"]["L"]).apply(null,arguments)};var _LogicalAnd=Module["_LogicalAnd"]=function(){return (_LogicalAnd=Module["_LogicalAnd"]=Module["asm"]["M"]).apply(null,arguments)};var _Max=Module["_Max"]=function(){return (_Max=Module["_Max"]=Module["asm"]["N"]).apply(null,arguments)};var _MaxPool=Module["_MaxPool"]=function(){return (_MaxPool=Module["_MaxPool"]=Module["asm"]["O"]).apply(null,arguments)};var _Maximum=Module["_Maximum"]=function(){return (_Maximum=Module["_Maximum"]=Module["asm"]["P"]).apply(null,arguments)};var _Min=Module["_Min"]=function(){return (_Min=Module["_Min"]=Module["asm"]["Q"]).apply(null,arguments)};var _Minimum=Module["_Minimum"]=function(){return (_Minimum=Module["_Minimum"]=Module["asm"]["R"]).apply(null,arguments)};var _Multiply=Module["_Multiply"]=function(){return (_Multiply=Module["_Multiply"]=Module["asm"]["S"]).apply(null,arguments)};var _Negate=Module["_Negate"]=function(){return (_Negate=Module["_Negate"]=Module["asm"]["T"]).apply(null,arguments)};var _NonMaxSuppressionV3=Module["_NonMaxSuppressionV3"]=function(){return (_NonMaxSuppressionV3=Module["_NonMaxSuppressionV3"]=Module["asm"]["U"]).apply(null,arguments)};var _NonMaxSuppressionV4=Module["_NonMaxSuppressionV4"]=function(){return (_NonMaxSuppressionV4=Module["_NonMaxSuppressionV4"]=Module["asm"]["V"]).apply(null,arguments)};var _NonMaxSuppressionV5=Module["_NonMaxSuppressionV5"]=function(){return (_NonMaxSuppressionV5=Module["_NonMaxSuppressionV5"]=Module["asm"]["W"]).apply(null,arguments)};var _NotEqual=Module["_NotEqual"]=function(){return (_NotEqual=Module["_NotEqual"]=Module["asm"]["X"]).apply(null,arguments)};var _OneHot=Module["_OneHot"]=function(){return (_OneHot=Module["_OneHot"]=Module["asm"]["Y"]).apply(null,arguments)};var _PadV2=Module["_PadV2"]=function(){return (_PadV2=Module["_PadV2"]=Module["asm"]["Z"]).apply(null,arguments)};var _Pow=Module["_Pow"]=function(){return (_Pow=Module["_Pow"]=Module["asm"]["_"]).apply(null,arguments)};var _Prelu=Module["_Prelu"]=function(){return (_Prelu=Module["_Prelu"]=Module["asm"]["$"]).apply(null,arguments)};var _Relu=Module["_Relu"]=function(){return (_Relu=Module["_Relu"]=Module["asm"]["aa"]).apply(null,arguments)};var _Relu6=Module["_Relu6"]=function(){return (_Relu6=Module["_Relu6"]=Module["asm"]["ba"]).apply(null,arguments)};var _ResizeBilinear=Module["_ResizeBilinear"]=function(){return (_ResizeBilinear=Module["_ResizeBilinear"]=Module["asm"]["ca"]).apply(null,arguments)};var _Reverse=Module["_Reverse"]=function(){return (_Reverse=Module["_Reverse"]=Module["asm"]["da"]).apply(null,arguments)};var _RotateWithOffset=Module["_RotateWithOffset"]=function(){return (_RotateWithOffset=Module["_RotateWithOffset"]=Module["asm"]["ea"]).apply(null,arguments)};var _Rsqrt=Module["_Rsqrt"]=function(){return (_Rsqrt=Module["_Rsqrt"]=Module["asm"]["fa"]).apply(null,arguments)};var _ScatterNd=Module["_ScatterNd"]=function(){return (_ScatterNd=Module["_ScatterNd"]=Module["asm"]["ga"]).apply(null,arguments)};var _SelectV2=Module["_SelectV2"]=function(){return (_SelectV2=Module["_SelectV2"]=Module["asm"]["ha"]).apply(null,arguments)};var _Sigmoid=Module["_Sigmoid"]=function(){return (_Sigmoid=Module["_Sigmoid"]=Module["asm"]["ia"]).apply(null,arguments)};var _Sin=Module["_Sin"]=function(){return (_Sin=Module["_Sin"]=Module["asm"]["ja"]).apply(null,arguments)};var _Softmax=Module["_Softmax"]=function(){return (_Softmax=Module["_Softmax"]=Module["asm"]["ka"]).apply(null,arguments)};var _Sqrt=Module["_Sqrt"]=function(){return (_Sqrt=Module["_Sqrt"]=Module["asm"]["la"]).apply(null,arguments)};var _Square=Module["_Square"]=function(){return (_Square=Module["_Square"]=Module["asm"]["ma"]).apply(null,arguments)};var _Sub=Module["_Sub"]=function(){return (_Sub=Module["_Sub"]=Module["asm"]["na"]).apply(null,arguments)};var _Sum=Module["_Sum"]=function(){return (_Sum=Module["_Sum"]=Module["asm"]["oa"]).apply(null,arguments)};var _Tanh=Module["_Tanh"]=function(){return (_Tanh=Module["_Tanh"]=Module["asm"]["pa"]).apply(null,arguments)};var _Tile=Module["_Tile"]=function(){return (_Tile=Module["_Tile"]=Module["asm"]["qa"]).apply(null,arguments)};var _Transpose=Module["_Transpose"]=function(){return (_Transpose=Module["_Transpose"]=Module["asm"]["ra"]).apply(null,arguments)};var __FusedMatMul=Module["__FusedMatMul"]=function(){return (__FusedMatMul=Module["__FusedMatMul"]=Module["asm"]["sa"]).apply(null,arguments)};var _malloc=Module["_malloc"]=function(){return (_malloc=Module["_malloc"]=Module["asm"]["ta"]).apply(null,arguments)};var _free=Module["_free"]=function(){return (_free=Module["_free"]=Module["asm"]["ua"]).apply(null,arguments)};var stackSave=Module["stackSave"]=function(){return (stackSave=Module["stackSave"]=Module["asm"]["va"]).apply(null,arguments)};var stackAlloc=Module["stackAlloc"]=function(){return (stackAlloc=Module["stackAlloc"]=Module["asm"]["wa"]).apply(null,arguments)};var stackRestore=Module["stackRestore"]=function(){return (stackRestore=Module["stackRestore"]=Module["asm"]["xa"]).apply(null,arguments)};var dynCall_vi=Module["dynCall_vi"]=function(){return (dynCall_vi=Module["dynCall_vi"]=Module["asm"]["ya"]).apply(null,arguments)};var dynCall_v=Module["dynCall_v"]=function(){return (dynCall_v=Module["dynCall_v"]=Module["asm"]["za"]).apply(null,arguments)};Module["asm"]=asm;Module["cwrap"]=cwrap;var calledRun;Module["then"]=function(func){if(calledRun){func(Module);}else{var old=Module["onRuntimeInitialized"];Module["onRuntimeInitialized"]=function(){if(old)old();func(Module);};}return Module};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();preMain();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()();}}noExitRuntime=true;run();
return WasmBackendModuleSimd
}
);
})();
module.exports = WasmBackendModuleSimd;
});
var tfjsBackendWasm = createCommonjsModule(function (module, exports) {
var WasmBackendModule = (function() {
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 moduleOverrides={};var key;for(key in Module){if(Module.hasOwnProperty(key)){moduleOverrides[key]=Module[key];}}var arguments_=[];var thisProgram="./this.program";var quit_=function(status,toThrow){throw toThrow};var ENVIRONMENT_IS_WEB=false;var ENVIRONMENT_IS_WORKER=false;var ENVIRONMENT_IS_NODE=false;var ENVIRONMENT_IS_SHELL=false;ENVIRONMENT_IS_WEB=typeof window==="object";ENVIRONMENT_IS_WORKER=typeof importScripts==="function";ENVIRONMENT_IS_NODE=typeof process==="object"&&typeof process.versions==="object"&&typeof process.versions.node==="string";ENVIRONMENT_IS_SHELL=!ENVIRONMENT_IS_WEB&&!ENVIRONMENT_IS_NODE&&!ENVIRONMENT_IS_WORKER;var scriptDirectory="";function locateFile(path){if(Module["locateFile"]){return Module["locateFile"](path,scriptDirectory)}return scriptDirectory+path}var read_,readBinary;var nodeFS;var nodePath;if(ENVIRONMENT_IS_NODE){if(ENVIRONMENT_IS_WORKER){scriptDirectory=path.dirname(scriptDirectory)+"/";}else{scriptDirectory=__dirname+"/";}read_=function shell_read(filename,binary){if(!nodeFS)nodeFS=fs;if(!nodePath)nodePath=path;filename=nodePath["normalize"](filename);return nodeFS["readFileSync"](filename,binary?null:"utf8")};readBinary=function readBinary(filename){var ret=read_(filename,true);if(!ret.buffer){ret=new Uint8Array(ret);}assert(ret.buffer);return ret};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",abort);quit_=function(status){process["exit"](status);};Module["inspect"]=function(){return "[Emscripten Module object]"};}else if(ENVIRONMENT_IS_SHELL){if(typeof read!="undefined"){read_=function shell_read(f){return read(f)};}readBinary=function readBinary(f){var data;if(typeof readbuffer==="function"){return new Uint8Array(readbuffer(f))}data=read(f,"binary");assert(typeof data==="object");return data};if(typeof scriptArgs!="undefined"){arguments_=scriptArgs;}else if(typeof arguments!="undefined"){arguments_=arguments;}if(typeof quit==="function"){quit_=function(status){quit(status);};}if(typeof print!=="undefined"){if(typeof console==="undefined")console={};console.log=print;console.warn=console.error=typeof printErr!=="undefined"?printErr:print;}}else if(ENVIRONMENT_IS_WEB||ENVIRONMENT_IS_WORKER){if(ENVIRONMENT_IS_WORKER){scriptDirectory=self.location.href;}else if(document.currentScript){scriptDirectory=document.currentScript.src;}if(_scriptDir){scriptDirectory=_scriptDir;}if(scriptDirectory.indexOf("blob:")!==0){scriptDirectory=scriptDirectory.substr(0,scriptDirectory.lastIndexOf("/")+1);}else{scriptDirectory="";}{read_=function shell_read(url){var xhr=new XMLHttpRequest;xhr.open("GET",url,false);xhr.send(null);return xhr.responseText};if(ENVIRONMENT_IS_WORKER){readBinary=function readBinary(url){var xhr=new XMLHttpRequest;xhr.open("GET",url,false);xhr.responseType="arraybuffer";xhr.send(null);return new Uint8Array(xhr.response)};}}}var out=Module["print"]||console.log.bind(console);var err=Module["printErr"]||console.warn.bind(console);for(key in moduleOverrides){if(moduleOverrides.hasOwnProperty(key)){Module[key]=moduleOverrides[key];}}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;if(Module["noExitRuntime"])noExitRuntime=Module["noExitRuntime"];if(typeof WebAssembly!=="object"){err("no native wasm support detected");}var wasmMemory;var wasmTable=new WebAssembly.Table({"initial":146,"maximum":146+0,"element":"anyfunc"});var ABORT=false;function assert(condition,text){if(!condition){abort("Assertion failed: "+text);}}function getCFunc(ident){var func=Module["_"+ident];assert(func,"Cannot call unknown function "+ident+", make sure it is exported");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);ret=convertReturnValue(ret);if(stack!==0)stackRestore(stack);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)}function writeArrayToMemory(array,buffer){HEAP8.set(array,buffer);}var WASM_PAGE_SIZE=65536;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 DYNAMIC_BASE=5254800,DYNAMICTOP_PTR=11760;var INITIAL_INITIAL_MEMORY=Module["INITIAL_MEMORY"]||16777216;if(Module["wasmMemory"]){wasmMemory=Module["wasmMemory"];}else{wasmMemory=new WebAssembly.Memory({"initial":INITIAL_INITIAL_MEMORY/WASM_PAGE_SIZE,"maximum":2147483648/WASM_PAGE_SIZE});}if(wasmMemory){buffer=wasmMemory.buffer;}INITIAL_INITIAL_MEMORY=buffer.byteLength;updateGlobalBufferAndViews(buffer);HEAP32[DYNAMICTOP_PTR>>2]=DYNAMIC_BASE;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){Module["dynCall_v"](func);}else{Module["dynCall_vi"](func,callback.arg);}}else{func(callback.arg===undefined?null:callback.arg);}}}var __ATPRERUN__=[];var __ATINIT__=[];var __ATMAIN__=[];var __ATPOSTRUN__=[];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 preMain(){callRuntimeCallbacks(__ATMAIN__);}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 addOnPostRun(cb){__ATPOSTRUN__.unshift(cb);}var Math_ceil=Math.ceil;var Math_floor=Math.floor;var runDependencies=0;var runDependencyWatcher=null;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(runDependencyWatcher!==null){clearInterval(runDependencyWatcher);runDependencyWatcher=null;}if(dependenciesFulfilled){var callback=dependenciesFulfilled;dependenciesFulfilled=null;callback();}}}Module["preloadedImages"]={};Module["preloadedAudios"]={};function abort(what){if(Module["onAbort"]){Module["onAbort"](what);}what+="";out(what);err(what);ABORT=true;what="abort("+what+"). Build with -s ASSERTIONS=1 for more info.";throw new WebAssembly.RuntimeError(what)}function hasPrefix(str,prefix){return String.prototype.startsWith?str.startsWith(prefix):str.indexOf(prefix)===0}var dataURIPrefix="data:application/octet-stream;base64,";function isDataURI(filename){return hasPrefix(filename,dataURIPrefix)}var fileURIPrefix="file://";function isFileURI(filename){return hasPrefix(filename,fileURIPrefix)}var wasmBinaryFile="tfjs-backend-wasm.wasm";if(!isDataURI(wasmBinaryFile)){wasmBinaryFile=locateFile(wasmBinaryFile);}function getBinary(){try{if(wasmBinary){return new Uint8Array(wasmBinary)}if(readBinary){return readBinary(wasmBinaryFile)}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)&&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()})}return new Promise(function(resolve,reject){resolve(getBinary());})}function createWasm(){var info={"a":asmLibraryArg};function receiveInstance(instance,module){var exports=instance.exports;Module["asm"]=exports;removeRunDependency();}addRunDependency();function receiveInstantiatedSource(output){receiveInstance(output["instance"]);}function instantiateArrayBuffer(receiver){return getBinaryPromise().then(function(binary){return WebAssembly.instantiate(binary,info)}).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"){fetch(wasmBinaryFile,{credentials:"same-origin"}).then(function(response){var result=WebAssembly.instantiateStreaming(response,info);return result.then(receiveInstantiatedSource,function(reason){err("wasm streaming compile failed: "+reason);err("falling back to ArrayBuffer instantiation");instantiateArrayBuffer(receiveInstantiatedSource);})});}else{return instantiateArrayBuffer(receiveInstantiatedSource)}}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();return {}}__ATINIT__.push({func:function(){___wasm_call_ctors();}});function _abort(){abort();}function _emscripten_memcpy_big(dest,src,num){HEAPU8.copyWithin(dest,src,src+num);}function _emscripten_get_heap_size(){return HEAPU8.length}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){requestedSize=requestedSize>>>0;var oldSize=_emscripten_get_heap_size();var PAGE_MULTIPLE=65536;var maxHeapSize=2147483648;if(requestedSize>maxHeapSize){return false}var minHeapSize=16777216;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(minHeapSize,requestedSize,overGrownHeapSize),PAGE_MULTIPLE));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+i*8>>2];var len=HEAP32[iov+(i*8+4)>>2];for(var j=0;j<len;j++){SYSCALLS.printChar(fd,HEAPU8[ptr+j]);}num+=len;}HEAP32[pnum>>2]=num;return 0}function _roundf(d){d=+d;return d>=+0?+Math_floor(d+ +.5):+Math_ceil(d-+.5)}var asmLibraryArg={"a":_abort,"e":_emscripten_memcpy_big,"f":_emscripten_resize_heap,"g":_fd_close,"d":_fd_seek,"c":_fd_write,"memory":wasmMemory,"b":_roundf,"table":wasmTable};var asm=createWasm();Module["asm"]=asm;var ___wasm_call_ctors=Module["___wasm_call_ctors"]=function(){return (___wasm_call_ctors=Module["___wasm_call_ctors"]=Module["asm"]["h"]).apply(null,arguments)};var _init=Module["_init"]=function(){return (_init=Module["_init"]=Module["asm"]["i"]).apply(null,arguments)};var _register_tensor=Module["_register_tensor"]=function(){return (_register_tensor=Module["_register_tensor"]=Module["asm"]["j"]).apply(null,arguments)};var _dispose_data=Module["_dispose_data"]=function(){return (_dispose_data=Module["_dispose_data"]=Module["asm"]["k"]).apply(null,arguments)};var _dispose=Module["_dispose"]=function(){return (_dispose=Module["_dispose"]=Module["asm"]["l"]).apply(null,arguments)};var _Abs=Module["_Abs"]=function(){return (_Abs=Module["_Abs"]=Module["asm"]["m"]).apply(null,arguments)};var _Add=Module["_Add"]=function(){return (_Add=Module["_Add"]=Module["asm"]["n"]).apply(null,arguments)};var _AddN=Module["_AddN"]=function(){return (_AddN=Module["_AddN"]=Module["asm"]["o"]).apply(null,arguments)};var _ArgMax=Module["_ArgMax"]=function(){return (_ArgMax=Module["_ArgMax"]=Module["asm"]["p"]).apply(null,arguments)};var _AvgPool=Module["_AvgPool"]=function(){return (_AvgPool=Module["_AvgPool"]=Module["asm"]["q"]).apply(null,arguments)};var _BatchMatMul=Module["_BatchMatMul"]=function(){return (_BatchMatMul=Module["_BatchMatMul"]=Module["asm"]["r"]).apply(null,arguments)};var _ClipByValue=Module["_ClipByValue"]=function(){return (_ClipByValue=Module["_ClipByValue"]=Module["asm"]["s"]).apply(null,arguments)};var _Conv2D=Module["_Conv2D"]=function(){return (_Conv2D=Module["_Conv2D"]=Module["asm"]["t"]).apply(null,arguments)};var _Conv2DBackpropInput=Module["_Conv2DBackpropInput"]=function(){return (_Conv2DBackpropInput=Module["_Conv2DBackpropInput"]=Module["asm"]["u"]).apply(null,arguments)};var _Cos=Module["_Cos"]=function(){return (_Cos=Module["_Cos"]=Module["asm"]["v"]).apply(null,arguments)};var _CropAndResize=Module["_CropAndResize"]=function(){return (_CropAndResize=Module["_CropAndResize"]=Module["asm"]["w"]).apply(null,arguments)};var _DepthwiseConv2dNative=Module["_DepthwiseConv2dNative"]=function(){return (_DepthwiseConv2dNative=Module["_DepthwiseConv2dNative"]=Module["asm"]["x"]).apply(null,arguments)};var _Div=Module["_Div"]=function(){return (_Div=Module["_Div"]=Module["asm"]["y"]).apply(null,arguments)};var _Equal=Module["_Equal"]=function(){return (_Equal=Module["_Equal"]=Module["asm"]["z"]).apply(null,arguments)};var _Exp=Module["_Exp"]=function(){return (_Exp=Module["_Exp"]=Module["asm"]["A"]).apply(null,arguments)};var _FloorDiv=Module["_FloorDiv"]=function(){return (_FloorDiv=Module["_FloorDiv"]=Module["asm"]["B"]).apply(null,arguments)};var _FusedBatchNorm=Module["_FusedBatchNorm"]=function(){return (_FusedBatchNorm=Module["_FusedBatchNorm"]=Module["asm"]["C"]).apply(null,arguments)};var _FusedConv2D=Module["_FusedConv2D"]=function(){return (_FusedConv2D=Module["_FusedConv2D"]=Module["asm"]["D"]).apply(null,arguments)};var _FusedDepthwiseConv2D=Module["_FusedDepthwiseConv2D"]=function(){return (_FusedDepthwiseConv2D=Module["_FusedDepthwiseConv2D"]=Module["asm"]["E"]).apply(null,arguments)};var _Gather=Module["_Gather"]=function(){return (_Gather=Module["_Gather"]=Module["asm"]["F"]).apply(null,arguments)};var _GatherNd=Module["_GatherNd"]=function(){return (_GatherNd=Module["_GatherNd"]=Module["asm"]["G"]).apply(null,arguments)};var _Greater=Module["_Greater"]=function(){return (_Greater=Module["_Greater"]=Module["asm"]["H"]).apply(null,arguments)};var _GreaterEqual=Module["_GreaterEqual"]=function(){return (_GreaterEqual=Module["_GreaterEqual"]=Module["asm"]["I"]).apply(null,arguments)};var _Less=Module["_Less"]=function(){return (_Less=Module["_Less"]=Module["asm"]["J"]).apply(null,arguments)};var _LessEqual=Module["_LessEqual"]=function(){return (_LessEqual=Module["_LessEqual"]=Module["asm"]["K"]).apply(null,arguments)};var _Log=Module["_Log"]=function(){return (_Log=Module["_Log"]=Module["asm"]["L"]).apply(null,arguments)};var _LogicalAnd=Module["_LogicalAnd"]=function(){return (_LogicalAnd=Module["_LogicalAnd"]=Module["asm"]["M"]).apply(null,arguments)};var _Max=Module["_Max"]=function(){return (_Max=Module["_Max"]=Module["asm"]["N"]).apply(null,arguments)};var _MaxPool=Module["_MaxPool"]=function(){return (_MaxPool=Module["_MaxPool"]=Module["asm"]["O"]).apply(null,arguments)};var _Maximum=Module["_Maximum"]=function(){return (_Maximum=Module["_Maximum"]=Module["asm"]["P"]).apply(null,arguments)};var _Min=Module["_Min"]=function(){return (_Min=Module["_Min"]=Module["asm"]["Q"]).apply(null,arguments)};var _Minimum=Module["_Minimum"]=function(){return (_Minimum=Module["_Minimum"]=Module["asm"]["R"]).apply(null,arguments)};var _Multiply=Module["_Multiply"]=function(){return (_Multiply=Module["_Multiply"]=Module["asm"]["S"]).apply(null,arguments)};var _Negate=Module["_Negate"]=function(){return (_Negate=Module["_Negate"]=Module["asm"]["T"]).apply(null,arguments)};var _NonMaxSuppressionV3=Module["_NonMaxSuppressionV3"]=function(){return (_NonMaxSuppressionV3=Module["_NonMaxSuppressionV3"]=Module["asm"]["U"]).apply(null,arguments)};var _NonMaxSuppressionV4=Module["_NonMaxSuppressionV4"]=function(){return (_NonMaxSuppressionV4=Module["_NonMaxSuppressionV4"]=Module["asm"]["V"]).apply(null,arguments)};var _NonMaxSuppressionV5=Module["_NonMaxSuppressionV5"]=function(){return (_NonMaxSuppressionV5=Module["_NonMaxSuppressionV5"]=Module["asm"]["W"]).apply(null,arguments)};var _NotEqual=Module["_NotEqual"]=function(){return (_NotEqual=Module["_NotEqual"]=Module["asm"]["X"]).apply(null,arguments)};var _OneHot=Module["_OneHot"]=function(){return (_OneHot=Module["_OneHot"]=Module["asm"]["Y"]).apply(null,arguments)};var _PadV2=Module["_PadV2"]=function(){return (_PadV2=Module["_PadV2"]=Module["asm"]["Z"]).apply(null,arguments)};var _Pow=Module["_Pow"]=function(){return (_Pow=Module["_Pow"]=Module["asm"]["_"]).apply(null,arguments)};var _Prelu=Module["_Prelu"]=function(){return (_Prelu=Module["_Prelu"]=Module["asm"]["$"]).apply(null,arguments)};var _Relu=Module["_Relu"]=function(){return (_Relu=Module["_Relu"]=Module["asm"]["aa"]).apply(null,arguments)};var _Relu6=Module["_Relu6"]=function(){return (_Relu6=Module["_Relu6"]=Module["asm"]["ba"]).apply(null,arguments)};var _ResizeBilinear=Module["_ResizeBilinear"]=function(){return (_ResizeBilinear=Module["_ResizeBilinear"]=Module["asm"]["ca"]).apply(null,arguments)};var _Reverse=Module["_Reverse"]=function(){return (_Reverse=Module["_Reverse"]=Module["asm"]["da"]).apply(null,arguments)};var _RotateWithOffset=Module["_RotateWithOffset"]=function(){return (_RotateWithOffset=Module["_RotateWithOffset"]=Module["asm"]["ea"]).apply(null,arguments)};var _Rsqrt=Module["_Rsqrt"]=function(){return (_Rsqrt=Module["_Rsqrt"]=Module["asm"]["fa"]).apply(null,arguments)};var _ScatterNd=Module["_ScatterNd"]=function(){return (_ScatterNd=Module["_ScatterNd"]=Module["asm"]["ga"]).apply(null,arguments)};var _SelectV2=Module["_SelectV2"]=function(){return (_SelectV2=Module["_SelectV2"]=Module["asm"]["ha"]).apply(null,arguments)};var _Sigmoid=Module["_Sigmoid"]=function(){return (_Sigmoid=Module["_Sigmoid"]=Module["asm"]["ia"]).apply(null,arguments)};var _Sin=Module["_Sin"]=function(){return (_Sin=Module["_Sin"]=Module["asm"]["ja"]).apply(null,arguments)};var _Softmax=Module["_Softmax"]=function(){return (_Softmax=Module["_Softmax"]=Module["asm"]["ka"]).apply(null,arguments)};var _Sqrt=Module["_Sqrt"]=function(){return (_Sqrt=Module["_Sqrt"]=Module["asm"]["la"]).apply(null,arguments)};var _Square=Module["_Square"]=function(){return (_Square=Module["_Square"]=Module["asm"]["ma"]).apply(null,arguments)};var _Sub=Module["_Sub"]=function(){return (_Sub=Module["_Sub"]=Module["asm"]["na"]).apply(null,arguments)};var _Sum=Module["_Sum"]=function(){return (_Sum=Module["_Sum"]=Module["asm"]["oa"]).apply(null,arguments)};var _Tanh=Module["_Tanh"]=function(){return (_Tanh=Module["_Tanh"]=Module["asm"]["pa"]).apply(null,arguments)};var _Tile=Module["_Tile"]=function(){return (_Tile=Module["_Tile"]=Module["asm"]["qa"]).apply(null,arguments)};var _Transpose=Module["_Transpose"]=function(){return (_Transpose=Module["_Transpose"]=Module["asm"]["ra"]).apply(null,arguments)};var __FusedMatMul=Module["__FusedMatMul"]=function(){return (__FusedMatMul=Module["__FusedMatMul"]=Module["asm"]["sa"]).apply(null,arguments)};var _malloc=Module["_malloc"]=function(){return (_malloc=Module["_malloc"]=Module["asm"]["ta"]).apply(null,arguments)};var _free=Module["_free"]=function(){return (_free=Module["_free"]=Module["asm"]["ua"]).apply(null,arguments)};var stackSave=Module["stackSave"]=function(){return (stackSave=Module["stackSave"]=Module["asm"]["va"]).apply(null,arguments)};var stackAlloc=Module["stackAlloc"]=function(){return (stackAlloc=Module["stackAlloc"]=Module["asm"]["wa"]).apply(null,arguments)};var stackRestore=Module["stackRestore"]=function(){return (stackRestore=Module["stackRestore"]=Module["asm"]["xa"]).apply(null,arguments)};var dynCall_vi=Module["dynCall_vi"]=function(){return (dynCall_vi=Module["dynCall_vi"]=Module["asm"]["ya"]).apply(null,arguments)};var dynCall_v=Module["dynCall_v"]=function(){return (dynCall_v=Module["dynCall_v"]=Module["asm"]["za"]).apply(null,arguments)};Module["asm"]=asm;Module["cwrap"]=cwrap;var calledRun;Module["then"]=function(func){if(calledRun){func(Module);}else{var old=Module["onRuntimeInitialized"];Module["onRuntimeInitialized"]=function(){if(old)old();func(Module);};}return Module};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();preMain();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()();}}noExitRuntime=true;run();
return WasmBackendModule
}
);
})();
module.exports = WasmBackendModule;
});
/**
* @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.
* =============================================================================
*/
const WASM_PRIORITY = 2;
class BackendWasm extends tfjsCore.KernelBackend {
constructor(wasm) {
super();
this.wasm = wasm;
// 0 is reserved for null data ids.
this.dataIdNextNumber = 1;
this.wasm.tfjs.init();
this.dataIdMap = new tfjsCore.DataStorage(this, tfjsCore.engine());
}
write(values, shape, dtype) {
const dataId = {};
this.move(dataId, values, shape, dtype);
return dataId;
}
numDataIds() {
return this.dataIdMap.numDataIds();
}
async time(f) {
const start = tfjsCore.util.now();
f();
const kernelMs = tfjsCore.util.now() - start;
return { kernelMs };
}
move(dataId, values, shape, dtype) {
const id = this.dataIdNextNumber++;
if (dtype === 'string') {
const stringBytes = values;
this.dataIdMap.set(dataId, { id, stringBytes, shape, dtype, memoryOffset: null });
return;
}
const size = tfjsCore.util.sizeFromShape(shape);
const numBytes = size * tfjsCore.util.bytesPerElement(dtype);
const memoryOffset = this.wasm._malloc(numBytes);
this.dataIdMap.set(dataId, { id, memoryOffset, shape, dtype });
this.wasm.tfjs.registerTensor(id, size, memoryOffset);
if (values != null) {
this.wasm.HEAPU8.set(new Uint8Array(values.buffer, values.byteOffset, numBytes), memoryOffset);
}
}
async read(dataId) {
return this.readSync(dataId);
}
readSync(dataId) {
const { memoryOffset, dtype, shape, stringBytes } = this.dataIdMap.get(dataId);
if (dtype === 'string') {
return stringBytes;
}
const bytes = this.wasm.HEAPU8.slice(memoryOffset, memoryOffset + tfjsCore.util.sizeFromShape(shape) * tfjsCore.util.bytesPerElement(dtype));
return typedArrayFromBuffer(bytes.buffer, dtype);
}
disposeData(dataId) {
const data = this.dataIdMap.get(dataId);
this.wasm._free(data.memoryOffset);
this.wasm.tfjs.disposeData(data.id);
this.dataIdMap.delete(dataId);
}
floatPrecision() {
return 32;
}
// Returns the memory offset of a tensor. Useful for debugging and unit
// testing.
getMemoryOffset(dataId) {
return this.dataIdMap.get(dataId).memoryOffset;
}
dispose() {
this.wasm.tfjs.dispose();
this.wasm = null;
}
memory() {
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.
*/
makeOutput(shape, dtype, memoryOffset) {
let dataId;
if (memoryOffset == null) {
dataId = this.write(null /* values */, shape, dtype);
}
else {
dataId = {};
const id = this.dataIdNextNumber++;
this.dataIdMap.set(dataId, { id, memoryOffset, shape, dtype });
const size = tfjsCore.util.sizeFromShape(shape);
this.wasm.tfjs.registerTensor(id, size, memoryOffset);
}
return { dataId, shape, dtype };
}
typedArrayFromHeap({ shape, dtype, dataId }) {
const buffer = this.wasm.HEAPU8.buffer;
const { memoryOffset } = this.dataIdMap.get(dataId);
const 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(`Uknown dtype ${dtype}`);
}
}
}
tfjsCore.registerBackend('wasm', async () => {
const { wasm } = await init();
return new BackendWasm(wasm);
}, WASM_PRIORITY);
function createInstantiateWasmFunc(path) {
// tslint:disable-next-line:no-any
return (imports, callback) => {
tfjsCore.util.fetch(path, { credentials: 'same-origin' }).then((response) => {
if (!response['ok']) {
imports.env.a(`failed to load wasm binary file at '${path}'`);
}
response.arrayBuffer().then(binary => {
WebAssembly.instantiate(binary, imports).then(output => {
callback(output.instance);
});
});
});
return {};
};
}
/**
* 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).
*/
async function init() {
const simdSupported = await tfjsCore.env().getAsync('WASM_HAS_SIMD_SUPPORT');
return new Promise((resolve, reject) => {
const factoryConfig = {};
if (wasmPath != null) {
factoryConfig.locateFile = (path, prefix) => {
if (path.endsWith('.wasm')) {
return wasmPath;
}
return prefix + path;
};
// use wasm instantiateWasm override when system fetch is not available.
// For detail references
// https://github.com/emscripten-core/emscripten/blob/2bca083cbbd5a4133db61fbd74d04f7feecfa907/tests/manual_wasm_instantiate.html#L170
if (customFetch) {
factoryConfig.instantiateWasm = createInstantiateWasmFunc(wasmPath);
}
}
const wasm = simdSupported ? tfjsBackendWasmSimd(factoryConfig) :
tfjsBackendWasm(factoryConfig);
const voidReturnType = null;
// Using the tfjs namespace to avoid conflict with emscripten's API.
wasm.tfjs = {
init: wasm.cwrap('init', null, []),
registerTensor: wasm.cwrap('register_tensor', null, [
'number',
'number',
'number',
]),
disposeData: wasm.cwrap('dispose_data', voidReturnType, ['number']),
dispose: wasm.cwrap('dispose', voidReturnType, []),
};
let initialized = false;
wasm.onRuntimeInitialized = () => {
initialized = true;
initAborted = false;
resolve({ wasm });
};
wasm.onAbort = () => {
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;
const 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 });
};
});
}
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}`);
}
}
let wasmPath = null;
let initAborted = false;
let customFetch = false;
/**
* 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 = false) {
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;
}
/** @license See the LICENSE file. */
// This code is auto-generated, do not modify this file!
const version = '2.1.0';
exports.BackendWasm = BackendWasm;
exports.setWasmPath = setWasmPath;
exports.version_wasm = version;
Object.defineProperty(exports, '__esModule', { value: true });
})));