tf-backend-wasm.js

/**
 * @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'), require('worker_threads'), require('perf_hooks')) :
    typeof define === 'function' && define.amd ? define(['exports', '@tensorflow/tfjs-core', 'path', 'fs', 'worker_threads', 'perf_hooks'], factory) :
    (global = global || self, factory((global.tf = global.tf || {}, global.tf.wasm = global.tf.wasm || {}), global.tf, global.path, global.fs, global.worker_threads, global.perf_hooks));
  }(this, (function (exports, tfjsCore, path, fs, worker_threads, perf_hooks) { 'use strict';
  
    path = path && path.hasOwnProperty('default') ? path['default'] : path;
    fs = fs && fs.hasOwnProperty('default') ? fs['default'] : fs;
    worker_threads = worker_threads && worker_threads.hasOwnProperty('default') ? worker_threads['default'] : worker_threads;
    perf_hooks = perf_hooks && perf_hooks.hasOwnProperty('default') ? perf_hooks['default'] : perf_hooks;
  
    /**
     * @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(
    // This typed array passed in to WebAssembly.validate is WebAssembly binary
    // code. In this case it is a small program that contains SIMD
    // instructions.
    'WASM_HAS_SIMD_SUPPORT', 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
    ])));
    /**
     * True if threads are supported.
     */
    // From: https://github.com/GoogleChromeLabs/wasm-feature-detect
    ENV.registerFlag('WASM_HAS_MULTITHREAD_SUPPORT', async () => {
        try {
            // Test for transferability of SABs (needed for Firefox)
            // https://groups.google.com/forum/#!msg/mozilla.dev.platform/IHkBZlHETpA/dwsMNchWEQAJ
            new MessageChannel().port1.postMessage(new SharedArrayBuffer(1));
            // This typed array is a WebAssembly program containing threaded
            // instructions.
            return WebAssembly.validate(new Uint8Array([
                0, 97, 115, 109, 1, 0, 0, 0, 1, 4, 1, 96, 0, 0, 3, 2, 1, 0, 5,
                4, 1, 3, 1, 1, 10, 11, 1, 9, 0, 65, 0, 254, 16, 2, 0, 26, 11
            ]));
        }
        catch (e) {
            return false;
        }
    });
  
    function createCommonjsModule(fn, module) {
        return module = { exports: {} }, fn(module, module.exports), module.exports;
    }
  
    var tfjsBackendWasmThreadedSimd = createCommonjsModule(function (module, exports) {
    var WasmBackendModuleThreadedSimd = (function() {
      var _scriptDir = typeof document !== 'undefined' && document.currentScript ? document.currentScript.src : undefined;
      if (typeof __filename !== 'undefined') _scriptDir = _scriptDir || __filename;
      return (
    function(WasmBackendModuleThreadedSimd) {
      WasmBackendModuleThreadedSimd = WasmBackendModuleThreadedSimd || {};
  
    function GROWABLE_HEAP_I8(){if(wasmMemory.buffer!=buffer){updateGlobalBufferAndViews(wasmMemory.buffer);}return HEAP8}function GROWABLE_HEAP_U8(){if(wasmMemory.buffer!=buffer){updateGlobalBufferAndViews(wasmMemory.buffer);}return HEAPU8}function GROWABLE_HEAP_I32(){if(wasmMemory.buffer!=buffer){updateGlobalBufferAndViews(wasmMemory.buffer);}return HEAP32}function GROWABLE_HEAP_U32(){if(wasmMemory.buffer!=buffer){updateGlobalBufferAndViews(wasmMemory.buffer);}return HEAPU32}function GROWABLE_HEAP_F64(){if(wasmMemory.buffer!=buffer){updateGlobalBufferAndViews(wasmMemory.buffer);}return HEAPF64}var Module=typeof WasmBackendModuleThreadedSimd!=="undefined"?WasmBackendModuleThreadedSimd:{};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 ENVIRONMENT_IS_PTHREAD=Module["ENVIRONMENT_IS_PTHREAD"]||false;if(ENVIRONMENT_IS_PTHREAD){buffer=Module["buffer"];DYNAMIC_BASE=Module["DYNAMIC_BASE"];DYNAMICTOP_PTR=Module["DYNAMICTOP_PTR"];}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]"};var nodeWorkerThreads;try{nodeWorkerThreads=worker_threads;}catch(e){console.error('The "worker_threads" module is not supported in this node.js build - perhaps a newer version is needed?');throw e}Worker=nodeWorkerThreads.Worker;}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="";}if(ENVIRONMENT_IS_NODE){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};}else{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)};}}}if(ENVIRONMENT_IS_NODE){if(typeof performance==="undefined"){performance=perf_hooks.performance;}}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":165,"maximum":165+0,"element":"anyfunc"});var wasmModule;var threadInfoStruct=0;var selfThreadId=0;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)}}function UTF8ArrayToString(heap,idx,maxBytesToRead){var endIdx=idx+maxBytesToRead;var str="";while(!(idx>=endIdx)){var u0=heap[idx++];if(!u0)return str;if(!(u0&128)){str+=String.fromCharCode(u0);continue}var u1=heap[idx++]&63;if((u0&224)==192){str+=String.fromCharCode((u0&31)<<6|u1);continue}var u2=heap[idx++]&63;if((u0&240)==224){u0=(u0&15)<<12|u1<<6|u2;}else{u0=(u0&7)<<18|u1<<12|u2<<6|heap[idx++]&63;}if(u0<65536){str+=String.fromCharCode(u0);}else{var ch=u0-65536;str+=String.fromCharCode(55296|ch>>10,56320|ch&1023);}}return str}function UTF8ToString(ptr,maxBytesToRead){return ptr?UTF8ArrayToString(GROWABLE_HEAP_U8(),ptr,maxBytesToRead):""}function stringToUTF8Array(str,heap,outIdx,maxBytesToWrite){if(!(maxBytesToWrite>0))return 0;var startIdx=outIdx;var endIdx=outIdx+maxBytesToWrite-1;for(var i=0;i<str.length;++i){var u=str.charCodeAt(i);if(u>=55296&&u<=57343){var u1=str.charCodeAt(++i);u=65536+((u&1023)<<10)|u1&1023;}if(u<=127){if(outIdx>=endIdx)break;heap[outIdx++]=u;}else if(u<=2047){if(outIdx+1>=endIdx)break;heap[outIdx++]=192|u>>6;heap[outIdx++]=128|u&63;}else if(u<=65535){if(outIdx+2>=endIdx)break;heap[outIdx++]=224|u>>12;heap[outIdx++]=128|u>>6&63;heap[outIdx++]=128|u&63;}else{if(outIdx+3>=endIdx)break;heap[outIdx++]=240|u>>18;heap[outIdx++]=128|u>>12&63;heap[outIdx++]=128|u>>6&63;heap[outIdx++]=128|u&63;}}heap[outIdx]=0;return outIdx-startIdx}function stringToUTF8(str,outPtr,maxBytesToWrite){return stringToUTF8Array(str,GROWABLE_HEAP_U8(),outPtr,maxBytesToWrite)}function lengthBytesUTF8(str){var len=0;for(var i=0;i<str.length;++i){var u=str.charCodeAt(i);if(u>=55296&&u<=57343)u=65536+((u&1023)<<10)|str.charCodeAt(++i)&1023;if(u<=127)++len;else if(u<=2047)len+=2;else if(u<=65535)len+=3;else len+=4;}return len}function writeArrayToMemory(array,buffer){GROWABLE_HEAP_I8().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=5256288,DYNAMICTOP_PTR=12480;var INITIAL_INITIAL_MEMORY=Module["INITIAL_MEMORY"]||16777216;if(ENVIRONMENT_IS_PTHREAD){wasmMemory=Module["wasmMemory"];buffer=Module["buffer"];}else{if(Module["wasmMemory"]){wasmMemory=Module["wasmMemory"];}else{wasmMemory=new WebAssembly.Memory({"initial":INITIAL_INITIAL_MEMORY/WASM_PAGE_SIZE,"maximum":2147483648/WASM_PAGE_SIZE,"shared":true});if(!(wasmMemory.buffer instanceof SharedArrayBuffer)){err("requested a shared WebAssembly.Memory but the returned buffer is not a SharedArrayBuffer, indicating that while the browser has SharedArrayBuffer it does not have WebAssembly threads support - you may need to set a flag");if(ENVIRONMENT_IS_NODE){console.log("(on node you may need: --experimental-wasm-threads --experimental-wasm-bulk-memory and also use a recent version)");}throw Error("bad memory")}}}if(wasmMemory){buffer=wasmMemory.buffer;}INITIAL_INITIAL_MEMORY=buffer.byteLength;updateGlobalBufferAndViews(buffer);if(!ENVIRONMENT_IS_PTHREAD){GROWABLE_HEAP_I32()[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(ENVIRONMENT_IS_PTHREAD)return;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(){if(ENVIRONMENT_IS_PTHREAD)return;callRuntimeCallbacks(__ATMAIN__);}function postRun(){if(ENVIRONMENT_IS_PTHREAD)return;if(Module["postRun"]){if(typeof Module["postRun"]=="function")Module["postRun"]=[Module["postRun"]];while(Module["postRun"].length){addOnPostRun(Module["postRun"].shift());}}callRuntimeCallbacks(__ATPOSTRUN__);}function addOnPreRun(cb){__ATPRERUN__.unshift(cb);}function 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){assert(!ENVIRONMENT_IS_PTHREAD,"addRunDependency cannot be used in a pthread worker");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);}if(ENVIRONMENT_IS_PTHREAD)console.error("Pthread aborting at "+(new Error).stack);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-threaded-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;wasmModule=module;if(!ENVIRONMENT_IS_PTHREAD){var numWorkersToLoad=PThread.unusedWorkers.length;PThread.unusedWorkers.forEach(function(w){PThread.loadWasmModuleToWorker(w,function(){if(!--numWorkersToLoad)removeRunDependency();});});}}if(!ENVIRONMENT_IS_PTHREAD){addRunDependency();}function receiveInstantiatedSource(output){receiveInstance(output["instance"],output["module"]);}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 {}}var ASM_CONSTS={};function initPthreadsJS(){PThread.initRuntime();}if(!ENVIRONMENT_IS_PTHREAD)__ATINIT__.push({func:function(){___wasm_call_ctors();}});var __pthread_ptr=0;var __pthread_is_main_runtime_thread=0;var __pthread_is_main_browser_thread=0;function __register_pthread_ptr(pthreadPtr,isMainBrowserThread,isMainRuntimeThread){pthreadPtr=pthreadPtr|0;isMainBrowserThread=isMainBrowserThread|0;isMainRuntimeThread=isMainRuntimeThread|0;__pthread_ptr=pthreadPtr;__pthread_is_main_browser_thread=isMainBrowserThread;__pthread_is_main_runtime_thread=isMainRuntimeThread;}Module["__register_pthread_ptr"]=__register_pthread_ptr;var ERRNO_CODES={EPERM:63,ENOENT:44,ESRCH:71,EINTR:27,EIO:29,ENXIO:60,E2BIG:1,ENOEXEC:45,EBADF:8,ECHILD:12,EAGAIN:6,EWOULDBLOCK:6,ENOMEM:48,EACCES:2,EFAULT:21,ENOTBLK:105,EBUSY:10,EEXIST:20,EXDEV:75,ENODEV:43,ENOTDIR:54,EISDIR:31,EINVAL:28,ENFILE:41,EMFILE:33,ENOTTY:59,ETXTBSY:74,EFBIG:22,ENOSPC:51,ESPIPE:70,EROFS:69,EMLINK:34,EPIPE:64,EDOM:18,ERANGE:68,ENOMSG:49,EIDRM:24,ECHRNG:106,EL2NSYNC:156,EL3HLT:107,EL3RST:108,ELNRNG:109,EUNATCH:110,ENOCSI:111,EL2HLT:112,EDEADLK:16,ENOLCK:46,EBADE:113,EBADR:114,EXFULL:115,ENOANO:104,EBADRQC:103,EBADSLT:102,EDEADLOCK:16,EBFONT:101,ENOSTR:100,ENODATA:116,ETIME:117,ENOSR:118,ENONET:119,ENOPKG:120,EREMOTE:121,ENOLINK:47,EADV:122,ESRMNT:123,ECOMM:124,EPROTO:65,EMULTIHOP:36,EDOTDOT:125,EBADMSG:9,ENOTUNIQ:126,EBADFD:127,EREMCHG:128,ELIBACC:129,ELIBBAD:130,ELIBSCN:131,ELIBMAX:132,ELIBEXEC:133,ENOSYS:52,ENOTEMPTY:55,ENAMETOOLONG:37,ELOOP:32,EOPNOTSUPP:138,EPFNOSUPPORT:139,ECONNRESET:15,ENOBUFS:42,EAFNOSUPPORT:5,EPROTOTYPE:67,ENOTSOCK:57,ENOPROTOOPT:50,ESHUTDOWN:140,ECONNREFUSED:14,EADDRINUSE:3,ECONNABORTED:13,ENETUNREACH:40,ENETDOWN:38,ETIMEDOUT:73,EHOSTDOWN:142,EHOSTUNREACH:23,EINPROGRESS:26,EALREADY:7,EDESTADDRREQ:17,EMSGSIZE:35,EPROTONOSUPPORT:66,ESOCKTNOSUPPORT:137,EADDRNOTAVAIL:4,ENETRESET:39,EISCONN:30,ENOTCONN:53,ETOOMANYREFS:141,EUSERS:136,EDQUOT:19,ESTALE:72,ENOTSUP:138,ENOMEDIUM:148,EILSEQ:25,EOVERFLOW:61,ECANCELED:11,ENOTRECOVERABLE:56,EOWNERDEAD:62,ESTRPIPE:135};var __main_thread_futex_wait_address=13392;function _emscripten_futex_wake(addr,count){if(addr<=0||addr>GROWABLE_HEAP_I8().length||addr&3!=0||count<0)return -28;if(count==0)return 0;if(count>=2147483647)count=Infinity;var mainThreadWaitAddress=Atomics.load(GROWABLE_HEAP_I32(),__main_thread_futex_wait_address>>2);var mainThreadWoken=0;if(mainThreadWaitAddress==addr){var loadedAddr=Atomics.compareExchange(GROWABLE_HEAP_I32(),__main_thread_futex_wait_address>>2,mainThreadWaitAddress,0);if(loadedAddr==mainThreadWaitAddress){--count;mainThreadWoken=1;if(count<=0)return 1}}var ret=Atomics.notify(GROWABLE_HEAP_I32(),addr>>2,count);if(ret>=0)return ret+mainThreadWoken;throw "Atomics.notify returned an unexpected value "+ret}Module["_emscripten_futex_wake"]=_emscripten_futex_wake;function __kill_thread(pthread_ptr){if(ENVIRONMENT_IS_PTHREAD)throw "Internal Error! _kill_thread() can only ever be called from main application thread!";if(!pthread_ptr)throw "Internal Error! Null pthread_ptr in _kill_thread!";GROWABLE_HEAP_I32()[pthread_ptr+12>>2]=0;var pthread=PThread.pthreads[pthread_ptr];pthread.worker.terminate();PThread.freeThreadData(pthread);PThread.runningWorkers.splice(PThread.runningWorkers.indexOf(pthread.worker),1);pthread.worker.pthread=undefined;}function __cancel_thread(pthread_ptr){if(ENVIRONMENT_IS_PTHREAD)throw "Internal Error! _cancel_thread() can only ever be called from main application thread!";if(!pthread_ptr)throw "Internal Error! Null pthread_ptr in _cancel_thread!";var pthread=PThread.pthreads[pthread_ptr];pthread.worker.postMessage({"cmd":"cancel"});}function __cleanup_thread(pthread_ptr){if(ENVIRONMENT_IS_PTHREAD)throw "Internal Error! _cleanup_thread() can only ever be called from main application thread!";if(!pthread_ptr)throw "Internal Error! Null pthread_ptr in _cleanup_thread!";GROWABLE_HEAP_I32()[pthread_ptr+12>>2]=0;var pthread=PThread.pthreads[pthread_ptr];if(pthread){var worker=pthread.worker;PThread.returnWorkerToPool(worker);}}var PThread={MAIN_THREAD_ID:1,mainThreadInfo:{schedPolicy:0,schedPrio:0},unusedWorkers:[],runningWorkers:[],initRuntime:function(){__register_pthread_ptr(PThread.mainThreadBlock,!ENVIRONMENT_IS_WORKER,1);_emscripten_register_main_browser_thread_id(PThread.mainThreadBlock);},initMainThreadBlock:function(){var pthreadPoolSize=8;for(var i=0;i<pthreadPoolSize;++i){PThread.allocateUnusedWorker();}PThread.mainThreadBlock=12640;for(var i=0;i<232/4;++i)GROWABLE_HEAP_U32()[PThread.mainThreadBlock/4+i]=0;GROWABLE_HEAP_I32()[PThread.mainThreadBlock+12>>2]=PThread.mainThreadBlock;var headPtr=PThread.mainThreadBlock+156;GROWABLE_HEAP_I32()[headPtr>>2]=headPtr;var tlsMemory=12880;for(var i=0;i<128;++i)GROWABLE_HEAP_U32()[tlsMemory/4+i]=0;Atomics.store(GROWABLE_HEAP_U32(),PThread.mainThreadBlock+104>>2,tlsMemory);Atomics.store(GROWABLE_HEAP_U32(),PThread.mainThreadBlock+40>>2,PThread.mainThreadBlock);Atomics.store(GROWABLE_HEAP_U32(),PThread.mainThreadBlock+44>>2,42);},initWorker:function(){},pthreads:{},exitHandlers:null,setThreadStatus:function(){},runExitHandlers:function(){if(PThread.exitHandlers!==null){while(PThread.exitHandlers.length>0){PThread.exitHandlers.pop()();}PThread.exitHandlers=null;}if(ENVIRONMENT_IS_PTHREAD&&threadInfoStruct)___pthread_tsd_run_dtors();},threadExit:function(exitCode){var tb=_pthread_self();if(tb){Atomics.store(GROWABLE_HEAP_U32(),tb+4>>2,exitCode);Atomics.store(GROWABLE_HEAP_U32(),tb+0>>2,1);Atomics.store(GROWABLE_HEAP_U32(),tb+60>>2,1);Atomics.store(GROWABLE_HEAP_U32(),tb+64>>2,0);PThread.runExitHandlers();_emscripten_futex_wake(tb+0,2147483647);__register_pthread_ptr(0,0,0);threadInfoStruct=0;if(ENVIRONMENT_IS_PTHREAD){postMessage({"cmd":"exit"});}}},threadCancel:function(){PThread.runExitHandlers();Atomics.store(GROWABLE_HEAP_U32(),threadInfoStruct+4>>2,-1);Atomics.store(GROWABLE_HEAP_U32(),threadInfoStruct+0>>2,1);_emscripten_futex_wake(threadInfoStruct+0,2147483647);threadInfoStruct=selfThreadId=0;__register_pthread_ptr(0,0,0);postMessage({"cmd":"cancelDone"});},terminateAllThreads:function(){for(var t in PThread.pthreads){var pthread=PThread.pthreads[t];if(pthread&&pthread.worker){PThread.returnWorkerToPool(pthread.worker);}}PThread.pthreads={};for(var i=0;i<PThread.unusedWorkers.length;++i){var worker=PThread.unusedWorkers[i];worker.terminate();}PThread.unusedWorkers=[];for(var i=0;i<PThread.runningWorkers.length;++i){var worker=PThread.runningWorkers[i];var pthread=worker.pthread;PThread.freeThreadData(pthread);worker.terminate();}PThread.runningWorkers=[];},freeThreadData:function(pthread){if(!pthread)return;if(pthread.threadInfoStruct){var tlsMemory=GROWABLE_HEAP_I32()[pthread.threadInfoStruct+104>>2];GROWABLE_HEAP_I32()[pthread.threadInfoStruct+104>>2]=0;_free(tlsMemory);_free(pthread.threadInfoStruct);}pthread.threadInfoStruct=0;if(pthread.allocatedOwnStack&&pthread.stackBase)_free(pthread.stackBase);pthread.stackBase=0;if(pthread.worker)pthread.worker.pthread=null;},returnWorkerToPool:function(worker){delete PThread.pthreads[worker.pthread.thread];PThread.unusedWorkers.push(worker);PThread.runningWorkers.splice(PThread.runningWorkers.indexOf(worker),1);PThread.freeThreadData(worker.pthread);worker.pthread=undefined;},receiveObjectTransfer:function(data){},loadWasmModuleToWorker:function(worker,onFinishedLoading){worker.onmessage=function(e){var d=e["data"];var cmd=d["cmd"];if(worker.pthread)PThread.currentProxiedOperationCallerThread=worker.pthread.threadInfoStruct;if(d["targetThread"]&&d["targetThread"]!=_pthread_self()){var thread=PThread.pthreads[d.targetThread];if(thread){thread.worker.postMessage(e.data,d["transferList"]);}else{console.error('Internal error! Worker sent a message "'+cmd+'" to target pthread '+d["targetThread"]+", but that thread no longer exists!");}PThread.currentProxiedOperationCallerThread=undefined;return}if(cmd==="processQueuedMainThreadWork"){_emscripten_main_thread_process_queued_calls();}else if(cmd==="spawnThread"){__spawn_thread(e.data);}else if(cmd==="cleanupThread"){__cleanup_thread(d["thread"]);}else if(cmd==="killThread"){__kill_thread(d["thread"]);}else if(cmd==="cancelThread"){__cancel_thread(d["thread"]);}else if(cmd==="loaded"){worker.loaded=true;if(onFinishedLoading)onFinishedLoading(worker);if(worker.runPthread){worker.runPthread();delete worker.runPthread;}}else if(cmd==="print"){out("Thread "+d["threadId"]+": "+d["text"]);}else if(cmd==="printErr"){err("Thread "+d["threadId"]+": "+d["text"]);}else if(cmd==="alert"){alert("Thread "+d["threadId"]+": "+d["text"]);}else if(cmd==="exit"){var detached=worker.pthread&&Atomics.load(GROWABLE_HEAP_U32(),worker.pthread.thread+68>>2);if(detached){PThread.returnWorkerToPool(worker);}}else if(cmd==="cancelDone"){PThread.returnWorkerToPool(worker);}else if(cmd==="objectTransfer"){PThread.receiveObjectTransfer(e.data);}else if(e.data.target==="setimmediate"){worker.postMessage(e.data);}else{err("worker sent an unknown command "+cmd);}PThread.currentProxiedOperationCallerThread=undefined;};worker.onerror=function(e){err("pthread sent an error! "+e.filename+":"+e.lineno+": "+e.message);};if(ENVIRONMENT_IS_NODE){worker.on("message",function(data){worker.onmessage({data:data});});worker.on("error",function(data){worker.onerror(data);});worker.on("exit",function(data){console.log("worker exited - TODO: update the worker queue?");});}worker.postMessage({"cmd":"load","urlOrBlob":Module["mainScriptUrlOrBlob"]||_scriptDir,"wasmMemory":wasmMemory,"wasmModule":wasmModule,"DYNAMIC_BASE":DYNAMIC_BASE,"DYNAMICTOP_PTR":DYNAMICTOP_PTR});},allocateUnusedWorker:function(){var pthreadMainJs=locateFile("tfjs-backend-wasm-threaded-simd.worker.js");PThread.unusedWorkers.push(new Worker(pthreadMainJs));},getNewWorker:function(){if(PThread.unusedWorkers.length==0){PThread.allocateUnusedWorker();PThread.loadWasmModuleToWorker(PThread.unusedWorkers[0]);}if(PThread.unusedWorkers.length>0)return PThread.unusedWorkers.pop();else return null},busySpinWait:function(msecs){var t=performance.now()+msecs;while(performance.now()<t){}}};function establishStackSpace(stackTop,stackMax){stackRestore(stackTop);}Module["establishStackSpace"]=establishStackSpace;function getNoExitRuntime(){return noExitRuntime}Module["getNoExitRuntime"]=getNoExitRuntime;function ___assert_fail(condition,filename,line,func){abort("Assertion failed: "+UTF8ToString(condition)+", at: "+[filename?UTF8ToString(filename):"unknown filename",line,func?UTF8ToString(func):"unknown function"]);}function ___call_main(argc,argv){var returnCode=_main(argc,argv);}var _emscripten_get_now;if(ENVIRONMENT_IS_NODE){_emscripten_get_now=function(){var t=process["hrtime"]();return t[0]*1e3+t[1]/1e6};}else if(ENVIRONMENT_IS_PTHREAD){_emscripten_get_now=function(){return performance.now()-Module["__performance_now_clock_drift"]};}else if(typeof dateNow!=="undefined"){_emscripten_get_now=dateNow;}else _emscripten_get_now=function(){return performance.now()};function setErrNo(value){GROWABLE_HEAP_I32()[___errno_location()>>2]=value;return value}function _atexit(func,arg){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(1,1,func,arg);}function __emscripten_notify_thread_queue(targetThreadId,mainThreadId){if(targetThreadId==mainThreadId){postMessage({"cmd":"processQueuedMainThreadWork"});}else if(ENVIRONMENT_IS_PTHREAD){postMessage({"targetThread":targetThreadId,"cmd":"processThreadQueue"});}else{var pthread=PThread.pthreads[targetThreadId];var worker=pthread&&pthread.worker;if(!worker){return}worker.postMessage({"cmd":"processThreadQueue"});}return 1}function _abort(){abort();}function _emscripten_conditional_set_current_thread_status(expectedStatus,newStatus){}function _emscripten_futex_wait(addr,val,timeout){if(addr<=0||addr>GROWABLE_HEAP_I8().length||addr&3!=0)return -28;if(ENVIRONMENT_IS_WORKER){var ret=Atomics.wait(GROWABLE_HEAP_I32(),addr>>2,val,timeout);if(ret==="timed-out")return -73;if(ret==="not-equal")return -6;if(ret==="ok")return 0;throw "Atomics.wait returned an unexpected value "+ret}else{var loadedVal=Atomics.load(GROWABLE_HEAP_I32(),addr>>2);if(val!=loadedVal)return -6;var tNow=performance.now();var tEnd=tNow+timeout;Atomics.store(GROWABLE_HEAP_I32(),__main_thread_futex_wait_address>>2,addr);var ourWaitAddress=addr;while(addr==ourWaitAddress){tNow=performance.now();if(tNow>tEnd){return -73}_emscripten_main_thread_process_queued_calls();addr=Atomics.load(GROWABLE_HEAP_I32(),__main_thread_futex_wait_address>>2);}return 0}}function _emscripten_is_main_browser_thread(){return __pthread_is_main_browser_thread|0}function _emscripten_is_main_runtime_thread(){return __pthread_is_main_runtime_thread|0}function _emscripten_memcpy_big(dest,src,num){GROWABLE_HEAP_U8().copyWithin(dest,src,src+num);}function _emscripten_num_logical_cores(){return navigator["hardwareConcurrency"]}function _emscripten_proxy_to_main_thread_js(index,sync){var numCallArgs=arguments.length-2;var stack=stackSave();var args=stackAlloc(numCallArgs*8);var b=args>>3;for(var i=0;i<numCallArgs;i++){GROWABLE_HEAP_F64()[b+i]=arguments[2+i];}var ret=_emscripten_run_in_main_runtime_thread_js(index,numCallArgs,args,sync);stackRestore(stack);return ret}var _emscripten_receive_on_main_thread_js_callArgs=[];function readAsmConstArgs(sigPtr,buf){if(!readAsmConstArgs.array){readAsmConstArgs.array=[];}var args=readAsmConstArgs.array;args.length=0;var ch;while(ch=GROWABLE_HEAP_U8()[sigPtr++]){if(ch===100||ch===102){buf=buf+7&~7;args.push(GROWABLE_HEAP_F64()[buf>>3]);buf+=8;}else{buf=buf+3&~3;args.push(GROWABLE_HEAP_I32()[buf>>2]);buf+=4;}}return args}function _emscripten_receive_on_main_thread_js(index,numCallArgs,args){_emscripten_receive_on_main_thread_js_callArgs.length=numCallArgs;var b=args>>3;for(var i=0;i<numCallArgs;i++){_emscripten_receive_on_main_thread_js_callArgs[i]=GROWABLE_HEAP_F64()[b+i];}var isEmAsmConst=index<0;var func=!isEmAsmConst?proxiedFunctionTable[index]:ASM_CONSTS[-index-1];if(isEmAsmConst){var sigPtr=_emscripten_receive_on_main_thread_js_callArgs[1];var varargPtr=_emscripten_receive_on_main_thread_js_callArgs[2];var constArgs=readAsmConstArgs(sigPtr,varargPtr);return func.apply(null,constArgs)}return func.apply(null,_emscripten_receive_on_main_thread_js_callArgs)}function _emscripten_get_heap_size(){return GROWABLE_HEAP_U8().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();if(requestedSize<=oldSize){return false}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 JSEvents={keyEvent:0,mouseEvent:0,wheelEvent:0,uiEvent:0,focusEvent:0,deviceOrientationEvent:0,deviceMotionEvent:0,fullscreenChangeEvent:0,pointerlockChangeEvent:0,visibilityChangeEvent:0,touchEvent:0,previousFullscreenElement:null,previousScreenX:null,previousScreenY:null,removeEventListenersRegistered:false,removeAllEventListeners:function(){for(var i=JSEvents.eventHandlers.length-1;i>=0;--i){JSEvents._removeHandler(i);}JSEvents.eventHandlers=[];JSEvents.deferredCalls=[];},registerRemoveEventListeners:function(){if(!JSEvents.removeEventListenersRegistered){JSEvents.removeEventListenersRegistered=true;}},deferredCalls:[],deferCall:function(targetFunction,precedence,argsList){function arraysHaveEqualContent(arrA,arrB){if(arrA.length!=arrB.length)return false;for(var i in arrA){if(arrA[i]!=arrB[i])return false}return true}for(var i in JSEvents.deferredCalls){var call=JSEvents.deferredCalls[i];if(call.targetFunction==targetFunction&&arraysHaveEqualContent(call.argsList,argsList)){return}}JSEvents.deferredCalls.push({targetFunction:targetFunction,precedence:precedence,argsList:argsList});JSEvents.deferredCalls.sort(function(x,y){return x.precedence<y.precedence});},removeDeferredCalls:function(targetFunction){for(var i=0;i<JSEvents.deferredCalls.length;++i){if(JSEvents.deferredCalls[i].targetFunction==targetFunction){JSEvents.deferredCalls.splice(i,1);--i;}}},canPerformEventHandlerRequests:function(){return JSEvents.inEventHandler&&JSEvents.currentEventHandler.allowsDeferredCalls},runDeferredCalls:function(){if(!JSEvents.canPerformEventHandlerRequests()){return}for(var i=0;i<JSEvents.deferredCalls.length;++i){var call=JSEvents.deferredCalls[i];JSEvents.deferredCalls.splice(i,1);--i;call.targetFunction.apply(null,call.argsList);}},inEventHandler:0,currentEventHandler:null,eventHandlers:[],removeAllHandlersOnTarget:function(target,eventTypeString){for(var i=0;i<JSEvents.eventHandlers.length;++i){if(JSEvents.eventHandlers[i].target==target&&(!eventTypeString||eventTypeString==JSEvents.eventHandlers[i].eventTypeString)){JSEvents._removeHandler(i--);}}},_removeHandler:function(i){var h=JSEvents.eventHandlers[i];h.target.removeEventListener(h.eventTypeString,h.eventListenerFunc,h.useCapture);JSEvents.eventHandlers.splice(i,1);},registerOrRemoveHandler:function(eventHandler){var jsEventHandler=function jsEventHandler(event){++JSEvents.inEventHandler;JSEvents.currentEventHandler=eventHandler;JSEvents.runDeferredCalls();eventHandler.handlerFunc(event);JSEvents.runDeferredCalls();--JSEvents.inEventHandler;};if(eventHandler.callbackfunc){eventHandler.eventListenerFunc=jsEventHandler;eventHandler.target.addEventListener(eventHandler.eventTypeString,jsEventHandler,eventHandler.useCapture);JSEvents.eventHandlers.push(eventHandler);JSEvents.registerRemoveEventListeners();}else{for(var i=0;i<JSEvents.eventHandlers.length;++i){if(JSEvents.eventHandlers[i].target==eventHandler.target&&JSEvents.eventHandlers[i].eventTypeString==eventHandler.eventTypeString){JSEvents._removeHandler(i--);}}}},queueEventHandlerOnThread_iiii:function(targetThread,eventHandlerFunc,eventTypeId,eventData,userData){var stackTop=stackSave();var varargs=stackAlloc(12);GROWABLE_HEAP_I32()[varargs>>2]=eventTypeId;GROWABLE_HEAP_I32()[varargs+4>>2]=eventData;GROWABLE_HEAP_I32()[varargs+8>>2]=userData;_emscripten_async_queue_on_thread_(targetThread,637534208,eventHandlerFunc,eventData,varargs);stackRestore(stackTop);},getTargetThreadForEventCallback:function(targetThread){switch(targetThread){case 1:return 0;case 2:return PThread.currentProxiedOperationCallerThread;default:return targetThread}},getNodeNameForTarget:function(target){if(!target)return "";if(target==window)return "#window";if(target==screen)return "#screen";return target&&target.nodeName?target.nodeName:""},fullscreenEnabled:function(){return document.fullscreenEnabled||document.webkitFullscreenEnabled}};function stringToNewUTF8(jsString){var length=lengthBytesUTF8(jsString)+1;var cString=_malloc(length);stringToUTF8(jsString,cString,length);return cString}function _emscripten_set_offscreencanvas_size_on_target_thread_js(targetThread,targetCanvas,width,height){var stackTop=stackSave();var varargs=stackAlloc(12);var targetCanvasPtr=0;if(targetCanvas){targetCanvasPtr=stringToNewUTF8(targetCanvas);}GROWABLE_HEAP_I32()[varargs>>2]=targetCanvasPtr;GROWABLE_HEAP_I32()[varargs+4>>2]=width;GROWABLE_HEAP_I32()[varargs+8>>2]=height;_emscripten_async_queue_on_thread_(targetThread,657457152,0,targetCanvasPtr,varargs);stackRestore(stackTop);}function _emscripten_set_offscreencanvas_size_on_target_thread(targetThread,targetCanvas,width,height){targetCanvas=targetCanvas?UTF8ToString(targetCanvas):"";_emscripten_set_offscreencanvas_size_on_target_thread_js(targetThread,targetCanvas,width,height);}function __maybeCStringToJsString(cString){return cString>2?UTF8ToString(cString):cString}var specialHTMLTargets=[0,typeof document!=="undefined"?document:0,typeof window!=="undefined"?window:0];function __findEventTarget(target){target=__maybeCStringToJsString(target);var domElement=specialHTMLTargets[target]||(typeof document!=="undefined"?document.querySelector(target):undefined);return domElement}function __findCanvasEventTarget(target){return __findEventTarget(target)}function _emscripten_set_canvas_element_size_calling_thread(target,width,height){var canvas=__findCanvasEventTarget(target);if(!canvas)return -4;if(canvas.canvasSharedPtr){GROWABLE_HEAP_I32()[canvas.canvasSharedPtr>>2]=width;GROWABLE_HEAP_I32()[canvas.canvasSharedPtr+4>>2]=height;}if(canvas.offscreenCanvas||!canvas.controlTransferredOffscreen){if(canvas.offscreenCanvas)canvas=canvas.offscreenCanvas;var autoResizeViewport=false;if(canvas.GLctxObject&&canvas.GLctxObject.GLctx){var prevViewport=canvas.GLctxObject.GLctx.getParameter(2978);autoResizeViewport=prevViewport[0]===0&&prevViewport[1]===0&&prevViewport[2]===canvas.width&&prevViewport[3]===canvas.height;}canvas.width=width;canvas.height=height;if(autoResizeViewport){canvas.GLctxObject.GLctx.viewport(0,0,width,height);}}else if(canvas.canvasSharedPtr){var targetThread=GROWABLE_HEAP_I32()[canvas.canvasSharedPtr+8>>2];_emscripten_set_offscreencanvas_size_on_target_thread(targetThread,target,width,height);return 1}else{return -4}return 0}function _emscripten_set_canvas_element_size_main_thread(target,width,height){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(2,1,target,width,height);return _emscripten_set_canvas_element_size_calling_thread(target,width,height)}function _emscripten_set_canvas_element_size(target,width,height){var canvas=__findCanvasEventTarget(target);if(canvas){return _emscripten_set_canvas_element_size_calling_thread(target,width,height)}else{return _emscripten_set_canvas_element_size_main_thread(target,width,height)}}function _emscripten_set_current_thread_status(newStatus){}function _emscripten_set_thread_name(threadId,name){}function __webgl_enable_ANGLE_instanced_arrays(ctx){var ext=ctx.getExtension("ANGLE_instanced_arrays");if(ext){ctx["vertexAttribDivisor"]=function(index,divisor){ext["vertexAttribDivisorANGLE"](index,divisor);};ctx["drawArraysInstanced"]=function(mode,first,count,primcount){ext["drawArraysInstancedANGLE"](mode,first,count,primcount);};ctx["drawElementsInstanced"]=function(mode,count,type,indices,primcount){ext["drawElementsInstancedANGLE"](mode,count,type,indices,primcount);};return 1}}function __webgl_enable_OES_vertex_array_object(ctx){var ext=ctx.getExtension("OES_vertex_array_object");if(ext){ctx["createVertexArray"]=function(){return ext["createVertexArrayOES"]()};ctx["deleteVertexArray"]=function(vao){ext["deleteVertexArrayOES"](vao);};ctx["bindVertexArray"]=function(vao){ext["bindVertexArrayOES"](vao);};ctx["isVertexArray"]=function(vao){return ext["isVertexArrayOES"](vao)};return 1}}function __webgl_enable_WEBGL_draw_buffers(ctx){var ext=ctx.getExtension("WEBGL_draw_buffers");if(ext){ctx["drawBuffers"]=function(n,bufs){ext["drawBuffersWEBGL"](n,bufs);};return 1}}var GL={counter:1,lastError:0,buffers:[],mappedBuffers:{},programs:[],framebuffers:[],renderbuffers:[],textures:[],uniforms:[],shaders:[],vaos:[],contexts:{},currentContext:null,offscreenCanvases:{},timerQueriesEXT:[],programInfos:{},stringCache:{},unpackAlignment:4,init:function(){var miniTempFloatBuffer=new Float32Array(GL.MINI_TEMP_BUFFER_SIZE);for(var i=0;i<GL.MINI_TEMP_BUFFER_SIZE;i++){GL.miniTempBufferFloatViews[i]=miniTempFloatBuffer.subarray(0,i+1);}var miniTempIntBuffer=new Int32Array(GL.MINI_TEMP_BUFFER_SIZE);for(var i=0;i<GL.MINI_TEMP_BUFFER_SIZE;i++){GL.miniTempBufferIntViews[i]=miniTempIntBuffer.subarray(0,i+1);}},recordError:function recordError(errorCode){if(!GL.lastError){GL.lastError=errorCode;}},getNewId:function(table){var ret=GL.counter++;for(var i=table.length;i<ret;i++){table[i]=null;}return ret},MINI_TEMP_BUFFER_SIZE:256,miniTempBufferFloatViews:[0],miniTempBufferIntViews:[0],getSource:function(shader,count,string,length){var source="";for(var i=0;i<count;++i){var len=length?GROWABLE_HEAP_I32()[length+i*4>>2]:-1;source+=UTF8ToString(GROWABLE_HEAP_I32()[string+i*4>>2],len<0?undefined:len);}return source},createContext:function(canvas,webGLContextAttributes){var ctx=canvas.getContext("webgl",webGLContextAttributes);if(!ctx)return 0;var handle=GL.registerContext(ctx,webGLContextAttributes);return handle},registerContext:function(ctx,webGLContextAttributes){var handle=_malloc(8);GROWABLE_HEAP_I32()[handle+4>>2]=_pthread_self();var context={handle:handle,attributes:webGLContextAttributes,version:webGLContextAttributes.majorVersion,GLctx:ctx};if(ctx.canvas)ctx.canvas.GLctxObject=context;GL.contexts[handle]=context;if(typeof webGLContextAttributes.enableExtensionsByDefault==="undefined"||webGLContextAttributes.enableExtensionsByDefault){GL.initExtensions(context);}return handle},makeContextCurrent:function(contextHandle){GL.currentContext=GL.contexts[contextHandle];Module.ctx=GLctx=GL.currentContext&&GL.currentContext.GLctx;return !(contextHandle&&!GLctx)},getContext:function(contextHandle){return GL.contexts[contextHandle]},deleteContext:function(contextHandle){if(GL.currentContext===GL.contexts[contextHandle])GL.currentContext=null;if(typeof JSEvents==="object")JSEvents.removeAllHandlersOnTarget(GL.contexts[contextHandle].GLctx.canvas);if(GL.contexts[contextHandle]&&GL.contexts[contextHandle].GLctx.canvas)GL.contexts[contextHandle].GLctx.canvas.GLctxObject=undefined;_free(GL.contexts[contextHandle].handle);GL.contexts[contextHandle]=null;},initExtensions:function(context){if(!context)context=GL.currentContext;if(context.initExtensionsDone)return;context.initExtensionsDone=true;var GLctx=context.GLctx;__webgl_enable_ANGLE_instanced_arrays(GLctx);__webgl_enable_OES_vertex_array_object(GLctx);__webgl_enable_WEBGL_draw_buffers(GLctx);GLctx.disjointTimerQueryExt=GLctx.getExtension("EXT_disjoint_timer_query");var automaticallyEnabledExtensions=["OES_texture_float","OES_texture_half_float","OES_standard_derivatives","OES_vertex_array_object","WEBGL_compressed_texture_s3tc","WEBGL_depth_texture","OES_element_index_uint","EXT_texture_filter_anisotropic","EXT_frag_depth","WEBGL_draw_buffers","ANGLE_instanced_arrays","OES_texture_float_linear","OES_texture_half_float_linear","EXT_blend_minmax","EXT_shader_texture_lod","EXT_texture_norm16","WEBGL_compressed_texture_pvrtc","EXT_color_buffer_half_float","WEBGL_color_buffer_float","EXT_sRGB","WEBGL_compressed_texture_etc1","EXT_disjoint_timer_query","WEBGL_compressed_texture_etc","WEBGL_compressed_texture_astc","EXT_color_buffer_float","WEBGL_compressed_texture_s3tc_srgb","EXT_disjoint_timer_query_webgl2","WEBKIT_WEBGL_compressed_texture_pvrtc"];var exts=GLctx.getSupportedExtensions()||[];exts.forEach(function(ext){if(automaticallyEnabledExtensions.indexOf(ext)!=-1){GLctx.getExtension(ext);}});},populateUniformTable:function(program){var p=GL.programs[program];var ptable=GL.programInfos[program]={uniforms:{},maxUniformLength:0,maxAttributeLength:-1,maxUniformBlockNameLength:-1};var utable=ptable.uniforms;var numUniforms=GLctx.getProgramParameter(p,35718);for(var i=0;i<numUniforms;++i){var u=GLctx.getActiveUniform(p,i);var name=u.name;ptable.maxUniformLength=Math.max(ptable.maxUniformLength,name.length+1);if(name.slice(-1)=="]"){name=name.slice(0,name.lastIndexOf("["));}var loc=GLctx.getUniformLocation(p,name);if(loc){var id=GL.getNewId(GL.uniforms);utable[name]=[u.size,id];GL.uniforms[id]=loc;for(var j=1;j<u.size;++j){var n=name+"["+j+"]";loc=GLctx.getUniformLocation(p,n);id=GL.getNewId(GL.uniforms);GL.uniforms[id]=loc;}}}}};var __emscripten_webgl_power_preferences=["default","low-power","high-performance"];function _emscripten_webgl_do_create_context(target,attributes){var contextAttributes={};var a=attributes>>2;contextAttributes["alpha"]=!!GROWABLE_HEAP_I32()[a+(0>>2)];contextAttributes["depth"]=!!GROWABLE_HEAP_I32()[a+(4>>2)];contextAttributes["stencil"]=!!GROWABLE_HEAP_I32()[a+(8>>2)];contextAttributes["antialias"]=!!GROWABLE_HEAP_I32()[a+(12>>2)];contextAttributes["premultipliedAlpha"]=!!GROWABLE_HEAP_I32()[a+(16>>2)];contextAttributes["preserveDrawingBuffer"]=!!GROWABLE_HEAP_I32()[a+(20>>2)];var powerPreference=GROWABLE_HEAP_I32()[a+(24>>2)];contextAttributes["powerPreference"]=__emscripten_webgl_power_preferences[powerPreference];contextAttributes["failIfMajorPerformanceCaveat"]=!!GROWABLE_HEAP_I32()[a+(28>>2)];contextAttributes.majorVersion=GROWABLE_HEAP_I32()[a+(32>>2)];contextAttributes.minorVersion=GROWABLE_HEAP_I32()[a+(36>>2)];contextAttributes.enableExtensionsByDefault=GROWABLE_HEAP_I32()[a+(40>>2)];contextAttributes.explicitSwapControl=GROWABLE_HEAP_I32()[a+(44>>2)];contextAttributes.proxyContextToMainThread=GROWABLE_HEAP_I32()[a+(48>>2)];contextAttributes.renderViaOffscreenBackBuffer=GROWABLE_HEAP_I32()[a+(52>>2)];var canvas=__findCanvasEventTarget(target);if(!canvas){return -4}if(contextAttributes.explicitSwapControl){return -1}var contextHandle=GL.createContext(canvas,contextAttributes);return contextHandle}function _emscripten_webgl_create_context(a0,a1){return _emscripten_webgl_do_create_context(a0,a1)}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=GROWABLE_HEAP_I32()[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){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(3,1,fd);return 0}function _fd_seek(fd,offset_low,offset_high,whence,newOffset){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(4,1,fd,offset_low,offset_high,whence,newOffset)}function _fd_write(fd,iov,iovcnt,pnum){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(5,1,fd,iov,iovcnt,pnum);var num=0;for(var i=0;i<iovcnt;i++){var ptr=GROWABLE_HEAP_I32()[iov+i*8>>2];var len=GROWABLE_HEAP_I32()[iov+(i*8+4)>>2];for(var j=0;j<len;j++){SYSCALLS.printChar(fd,GROWABLE_HEAP_U8()[ptr+j]);}num+=len;}GROWABLE_HEAP_I32()[pnum>>2]=num;return 0}function _pthread_cleanup_pop(execute){var routine=PThread.exitHandlers.pop();if(execute)routine();}function _pthread_cleanup_push(routine,arg){if(PThread.exitHandlers===null){PThread.exitHandlers=[];}PThread.exitHandlers.push(function(){dynCall_vi(routine,arg);});}function __spawn_thread(threadParams){if(ENVIRONMENT_IS_PTHREAD)throw "Internal Error! _spawn_thread() can only ever be called from main application thread!";var worker=PThread.getNewWorker();if(worker.pthread!==undefined)throw "Internal error!";if(!threadParams.pthread_ptr)throw "Internal error, no pthread ptr!";PThread.runningWorkers.push(worker);var tlsMemory=_malloc(128*4);for(var i=0;i<128;++i){GROWABLE_HEAP_I32()[tlsMemory+i*4>>2]=0;}var stackHigh=threadParams.stackBase+threadParams.stackSize;var pthread=PThread.pthreads[threadParams.pthread_ptr]={worker:worker,stackBase:threadParams.stackBase,stackSize:threadParams.stackSize,allocatedOwnStack:threadParams.allocatedOwnStack,thread:threadParams.pthread_ptr,threadInfoStruct:threadParams.pthread_ptr};var tis=pthread.threadInfoStruct>>2;Atomics.store(GROWABLE_HEAP_U32(),tis+(0>>2),0);Atomics.store(GROWABLE_HEAP_U32(),tis+(4>>2),0);Atomics.store(GROWABLE_HEAP_U32(),tis+(8>>2),0);Atomics.store(GROWABLE_HEAP_U32(),tis+(68>>2),threadParams.detached);Atomics.store(GROWABLE_HEAP_U32(),tis+(104>>2),tlsMemory);Atomics.store(GROWABLE_HEAP_U32(),tis+(48>>2),0);Atomics.store(GROWABLE_HEAP_U32(),tis+(40>>2),pthread.threadInfoStruct);Atomics.store(GROWABLE_HEAP_U32(),tis+(44>>2),42);Atomics.store(GROWABLE_HEAP_U32(),tis+(108>>2),threadParams.stackSize);Atomics.store(GROWABLE_HEAP_U32(),tis+(84>>2),threadParams.stackSize);Atomics.store(GROWABLE_HEAP_U32(),tis+(80>>2),stackHigh);Atomics.store(GROWABLE_HEAP_U32(),tis+(108+8>>2),stackHigh);Atomics.store(GROWABLE_HEAP_U32(),tis+(108+12>>2),threadParams.detached);Atomics.store(GROWABLE_HEAP_U32(),tis+(108+20>>2),threadParams.schedPolicy);Atomics.store(GROWABLE_HEAP_U32(),tis+(108+24>>2),threadParams.schedPrio);var global_libc=_emscripten_get_global_libc();var global_locale=global_libc+40;Atomics.store(GROWABLE_HEAP_U32(),tis+(176>>2),global_locale);worker.pthread=pthread;var msg={"cmd":"run","start_routine":threadParams.startRoutine,"arg":threadParams.arg,"threadInfoStruct":threadParams.pthread_ptr,"selfThreadId":threadParams.pthread_ptr,"parentThreadId":threadParams.parent_pthread_ptr,"stackBase":threadParams.stackBase,"stackSize":threadParams.stackSize};worker.runPthread=function(){msg.time=performance.now();worker.postMessage(msg,threadParams.transferList);};if(worker.loaded){worker.runPthread();delete worker.runPthread;}}function _pthread_getschedparam(thread,policy,schedparam){if(!policy&&!schedparam)return ERRNO_CODES.EINVAL;if(!thread){err("pthread_getschedparam called with a null thread pointer!");return ERRNO_CODES.ESRCH}var self=GROWABLE_HEAP_I32()[thread+12>>2];if(self!==thread){err("pthread_getschedparam attempted on thread "+thread+", which does not point to a valid thread, or does not exist anymore!");return ERRNO_CODES.ESRCH}var schedPolicy=Atomics.load(GROWABLE_HEAP_U32(),thread+108+20>>2);var schedPrio=Atomics.load(GROWABLE_HEAP_U32(),thread+108+24>>2);if(policy)GROWABLE_HEAP_I32()[policy>>2]=schedPolicy;if(schedparam)GROWABLE_HEAP_I32()[schedparam>>2]=schedPrio;return 0}function _pthread_self(){return __pthread_ptr|0}Module["_pthread_self"]=_pthread_self;function _pthread_create(pthread_ptr,attr,start_routine,arg){if(typeof SharedArrayBuffer==="undefined"){err("Current environment does not support SharedArrayBuffer, pthreads are not available!");return 6}if(!pthread_ptr){err("pthread_create called with a null thread pointer!");return 28}var transferList=[];var error=0;if(ENVIRONMENT_IS_PTHREAD&&(transferList.length===0||error)){return _emscripten_sync_run_in_main_thread_4(687865856,pthread_ptr,attr,start_routine,arg)}var stackSize=0;var stackBase=0;var detached=0;var schedPolicy=0;var schedPrio=0;if(attr){stackSize=GROWABLE_HEAP_I32()[attr>>2];stackSize+=81920;stackBase=GROWABLE_HEAP_I32()[attr+8>>2];detached=GROWABLE_HEAP_I32()[attr+12>>2]!==0;var inheritSched=GROWABLE_HEAP_I32()[attr+16>>2]===0;if(inheritSched){var prevSchedPolicy=GROWABLE_HEAP_I32()[attr+20>>2];var prevSchedPrio=GROWABLE_HEAP_I32()[attr+24>>2];var parentThreadPtr=PThread.currentProxiedOperationCallerThread?PThread.currentProxiedOperationCallerThread:_pthread_self();_pthread_getschedparam(parentThreadPtr,attr+20,attr+24);schedPolicy=GROWABLE_HEAP_I32()[attr+20>>2];schedPrio=GROWABLE_HEAP_I32()[attr+24>>2];GROWABLE_HEAP_I32()[attr+20>>2]=prevSchedPolicy;GROWABLE_HEAP_I32()[attr+24>>2]=prevSchedPrio;}else{schedPolicy=GROWABLE_HEAP_I32()[attr+20>>2];schedPrio=GROWABLE_HEAP_I32()[attr+24>>2];}}else{stackSize=2097152;}var allocatedOwnStack=stackBase==0;if(allocatedOwnStack){stackBase=_memalign(16,stackSize);}else{stackBase-=stackSize;assert(stackBase>0);}var threadInfoStruct=_malloc(232);for(var i=0;i<232>>2;++i)GROWABLE_HEAP_U32()[(threadInfoStruct>>2)+i]=0;GROWABLE_HEAP_I32()[pthread_ptr>>2]=threadInfoStruct;GROWABLE_HEAP_I32()[threadInfoStruct+12>>2]=threadInfoStruct;var headPtr=threadInfoStruct+156;GROWABLE_HEAP_I32()[headPtr>>2]=headPtr;var threadParams={stackBase:stackBase,stackSize:stackSize,allocatedOwnStack:allocatedOwnStack,schedPolicy:schedPolicy,schedPrio:schedPrio,detached:detached,startRoutine:start_routine,pthread_ptr:threadInfoStruct,parent_pthread_ptr:_pthread_self(),arg:arg,transferList:transferList};if(ENVIRONMENT_IS_PTHREAD){threadParams.cmd="spawnThread";postMessage(threadParams,transferList);}else{__spawn_thread(threadParams);}return 0}function _roundf(d){d=+d;return d>=+0?+Math_floor(d+ +.5):+Math_ceil(d-+.5)}function _sysconf(name){if(ENVIRONMENT_IS_PTHREAD)return _emscripten_proxy_to_main_thread_js(6,1,name);switch(name){case 30:return 16384;case 85:var maxHeapSize=2147483648;return maxHeapSize/16384;case 132:case 133:case 12:case 137:case 138:case 15:case 235:case 16:case 17:case 18:case 19:case 20:case 149:case 13:case 10:case 236:case 153:case 9:case 21:case 22:case 159:case 154:case 14:case 77:case 78:case 139:case 80:case 81:case 82:case 68:case 67:case 164:case 11:case 29:case 47:case 48:case 95:case 52:case 51:case 46:case 79:return 200809;case 27:case 246:case 127:case 128:case 23:case 24:case 160:case 161:case 181:case 182:case 242:case 183:case 184:case 243:case 244:case 245:case 165:case 178:case 179:case 49:case 50:case 168:case 169:case 175:case 170:case 171:case 172:case 97:case 76:case 32:case 173:case 35:return -1;case 176:case 177:case 7:case 155:case 8:case 157:case 125:case 126:case 92:case 93:case 129:case 130:case 131:case 94:case 91:return 1;case 74:case 60:case 69:case 70:case 4:return 1024;case 31:case 42:case 72:return 32;case 87:case 26:case 33:return 2147483647;case 34:case 1:return 47839;case 38:case 36:return 99;case 43:case 37:return 2048;case 0:return 2097152;case 3:return 65536;case 28:return 32768;case 44:return 32767;case 75:return 16384;case 39:return 1e3;case 89:return 700;case 71:return 256;case 40:return 255;case 2:return 100;case 180:return 64;case 25:return 20;case 5:return 16;case 6:return 6;case 73:return 4;case 84:{if(typeof navigator==="object")return navigator["hardwareConcurrency"]||1;return 1}}setErrNo(28);return -1}if(!ENVIRONMENT_IS_PTHREAD)PThread.initMainThreadBlock();else PThread.initWorker();var GLctx;GL.init();var proxiedFunctionTable=[null,_atexit,_emscripten_set_canvas_element_size_main_thread,_fd_close,_fd_seek,_fd_write,_sysconf];var asmLibraryArg={"e":___assert_fail,"r":___call_main,"w":__emscripten_notify_thread_queue,"a":_abort,"l":_emscripten_conditional_set_current_thread_status,"d":_emscripten_futex_wait,"c":_emscripten_futex_wake,"h":_emscripten_get_now,"g":_emscripten_is_main_browser_thread,"x":_emscripten_is_main_runtime_thread,"q":_emscripten_memcpy_big,"B":_emscripten_num_logical_cores,"t":_emscripten_receive_on_main_thread_js,"A":_emscripten_resize_heap,"u":_emscripten_set_canvas_element_size,"k":_emscripten_set_current_thread_status,"s":_emscripten_set_thread_name,"v":_emscripten_webgl_create_context,"m":_fd_close,"o":_fd_seek,"i":_fd_write,"p":initPthreadsJS,"memory":wasmMemory||Module["wasmMemory"],"y":_pthread_cleanup_pop,"z":_pthread_cleanup_push,"j":_pthread_create,"b":_pthread_self,"f":_roundf,"n":_sysconf,"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"]["C"]).apply(null,arguments)};var _init=Module["_init"]=function(){return (_init=Module["_init"]=Module["asm"]["D"]).apply(null,arguments)};var _register_tensor=Module["_register_tensor"]=function(){return (_register_tensor=Module["_register_tensor"]=Module["asm"]["E"]).apply(null,arguments)};var _dispose_data=Module["_dispose_data"]=function(){return (_dispose_data=Module["_dispose_data"]=Module["asm"]["F"]).apply(null,arguments)};var _dispose=Module["_dispose"]=function(){return (_dispose=Module["_dispose"]=Module["asm"]["G"]).apply(null,arguments)};var _Abs=Module["_Abs"]=function(){return (_Abs=Module["_Abs"]=Module["asm"]["H"]).apply(null,arguments)};var _Add=Module["_Add"]=function(){return (_Add=Module["_Add"]=Module["asm"]["I"]).apply(null,arguments)};var _AddN=Module["_AddN"]=function(){return (_AddN=Module["_AddN"]=Module["asm"]["J"]).apply(null,arguments)};var _ArgMax=Module["_ArgMax"]=function(){return (_ArgMax=Module["_ArgMax"]=Module["asm"]["K"]).apply(null,arguments)};var _AvgPool=Module["_AvgPool"]=function(){return (_AvgPool=Module["_AvgPool"]=Module["asm"]["L"]).apply(null,arguments)};var _BatchMatMul=Module["_BatchMatMul"]=function(){return (_BatchMatMul=Module["_BatchMatMul"]=Module["asm"]["M"]).apply(null,arguments)};var _ClipByValue=Module["_ClipByValue"]=function(){return (_ClipByValue=Module["_ClipByValue"]=Module["asm"]["N"]).apply(null,arguments)};var _Conv2D=Module["_Conv2D"]=function(){return (_Conv2D=Module["_Conv2D"]=Module["asm"]["O"]).apply(null,arguments)};var _Conv2DBackpropInput=Module["_Conv2DBackpropInput"]=function(){return (_Conv2DBackpropInput=Module["_Conv2DBackpropInput"]=Module["asm"]["P"]).apply(null,arguments)};var _Cos=Module["_Cos"]=function(){return (_Cos=Module["_Cos"]=Module["asm"]["Q"]).apply(null,arguments)};var _CropAndResize=Module["_CropAndResize"]=function(){return 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(_LessEqual=Module["_LessEqual"]=Module["asm"]["da"]).apply(null,arguments)};var _Log=Module["_Log"]=function(){return (_Log=Module["_Log"]=Module["asm"]["ea"]).apply(null,arguments)};var _LogicalAnd=Module["_LogicalAnd"]=function(){return (_LogicalAnd=Module["_LogicalAnd"]=Module["asm"]["fa"]).apply(null,arguments)};var _Max=Module["_Max"]=function(){return (_Max=Module["_Max"]=Module["asm"]["ga"]).apply(null,arguments)};var _MaxPool=Module["_MaxPool"]=function(){return (_MaxPool=Module["_MaxPool"]=Module["asm"]["ha"]).apply(null,arguments)};var _Maximum=Module["_Maximum"]=function(){return (_Maximum=Module["_Maximum"]=Module["asm"]["ia"]).apply(null,arguments)};var _Min=Module["_Min"]=function(){return (_Min=Module["_Min"]=Module["asm"]["ja"]).apply(null,arguments)};var _Minimum=Module["_Minimum"]=function(){return (_Minimum=Module["_Minimum"]=Module["asm"]["ka"]).apply(null,arguments)};var _Multiply=Module["_Multiply"]=function(){return 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(_Rsqrt=Module["_Rsqrt"]=Module["asm"]["Aa"]).apply(null,arguments)};var _ScatterNd=Module["_ScatterNd"]=function(){return (_ScatterNd=Module["_ScatterNd"]=Module["asm"]["Ba"]).apply(null,arguments)};var _SelectV2=Module["_SelectV2"]=function(){return (_SelectV2=Module["_SelectV2"]=Module["asm"]["Ca"]).apply(null,arguments)};var _Sigmoid=Module["_Sigmoid"]=function(){return (_Sigmoid=Module["_Sigmoid"]=Module["asm"]["Da"]).apply(null,arguments)};var _Sin=Module["_Sin"]=function(){return (_Sin=Module["_Sin"]=Module["asm"]["Ea"]).apply(null,arguments)};var _Softmax=Module["_Softmax"]=function(){return (_Softmax=Module["_Softmax"]=Module["asm"]["Fa"]).apply(null,arguments)};var _Sqrt=Module["_Sqrt"]=function(){return (_Sqrt=Module["_Sqrt"]=Module["asm"]["Ga"]).apply(null,arguments)};var _Square=Module["_Square"]=function(){return (_Square=Module["_Square"]=Module["asm"]["Ha"]).apply(null,arguments)};var _Sub=Module["_Sub"]=function(){return (_Sub=Module["_Sub"]=Module["asm"]["Ia"]).apply(null,arguments)};var _Sum=Module["_Sum"]=function(){return (_Sum=Module["_Sum"]=Module["asm"]["Ja"]).apply(null,arguments)};var _Tanh=Module["_Tanh"]=function(){return (_Tanh=Module["_Tanh"]=Module["asm"]["Ka"]).apply(null,arguments)};var _Tile=Module["_Tile"]=function(){return (_Tile=Module["_Tile"]=Module["asm"]["La"]).apply(null,arguments)};var _Transpose=Module["_Transpose"]=function(){return (_Transpose=Module["_Transpose"]=Module["asm"]["Ma"]).apply(null,arguments)};var __FusedMatMul=Module["__FusedMatMul"]=function(){return (__FusedMatMul=Module["__FusedMatMul"]=Module["asm"]["Na"]).apply(null,arguments)};var _malloc=Module["_malloc"]=function(){return (_malloc=Module["_malloc"]=Module["asm"]["Oa"]).apply(null,arguments)};var _free=Module["_free"]=function(){return (_free=Module["_free"]=Module["asm"]["Pa"]).apply(null,arguments)};var ___em_js__initPthreadsJS=Module["___em_js__initPthreadsJS"]=function(){return (___em_js__initPthreadsJS=Module["___em_js__initPthreadsJS"]=Module["asm"]["Qa"]).apply(null,arguments)};var ___errno_location=Module["___errno_location"]=function(){return (___errno_location=Module["___errno_location"]=Module["asm"]["Ra"]).apply(null,arguments)};var _emscripten_get_global_libc=Module["_emscripten_get_global_libc"]=function(){return (_emscripten_get_global_libc=Module["_emscripten_get_global_libc"]=Module["asm"]["Sa"]).apply(null,arguments)};var _memalign=Module["_memalign"]=function(){return (_memalign=Module["_memalign"]=Module["asm"]["Ta"]).apply(null,arguments)};var ___pthread_tsd_run_dtors=Module["___pthread_tsd_run_dtors"]=function(){return (___pthread_tsd_run_dtors=Module["___pthread_tsd_run_dtors"]=Module["asm"]["Ua"]).apply(null,arguments)};var _emscripten_main_thread_process_queued_calls=Module["_emscripten_main_thread_process_queued_calls"]=function(){return (_emscripten_main_thread_process_queued_calls=Module["_emscripten_main_thread_process_queued_calls"]=Module["asm"]["Va"]).apply(null,arguments)};var _emscripten_current_thread_process_queued_calls=Module["_emscripten_current_thread_process_queued_calls"]=function(){return (_emscripten_current_thread_process_queued_calls=Module["_emscripten_current_thread_process_queued_calls"]=Module["asm"]["Wa"]).apply(null,arguments)};var _emscripten_register_main_browser_thread_id=Module["_emscripten_register_main_browser_thread_id"]=function(){return (_emscripten_register_main_browser_thread_id=Module["_emscripten_register_main_browser_thread_id"]=Module["asm"]["Xa"]).apply(null,arguments)};var _emscripten_main_browser_thread_id=Module["_emscripten_main_browser_thread_id"]=function(){return (_emscripten_main_browser_thread_id=Module["_emscripten_main_browser_thread_id"]=Module["asm"]["Ya"]).apply(null,arguments)};var _emscripten_async_run_in_main_thread=Module["_emscripten_async_run_in_main_thread"]=function(){return (_emscripten_async_run_in_main_thread=Module["_emscripten_async_run_in_main_thread"]=Module["asm"]["Za"]).apply(null,arguments)};var _emscripten_sync_run_in_main_thread=Module["_emscripten_sync_run_in_main_thread"]=function(){return (_emscripten_sync_run_in_main_thread=Module["_emscripten_sync_run_in_main_thread"]=Module["asm"]["_a"]).apply(null,arguments)};var _emscripten_sync_run_in_main_thread_0=Module["_emscripten_sync_run_in_main_thread_0"]=function(){return (_emscripten_sync_run_in_main_thread_0=Module["_emscripten_sync_run_in_main_thread_0"]=Module["asm"]["$a"]).apply(null,arguments)};var _emscripten_sync_run_in_main_thread_1=Module["_emscripten_sync_run_in_main_thread_1"]=function(){return (_emscripten_sync_run_in_main_thread_1=Module["_emscripten_sync_run_in_main_thread_1"]=Module["asm"]["ab"]).apply(null,arguments)};var _emscripten_sync_run_in_main_thread_2=Module["_emscripten_sync_run_in_main_thread_2"]=function(){return (_emscripten_sync_run_in_main_thread_2=Module["_emscripten_sync_run_in_main_thread_2"]=Module["asm"]["bb"]).apply(null,arguments)};var _emscripten_sync_run_in_main_thread_xprintf_varargs=Module["_emscripten_sync_run_in_main_thread_xprintf_varargs"]=function(){return (_emscripten_sync_run_in_main_thread_xprintf_varargs=Module["_emscripten_sync_run_in_main_thread_xprintf_varargs"]=Module["asm"]["cb"]).apply(null,arguments)};var _emscripten_sync_run_in_main_thread_3=Module["_emscripten_sync_run_in_main_thread_3"]=function(){return (_emscripten_sync_run_in_main_thread_3=Module["_emscripten_sync_run_in_main_thread_3"]=Module["asm"]["db"]).apply(null,arguments)};var _emscripten_sync_run_in_main_thread_4=Module["_emscripten_sync_run_in_main_thread_4"]=function(){return (_emscripten_sync_run_in_main_thread_4=Module["_emscripten_sync_run_in_main_thread_4"]=Module["asm"]["eb"]).apply(null,arguments)};var _emscripten_sync_run_in_main_thread_5=Module["_emscripten_sync_run_in_main_thread_5"]=function(){return (_emscripten_sync_run_in_main_thread_5=Module["_emscripten_sync_run_in_main_thread_5"]=Module["asm"]["fb"]).apply(null,arguments)};var _emscripten_sync_run_in_main_thread_6=Module["_emscripten_sync_run_in_main_thread_6"]=function(){return (_emscripten_sync_run_in_main_thread_6=Module["_emscripten_sync_run_in_main_thread_6"]=Module["asm"]["gb"]).apply(null,arguments)};var _emscripten_sync_run_in_main_thread_7=Module["_emscripten_sync_run_in_main_thread_7"]=function(){return (_emscripten_sync_run_in_main_thread_7=Module["_emscripten_sync_run_in_main_thread_7"]=Module["asm"]["hb"]).apply(null,arguments)};var _emscripten_run_in_main_runtime_thread_js=Module["_emscripten_run_in_main_runtime_thread_js"]=function(){return (_emscripten_run_in_main_runtime_thread_js=Module["_emscripten_run_in_main_runtime_thread_js"]=Module["asm"]["ib"]).apply(null,arguments)};var _emscripten_async_queue_on_thread_=Module["_emscripten_async_queue_on_thread_"]=function(){return (_emscripten_async_queue_on_thread_=Module["_emscripten_async_queue_on_thread_"]=Module["asm"]["jb"]).apply(null,arguments)};var _emscripten_tls_init=Module["_emscripten_tls_init"]=function(){return (_emscripten_tls_init=Module["_emscripten_tls_init"]=Module["asm"]["kb"]).apply(null,arguments)};var stackSave=Module["stackSave"]=function(){return (stackSave=Module["stackSave"]=Module["asm"]["lb"]).apply(null,arguments)};var stackAlloc=Module["stackAlloc"]=function(){return (stackAlloc=Module["stackAlloc"]=Module["asm"]["mb"]).apply(null,arguments)};var stackRestore=Module["stackRestore"]=function(){return (stackRestore=Module["stackRestore"]=Module["asm"]["nb"]).apply(null,arguments)};var dynCall_vi=Module["dynCall_vi"]=function(){return (dynCall_vi=Module["dynCall_vi"]=Module["asm"]["ob"]).apply(null,arguments)};var dynCall_v=Module["dynCall_v"]=function(){return (dynCall_v=Module["dynCall_v"]=Module["asm"]["pb"]).apply(null,arguments)};var dynCall_ii=Module["dynCall_ii"]=function(){return (dynCall_ii=Module["dynCall_ii"]=Module["asm"]["qb"]).apply(null,arguments)};Module["asm"]=asm;Module["cwrap"]=cwrap;Module["PThread"]=PThread;Module["PThread"]=PThread;Module["_pthread_self"]=_pthread_self;Module["wasmMemory"]=wasmMemory;Module["ExitStatus"]=ExitStatus;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()();}}if(!ENVIRONMENT_IS_PTHREAD)noExitRuntime=true;if(!ENVIRONMENT_IS_PTHREAD)run();
  
  
      return WasmBackendModuleThreadedSimd
    }
    );
    })();
    module.exports = WasmBackendModuleThreadedSimd;
    });
  
    const wasmWorkerContents = 'var threadInfoStruct=0;var selfThreadId=0;var parentThreadId=0;var Module={};function threadPrintErr(){var text=Array.prototype.slice.call(arguments).join(" ");console.error(text)}function threadAlert(){var text=Array.prototype.slice.call(arguments).join(" ");postMessage({cmd:"alert",text:text,threadId:selfThreadId})}var err=threadPrintErr;this.alert=threadAlert;Module["instantiateWasm"]=function(info,receiveInstance){var instance=new WebAssembly.Instance(Module["wasmModule"],info);Module["wasmModule"]=null;receiveInstance(instance);return instance.exports};this.onmessage=function(e){try{if(e.data.cmd==="load"){Module["DYNAMIC_BASE"]=e.data.DYNAMIC_BASE;Module["DYNAMICTOP_PTR"]=e.data.DYNAMICTOP_PTR;Module["wasmModule"]=e.data.wasmModule;Module["wasmMemory"]=e.data.wasmMemory;Module["buffer"]=Module["wasmMemory"].buffer;Module["ENVIRONMENT_IS_PTHREAD"]=true;if(typeof e.data.urlOrBlob==="string"){importScripts(e.data.urlOrBlob)}else{var objectUrl=URL.createObjectURL(e.data.urlOrBlob);importScripts(objectUrl);URL.revokeObjectURL(objectUrl)}Module=WasmBackendModuleThreadedSimd(Module);postMessage({"cmd":"loaded"})}else if(e.data.cmd==="objectTransfer"){Module["PThread"].receiveObjectTransfer(e.data)}else if(e.data.cmd==="run"){Module["__performance_now_clock_drift"]=performance.now()-e.data.time;threadInfoStruct=e.data.threadInfoStruct;Module["__register_pthread_ptr"](threadInfoStruct,0,0);selfThreadId=e.data.selfThreadId;parentThreadId=e.data.parentThreadId;var max=e.data.stackBase;var top=e.data.stackBase+e.data.stackSize;Module["establishStackSpace"](top,max);Module["_emscripten_tls_init"]();Module["PThread"].receiveObjectTransfer(e.data);Module["PThread"].setThreadStatus(Module["_pthread_self"](),1);try{var result=Module["dynCall_ii"](e.data.start_routine,e.data.arg);if(!Module["getNoExitRuntime"]())Module["PThread"].threadExit(result)}catch(ex){if(ex==="Canceled!"){Module["PThread"].threadCancel()}else if(ex!="unwind"){Atomics.store(Module["HEAPU32"],threadInfoStruct+4>>2,ex instanceof Module["ExitStatus"]?ex.status:-2);Atomics.store(Module["HEAPU32"],threadInfoStruct+0>>2,1);Module["_emscripten_futex_wake"](threadInfoStruct+0,2147483647);if(!(ex instanceof Module["ExitStatus"]))throw ex}}}else if(e.data.cmd==="cancel"){if(threadInfoStruct){Module["PThread"].threadCancel()}}else if(e.data.target==="setimmediate"){}else if(e.data.cmd==="processThreadQueue"){if(threadInfoStruct){Module["_emscripten_current_thread_process_queued_calls"]()}}else{err("worker.js received unknown command "+e.data.cmd);err(e.data)}}catch(ex){err("worker.js onmessage() captured an uncaught exception: "+ex);if(ex.stack)err(ex.stack);throw ex}};if(typeof process==="object"&&typeof process.versions==="object"&&typeof process.versions.node==="string"){self={location:{href:__filename}};var onmessage=this.onmessage;var nodeWorkerThreads=require("worker_threads");Worker=nodeWorkerThreads.Worker;var parentPort=nodeWorkerThreads.parentPort;parentPort.on("message",function(data){onmessage({data:data})});var nodeFS=require("fs");var nodeRead=function(filename){return nodeFS.readFileSync(filename,"utf8")};function globalEval(x){global.require=require;global.Module=Module;eval.call(null,x)}importScripts=function(f){globalEval(nodeRead(f))};postMessage=function(msg){parentPort.postMessage(msg)};if(typeof performance==="undefined"){performance={now:function(){return Date.now()}}}}';
  
    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":147,"maximum":147+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 HEAP8,HEAPU8,HEAP16,HEAPU16,HEAP32,HEAPU32,HEAPF32,HEAPF64;function updateGlobalBufferAndViews(buf){Module["HEAP8"]=HEAP8=new Int8Array(buf);Module["HEAP16"]=HEAP16=new Int16Array(buf);Module["HEAP32"]=HEAP32=new Int32Array(buf);Module["HEAPU8"]=HEAPU8=new Uint8Array(buf);Module["HEAPU16"]=HEAPU16=new Uint16Array(buf);Module["HEAPU32"]=HEAPU32=new Uint32Array(buf);Module["HEAPF32"]=HEAPF32=new Float32Array(buf);Module["HEAPF64"]=HEAPF64=new Float64Array(buf);}var INITIAL_INITIAL_MEMORY=Module["INITIAL_MEMORY"]||16777216;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={"env":asmLibraryArg,"wasi_snapshot_preview1":asmLibraryArg};function receiveInstance(instance,module){var exports=instance.exports;Module["asm"]=exports;wasmMemory=exports["memory"];updateGlobalBufferAndViews(wasmMemory.buffer);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();function _emscripten_notify_memory_growth(memoryIndex){updateGlobalBufferAndViews(wasmMemory.buffer);}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 _exit(status){exit(status);}function _proc_exit(code){_exit(code);}function _roundf(d){d=+d;return d>=+0?+Math_floor(d+ +.5):+Math_ceil(d-+.5)}var asmLibraryArg={"emscripten_notify_memory_growth":_emscripten_notify_memory_growth,"fd_close":_fd_close,"fd_seek":_fd_seek,"fd_write":_fd_write,"proc_exit":_proc_exit,"roundf":_roundf};var asm=createWasm();Module["asm"]=asm;var _init=Module["_init"]=function(){return (_init=Module["_init"]=Module["asm"]["init"]).apply(null,arguments)};var _register_tensor=Module["_register_tensor"]=function(){return (_register_tensor=Module["_register_tensor"]=Module["asm"]["register_tensor"]).apply(null,arguments)};var _dispose_data=Module["_dispose_data"]=function(){return (_dispose_data=Module["_dispose_data"]=Module["asm"]["dispose_data"]).apply(null,arguments)};var _dispose=Module["_dispose"]=function(){return (_dispose=Module["_dispose"]=Module["asm"]["dispose"]).apply(null,arguments)};var _Abs=Module["_Abs"]=function(){return (_Abs=Module["_Abs"]=Module["asm"]["Abs"]).apply(null,arguments)};var _Add=Module["_Add"]=function(){return (_Add=Module["_Add"]=Module["asm"]["Add"]).apply(null,arguments)};var _AddN=Module["_AddN"]=function(){return (_AddN=Module["_AddN"]=Module["asm"]["AddN"]).apply(null,arguments)};var _ArgMax=Module["_ArgMax"]=function(){return (_ArgMax=Module["_ArgMax"]=Module["asm"]["ArgMax"]).apply(null,arguments)};var _AvgPool=Module["_AvgPool"]=function(){return (_AvgPool=Module["_AvgPool"]=Module["asm"]["AvgPool"]).apply(null,arguments)};var _BatchMatMul=Module["_BatchMatMul"]=function(){return (_BatchMatMul=Module["_BatchMatMul"]=Module["asm"]["BatchMatMul"]).apply(null,arguments)};var _ClipByValue=Module["_ClipByValue"]=function(){return (_ClipByValue=Module["_ClipByValue"]=Module["asm"]["ClipByValue"]).apply(null,arguments)};var _Conv2D=Module["_Conv2D"]=function(){return (_Conv2D=Module["_Conv2D"]=Module["asm"]["Conv2D"]).apply(null,arguments)};var _Conv2DBackpropInput=Module["_Conv2DBackpropInput"]=function(){return (_Conv2DBackpropInput=Module["_Conv2DBackpropInput"]=Module["asm"]["Conv2DBackpropInput"]).apply(null,arguments)};var _Cos=Module["_Cos"]=function(){return (_Cos=Module["_Cos"]=Module["asm"]["Cos"]).apply(null,arguments)};var _CropAndResize=Module["_CropAndResize"]=function(){return (_CropAndResize=Module["_CropAndResize"]=Module["asm"]["CropAndResize"]).apply(null,arguments)};var _DepthwiseConv2dNative=Module["_DepthwiseConv2dNative"]=function(){return (_DepthwiseConv2dNative=Module["_DepthwiseConv2dNative"]=Module["asm"]["DepthwiseConv2dNative"]).apply(null,arguments)};var _Div=Module["_Div"]=function(){return (_Div=Module["_Div"]=Module["asm"]["Div"]).apply(null,arguments)};var _Equal=Module["_Equal"]=function(){return (_Equal=Module["_Equal"]=Module["asm"]["Equal"]).apply(null,arguments)};var _Exp=Module["_Exp"]=function(){return (_Exp=Module["_Exp"]=Module["asm"]["Exp"]).apply(null,arguments)};var _FloorDiv=Module["_FloorDiv"]=function(){return (_FloorDiv=Module["_FloorDiv"]=Module["asm"]["FloorDiv"]).apply(null,arguments)};var _FusedBatchNorm=Module["_FusedBatchNorm"]=function(){return (_FusedBatchNorm=Module["_FusedBatchNorm"]=Module["asm"]["FusedBatchNorm"]).apply(null,arguments)};var _FusedConv2D=Module["_FusedConv2D"]=function(){return (_FusedConv2D=Module["_FusedConv2D"]=Module["asm"]["FusedConv2D"]).apply(null,arguments)};var _FusedDepthwiseConv2D=Module["_FusedDepthwiseConv2D"]=function(){return (_FusedDepthwiseConv2D=Module["_FusedDepthwiseConv2D"]=Module["asm"]["FusedDepthwiseConv2D"]).apply(null,arguments)};var _Gather=Module["_Gather"]=function(){return (_Gather=Module["_Gather"]=Module["asm"]["Gather"]).apply(null,arguments)};var _GatherNd=Module["_GatherNd"]=function(){return (_GatherNd=Module["_GatherNd"]=Module["asm"]["GatherNd"]).apply(null,arguments)};var _Greater=Module["_Greater"]=function(){return (_Greater=Module["_Greater"]=Module["asm"]["Greater"]).apply(null,arguments)};var _GreaterEqual=Module["_GreaterEqual"]=function(){return (_GreaterEqual=Module["_GreaterEqual"]=Module["asm"]["GreaterEqual"]).apply(null,arguments)};var _Less=Module["_Less"]=function(){return (_Less=Module["_Less"]=Module["asm"]["Less"]).apply(null,arguments)};var _LessEqual=Module["_LessEqual"]=function(){return (_LessEqual=Module["_LessEqual"]=Module["asm"]["LessEqual"]).apply(null,arguments)};var _Log=Module["_Log"]=function(){return (_Log=Module["_Log"]=Module["asm"]["Log"]).apply(null,arguments)};var _LogicalAnd=Module["_LogicalAnd"]=function(){return (_LogicalAnd=Module["_LogicalAnd"]=Module["asm"]["LogicalAnd"]).apply(null,arguments)};var _Max=Module["_Max"]=function(){return (_Max=Module["_Max"]=Module["asm"]["Max"]).apply(null,arguments)};var _MaxPool=Module["_MaxPool"]=function(){return (_MaxPool=Module["_MaxPool"]=Module["asm"]["MaxPool"]).apply(null,arguments)};var _Maximum=Module["_Maximum"]=function(){return (_Maximum=Module["_Maximum"]=Module["asm"]["Maximum"]).apply(null,arguments)};var _Min=Module["_Min"]=function(){return (_Min=Module["_Min"]=Module["asm"]["Min"]).apply(null,arguments)};var _Minimum=Module["_Minimum"]=function(){return (_Minimum=Module["_Minimum"]=Module["asm"]["Minimum"]).apply(null,arguments)};var _Multiply=Module["_Multiply"]=function(){return (_Multiply=Module["_Multiply"]=Module["asm"]["Multiply"]).apply(null,arguments)};var _Negate=Module["_Negate"]=function(){return (_Negate=Module["_Negate"]=Module["asm"]["Negate"]).apply(null,arguments)};var _NonMaxSuppressionV3=Module["_NonMaxSuppressionV3"]=function(){return (_NonMaxSuppressionV3=Module["_NonMaxSuppressionV3"]=Module["asm"]["NonMaxSuppressionV3"]).apply(null,arguments)};var _NonMaxSuppressionV4=Module["_NonMaxSuppressionV4"]=function(){return (_NonMaxSuppressionV4=Module["_NonMaxSuppressionV4"]=Module["asm"]["NonMaxSuppressionV4"]).apply(null,arguments)};var _NonMaxSuppressionV5=Module["_NonMaxSuppressionV5"]=function(){return (_NonMaxSuppressionV5=Module["_NonMaxSuppressionV5"]=Module["asm"]["NonMaxSuppressionV5"]).apply(null,arguments)};var _NotEqual=Module["_NotEqual"]=function(){return (_NotEqual=Module["_NotEqual"]=Module["asm"]["NotEqual"]).apply(null,arguments)};var _OneHot=Module["_OneHot"]=function(){return (_OneHot=Module["_OneHot"]=Module["asm"]["OneHot"]).apply(null,arguments)};var _PadV2=Module["_PadV2"]=function(){return (_PadV2=Module["_PadV2"]=Module["asm"]["PadV2"]).apply(null,arguments)};var _Pow=Module["_Pow"]=function(){return (_Pow=Module["_Pow"]=Module["asm"]["Pow"]).apply(null,arguments)};var _Prelu=Module["_Prelu"]=function(){return (_Prelu=Module["_Prelu"]=Module["asm"]["Prelu"]).apply(null,arguments)};var _Relu=Module["_Relu"]=function(){return (_Relu=Module["_Relu"]=Module["asm"]["Relu"]).apply(null,arguments)};var _Relu6=Module["_Relu6"]=function(){return (_Relu6=Module["_Relu6"]=Module["asm"]["Relu6"]).apply(null,arguments)};var _ResizeBilinear=Module["_ResizeBilinear"]=function(){return (_ResizeBilinear=Module["_ResizeBilinear"]=Module["asm"]["ResizeBilinear"]).apply(null,arguments)};var _Reverse=Module["_Reverse"]=function(){return (_Reverse=Module["_Reverse"]=Module["asm"]["Reverse"]).apply(null,arguments)};var _RotateWithOffset=Module["_RotateWithOffset"]=function(){return (_RotateWithOffset=Module["_RotateWithOffset"]=Module["asm"]["RotateWithOffset"]).apply(null,arguments)};var _Rsqrt=Module["_Rsqrt"]=function(){return (_Rsqrt=Module["_Rsqrt"]=Module["asm"]["Rsqrt"]).apply(null,arguments)};var _ScatterNd=Module["_ScatterNd"]=function(){return (_ScatterNd=Module["_ScatterNd"]=Module["asm"]["ScatterNd"]).apply(null,arguments)};var _SelectV2=Module["_SelectV2"]=function(){return (_SelectV2=Module["_SelectV2"]=Module["asm"]["SelectV2"]).apply(null,arguments)};var _Sigmoid=Module["_Sigmoid"]=function(){return (_Sigmoid=Module["_Sigmoid"]=Module["asm"]["Sigmoid"]).apply(null,arguments)};var _Sin=Module["_Sin"]=function(){return (_Sin=Module["_Sin"]=Module["asm"]["Sin"]).apply(null,arguments)};var _Softmax=Module["_Softmax"]=function(){return (_Softmax=Module["_Softmax"]=Module["asm"]["Softmax"]).apply(null,arguments)};var _Sqrt=Module["_Sqrt"]=function(){return (_Sqrt=Module["_Sqrt"]=Module["asm"]["Sqrt"]).apply(null,arguments)};var _Square=Module["_Square"]=function(){return (_Square=Module["_Square"]=Module["asm"]["Square"]).apply(null,arguments)};var _Sub=Module["_Sub"]=function(){return (_Sub=Module["_Sub"]=Module["asm"]["Sub"]).apply(null,arguments)};var _Sum=Module["_Sum"]=function(){return (_Sum=Module["_Sum"]=Module["asm"]["Sum"]).apply(null,arguments)};var _Tanh=Module["_Tanh"]=function(){return (_Tanh=Module["_Tanh"]=Module["asm"]["Tanh"]).apply(null,arguments)};var _Tile=Module["_Tile"]=function(){return (_Tile=Module["_Tile"]=Module["asm"]["Tile"]).apply(null,arguments)};var _Transpose=Module["_Transpose"]=function(){return (_Transpose=Module["_Transpose"]=Module["asm"]["Transpose"]).apply(null,arguments)};var __FusedMatMul=Module["__FusedMatMul"]=function(){return (__FusedMatMul=Module["__FusedMatMul"]=Module["asm"]["_FusedMatMul"]).apply(null,arguments)};var _malloc=Module["_malloc"]=function(){return (_malloc=Module["_malloc"]=Module["asm"]["malloc"]).apply(null,arguments)};var _free=Module["_free"]=function(){return (_free=Module["_free"]=Module["asm"]["free"]).apply(null,arguments)};var __start=Module["__start"]=function(){return (__start=Module["__start"]=Module["asm"]["_start"]).apply(null,arguments)};var stackSave=Module["stackSave"]=function(){return (stackSave=Module["stackSave"]=Module["asm"]["stackSave"]).apply(null,arguments)};var stackAlloc=Module["stackAlloc"]=function(){return (stackAlloc=Module["stackAlloc"]=Module["asm"]["stackAlloc"]).apply(null,arguments)};var stackRestore=Module["stackRestore"]=function(){return (stackRestore=Module["stackRestore"]=Module["asm"]["stackRestore"]).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 callMain(args){var entryFunction=Module["__start"];try{entryFunction();var ret=0;exit(ret,true);}catch(e){if(e instanceof ExitStatus){return}else if(e=="unwind"){noExitRuntime=true;return}else{var toLog=e;if(e&&typeof e==="object"&&e.stack){toLog=[e,e.stack];}err("exception thrown: "+toLog);quit_(1,e);}}finally{}}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"]();if(shouldRunNow)callMain();postRun();}if(Module["setStatus"]){Module["setStatus"]("Running...");setTimeout(function(){setTimeout(function(){Module["setStatus"]("");},1);doRun();},1);}else{doRun();}}Module["run"]=run;function exit(status,implicit){if(implicit&&noExitRuntime&&status===0){return}if(noExitRuntime);else{ABORT=true;if(Module["onExit"])Module["onExit"](status);}quit_(status,new ExitStatus(status));}if(Module["preInit"]){if(typeof Module["preInit"]=="function")Module["preInit"]=[Module["preInit"]];while(Module["preInit"].length>0){Module["preInit"].pop()();}}var shouldRunNow=true;if(Module["noInitialRun"])shouldRunNow=false;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 {};
        };
    }
    /**
     * Returns the path of the WASM binary.
     * @param simdSupported whether SIMD is supported
     * @param threadsSupported whether multithreading is supported
     * @param wasmModuleFolder the directory containing the WASM binaries.
     */
    function getPathToWasmBinary(simdSupported, threadsSupported, wasmModuleFolder) {
        if (wasmPath != null) {
            // If wasmPath is defined, the user has supplied a full path to
            // the vanilla .wasm binary.
            return wasmPath;
        }
        let path = 'tfjs-backend-wasm.wasm';
        if (simdSupported && threadsSupported) {
            path = 'tfjs-backend-wasm-threaded-simd.wasm';
        } else if (simdSupported) {
            path = 'tfjs-backend-wasm-simd.wasm';
        }
        if (wasmFileMap != null) {
            if (wasmFileMap[path] != null) {
                return wasmFileMap[path];
            }
        }
        return wasmModuleFolder + path;
    }
    /**
     * Initializes the wasm module and creates the js <--> wasm bridge.
     *
     * NOTE: We wrap the wasm module in a object with property 'wasm' instead of
     * returning Promise<BackendWasmModule> to avoid freezing Chrome (last tested
     * in Chrome 76).
     */
    async function init() {
        const [simdSupported, threadsSupported] = await Promise.all([
            tfjsCore.env().getAsync('WASM_HAS_SIMD_SUPPORT'),
            tfjsCore.env().getAsync('WASM_HAS_MULTITHREAD_SUPPORT')
        ]);
        return new Promise((resolve, reject) => {
            const factoryConfig = {};
            /**
             * This function overrides the Emscripten module locateFile utility.
             * @param path The relative path to the file that needs to be loaded.
             * @param prefix The path to the main JavaScript file's directory.
             */
            factoryConfig.locateFile = (path, prefix) => {
                if (path.endsWith('.worker.js')) {
                    const response = wasmWorkerContents;
                    const blob = new Blob([response], { type: 'application/javascript' });
                    return URL.createObjectURL(blob);
                }
                if (path.endsWith('.wasm')) {
                    return getPathToWasmBinary(simdSupported, threadsSupported, wasmPathPrefix != null ? wasmPathPrefix : prefix);
                }
                return prefix + path;
            };
            // Use the instantiateWasm override when system fetch is not available.
            // Reference:
            // https://github.com/emscripten-core/emscripten/blob/2bca083cbbd5a4133db61fbd74d04f7feecfa907/tests/manual_wasm_instantiate.html#L170
            if (customFetch) {
                factoryConfig.instantiateWasm =
                    createInstantiateWasmFunc(getPathToWasmBinary(simdSupported, threadsSupported, wasmPathPrefix != null ? wasmPathPrefix : ''));
            }
            let wasm;
            // If `wasmPath` has been defined we must initialize the vanilla module.
            if (threadsSupported && simdSupported && wasmPath == null) {
                wasm = tfjsBackendWasmThreadedSimd(factoryConfig);
                wasm.mainScriptUrlOrBlob = new Blob([`var _scriptDir = undefined; var WasmBackendModuleThreadedSimd = ` +
                        tfjsBackendWasmThreadedSimd.toString()], { type: 'text/javascript' });
            }
            else {
                // The wasmFactory works for both vanilla and SIMD binaries.
                wasm = 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}`);
        }
    }
    const wasmBinaryNames = [
        'tfjs-backend-wasm.wasm', 'tfjs-backend-wasm-simd.wasm',
        'tfjs-backend-wasm-threaded-simd.wasm'
    ];
    let wasmPath = null;
    let wasmPathPrefix = null;
    let wasmFileMap = {};
    let initAborted = false;
    let customFetch = false;
    /**
     * @deprecated Use `setWasmPaths` instead.
     * Sets the path to the `.wasm` file which will be fetched when the wasm
     * backend is initialized. See
     * https://github.com/tensorflow/tfjs/blob/master/tfjs-backend-wasm/README.md#using-bundlers
     * for more details.
     * @param path wasm file path or url
     * @param usePlatformFetch optional boolean to use platform fetch to download
     *     the wasm file, default to false.
     */
    /** @doc {heading: 'Environment', namespace: 'wasm'} */
    function setWasmPath(path, usePlatformFetch = false) {
        tfjsCore.deprecationWarn('setWasmPath has been deprecated in favor of setWasmPaths and' +
            ' will be removed in a future release.');
        if (initAborted) {
            throw new Error('The WASM backend was already initialized. Make sure you call ' +
                '`setWasmPath()` before you call `tf.setBackend()` or `tf.ready()`');
        }
        wasmPath = path;
        customFetch = usePlatformFetch;
    }
    /**
     * Configures the locations of the WASM binaries.
     *
     * ```js
     * const customPrefix = null;
     * setWasmPaths(customPrefix, {
     *  'tfjs-backend-wasm.wasm': 'renamed.wasm',
     *  'tfjs-backend-wasm-simd.wasm': 'renamed-simd.wasm',
     *  'tfjs-backend-wasm-threaded-simd.wasm': 'renamed-threaded-simd.wasm'
     * });
     * tf.setBackend('wasm');
     * ```
     *
     * @param prefixOrFileMap This can be either a string or object:
     *  - (string) The path to the directory where the WASM binaries are located.
     *     Note that this prefix will be used to load each binary (vanilla,
     *     SIMD-enabled, threading-enabled, etc.).
     *  - (object) Mapping from names of WASM binaries to custom
     *     full paths specifying the locations of those binaries. This is useful if
     *     your WASM binaries are not all located in the same directory, or if your
     *     WASM binaries have been renamed.
     * @param usePlatformFetch optional boolean to use platform fetch to download
     *     the wasm file, default to false.
     */
    /** @doc {heading: 'Environment', namespace: 'wasm'} */
    function setWasmPaths(prefixOrFileMap, usePlatformFetch = false) {
        if (initAborted) {
            throw new Error('The WASM backend was already initialized. Make sure you call ' +
                '`setWasmPaths()` before you call `tf.setBackend()` or ' +
                '`tf.ready()`');
        }
        if (typeof prefixOrFileMap === 'string') {
            wasmPathPrefix = prefixOrFileMap;
        }
        else {
            wasmFileMap = prefixOrFileMap;
            const missingPaths = wasmBinaryNames.filter(name => wasmFileMap[name] == null);
            if (missingPaths.length) {
                console.warn(`You provided a map of overrides for WASM binaries, but there ` +
                    `were no entries found for the following binaries: ` +
                    `${missingPaths.join(',')}. We will fall back to their ` +
                    `default locations.`);
            }
        }
        customFetch = usePlatformFetch;
    }
  
    /** @license See the LICENSE file. */
    // This code is auto-generated, do not modify this file!
    const version = '0.0.0';
  
    exports.BackendWasm = BackendWasm;
    exports.setWasmPath = setWasmPath;
    exports.setWasmPaths = setWasmPaths;
    exports.version_wasm = version;
  
    Object.defineProperty(exports, '__esModule', { value: true });
  
  })));
  //# sourceMappingURL=tf-backend-wasm.js.map