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| Original file line number | Diff line number | Diff line change |
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| /** | ||
| * @license | ||
| * Copyright 2023 Google LLC. | ||
| * Licensed under the Apache License, Version 2.0 (the "License"); | ||
| * you may not use this file except in compliance with the License. | ||
| * You may obtain a copy of the License at | ||
| * | ||
| * http://www.apache.org/licenses/LICENSE-2.0 | ||
| * | ||
| * Unless required by applicable law or agreed to in writing, software | ||
| * distributed under the License is distributed on an "AS IS" BASIS, | ||
| * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
| * See the License for the specific language governing permissions and | ||
| * limitations under the License. | ||
| * ============================================================================= | ||
| */ | ||
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| #ifdef __EMSCRIPTEN__ | ||
| #include <emscripten.h> | ||
| #endif | ||
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| #include <algorithm> | ||
| #include <limits> | ||
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| #include "tfjs-backend-wasm/src/cc/backend.h" | ||
| #include "tfjs-backend-wasm/src/cc/pool3d_impl.h" | ||
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| namespace tfjs::wasm { | ||
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| // We use C-style API to interface with Javascript. | ||
| extern "C" { | ||
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| #ifdef __EMSCRIPTEN__ | ||
| EMSCRIPTEN_KEEPALIVE | ||
| #endif | ||
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| // REQUIRES: | ||
| // - Tensor `x`, `dx` and `dy` must have dtype float32 (checked in tfjs-core) | ||
| // - Tensor `x`, `dx` and `dy` must have data format 'NDHWC' (checked in | ||
| // tfjs-core) | ||
| void MaxPool3DGrad(int x_id, int dy_id, int dx_id, int batch_size, | ||
| int channel_size, int in_depth, int in_height, int in_width, | ||
| int out_depth, int out_height, int out_width, | ||
| int stride_depth, int stride_height, int stride_width, | ||
| int dilation_depth, int dilation_height, int dilation_width, | ||
| int effective_filter_depth, int effective_filter_height, | ||
| int effective_filter_width, int pad_front, int pad_top, | ||
| int pad_left, int filter_depth) { | ||
| const TensorInfo& x_info = backend::get_tensor_info(x_id); | ||
| const TensorInfo& dy_info = backend::get_tensor_info(dy_id); | ||
| TensorInfo& dx_info = backend::get_tensor_info_out(dx_id); | ||
| NDHWCPool3DInfo pool3d_info{ | ||
| .batch_size = batch_size, | ||
| .channel_size = channel_size, | ||
| .in_depth = in_depth, | ||
| .in_height = in_height, | ||
| .in_width = in_width, | ||
| .out_depth = out_depth, | ||
| .out_height = out_height, | ||
| .out_width = out_width, | ||
| .stride_depth = stride_depth, | ||
| .stride_height = stride_height, | ||
| .stride_width = stride_width, | ||
| .dilation_depth = dilation_depth, | ||
| .dilation_height = dilation_height, | ||
| .dilation_width = dilation_width, | ||
| .effective_filter_depth = effective_filter_depth, | ||
| .effective_filter_height = effective_filter_height, | ||
| .effective_filter_width = effective_filter_width, | ||
| .pad_front = pad_front, | ||
| .pad_top = pad_top, | ||
| .pad_left = pad_left, | ||
| }; | ||
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| int* max_positions = new int[pool3d_info.out_size()]; | ||
| NDHWCPool3DImpl</*IN=*/float, /*OUT=*/int>( | ||
| x_info.f32(), max_positions, pool3d_info, | ||
| /*filter_init=*/ | ||
| []() -> std::pair<float, int> { | ||
| return {std::numeric_limits<float>::min(), 0}; | ||
| }, | ||
| /*filter_apply=*/ | ||
| [](std::pair<float, int>& data, int x_offset, const float& x_val) { | ||
| if (x_val >= data.first) { | ||
| data = {x_val, x_offset}; | ||
| } | ||
| }, | ||
| /*filter_aggregate=*/ | ||
| [](const std::pair<float, int>& data) { return data.second; }); | ||
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| pool3d_info.pad_front = effective_filter_depth - 1 - pad_front; | ||
| pool3d_info.pad_top = effective_filter_height - 1 - pad_top; | ||
| pool3d_info.pad_left = effective_filter_width - 1 - pad_left; | ||
| NDHWCPool3DGradImpl( | ||
| dy_info.f32(), dx_info.f32_write(), pool3d_info, | ||
| /*pixel_mask=*/ | ||
| [&max_positions](int dy_offset, int dx_offset) { | ||
| return static_cast<float>(dx_offset == max_positions[dy_offset]); | ||
| }); | ||
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| delete[] max_positions; | ||
| } | ||
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| } // extern "C" | ||
| } // namespace tfjs::wasm |
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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1,108 @@ | ||
| /** | ||
| * @license | ||
| * Copyright 2023 Google LLC. | ||
| * Licensed under the Apache License, Version 2.0 (the "License"); | ||
| * you may not use this file except in compliance with the License. | ||
| * You may obtain a copy of the License at | ||
| * | ||
| * http://www.apache.org/licenses/LICENSE-2.0 | ||
| * | ||
| * Unless required by applicable law or agreed to in writing, software | ||
| * distributed under the License is distributed on an "AS IS" BASIS, | ||
| * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
| * See the License for the specific language governing permissions and | ||
| * limitations under the License. | ||
| * ============================================================================= | ||
| */ | ||
|
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| import {backend_util, KernelConfig, KernelFunc, MaxPool3DGrad, MaxPool3DGradAttrs, MaxPool3DGradInputs, TensorInfo} from '@tensorflow/tfjs-core'; | ||
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| import {BackendWasm} from '../backend_wasm'; | ||
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| let wasmMaxPool3DGrad: ( | ||
| xId: number, dyId: number, dxId: number, batchSize: number, | ||
| channelSize: number, inDepth: number, inHeight: number, inWidth: number, | ||
| outDepth: number, outHeight: number, outWidth: number, strideDepth: number, | ||
| strideHeight: number, strideWidth: number, dilationDepth: number, | ||
| dilationHeight: number, dilationWidth: number, effectiveFilterDepth: number, | ||
| effectiveFilterHeight: number, effectiveFilterWidth: number, | ||
| padFront: number, padTop: number, padLeft: number) => void; | ||
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| function setup(backend: BackendWasm) { | ||
| wasmMaxPool3DGrad = backend.wasm.cwrap('MaxPool3DGrad', null, [ | ||
| 'number', // xId | ||
| 'number', // dyId | ||
| 'number', // dxId | ||
| 'number', // batchSize | ||
| 'number', // channelSize | ||
| 'number', // inDepth | ||
| 'number', // inHeight | ||
| 'number', // inWidth | ||
| 'number', // outDepth | ||
| 'number', // outHeight | ||
| 'number', // outWidth | ||
| 'number', // strideDepth | ||
| 'number', // strideHeight | ||
| 'number', // strideWidth | ||
| 'number', // dilationDepth | ||
| 'number', // dilationHeight | ||
| 'number', // dilationWidth | ||
| 'number', // effectiveFilterDepth | ||
| 'number', // effectiveFilterHeight | ||
| 'number', // effectiveFilterWidth | ||
| 'number', // padFront | ||
| 'number', // padTop | ||
| 'number', // padLeft | ||
| ]); | ||
| } | ||
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| export function maxPool3DGrad(args: { | ||
| inputs: MaxPool3DGradInputs, | ||
| attrs: MaxPool3DGradAttrs, | ||
| backend: BackendWasm, | ||
| }): TensorInfo { | ||
| const {inputs, backend, attrs} = args; | ||
| const {dy, input} = inputs; | ||
| const {filterSize, strides, pad, dimRoundingMode} = attrs; | ||
|
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| const convInfo = backend_util.computePool3DInfo( | ||
| input.shape as [number, number, number, number, number], filterSize, | ||
| strides, /*dilations=*/1, pad, dimRoundingMode); | ||
| const dx = backend.makeOutput(input.shape, input.dtype); | ||
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| wasmMaxPool3DGrad( | ||
| backend.dataIdMap.get(input.dataId).id, | ||
| backend.dataIdMap.get(dy.dataId).id, | ||
| backend.dataIdMap.get(dx.dataId).id, | ||
| convInfo.batchSize, | ||
| // Since Pool3D ops (MaxPool3D and MaxPool3D) support 3D filter only, in | ||
| // channels should always equal to out channels. | ||
| /*channelSize=*/convInfo.inChannels, | ||
| convInfo.inDepth, | ||
| convInfo.inHeight, | ||
| convInfo.inWidth, | ||
| convInfo.outDepth, | ||
| convInfo.outHeight, | ||
| convInfo.outWidth, | ||
| convInfo.strideDepth, | ||
| convInfo.strideHeight, | ||
| convInfo.strideWidth, | ||
| convInfo.dilationDepth, | ||
| convInfo.dilationHeight, | ||
| convInfo.dilationWidth, | ||
| convInfo.effectiveFilterDepth, | ||
| convInfo.effectiveFilterHeight, | ||
| convInfo.effectiveFilterWidth, | ||
| convInfo.padInfo.front, | ||
| convInfo.padInfo.top, | ||
| convInfo.padInfo.left, | ||
| ); | ||
| return dx; | ||
| } | ||
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| export const maxPool3DGradConfig: KernelConfig = { | ||
| kernelName: MaxPool3DGrad, | ||
| backendName: 'wasm', | ||
| setupFunc: setup, | ||
| kernelFunc: maxPool3DGrad as unknown as KernelFunc | ||
| }; |
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