wehub-resource-sync
91 lines
4.4 KiB
Plaintext
91 lines
4.4 KiB
Plaintext
/*
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* ******************************************************************************
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* *
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* *
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* * This program and the accompanying materials are made available under the
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* * terms of the Apache License, Version 2.0 which is available at
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* * https://www.apache.org/licenses/LICENSE-2.0.
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* *
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* * See the NOTICE file distributed with this work for additional
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* * information regarding copyright ownership.
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* * Unless required by applicable law or agreed to in writing, software
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* * distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
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* * WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
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* * License for the specific language governing permissions and limitations
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* * under the License.
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* *
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* * SPDX-License-Identifier: Apache-2.0
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* *****************************************************************************
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*/
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//
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// @author Yurii Shyrma (iuriish@yahoo.com)
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//
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#include <ops/declarable/helpers/convolutions.h>
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namespace sd {
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namespace ops {
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//////////////////////////////////////////////////////////////////////////
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template <typename X, typename Y>
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static void sconv2d_(graph::Context& block, NDArray* input, NDArray* weightsDepth,
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NDArray* weightsPoint, NDArray* bias, NDArray* output, const LongType kH, const LongType kW,
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const LongType sH, const LongType sW, LongType pH, LongType pW, const LongType dH, const LongType dW, const int paddingMode,
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const int isNCHW, const int wFormat) {
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// input [bS, iH, iW, iC] (NHWC) or [bS, iC, iH, iW] (NCHW)
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// weightsDepth [kH, kW, iC, mC], [mC, iC, kH, kW], [mC, kH, kW, iC]
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// weightsPoint [1, 1, iC*mC, oC], [oC, iC*mC, 1, 1], [oC, 1, 1, iC*mC]
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// bias [oC], oC = iC*mC if weightsPoint=nullptr
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// output is [bS, oH, oW, oC] (NHWC) or [bS, oC, oH, oW] (NCHW)
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// kH filter(kernel) height
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// kW filter(kernel) width
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// sH strides height
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// sW strides width
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// pH paddings height
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// pW paddings width
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// dH dilations height
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// dW dilations width
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// paddingMode 0-VALID, 1-SAME
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// isNCHW 1-NCHW, 0-NHWC
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LongType bS, iC, iH, iW, mC, oC, oH,
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oW; // batch size, input channels, input height/width, channels multiplier, output channels, output height/width
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LongType indIOioC, indIiH, indWmC, indWiC, indWkH, indOoH; // corresponding indexes
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ConvolutionUtils::getSizesAndIndexesConv2d(isNCHW, wFormat, *input, *output, bS, iC, iH, iW, oC, oH, oW, indIOioC,
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indIiH, indWiC, indWmC, indWkH, indOoH);
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mC = weightsDepth->sizeAt(indWmC); // channels multiplier
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NDArray* outputDepth = output;
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if (weightsPoint) { // if pointwise convolution is expected
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std::vector<sd::LongType> shape1 = {bS, oH, oW, iC * mC};
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std::vector<sd::LongType> shape2 = {bS, iC * mC, oH, oW};
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outputDepth = new NDArray(output->ordering(), !isNCHW ? shape1 : shape2, input->dataType(), input->getContext());
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}
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// ----- perform depthwise convolution (if weightsPoint is absent then oC = iC*mC) ----- //
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ConvolutionUtils::depthwiseConv2d(block, input, weightsDepth, weightsPoint ? nullptr : bias, outputDepth, kH, kW, sH,
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sW, pH, pW, dH, dW, paddingMode, isNCHW, wFormat);
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// ----- perform pointwise convolution (oH = iH, oW = iW) ----- //
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if (weightsPoint) {
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ConvolutionUtils::conv2d(block, outputDepth, weightsPoint, bias, output, 1, 1, 1, 1, 0, 0, 1, 1, paddingMode,
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isNCHW, wFormat); // in this case oH=iH, oW=iW
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delete outputDepth;
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}
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}
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//////////////////////////////////////////////////////////////////////////
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void ConvolutionUtils::sconv2d(graph::Context& block, NDArray* input, NDArray* weightsDepth,
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NDArray* weightsPoint, NDArray* bias, NDArray* output, const LongType kH,
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const LongType kW, const LongType sH, const LongType sW, LongType pH, LongType pW, const LongType dH, const LongType dW,
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const int paddingMode, const int isNCHW, const int wFormat) {
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BUILD_SINGLE_SELECTOR_TWICE(input->dataType(), sconv2d_,
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(block, input, weightsDepth, weightsPoint, bias, output, kH, kW, sH, sW, pH, pW, dH, dW,
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paddingMode, isNCHW, wFormat),
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SD_FLOAT_TYPES);
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}
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} // namespace ops
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} // namespace sd
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