chore: import upstream snapshot with attribution
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wehub-resource-sync
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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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// @author Yurii Shyrma (iuriish@yahoo.com), created on 18.09.2018
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//
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#include <execution/Threads.h>
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#include <ops/declarable/helpers/convolutions.h>
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#include <stdexcept>
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namespace sd {
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namespace ops {
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//////////////////////////////////////////////////////////////////////////
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template <typename T>
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static void pooling2d_(sd::graph::Context& block, NDArray& input, NDArray& output, const LongType kH, const LongType kW,
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const LongType sH, const LongType sW, const LongType pH, const LongType pW, const LongType dH, const LongType dW,
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const int poolingMode, const int extraParam0) {
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// Cache shape information
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const auto inShapeInfo = input.shapeInfo();
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const auto outShapeInfo = output.shapeInfo();
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// Cache input dimensions
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const auto* inShape = shape::shapeOf(inShapeInfo);
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const LongType bS = inShape[0];
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const LongType iC = inShape[1];
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const LongType iH = inShape[2];
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const LongType iW = inShape[3];
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// Cache output dimensions
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const auto* outShape = shape::shapeOf(outShapeInfo);
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const LongType oH = outShape[2];
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const LongType oW = outShape[3];
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// Cache strides
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const auto* inStride = shape::stride(inShapeInfo);
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const auto* outStride = shape::stride(outShapeInfo);
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const sd::LongType iStride0 = inStride[0];
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const sd::LongType iStride1 = inStride[1];
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const sd::LongType iStride2 = inStride[2];
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const sd::LongType iStride3 = inStride[3];
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const sd::LongType oStride0 = outStride[0];
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const sd::LongType oStride1 = outStride[1];
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const sd::LongType oStride2 = outStride[2];
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const sd::LongType oStride3 = outStride[3];
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T* out = output.bufferAsT<T>();
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T* in = const_cast<NDArray&>(input).bufferAsT<T>();
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const int kHEff = kH + (kH - 1) * (dH - 1);
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const int kWEff = kW + (kW - 1) * (dW - 1);
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const sd::LongType iStep2 = dH * iStride2;
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const sd::LongType iStep3 = dW * iStride3;
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const int kProd = kH * kW;
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if (poolingMode == 0) { // max
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auto func = PRAGMA_THREADS_FOR_2D {
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sd::LongType hstart, wstart, hend, wend;
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T* pIn;
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for (int b = start_x; b < stop_x; b += inc_x) {
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for (int c = start_y; c < stop_y; c += inc_y) {
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for (int oh = 0; oh < oH; ++oh) {
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for (int ow = 0; ow < oW; ++ow) {
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pIn = in + b * iStride0 + c * iStride1;
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hstart = oh * sH - pH;
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wstart = ow * sW - pW;
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hend = hstart + kHEff;
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wend = wstart + kWEff;
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if (hstart < 0)
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hstart += dH * ((-hstart + dH - 1) / dH);
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if (wstart < 0)
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wstart += dW * ((-wstart + dW - 1) / dW);
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if (hend > iH)
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hend -= dH * ((hend - iH + dH - 1) / dH);
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if (wend > iW)
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wend -= dW * ((wend - iW + dW - 1) / dW);
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hstart *= iStride2;
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hend *= iStride2;
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wstart *= iStride3;
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wend *= iStride3;
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T max = -DataTypeUtils::max<T>();
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for (sd::LongType kh = hstart; kh < hend; kh += iStep2)
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for (sd::LongType kw = wstart; kw < wend; kw += iStep3) {
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T val = pIn[kh + kw];
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if (val > max) max = val;
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}
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out[b * oStride0 + c * oStride1 + oh * oStride2 + ow * oStride3] = max;
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}
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}
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}
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}
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};
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samediff::Threads::parallel_for(func, 0, bS, 1, 0, iC, 1);
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}
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/*************************************************************************/
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else if (poolingMode == 1) { // avg
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auto func = PRAGMA_THREADS_FOR_2D {
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sd::LongType hstart, wstart, hend, wend;
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T* pIn;
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for (int b = start_x; b < stop_x; b += inc_x) {
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for (int c = start_y; c < stop_y; c += inc_y) {
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for (int oh = 0; oh < oH; ++oh) {
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for (int ow = 0; ow < oW; ++ow) {
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pIn = in + b * iStride0 + c * iStride1;
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hstart = oh * sH - pH;
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wstart = ow * sW - pW;
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hend = hstart + kHEff;
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wend = wstart + kWEff;
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if (hstart < 0)
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hstart += dH * ((-hstart + dH - 1) / dH);
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if (wstart < 0)
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wstart += dW * ((-wstart + dW - 1) / dW);
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if (hend > iH)
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hend -= dH * ((hend - iH + dH - 1) / dH);
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if (wend > iW)
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wend -= dW * ((wend - iW + dW - 1) / dW);
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hstart *= iStride2;
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hend *= iStride2;
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wstart *= iStride3;
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wend *= iStride3;
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T sum = static_cast<T>(0.f);
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for (sd::LongType kh = hstart; kh < hend; kh += iStep2)
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for (sd::LongType kw = wstart; kw < wend; kw += iStep3)
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sum += pIn[kh + kw];
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if (extraParam0 == 0) { // Exclude padding
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int a = (hend - hstart) / iStep2 + ((hend - hstart) % iStep2 == 0 ? 0 : 1);
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int r = (wend - wstart) / iStep3 + ((wend - wstart) % iStep3 == 0 ? 0 : 1);
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sum /= static_cast<T>(a * r); // Accounts for dilation
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} else if (extraParam0 == 1) // Include padding
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sum /= kProd;
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out[b * oStride0 + c * oStride1 + oh * oStride2 + ow * oStride3] = sum;
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}
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}
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}
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}
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};
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samediff::Threads::parallel_for(func, 0, bS, 1, 0, iC, 1);
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}
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/*************************************************************************/
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else if (poolingMode == 2) { // pnorm
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auto func = PRAGMA_THREADS_FOR_2D {
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sd::LongType hstart, wstart, hend, wend;
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T* pIn;
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for (int b = start_x; b < stop_x; b += inc_x) {
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for (int c = start_y; c < stop_y; c += inc_y) {
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for (int oh = 0; oh < oH; ++oh) {
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for (int ow = 0; ow < oW; ++ow) {
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pIn = in + b * iStride0 + c * iStride1;
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hstart = oh * sH - pH;
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wstart = ow * sW - pW;
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hend = hstart + kHEff;
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wend = wstart + kWEff;
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if (hstart < 0)
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hstart += dH * ((-hstart + dH - 1) / dH);
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if (wstart < 0)
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wstart += dW * ((-wstart + dW - 1) / dW);
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if (hend > iH)
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hend -= dH * ((hend - iH + dH - 1) / dH);
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if (wend > iW)
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wend -= dW * ((wend - iW + dW - 1) / dW);
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hstart *= iStride2;
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hend *= iStride2;
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wstart *= iStride3;
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wend *= iStride3;
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T sum = static_cast<T>(0.f);
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for (sd::LongType kh = hstart; kh < hend; kh += iStep2)
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for (sd::LongType kw = wstart; kw < wend; kw += iStep3)
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sum += sd::math::sd_pow<T, T, T>(sd::math::sd_abs<T,T>(pIn[kh + kw]), static_cast<T>(extraParam0));
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sum = sd::math::sd_pow<T, T, T>(sum, static_cast<T>((T)1.f) / extraParam0);
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out[b * oStride0 + c * oStride1 + oh * oStride2 + ow * oStride3] = sum;
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}
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}
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}
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}
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};
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samediff::Threads::parallel_for(func, 0, bS, 1, 0, iC, 1);
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} else {
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char errorMsg[512];
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snprintf(errorMsg, sizeof(errorMsg),
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"ConvolutionUtils::pooling2d: pooling mode argument can take three values only: 0, 1, 2, but got %i instead!",
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poolingMode);
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THROW_EXCEPTION(errorMsg);
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}
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}
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void ConvolutionUtils::pooling2d(sd::graph::Context& block, NDArray& input, NDArray& output, const LongType kH,
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const LongType kW, const LongType sH, const LongType sW, const LongType pH, const LongType pW, const LongType dH,
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const LongType dW, const PoolingType poolingMode, const int extraParam0) {
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BUILD_SINGLE_SELECTOR(input.dataType(), pooling2d_,
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(block, input, output, kH, kW, sH, sW, pH, pW, dH, dW, poolingMode, extraParam0),
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SD_NUMERIC_TYPES);
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}
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} // namespace ops
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} // namespace sd
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