chore: import upstream snapshot with attribution

2026-07-13 12:47:05 +08:00
commit 4f3b7da785
7394 changed files with 2005594 additions and 0 deletions
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+/*
+ *  ******************************************************************************
+ *  *
+ *  *
+ *  * This program and the accompanying materials are made available under the
+ *  * terms of the Apache License, Version 2.0 which is available at
+ *  * https://www.apache.org/licenses/LICENSE-2.0.
+ *  *
+ *  * See the NOTICE file distributed with this work for additional
+ *  * information regarding copyright ownership.
+ *  * 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.
+ *  *
+ *  * SPDX-License-Identifier: Apache-2.0
+ *  *****************************************************************************
+ */
+
+// Created by Abdelrauf 2020
+
+#include <ops/declarable/OpRegistrator.h>
+#include <ops/declarable/PlatformHelper.h>
+#include <ops/declarable/helpers/convolutions.h>
+#include <system/platform_boilerplate.h>
+
+#include "armcomputeUtils.h"
+
+namespace sd {
+namespace ops {
+namespace platforms {
+
+//////////////////////////////////////////////////////////////////////////
+PLATFORM_IMPL(maxpool2d, ENGINE_CPU) {
+  auto input = INPUT_VARIABLE(0);
+  auto output = OUTPUT_VARIABLE(0);
+
+  REQUIRE_TRUE(input->rankOf() == 4, 0,
+               "MAXPOOL2D ARMCOMPUTE  OP: input array should have rank of 4, but got %i instead", input->rankOf());
+
+  // 0,1 - kernel Height/Width; 2,3 - stride Height/Width; 4,5 - pad Height/Width; 6,7 - dilation Height/Width; 8 - same
+  // mode;
+  const sd::LongType kH = INT_ARG(0);
+  const sd::LongType kW = INT_ARG(1);
+  const sd::LongType sH = INT_ARG(2);
+  const sd::LongType sW = INT_ARG(3);
+  sd::LongType pH = INT_ARG(4);
+  sd::LongType pW = INT_ARG(5);
+  const sd::LongType dH = INT_ARG(6);
+  const sd::LongType dW = INT_ARG(7);
+  const int paddingMode = INT_ARG(8);
+  // const int extraParam0 = INT_ARG(9);
+  const int isNCHW = block.getIArguments()->size() > 10 ? !INT_ARG(10) : 1;  // INT_ARG(10): 1-NHWC, 0-NCHW
+
+  auto dataLayout = isNCHW ? arm_compute::DataLayout::NCHW : arm_compute::DataLayout::NHWC;
+
+  // Calculate individual paddings
+  sd::LongType padLeft, padTop, padRight, padBottom;
+  sd::LongType bS, iC, iH, iW, oC, oH,
+      oW;  // batch size, input channels, input height/width, output channels, output height/width;
+  sd::LongType indIOioC, indIiH, indWoC, indWiC, indWkH, indOoH;  // corresponding indexes
+  ConvolutionUtils::getSizesAndIndexesConv2d(isNCHW, 0, *input, *output, bS, iC, iH, iW, oC, oH, oW, indIOioC, indIiH,
+                                             indWiC, indWoC, indWkH, indOoH);
+
+  if (paddingMode) {
+    ConvolutionUtils::calcPadding2D(pH, pW, oH, oW, iH, iW, kH, kW, sH, sW, dH, dW);
+  }
+  padLeft = pW;
+  padTop = pH;
+  padRight = (oW - 1) * sW - iW + kW - pW;
+  padBottom = (oH - 1) * sH - iH + kH - pH;
+
+  auto poolPad = arm_compute::PadStrideInfo(sW, sH, padLeft, padRight, padTop, padBottom,
+                                            arm_compute::DimensionRoundingType::FLOOR);
+  auto poolInfo =
+      arm_compute::PoolingLayerInfo(arm_compute::PoolingType::MAX, arm_compute::Size2D(kW, kH), dataLayout, poolPad);
+  ArmFunction<arm_compute::NEPoolingLayer> pool;
+
+  pool.configure(input, output, dataLayout, poolInfo);
+
+  pool.run();  // run function
+
+  return sd::Status::OK;
+}
+
+//////////////////////////////////////////////////////////////////////////
+PLATFORM_CHECK(maxpool2d, ENGINE_CPU) {
+  auto input = INPUT_VARIABLE(0);
+  auto output = OUTPUT_VARIABLE(0);
+  const int dH = INT_ARG(6);
+  const int dW = INT_ARG(7);
+  // Data types supported: QASYMM8/QASYMM8_SIGNED/F16/F32
+  // for now, we will ignore F16 as it shoulde be preconditioned for pool size 2,3 and arm64-v8.2-a architecture
+  Requirements req("ARMCOMPUTE MAXPOOL2d OP");
+  req.expectEq(makeInfoVariable(input->dataType(), TYPE_MSG_INPUT), DataType::FLOAT32) &&
+      req.expectEq(makeInfoVariable(output->dataType(), TYPE_MSG_OUTPUT), DataType::FLOAT32) &&
+      req.expectEq(makeInfoVariable(dH, "dilation#H"), 1) && req.expectEq(makeInfoVariable(dW, "dilation#W"), 1) &&
+      req.expectLessEq(makeInfoVariable(input->rankOf(), RANK_MSG_INPUT), arm_compute::MAX_DIMS) &&
+      req.expectEq(makeInfoVariable(input->ordering(), ORDERING_MSG_INPUT), 'c') &&
+      req.expectEq(makeInfoVariable(input->stridesOf()[input->rankOf() - 1], "input#lastStride"), 1) &&
+      req.expectLessEq(makeInfoVariable(output->rankOf(), RANK_MSG_OUTPUT), arm_compute::MAX_DIMS) &&
+      req.expectEq(makeInfoVariable(output->ordering(), ORDERING_MSG_OUTPUT), 'c') &&
+      req.expectEq(makeInfoVariable(output->stridesOf()[output->rankOf() - 1], "output#lastStride"), 1);
+  req.logTheSuccess();
+  return req;
+}
+
+}  // namespace platforms
+}  // namespace ops
+}  // namespace sd