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 raver119 on 17.10.2017.
+//
+
+#include <system/op_boilerplate.h>
+#if NOT_EXCLUDED(OP_im2col)
+
+#include <ops/declarable/CustomOperations.h>
+#include <ops/declarable/helpers/col2im.h>
+#include <ops/declarable/helpers/convolutions.h>
+#include <ops/declarable/helpers/im2col.h>
+
+namespace sd {
+namespace ops {
+CUSTOM_OP_IMPL(im2col, 1, 1, false, 0, 9) {
+  auto x = INPUT_VARIABLE(0);
+  auto z = OUTPUT_NULLIFIED(0);
+
+  REQUIRE_TRUE(x->rankOf() == 4, 0, "im2col input should be 4D, but got %i instead", x->rankOf());
+  REQUIRE_TRUE(z->rankOf() == 6, 0, "im2col output should be 6D, but got %i instead", z->rankOf());
+
+  LongType kernelHeight = INT_ARG(0);
+  LongType kernelWidth = INT_ARG(1);
+  LongType strideY = INT_ARG(2);
+  LongType strideX = INT_ARG(3);
+  LongType padHeight = INT_ARG(4);
+  LongType padWidth = INT_ARG(5);
+  LongType dY = INT_ARG(6);  // Dilation, height/y dimension
+  LongType dX = INT_ARG(7);  // Dilation, width/x dimension
+  bool isSameMode = INT_ARG(8) > 0;
+  double zeroPadVal = 0.0;
+  if (block.getTArguments()->size() > 0) zeroPadVal = T_ARG(0);
+
+  // FIXME: zeropad value is void
+  LaunchContext* ctx = block.launchContext();
+  NDArray *zero =  NDArrayFactory::create(zeroPadVal, block.launchContext());
+  sd::ops::helpers::im2col(*ctx, *x, *z, kernelHeight, kernelWidth, strideY, strideX, padHeight, padWidth, dY, dX,
+                          *zero);
+
+  delete zero;
+  return sd::Status::OK;
+}
+
+DECLARE_SHAPE_FN(im2col) {
+  auto inShape = inputShape->at(0);
+
+  LongType bS = shape::shapeOf(inShape)[0];
+  LongType iD = shape::shapeOf(inShape)[1];
+  LongType inY = shape::shapeOf(inShape)[2];
+  LongType inX = shape::shapeOf(inShape)[3];
+
+  LongType kY = INT_ARG(0);
+  LongType kX = INT_ARG(1);
+  LongType sY = INT_ARG(2);
+  LongType sX = INT_ARG(3);
+  sd::LongType pY = INT_ARG(4);
+  sd::LongType pX = INT_ARG(5);
+  LongType dY = INT_ARG(6);  // Dilation, height/y dimension
+  LongType dX = INT_ARG(7);  // Dilation, width/x dimension
+  int paddingMode = INT_ARG(8);
+  bool isSameMode = INT_ARG(8) == 1;
+  // output is always 6d for im2col
+  sd::LongType* zShape;
+  ALLOCATE(zShape, block.getWorkspace(), shape::shapeInfoLength(6), sd::LongType);
+
+  LongType oY = 0;
+  LongType oX = 0;
+
+  ConvolutionUtils::calcOutSizePool2D(oY, oX, kY, kX, sY, sX, pY, pX, dY, dX, inY, inX, paddingMode);
+
+  if (isSameMode) ConvolutionUtils::calcPadding2D(pY, pX, oY, oX, inY, inX, kY, kX, sY, sX, dY, dX);
+
+  zShape[0] = 6;
+  zShape[1] = bS;
+  zShape[2] = iD;
+  zShape[3] = kY;
+  zShape[4] = kX;
+  zShape[5] = oY;
+  zShape[6] = oX;
+
+  zShape[shape::shapeInfoLength(zShape) - 2] = 1;
+  zShape[shape::shapeInfoLength(zShape) - 1] = 99;
+
+  ShapeUtils::updateStridesAndType(zShape, inShape, 'c');
+
+  return SHAPELIST(CONSTANT(zShape));
+}
+
+CUSTOM_OP_IMPL(im2col_bp, 2, 1, false, 0, 9) {
+  auto input = INPUT_VARIABLE(0);
+  auto gradAtOutput = INPUT_VARIABLE(1);
+  auto z = OUTPUT_NULLIFIED(0);
+
+  REQUIRE_TRUE(input->rankOf() == 4, 0, "im2col_bp input should be 4D, but got %i instead", input->rankOf());
+  REQUIRE_TRUE(gradAtOutput->rankOf() == 6, 0,
+               "im2col_bp gradient at output (input idx 1) should be 6D, but got %i instead", gradAtOutput->rankOf());
+  REQUIRE_TRUE(z->rankOf() == 4, 0, "im2col_bp output (grad at input) should be 4D, but got %i instead", z->rankOf());
+
+  LongType kernelHeight = INT_ARG(0);
+  LongType kernelWidth = INT_ARG(1);
+  LongType strideY = INT_ARG(2);
+  LongType strideX = INT_ARG(3);
+  LongType pH = INT_ARG(4);
+  LongType pW = INT_ARG(5);
+  LongType dY = INT_ARG(6);  // Dilation, height/y dimension
+  LongType dX = INT_ARG(7);  // Dilation, width/x dimension
+
+  // Assuming NCHW format here
+  int imgH = input->sizeAt(2);
+  int imgW = input->sizeAt(3);
+
+  LaunchContext* ctx = block.launchContext();
+  // FIXME:: all helpers should accept NDArray
+  ops::helpers::col2im(*ctx, gradAtOutput, z, strideY, strideX, pH, pW, imgH, imgW, dY, dX);
+
+  return sd::Status::OK;
+}
+
+DECLARE_TYPES(im2col) {
+  getOpDescriptor()
+      ->setAllowedInputTypes(0, DataType::ANY)
+      ->setAllowedOutputTypes(0, DataType::INHERIT)
+      ->setSameMode(true);
+}
+
+DECLARE_TYPES(im2col_bp) {
+  getOpDescriptor()
+      ->setAllowedInputTypes(0, DataType::ANY)
+      ->setAllowedOutputTypes(0, DataType::INHERIT)
+      ->setSameMode(true);
+}
+
+DECLARE_SHAPE_FN(im2col_bp) {
+  return SHAPELIST(CONSTANT(inputShape->at(0)));
+}
+}  // namespace ops
+}  // namespace sd
+
+#endif