/* ****************************************************************************** * * * 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 GS at 3/30/2018 // #include #include namespace sd { namespace ops { CUSTOM_OP_IMPL(extract_image_patches, 1, 1, false, 0, 7) { auto input = INPUT_VARIABLE(0); auto output = OUTPUT_VARIABLE(0); int ksizeRows = INT_ARG(0); int ksizeCols = INT_ARG(1); int kstrideRows = INT_ARG(2); int kstrideCols = INT_ARG(3); int krateRows = INT_ARG(4); int krateCols = INT_ARG(5); bool isSame = INT_ARG(6) != 0; REQUIRE_TRUE(input->rankOf() == 4, 0, "extract_image_patches: The rank of input array should be 4, but %i is given", input->rankOf()); // if (output->isSameShape(input)) output->assign(input); else { output->nullify(); helpers::extractPatches(block.launchContext(), input, output, ksizeRows, ksizeCols, kstrideRows, kstrideCols, krateRows, krateCols, isSame); } return Status::OK(); } DECLARE_TYPES(extract_image_patches) { getOpDescriptor() ->setAllowedInputTypes(sd::DataType::ANY) ->setSameMode(true); } DECLARE_SHAPE_FN(extract_image_patches) { auto in = inputShape->at(0); int outRank = shape::rank(in); Nd4jLong *outputShape = nullptr; int ksizeRowsEffective = INT_ARG(0) + (INT_ARG(0) - 1) * (INT_ARG(4) - 1); int ksizeColsEffective = INT_ARG(1) + (INT_ARG(1) - 1) * (INT_ARG(5) - 1); auto batchSizeDim = shape::sizeAt(in, 0); auto inputRowsDim = shape::sizeAt(in, 1); auto inputColsDim = shape::sizeAt(in, 2); auto outputDepthDim = shape::sizeAt(in, 3) * INT_ARG(0) * INT_ARG(1); // last dim * ksizeRows * ksizeCols auto inputRowSize = inputRowsDim; //shape::sizeAt(in, inputRowsDim); auto inputColSize = inputColsDim; //shape::sizeAt(in, inputColsDim); Nd4jLong outRowSize; Nd4jLong outColSize; if (INT_ARG(6) == 0) { // Padding is "VALID": outRowSize = (inputRowSize - ksizeRowsEffective + INT_ARG(2)) / INT_ARG(2); outColSize = (inputColSize - ksizeColsEffective + INT_ARG(3)) / INT_ARG(3); } else { // Padding is "SAME": outRowSize = (inputRowSize + INT_ARG(2) - 1) / INT_ARG(2); outColSize = (inputColSize + INT_ARG(3) - 1) / INT_ARG(3); } ALLOCATE(outputShape, block.getWorkspace(), shape::shapeInfoLength(outRank), Nd4jLong); outputShape[0] = outRank; outputShape[1] = batchSizeDim; outputShape[2] = outRowSize; outputShape[3] = outColSize; outputShape[4] = outputDepthDim; ShapeUtils::updateStridesAndType(outputShape, in, shape::order(in)); return SHAPELIST(CONSTANT(outputShape)); } } }