wehub-resource-sync
101 lines
3.5 KiB
C++
101 lines
3.5 KiB
C++
/* ******************************************************************************
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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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// Created by raver119 on 02.11.2017.
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//
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#include <system/op_boilerplate.h>
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#if NOT_EXCLUDED(OP_expand_dims)
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#include <ops/declarable/CustomOperations.h>
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namespace sd {
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namespace ops {
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CUSTOM_OP_IMPL(expand_dims, 1, 1, false, 0, -2) {
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auto input = INPUT_VARIABLE(0);
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auto output = OUTPUT_VARIABLE(0);
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LongType axis = block.numI() > 0 ? INT_ARG(0) : INPUT_VARIABLE(1)->e<LongType>(0);
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if (axis < 0) axis += input->rankOf() + 1;
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if(!input->isEmpty() && !input->isScalar())
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REQUIRE_TRUE(axis >= 0 && axis <= input->rankOf(), 0,
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"ExpandDims: axis should be in range of 0...%i in this case, but got %i instead", input->rankOf() + 1,
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axis);
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//note we used to have a specific copy case here but we should
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//be abstracting away data copy and reshape details like buffer copying
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if(input->isEmpty()) {
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return Status::OK;
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}
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NDArray::copyDataForAssign(input,output,output->shapeInfo(),true);
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return Status::OK;
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}
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DECLARE_TYPES(expand_dims) { getOpDescriptor()->setAllowedInputTypes(ANY)->setSameMode(true); }
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DECLARE_SHAPE_FN(expand_dims) {
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auto inShape = inputShape->at(0);
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auto rank = shape::rank(inShape);
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// 0D scalar edge case
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if (shape::isScalar(inShape)) {
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if(rank < 1) {
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LongType x = 1;
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auto newShape = ConstantShapeHelper::getInstance().createShapeInfo(ArrayOptions::dataType(inShape), 'c', 1, &x, -1);
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return SHAPELIST(newShape);
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} else {
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std::vector<LongType> x = {1, 1};
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auto newShape = ConstantShapeHelper::getInstance().createShapeInfo(ArrayOptions::dataType(inShape), 'c', 2, x.data(), -1);
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return SHAPELIST(newShape);
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}
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}
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auto input = INPUT_VARIABLE(0);
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if(input->isEmpty() && input->rankOf() < 1) {
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auto newShape = ConstantShapeHelper::getInstance().emptyShapeInfo(ArrayOptions::dataType(inShape));
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return SHAPELIST(newShape);
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}
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auto x_rank = shape::rank(inShape);
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char order = shape::order(inShape);
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LongType axis = block.numI() > 0 ? INT_ARG(0) : INPUT_VARIABLE(1)->e<LongType>(0);
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if (axis < 0) axis += x_rank + 1;
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REQUIRE_TRUE(axis >= 0 && axis <= input->rankOf(), 0,
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"ExpandDims: axis should be in range of 0...%i in this case, but got %i instead", input->rankOf() + 1,
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axis);
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std::vector<LongType> shape;
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for (LongType e = 0; e < x_rank; e++) shape.emplace_back(shape::shapeOf(inShape)[e]);
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shape.insert(shape.begin() + axis, 1);
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auto newShape = input->isEmpty() ? ConstantShapeHelper::getInstance().emptyShapeInfoWithShape(ArrayOptions::dataType(inShape), shape) :
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ConstantShapeHelper::getInstance().createShapeInfo(ArrayOptions::dataType(inShape), order, shape);
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return SHAPELIST(newShape);
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}
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} // namespace ops
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} // namespace sd
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#endif
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