ac7fb903d7
* initial commit Signed-off-by: raver119@gmail.com <raver119@gmail.com> * some minor singleton changes Signed-off-by: raver119@gmail.com <raver119@gmail.com> * more iterations Signed-off-by: raver119 <raver119@gmail.com> * more singletons updated Signed-off-by: raver119 <raver119@gmail.com> * more singletons updated Signed-off-by: raver119 <raver119@gmail.com> * more changes Signed-off-by: raver119@gmail.com <raver119@gmail.com> * CUDA updates Signed-off-by: raver119@gmail.com <raver119@gmail.com> * Java side update Signed-off-by: raver119@gmail.com <raver119@gmail.com> * one commented out test Signed-off-by: raver119@gmail.com <raver119@gmail.com>
103 lines
3.7 KiB
C++
103 lines
3.7 KiB
C++
/*******************************************************************************
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* Copyright (c) 2015-2018 Skymind, Inc.
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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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* 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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if (input->isScalar()) {
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output->assign(input);
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return Status::OK();
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}
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Nd4jLong axis = block.numI() > 0 ? INT_ARG(0) : INPUT_VARIABLE(1)->e<int>(0);
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if (axis < 0)
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axis += input->rankOf() + 1;
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REQUIRE_TRUE(axis >= 0 && axis <= input->rankOf()+1, 0, "ExpandDims: axis should be in range of 0...%i in this case, but got %i instead", input->rankOf() + 1, axis);
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std::vector<Nd4jLong> shape(input->rankOf());
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for(int e = 0; e < input->rankOf(); e++)
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shape[input->sizeAt(e)];
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shape.insert(shape.begin() + axis, 1);
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if (input->ews() == 1 && output->ews() == 1 && input->ordering() == output->ordering()) {
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output->dataBuffer()->copyBufferFrom(*input->dataBuffer().get(), output->lengthOf() * DataTypeUtils::sizeOfElement(output->dataType()), 0, input->bufferOffset());
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} else {
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auto tmp = input->reshape(input->ordering(), shape);
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output->assign(tmp);
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}
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return Status::OK();
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}
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DECLARE_TYPES(expand_dims) {
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getOpDescriptor()
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->setAllowedInputTypes(sd::DataType::ANY)
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->setSameMode(true);
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}
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DECLARE_SHAPE_FN(expand_dims) {
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auto inShape = inputShape->at(0);
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// 0D scalar edge case
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if (shape::rank(inShape) == 0) {
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Nd4jLong x = 1;
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auto newShape = ConstantShapeHelper::getInstance().createShapeInfo(ArrayOptions::dataType(inShape), 'c', 1, &x);
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return SHAPELIST(newShape);
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}
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// FIXME: temp workaround for TF
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if (shape::isScalar(inShape)) {
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auto newShape = ConstantShapeHelper::getInstance().createShapeInfo(ArrayOptions::dataType(inShape), 'c', 2, shape::shapeOf(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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Nd4jLong axis = block.numI() > 0 ? INT_ARG(0) : INPUT_VARIABLE(1)->e<int>(0);
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if (axis < 0)
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axis += x_rank + 1;
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std::vector<Nd4jLong> shape;
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for(int e = 0; e < x_rank; e++)
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shape.emplace_back(shape::shapeOf(inShape)[e]);
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shape.insert(shape.begin() + axis, 1);
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auto newShape = ConstantShapeHelper::getInstance().createShapeInfo(ArrayOptions::dataType(inShape), order, shape);
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return SHAPELIST(newShape);
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}
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}
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}
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#endif |