141 lines
5.4 KiB
C++
141 lines
5.4 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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// @author raver119@gmail.com
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//
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#include <op_boilerplate.h>
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#if NOT_EXCLUDED(OP_unstack)
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#include <ops/declarable/CustomOperations.h>
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#include <helpers/ConstantTadHelper.h>
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namespace nd4j {
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namespace ops {
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CUSTOM_OP_IMPL(unstack, 1, -1, false, 0, 1) {
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auto input = INPUT_VARIABLE(0);
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auto dim = INT_ARG(0);
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if (dim < 0)
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dim += input->rankOf();
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REQUIRE_TRUE(dim < input->rankOf(), 0, "Unstack dimension should be lower then rank of input %i, but got dimension=%i !", input->rankOf(), dim);
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REQUIRE_TRUE(dim >= 0, 0, "Unstack dimension should be non-negative value, but got %i !", dim);
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if(input->isEmpty())
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return Status::OK();
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std::vector<int> dims;
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for (int e = 0; e < input->rankOf(); e++)
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if (e != dim)
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dims.emplace_back(e);
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if (dims.size() == 0 && input->rankOf() == 1) { // split vector into lenthOf scalars
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for (Nd4jLong e = 0; e < input->lengthOf(); e++) {
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auto outE = OUTPUT_VARIABLE(e);
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outE->assign(input->e(e));
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}
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}
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auto tads = input->allTensorsAlongDimension(dims);
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//nd4j_printf("Tad size: %d\n",tads->size());
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for (int e = 0; e < tads->size(); e++) {
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//nd4j_printf("Calling assign at index %d\n",e);
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auto outE = OUTPUT_VARIABLE(e);
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auto tadAtE = tads->at(e);
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outE->assign(tadAtE);
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this->storeResult(block, e, *outE);
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}
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delete tads;
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return Status::OK();
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}
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DECLARE_SYN(unpack, unstack);
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DECLARE_SHAPE_FN(unstack) {
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auto inShape = inputShape->at(0);
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auto dim = INT_ARG(0);
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if (dim < 0)
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dim += shape::rank(inShape);
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REQUIRE_TRUE(dim < inShape[0], 0, "UNSTACK op: dimension should be lower then rank of input %i, but got dimension=%i !", inShape[0], dim);
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REQUIRE_TRUE(dim >= 0, 0, "UNSTACK op: dimension should be non-negative value, but got %i !", dim);
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if(ArrayOptions::arrayType(inShape) == ArrayType::EMPTY) {
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if(shape::shapeOf(inShape)[dim] == 0)
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return SHAPELIST();
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const Nd4jLong numTads = shape::shapeOf(inShape)[dim];
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std::vector<Nd4jLong> outShape;
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for(uint i = 0; i < shape::rank(inShape); ++i)
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if(i != dim)
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outShape.push_back(shape::shapeOf(inShape)[i]);
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auto result = SHAPELIST();
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for(uint i = 0; i < numTads; ++i)
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result->push_back(ConstantShapeHelper::getInstance()->createShapeInfo(ArrayOptions::dataType(inShape), shape::order(inShape), outShape));
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return result;
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}
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std::vector<int> dims;
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for (int e = 0; e < shape::rank(inShape); e++)
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if (e != dim)
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dims.emplace_back(e);
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if (dims.size() == 0 && shape::rank(inShape) == 1) { // split vector into lenthOf scalars
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//
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auto result = SHAPELIST();
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for (Nd4jLong e = 0; e < shape::length(inShape); e++)
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result->push_back(ConstantShapeHelper::getInstance()->scalarShapeInfo(ArrayOptions::dataType(inShape)));
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return result;
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}
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auto tadPack = nd4j::ConstantTadHelper::getInstance()->tadForDimensions(inShape, dims);
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auto numTads = tadPack.numberOfTads();
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std::vector<Nd4jLong> shape(shape::rank(tadPack.primaryShapeInfo()));
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for (int e = 0; e < shape::rank(tadPack.primaryShapeInfo()); e++)
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shape[e] = shape::shapeOf(tadPack.primaryShapeInfo())[e];
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// remove leading and trailing 1
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if (inShape[0] == 2 && shape.size() == 2) {
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if (shape[0] == 1) {
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shape.erase(shape.begin());
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} else if (shape[1] == 1) {
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shape.erase(shape.end());
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}
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}
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auto result = SHAPELIST();
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for (int e = 0; e < numTads; e++) {
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auto newShape = ConstantShapeHelper::getInstance()->createShapeInfo(ArrayOptions::dataType(inShape), shape::order(inShape), shape);
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result->push_back(newShape);
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}
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return result;
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}
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DECLARE_TYPES(unstack) {
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getOpDescriptor()
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->setAllowedInputTypes({ALL_FLOATS, ALL_INTS})
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->setSameMode(true);
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}
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}
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}
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#endif |