95 lines
4.7 KiB
C++
95 lines
4.7 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 19.01.18.
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//
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#ifndef LIBND4J_S_T_B_H
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#define LIBND4J_S_T_B_H
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#include <ops/declarable/helpers/helpers.h>
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namespace nd4j {
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namespace ops {
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namespace helpers {
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void batchToSpace(nd4j::LaunchContext* context, const NDArray& input, NDArray& output, const uint cropBottom, const uint cropTop, const uint cropLeft, const uint cropRight, const uint blockSize);
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void spaceToBatch(nd4j::LaunchContext* context, const NDArray& input, NDArray& output, const uint padBottom, const uint padTop, const uint padLeft, const uint padRight, const uint blockSize);
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void spaceToBatchND(nd4j::LaunchContext* context, const NDArray& input, const NDArray& blockShape, const NDArray& padding, NDArray& output);
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void batchToSpaceND(nd4j::LaunchContext* context, const NDArray& input, const NDArray& blockShape, const NDArray& crop, NDArray& output);
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/*
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// this method MUST be platform-specific
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template <typename T, int NUM_BLOCK_DIMS, bool B2S>
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void _execute(nd4j::LaunchContext * context, void *ptrSpace, const Nd4jLong *space_shape, const Nd4jLong *space_strides, const Nd4jLong *block_shape, const Nd4jLong *pad_start, const Nd4jLong *block_offsets, void *ptrBatch, const Nd4jLong *batch_shape, const Nd4jLong *batch_strides);
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template <int NUM_BLOCK_DIMS, bool B2S>
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FORCEINLINE void _prepare(nd4j::LaunchContext * context, NDArray * space, NDArray *batch, const Nd4jLong block_array[NUM_BLOCK_DIMS], const Nd4jLong padding_array[NUM_BLOCK_DIMS * 2]) {
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Nd4jLong pad_start[NUM_BLOCK_DIMS];
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Nd4jLong block_shape[NUM_BLOCK_DIMS];
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Nd4jLong space_shape[NUM_BLOCK_DIMS];
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Nd4jLong batch_shape[NUM_BLOCK_DIMS];
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const int batchSize = batch->sizeAt(0);
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const int space_size = space->sizeAt(0);
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#pragma unroll
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for (int block_dim = 0; block_dim < NUM_BLOCK_DIMS; block_dim++) {
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pad_start[block_dim] = padding_array[block_dim * 2];
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block_shape[block_dim] = block_array[block_dim];
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space_shape[block_dim] = space->sizeAt(block_dim + 1);
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batch_shape[block_dim] = batch->sizeAt(block_dim + 1);
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}
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auto space_strides = space->stridesOf();
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auto batch_strides = batch->stridesOf();
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// TODO: this loop should be moved to _execute phase
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for (int batch_b = 0; batch_b < batchSize; ++batch_b) {
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const Nd4jLong space_b = batch_b % space_size;
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Nd4jLong block_index = batch_b / space_size;
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Nd4jLong block_offsets[NUM_BLOCK_DIMS];
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for (Nd4jLong block_dim = NUM_BLOCK_DIMS - 1; block_dim >= 0; --block_dim) {
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block_offsets[block_dim] = block_dim > 0 ? block_index % block_shape[block_dim] : block_index;
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block_index /= block_shape[block_dim];
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}
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Nd4jLong space_offset = space_b * space_strides[0];
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Nd4jLong batch_offset = batch_b * batch_strides[0];
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auto xType = space->dataType();
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//_execute<T, NUM_BLOCK_DIMS, B2S>(space->buffer() + space_offset, space_shape, &space_strides[1], block_shape, pad_start, block_offsets, batch->buffer() + batch_offset, batch_shape, &batch_strides[1]);
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BUILD_SINGLE_PARTIAL_SELECTOR(xType, _execute<, (NUM_BLOCK_DIMS, B2S>(context, space->bufferWithOffset(space_offset), space_shape, &space_strides[1], block_shape, pad_start, block_offsets, batch->bufferWithOffset(batch_offset), batch_shape, &batch_strides[1])), LIBND4J_TYPES);
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}
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};
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Nd4jStatus _spaceToBatch(nd4j::LaunchContext * context, int internal_block_dims, NDArray *input, NDArray *output, std::vector<Nd4jLong> &internal_input_shape, std::vector<Nd4jLong> &internal_output_shape, Nd4jLong *block_shape, Nd4jLong *paddings);
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Nd4jStatus _batchToSpace(nd4j::LaunchContext * context, int internal_block_dims, NDArray *input, NDArray *output, std::vector<Nd4jLong> &internal_input_shape, std::vector<Nd4jLong> &internal_output_shape, Nd4jLong *block_shape, Nd4jLong *crops);
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*/
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}
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}
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}
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#endif //LIBND4J_S_T_B_H
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