77 lines
3.5 KiB
C++
77 lines
3.5 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 <ops/declarable/helpers/dilation2d.h>
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#include <array/DataTypeUtils.h>
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namespace nd4j {
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namespace ops {
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namespace helpers {
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template <typename X, typename Y>
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static void dilation2d_(NDArray *input, NDArray *weights, NDArray *output, int stride_rows, int stride_cols, int rate_rows, int rate_cols, int pad_top, int pad_left) {
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const int batch = input->sizeAt(0);
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const int input_rows = input->sizeAt(1);
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const int input_cols = input->sizeAt(2);
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const int depth = input->sizeAt(3);
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const int filter_rows = weights->sizeAt(0);
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const int filter_cols = weights->sizeAt(1);
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const int output_rows = output->sizeAt(1);
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const int output_cols = output->sizeAt(2);
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PRAGMA_OMP_PARALLEL_FOR_SIMD
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for (int b = 0; b < batch; ++b) {
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for (int h_out = 0; h_out < output_rows; ++h_out) {
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int h_beg = h_out * stride_rows - pad_top;
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for (int w_out = 0; w_out < output_cols; ++w_out) {
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int w_beg = w_out * stride_cols - pad_left;
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for (int d = 0; d < depth; ++d) {
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Y cur_val = -DataTypeUtils::max<Y>();
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for (int h = 0; h < filter_rows; ++h) {
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const int h_in = h_beg + h * rate_rows;
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if (h_in >= 0 && h_in < input_rows) {
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for (int w = 0; w < filter_cols; ++w) {
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const int w_in = w_beg + w * rate_cols;
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if (w_in >= 0 && w_in < input_cols) {
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const Y val = input->e<Y>(b, h_in, w_in, d) + weights->e<Y>(h, w, d);
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if (val > cur_val) {
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cur_val = val;
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}
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}
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}
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}
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}
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(*output).p<Y>(b, h_out, w_out, d, cur_val);
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}
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}
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}
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}
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};
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void dilation2d(nd4j::LaunchContext * context, NDArray *input, NDArray *weights, NDArray *output, int stride_rows, int stride_cols, int rate_rows, int rate_cols, int pad_top, int pad_left) {
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BUILD_DOUBLE_SELECTOR(input->dataType(), output->dataType(), dilation2d_, (input, weights, output, stride_rows, stride_cols, rate_rows, rate_cols, pad_top, pad_left), LIBND4J_TYPES, FLOAT_TYPES);
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}
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BUILD_DOUBLE_TEMPLATE(template void dilation2d_, (NDArray *input, NDArray *weights, NDArray *output, int stride_rows, int stride_cols, int rate_rows, int rate_cols, int pad_top, int pad_left), LIBND4J_TYPES, FLOAT_TYPES);
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}
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}
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} |