cavis/libnd4j/include/ops/declarable/generic/convo/dilation2d.cpp

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2019-06-06 14:21:15 +02:00
/*******************************************************************************
* Copyright (c) 2015-2018 Skymind, Inc.
*
* This program and the accompanying materials are made available under the
* terms of the Apache License, Version 2.0 which is available at
* https://www.apache.org/licenses/LICENSE-2.0.
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
* WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
* License for the specific language governing permissions and limitations
* under the License.
*
* SPDX-License-Identifier: Apache-2.0
******************************************************************************/
//
// @author raver119@gmail.com
//
#include <op_boilerplate.h>
#if NOT_EXCLUDED(OP_dilation2d)
#include <ops/declarable/headers/convo.h>
#include <ops/declarable/helpers/dilation2d.h>
namespace nd4j {
namespace ops {
CUSTOM_OP_IMPL(dilation2d, 2, 1, false, 0, 1) {
auto input = INPUT_VARIABLE(0);
auto weights = INPUT_VARIABLE(1);
auto output = OUTPUT_VARIABLE(0);
REQUIRE_TRUE(input->rankOf() == 4, 0, "Dilation2D: input should be 4D");
REQUIRE_TRUE(weights->rankOf() == 3, 0, "Dilation2D: weights should be 3D");
const int batch_size = input->sizeAt(0);
const int depth = input->sizeAt(3);
const bool isSameShape = INT_ARG(0) == 1;
REQUIRE_TRUE(input->sizeAt(3) == weights->sizeAt(2), 0, "Dilation2D: number of input channels doesn't match number of channels in weights: %i vs %i", input->sizeAt(3), weights->sizeAt(2));
std::vector<int> strides(4);
std::vector<int> rates(4);
if (block.width() > 2) {
REQUIRE_TRUE(block.width() >= 4, 0, "Dilation2D: number of input arrays should be 4 at least");
auto r = INPUT_VARIABLE(2);
auto s = INPUT_VARIABLE(3);
strides = s->template asVectorT<int>();
rates = r->template asVectorT<int>();
} else {
REQUIRE_TRUE(block.numI() >= 9, 0, "Dilation2D: number of Int arguments should be 9 at least");
int e = 1;
for (int cnt = 0;cnt < 4; cnt++)
rates[cnt] = INT_ARG(e++);
for (int cnt = 0; cnt < 4; cnt++)
strides[cnt] = INT_ARG(e++);
}
int stride_rows = 0, stride_cols = 0;
int rate_rows = 0, rate_cols = 0;
int pad_top = 0, pad_left = 0;
int out_rows = 0, out_cols = 0;
helpers::_dilation_hw(block.launchContext(), input->shapeInfo(), weights->shapeInfo(), strides, rates, isSameShape, &stride_rows, &stride_cols, &rate_rows, &rate_cols, &pad_top, &pad_left, &out_rows, &out_cols);
REQUIRE_TRUE(out_rows > 0 && out_cols > 0, 0, "Dilation2D: outY and outX should have positive values, but got [%i, %i] instead", out_rows, out_cols);
helpers::dilation2d(block.launchContext(), input, weights, output, stride_rows, stride_cols, rate_rows, rate_cols, pad_top, pad_left);
return Status::OK();
}
DECLARE_TYPES(dilation2d) {
getOpDescriptor()
->setAllowedInputTypes(nd4j::DataType::ANY)
->setAllowedOutputTypes({ALL_FLOATS});
}
DECLARE_SHAPE_FN(dilation2d) {
auto input = inputShape->at(0);
auto weights = inputShape->at(1);
const int batch_size = shape::sizeAt(input, 0);
const int depth = shape::sizeAt(input, 3);
const bool isSameShape = INT_ARG(0) == 1;
std::vector<int> strides(4);
std::vector<int> rates(4);
Nd4jLong *newShape;
if (block.width() > 2) {
auto r = INPUT_VARIABLE(2);
auto s = INPUT_VARIABLE(3);
strides = s->template asVectorT<int>();
rates = r->template asVectorT<int>();
} else {
if (block.numI() < 9) {
newShape = ConstantShapeHelper::getInstance()->scalarShapeInfo(block.dataType());
return SHAPELIST(newShape);
}
int e = 1;
for (int cnt = 0;cnt < 4; cnt++)
rates[cnt] = INT_ARG(e++);
for (int cnt = 0; cnt < 4; cnt++)
strides[cnt] = INT_ARG(e++);
}
int stride_rows = 0, stride_cols = 0;
int rate_rows = 0, rate_cols = 0;
int pad_top = 0, pad_left = 0;
int out_rows = 0, out_cols = 0;
helpers::_dilation_hw(block.launchContext(), input, weights, strides, rates, isSameShape, &stride_rows, &stride_cols, &rate_rows, &rate_cols, &pad_top, &pad_left, &out_rows, &out_cols);
std::array<Nd4jLong, 4> shape = {{batch_size, out_rows, out_cols, depth}};
newShape = ConstantShapeHelper::getInstance()->createShapeInfo(ArrayOptions::dataType(weights), 'c', 4, shape.data());
return SHAPELIST(newShape);
}
}
}
#endif