blob: 52d2f11a464bc21a273bf1fb35a3f2412050c07d [file] [log] [blame]
/*
* Licensed to the Apache Software Foundation (ASF) under one
* or more contributor license agreements. See the NOTICE file
* distributed with this work for additional information
* regarding copyright ownership. The ASF licenses this file
* to you under the Apache License, Version 2.0 (the
* "License"); you may not use this file except in compliance
* with the License. You may obtain a copy of the License at
*
* http://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.
*/
/*!
* Copyright (c) 2019 by Contributors
* \file crop-cc.h
* \brief the image crop operator registration
*/
#include "mxnet/base.h"
#include "crop-inl.h"
#include "../operator_common.h"
#include "../elemwise_op_common.h"
namespace mxnet {
namespace op {
namespace image {
DMLC_REGISTER_PARAMETER(CropParam);
NNVM_REGISTER_OP(_image_crop)
.describe(R"code(Crop an image NDArray of shape (H x W x C) or (N x H x W x C)
to the given size.
Example:
.. code-block:: python
image = mx.nd.random.uniform(0, 255, (4, 2, 3)).astype(dtype=np.uint8)
mx.nd.image.crop(image, 1, 1, 2, 2)
[[[144 34 4]
[ 82 157 38]]
[[156 111 230]
[177 25 15]]]
<NDArray 2x2x3 @cpu(0)>
image = mx.nd.random.uniform(0, 255, (2, 4, 2, 3)).astype(dtype=np.uint8)
mx.nd.image.crop(image, 1, 1, 2, 2)
[[[[ 35 198 50]
[242 94 168]]
[[223 119 129]
[249 14 154]]]
[[[137 215 106]
[ 79 174 133]]
[[116 142 109]
[ 35 239 50]]]]
<NDArray 2x2x2x3 @cpu(0)>
)code" ADD_FILELINE)
.set_num_inputs(1)
.set_num_outputs(1)
.set_attr_parser(ParamParser<CropParam>)
.set_attr<mxnet::FInferShape>("FInferShape", CropShape)
.set_attr<nnvm::FInferType>("FInferType", ElemwiseType<1, 1>)
.set_attr<FCompute>("FCompute<cpu>", CropOpForward)
.set_attr<nnvm::FGradient>("FGradient", ElemwiseGradUseNone{ "_backward_image_crop" })
.add_argument("data", "NDArray-or-Symbol", "The input.")
.add_arguments(CropParam::__FIELDS__());
NNVM_REGISTER_OP(_backward_image_crop)
.set_attr_parser(ParamParser<CropParam>)
.set_num_inputs(1)
.set_num_outputs(1)
.set_attr<nnvm::TIsBackward>("TIsBackward", true)
.set_attr<FCompute>("FCompute<cpu>", CropOpBackward);
} // namespace image
} // namespace op
} // namespace mxnet