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- #!/usr/bin/env python3
- # coding: utf-8
- # Copyright 2019 Huawei Technologies Co., Ltd
- #
- # Licensed 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.
-
- """conv_backprop_input"""
- from akg.ops.nn import conv_backprop_input
-
- def Conv2DBackpropInput(out_backprop, input_sizes, filter, filter_shape, pad_list, stride=1, dilation=1):
- """back propagation of 2d convolution on input"""
- if len(pad_list) != 4:
- raise IndexError("Length of pad must be equal 4")
-
- pad_ = pad_list
- data = []
- data.append(out_backprop)
- data.append(filter)
- fmap_shape = input_sizes
- filter_shape = filter_shape
- stride_ = [stride, stride]
- dilation_ = [dilation, dilation]
-
- return conv_backprop_input.conv_backprop_input(data, fmap_shape, filter_shape, pad_, stride_, dilation_)
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