blob: b17281e9368c36d409da1ed08d50022e731b138f [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.
#
#-------------------------------------------------------------
imgSize=$1
numImg=$2
numChannels=$3
numFilters=$4
filterSize=$5
stride=$6
pad=$7
P = $8
Q = $9
# Assumption: NCHW image format
x=matrix(seq(1, numImg*numChannels*imgSize*imgSize), rows=numImg, cols=numChannels*imgSize*imgSize)
dout=matrix(seq(1, numImg*numFilters*P*Q), rows=numImg, cols=numFilters*P*Q)
if($11) {
zero_mask = (x - mean(x)*1.5) > 0
x = x * zero_mask
}
else {
x = x - mean(x)
}
if($12) {
zero_mask = (dout - mean(dout)*1.5) > 0
dout = dout * zero_mask
}
else {
dout = dout - mean(dout)
}
dw = conv2d_backward_filter(x, dout, stride=[stride, stride], padding=[pad, pad], input_shape=[numImg, numChannels, imgSize, imgSize], filter_shape=[numFilters, numChannels, filterSize, filterSize])
write(dw, $10, format="text")