#-------------------------------------------------------------
#
# Licensed to the Apache Software Foundation (ASF) under one
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# 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
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# KIND, either express or implied.  See the License for the
# specific language governing permissions and limitations
# under the License.
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#-------------------------------------------------------------

imgSize=8
numImg=16
numChannels=4
numFilters=3
filterSize=4
stride=1
pad=0

X = matrix(seq(1, numImg*numChannels*imgSize*imgSize), rows=numImg, cols=numChannels*imgSize*imgSize);
W1 = matrix(seq(1, numFilters*numChannels*filterSize*filterSize), rows=numFilters, cols=numChannels*filterSize*filterSize)
W2 = matrix(seq(1, numFilters*numChannels*filterSize*filterSize)+7, rows=numFilters, cols=numChannels*filterSize*filterSize)
b = matrix(seq(1, numFilters), rows=numFilters, cols=1) 

while(FALSE){}

X = X - rowMeans(X);

R1 = conv2d(X, W1, padding=[pad, pad], stride=[stride, stride], input_shape=[numImg, numChannels, imgSize, imgSize], filter_shape=[numFilters, numChannels, filterSize, filterSize])
R2 = conv2d(X, W2, padding=[pad, pad], stride=[stride, stride], input_shape=[numImg, numChannels, imgSize, imgSize], filter_shape=[numFilters, numChannels, filterSize, filterSize])
R = R1 + R2;

write(R, $1, format="text");