Repository: incubator-systemml Updated Branches: refs/heads/master 32f075695 -> 2d2196d84
http://git-wip-us.apache.org/repos/asf/incubator-systemml/blob/2d2196d8/src/test/scripts/functions/tensor/Conv2DTest.dml ---------------------------------------------------------------------- diff --git a/src/test/scripts/functions/tensor/Conv2DTest.dml b/src/test/scripts/functions/tensor/Conv2DTest.dml index aec8499..792367f 100644 --- a/src/test/scripts/functions/tensor/Conv2DTest.dml +++ b/src/test/scripts/functions/tensor/Conv2DTest.dml @@ -31,6 +31,16 @@ x=matrix(seq(1, numImg*numChannels*imgSize*imgSize), rows=numImg, cols=numChanne w=matrix(seq(1, numFilters*numChannels*filterSize*filterSize), rows=numFilters, cols=numChannels*filterSize*filterSize) b=matrix(seq(1, numFilters), rows=numFilters, cols=1) +if($9) { + zero_mask = (x - mean(x)) > 0 + x = x * zero_mask +} +if($10) { + zero_mask = (w - mean(w)) > 0 + w = w * zero_mask +} +x = x - mean(x) +w = w - mean(w) output = conv2d(x, w, padding=[pad, pad], stride=[stride, stride], input_shape=[numImg, numChannels, imgSize, imgSize], filter_shape=[numFilters, numChannels, filterSize, filterSize], bias=b) output = bias_add(output, b) write(output, $8, format="text") \ No newline at end of file http://git-wip-us.apache.org/repos/asf/incubator-systemml/blob/2d2196d8/src/test/scripts/functions/tensor/PoolBackwardTest.R ---------------------------------------------------------------------- diff --git a/src/test/scripts/functions/tensor/PoolBackwardTest.R b/src/test/scripts/functions/tensor/PoolBackwardTest.R index 8cb8a7c..f3133a7 100644 --- a/src/test/scripts/functions/tensor/PoolBackwardTest.R +++ b/src/test/scripts/functions/tensor/PoolBackwardTest.R @@ -34,7 +34,16 @@ Q=as.integer(args[9]) # Assumption: NCHW image format x=matrix(seq(1, numImg*numChannels*imgSize*imgSize), numImg, numChannels*imgSize*imgSize, byrow=TRUE) dout=matrix(seq(1, numImg*numChannels*P*Q), numImg, numChannels*P*Q, byrow=TRUE) - +if(as.logical(args[11])) { + # zero_mask = (x - mean(x)) > 0 + # x = x * zero_mask +} +if(as.logical(args[12])) { + # zero_mask = (dout - mean(dout)) > 0 + # dout = dout * zero_mask +} +x = x - mean(x) +dout = dout - mean(dout) max_pool_backward <- function(dout, Hout, Wout, X, C, Hin, Win, Hf, Wf, strideh, stridew) { http://git-wip-us.apache.org/repos/asf/incubator-systemml/blob/2d2196d8/src/test/scripts/functions/tensor/PoolBackwardTest.dml ---------------------------------------------------------------------- diff --git a/src/test/scripts/functions/tensor/PoolBackwardTest.dml b/src/test/scripts/functions/tensor/PoolBackwardTest.dml index 0ee80df..22f778f 100644 --- a/src/test/scripts/functions/tensor/PoolBackwardTest.dml +++ b/src/test/scripts/functions/tensor/PoolBackwardTest.dml @@ -33,6 +33,16 @@ Q = $10 # Assumption: NCHW image format x=matrix(seq(1, numImg*numChannels*imgSize*imgSize), rows=numImg, cols=numChannels*imgSize*imgSize) dout=matrix(seq(1, numImg*numChannels*P*Q), rows=numImg, cols=numChannels*P*Q) +if($12) { + # zero_mask = (x - mean(x)) > 0 + # x = x * zero_mask +} +if($13) { + # zero_mask = (dout - mean(dout)) > 0 + # dout = dout * zero_mask +} +x = x - mean(x) +dout = dout - mean(dout) if(poolMode == "max") { output = max_pool_backward(x, dout, stride=[stride, stride], padding=[pad, pad], input_shape=[numImg, numChannels, imgSize, imgSize], pool_size=[poolSize1, poolSize2]) } http://git-wip-us.apache.org/repos/asf/incubator-systemml/blob/2d2196d8/src/test/scripts/functions/tensor/PoolTest.R ---------------------------------------------------------------------- diff --git a/src/test/scripts/functions/tensor/PoolTest.R b/src/test/scripts/functions/tensor/PoolTest.R index 3731807..d9c8d0c 100644 --- a/src/test/scripts/functions/tensor/PoolTest.R +++ b/src/test/scripts/functions/tensor/PoolTest.R @@ -31,7 +31,11 @@ pad=as.integer(args[7]) # Assumption: NCHW image format x=matrix(seq(1, numImg*numChannels*imgSize*imgSize), numImg, numChannels*imgSize*imgSize, byrow=TRUE) - +if(as.logical(args[9])) { + zero_mask = (x - mean(x)) > 0 + x = x * zero_mask +} +x = x - mean(x) pad_image <- function(img, Hin, Win, padh, padw){ C = nrow(img) img_padded = matrix(0, C, (Hin+2*padh)*(Win+2*padw)) # zeros http://git-wip-us.apache.org/repos/asf/incubator-systemml/blob/2d2196d8/src/test/scripts/functions/tensor/PoolTest.dml ---------------------------------------------------------------------- diff --git a/src/test/scripts/functions/tensor/PoolTest.dml b/src/test/scripts/functions/tensor/PoolTest.dml index e163e89..b701e71 100644 --- a/src/test/scripts/functions/tensor/PoolTest.dml +++ b/src/test/scripts/functions/tensor/PoolTest.dml @@ -29,6 +29,11 @@ poolMode=$8 # Assumption: NCHW image format x=matrix(seq(1, numImg*numChannels*imgSize*imgSize), rows=numImg, cols=numChannels*imgSize*imgSize) +if($10) { + zero_mask = (x - mean(x)) > 0 + x = x * zero_mask +} +x = x - mean(x) if(poolMode == "max") { output = max_pool(x, stride=[stride, stride], padding=[pad, pad], input_shape=[numImg, numChannels, imgSize, imgSize], pool_size=[poolSize1, poolSize2]) }
