no message

7 files changed, 47 insertions, 50 deletions

diff --git a/README.md b/README.md
index 98071ff..11dc862 100644
--- a/README.md
+++ b/README.md
@@ -19,7 +19,7 @@ python run.py --model lf --first ./images/first.png --second ./images/second.png
 <a href="http://web.cecs.pdx.edu/~fliu/project/sepconv/demo.mp4" rel="Video"><img src="http://web.cecs.pdx.edu/~fliu/project/sepconv/screen.jpg" alt="Video" width="100%"></a>
 
 ## license
-The provided implementation is strictly for academic purposes only. Should you be interested in using our intellectual property, please feel free to contact us.
+The provided implementation is strictly for academic purposes only. Should you be interested in using our technology for any commercial use, please feel free to contact us.
 
 ## references
 ```
diff --git a/SeparableConvolution.py b/SeparableConvolution.py
index 2ac31f9..d97a87f 100644
--- a/SeparableConvolution.py
+++ b/SeparableConvolution.py
@@ -7,34 +7,34 @@ class SeparableConvolution(torch.autograd.Function):
 		super(SeparableConvolution, self).__init__()
 	# end
 
-	def forward(self, input1, input2, input3):
-		intBatches = input1.size(0)
-		intInputDepth = input1.size(1)
-		intInputHeight = input1.size(2)
-		intInputWidth = input1.size(3)
-		intFilterSize = min(input2.size(1), input3.size(1))
-		intOutputHeight = min(input2.size(2), input3.size(2))
-		intOutputWidth = min(input2.size(3), input3.size(3))
+	def forward(self, input, vertical, horizontal):
+		intBatches = input.size(0)
+		intInputDepth = input.size(1)
+		intInputHeight = input.size(2)
+		intInputWidth = input.size(3)
+		intFilterSize = min(vertical.size(1), horizontal.size(1))
+		intOutputHeight = min(vertical.size(2), horizontal.size(2))
+		intOutputWidth = min(vertical.size(3), horizontal.size(3))
 
 		assert(intInputHeight - 51 == intOutputHeight - 1)
 		assert(intInputWidth - 51 == intOutputWidth - 1)
 		assert(intFilterSize == 51)
 
-		assert(input1.is_contiguous() == True)
-		assert(input2.is_contiguous() == True)
-		assert(input3.is_contiguous() == True)
+		assert(input.is_contiguous() == True)
+		assert(vertical.is_contiguous() == True)
+		assert(horizontal.is_contiguous() == True)
 
-		output = input1.new().resize_(intBatches, intInputDepth, intOutputHeight, intOutputWidth).zero_()
+		output = input.new().resize_(intBatches, intInputDepth, intOutputHeight, intOutputWidth).zero_()
 
-		if input1.is_cuda == True:
+		if input.is_cuda == True:
 			_ext.cunnex.SeparableConvolution_cuda_forward(
-				input1,
-				input2,
-				input3,
+				input,
+				vertical,
+				horizontal,
 				output
 			)
 
-		elif input1.is_cuda == False:
+		elif input.is_cuda == False:
 			raise NotImplementedError() # CPU VERSION NOT IMPLEMENTED
 
 		# end
diff --git a/run.py b/run.py
index 63aebb9..a1f26a3 100644
--- a/run.py
+++ b/run.py
@@ -181,8 +181,7 @@ intPaddingLeft = int(math.floor(51 / 2.0))
 intPaddingTop = int(math.floor(51 / 2.0))
 intPaddingRight = int(math.floor(51 / 2.0))
 intPaddingBottom = int(math.floor(51 / 2.0))
-modulePaddingFirst = torch.nn.Module()
-modulePaddingSecond = torch.nn.Module()
+modulePaddingInput = torch.nn.Module()
 modulePaddingOutput = torch.nn.Module()
 
 if True:
@@ -200,24 +199,22 @@ if True:
 	intPaddingWidth = intPaddingWidth - (intPaddingLeft + intWidth + intPaddingRight)
 	intPaddingHeight = intPaddingHeight - (intPaddingTop + intHeight + intPaddingBottom)
 
-	modulePaddingFirst = torch.nn.ReplicationPad2d([intPaddingLeft, intPaddingRight + intPaddingWidth, intPaddingTop, intPaddingBottom + intPaddingHeight])
-	modulePaddingSecond = torch.nn.ReplicationPad2d([intPaddingLeft, intPaddingRight + intPaddingWidth, intPaddingTop, intPaddingBottom + intPaddingHeight])
+	modulePaddingInput = torch.nn.ReplicationPad2d([intPaddingLeft, intPaddingRight + intPaddingWidth, intPaddingTop, intPaddingBottom + intPaddingHeight])
 	modulePaddingOutput = torch.nn.ReplicationPad2d([0 - intPaddingLeft, 0 - intPaddingRight - intPaddingWidth, 0 - intPaddingTop, 0 - intPaddingBottom - intPaddingHeight])
-
-	modulePaddingFirst = modulePaddingFirst.cuda()
-	modulePaddingSecond = modulePaddingSecond.cuda()
-	modulePaddingOutput = modulePaddingOutput.cuda()
 # end
 
 if True:
 	tensorInputFirst = tensorInputFirst.cuda()
 	tensorInputSecond = tensorInputSecond.cuda()
 	tensorOutput = tensorOutput.cuda()
+
+	modulePaddingInput = modulePaddingInput.cuda()
+	modulePaddingOutput = modulePaddingOutput.cuda()
 # end
 
 if True:
-	variablePaddingFirst = modulePaddingFirst(torch.autograd.Variable(data=tensorInputFirst.view(1, 3, intHeight, intWidth), volatile=True))
-	variablePaddingSecond = modulePaddingSecond(torch.autograd.Variable(data=tensorInputSecond.view(1, 3, intHeight, intWidth), volatile=True))
+	variablePaddingFirst = modulePaddingInput(torch.autograd.Variable(data=tensorInputFirst.view(1, 3, intHeight, intWidth), volatile=True))
+	variablePaddingSecond = modulePaddingInput(torch.autograd.Variable(data=tensorInputSecond.view(1, 3, intHeight, intWidth), volatile=True))
 	variablePaddingOutput = modulePaddingOutput(moduleNetwork(variablePaddingFirst, variablePaddingSecond))
 
 	tensorOutput.resize_(3, intHeight, intWidth).copy_(variablePaddingOutput.data[0])
diff --git a/src/SeparableConvolution_cuda.c b/src/SeparableConvolution_cuda.c
index a48622e..973e4c1 100644
--- a/src/SeparableConvolution_cuda.c
+++ b/src/SeparableConvolution_cuda.c
@@ -6,16 +6,16 @@
 extern THCState* state;
 
 int SeparableConvolution_cuda_forward(
-	THCudaTensor* input1,
-	THCudaTensor* input2,
-	THCudaTensor* input3,
+	THCudaTensor* input,
+	THCudaTensor* vertical,
+	THCudaTensor* horizontal,
 	THCudaTensor* output
 ) {
 	SeparableConvolution_kernel_forward(
 		state,
-		input1,
-		input2,
-		input3,
+		input,
+		vertical,
+		horizontal,
 		output
 	);
 
diff --git a/src/SeparableConvolution_cuda.h b/src/SeparableConvolution_cuda.h
index 7320fee..a3d5ed0 100644
--- a/src/SeparableConvolution_cuda.h
+++ b/src/SeparableConvolution_cuda.h
@@ -1,6 +1,6 @@
 int SeparableConvolution_cuda_forward(
-	THCudaTensor* input1,
-	THCudaTensor* input2,
-	THCudaTensor* input3,
+	THCudaTensor* input,
+	THCudaTensor* vertical,
+	THCudaTensor* horizontal,
 	THCudaTensor* output
 );
\ No newline at end of file
diff --git a/src/SeparableConvolution_kernel.cu b/src/SeparableConvolution_kernel.cu
index b40786d..b4e6d59 100644
--- a/src/SeparableConvolution_kernel.cu
+++ b/src/SeparableConvolution_kernel.cu
@@ -17,9 +17,9 @@
 
 __global__ void kernel_SeparableConvolution_updateOutput(
 	const int n,
-	const float* input1, const long4 input1_size, const long4 input1_stride,
-	const float* input2, const long4 input2_size, const long4 input2_stride,
-	const float* input3, const long4 input3_size, const long4 input3_stride,
+	const float* input, const long4 input_size, const long4 input_stride,
+	const float* vertical, const long4 vertical_size, const long4 vertical_stride,
+	const float* horizontal, const long4 horizontal_size, const long4 horizontal_stride,
 	float* output, const long4 output_size, const long4 output_stride
 ) {
 	int intIndex = blockIdx.x * blockDim.x + threadIdx.x;
@@ -37,7 +37,7 @@ __global__ void kernel_SeparableConvolution_updateOutput(
 
 	for (int intFilterY = 0; intFilterY < 51; intFilterY += 1) {
 		for (int intFilterX = 0; intFilterX < 51; intFilterX += 1) {
-			dblOutput += IDX_4(input1, intBatch, intDepth, intY + intFilterY, intX + intFilterX) * IDX_4(input2, intBatch, intFilterY, intY, intX) * IDX_4(input3, intBatch, intFilterX, intY, intX);
+			dblOutput += IDX_4(input, intBatch, intDepth, intY + intFilterY, intX + intFilterX) * IDX_4(vertical, intBatch, intFilterY, intY, intX) * IDX_4(horizontal, intBatch, intFilterX, intY, intX);
 		}
 	}
 
@@ -46,9 +46,9 @@ __global__ void kernel_SeparableConvolution_updateOutput(
 
 void SeparableConvolution_kernel_forward(
 	THCState* state,
-	THCudaTensor* input1,
-	THCudaTensor* input2,
-	THCudaTensor* input3,
+	THCudaTensor* input,
+	THCudaTensor* vertical,
+	THCudaTensor* horizontal,
 	THCudaTensor* output
 ) {
 	int n = 0;
@@ -56,9 +56,9 @@ void SeparableConvolution_kernel_forward(
 	n = THCudaTensor_nElement(state, output);
 	kernel_SeparableConvolution_updateOutput<<< (n + 512 - 1) / 512, 512, 0, THCState_getCurrentStream(state) >>>(
 		n,
-		THCudaTensor_data(state, input1), make_long4(input1->size[0], input1->size[1], input1->size[2], input1->size[3]), make_long4(input1->stride[0], input1->stride[1], input1->stride[2], input1->stride[3]),
-		THCudaTensor_data(state, input2), make_long4(input2->size[0], input2->size[1], input2->size[2], input2->size[3]), make_long4(input2->stride[0], input2->stride[1], input2->stride[2], input2->stride[3]),
-		THCudaTensor_data(state, input3), make_long4(input3->size[0], input3->size[1], input3->size[2], input3->size[3]), make_long4(input3->stride[0], input3->stride[1], input3->stride[2], input3->stride[3]),
+		THCudaTensor_data(state, input), make_long4(input->size[0], input->size[1], input->size[2], input->size[3]), make_long4(input->stride[0], input->stride[1], input->stride[2], input->stride[3]),
+		THCudaTensor_data(state, vertical), make_long4(vertical->size[0], vertical->size[1], vertical->size[2], vertical->size[3]), make_long4(vertical->stride[0], vertical->stride[1], vertical->stride[2], vertical->stride[3]),
+		THCudaTensor_data(state, horizontal), make_long4(horizontal->size[0], horizontal->size[1], horizontal->size[2], horizontal->size[3]), make_long4(horizontal->stride[0], horizontal->stride[1], horizontal->stride[2], horizontal->stride[3]),
 		THCudaTensor_data(state, output), make_long4(output->size[0], output->size[1], output->size[2], output->size[3]), make_long4(output->stride[0], output->stride[1], output->stride[2], output->stride[3])
 	);
 
diff --git a/src/SeparableConvolution_kernel.h b/src/SeparableConvolution_kernel.h
index b400579..11a0238 100644
--- a/src/SeparableConvolution_kernel.h
+++ b/src/SeparableConvolution_kernel.h
@@ -4,9 +4,9 @@
 
 void SeparableConvolution_kernel_forward(
 	THCState* state,
-	THCudaTensor* input1,
-	THCudaTensor* input2,
-	THCudaTensor* input3,
+	THCudaTensor* input,
+	THCudaTensor* vertical,
+	THCudaTensor* horizontal,
 	THCudaTensor* output
 );