no message

1 files changed, 48 insertions, 0 deletions

diff --git a/SeparableConvolution.py b/SeparableConvolution.py
new file mode 100644
index 0000000..9e5d1e9
--- /dev/null
+++ b/SeparableConvolution.py
@@ -0,0 +1,48 @@
+import torch
+
+import _ext.cunnex
+
+class SeparableConvolution(torch.autograd.Function):
+	def __init__(self):
+		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))
+
+		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)
+
+		output = input1.new().resize_(intBatches, intInputDepth, intOutputHeight, intOutputWidth).zero_()
+
+		if input1.is_cuda == True:
+			_ext.cunnex.SeparableConvolution_cuda_forward(
+				input1,
+				input2,
+				input3,
+				output
+			)
+
+		elif input1.is_cuda == False:
+			assert(False) # NOT IMPLEMENTED
+
+		# end
+
+		return output
+	# end
+
+	def backward(self, gradOutput):
+		assert(false) # NOT IMPLEMENTED
+	# end
+# end
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