diff options
Diffstat (limited to 'run.py')
| -rw-r--r-- | run.py | 17 |
1 files changed, 7 insertions, 10 deletions
@@ -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]) |