Class for the residual block layer.
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def | __init__ (self, ninput, noutput, upsample=True) |
| Constructor to create a new residual block layer.
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def | forward (self, x) |
| Function to perform a forward pass. More...
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| upsample |
| Whether to double the height and width of input.
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| conv |
| Convolutional layer in the shortcut branch.
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| norm1 |
| First batch normalization layer in the residual branch.
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| conv1 |
| First convolutional layer in the residual branch.
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| norm2 |
| Second batch normalization layer in the residual branch.
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| conv2 |
| Second convolutional layer in the residual branch.
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Class for the residual block layer.
Residual block layer.
Definition at line 19 of file resnet.py.
◆ forward()
Function to perform a forward pass.
Compute the layer output for a given input.
Definition at line 39 of file resnet.py.
40 """Compute the layer output for a given input."""
46 h = F.interpolate(h, mode=
"nearest", scale_factor=2)
53 x = F.interpolate(x, mode=
"nearest", scale_factor=2)
The documentation for this class was generated from the following file:
- pxd/scripts/pxd/background_generator/models/resnet.py