Add optional trailing activation to residual block
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@ -75,16 +75,28 @@ class ConvBlock(nn.Module):
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class ResBlock(ConvBlock):
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"""Residual convolution blocks of the form specified by `seq`. Input is added
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to the residual followed by an optional activation (trailing `'A'` in `seq`).
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"""Residual convolution blocks of the form specified by `seq`.
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Input, via a skip connection, is added to the residual followed by an
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optional activation.
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The skip connection is identity if `out_chan` is omitted, otherwise it uses
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a size 1 "convolution", i.e. one can trigger the latter by setting
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`out_chan` even if it equals `in_chan`.
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A trailing `'A'` in seq can either operate before or after the addition,
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depending on the boolean value of `last_act`.
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See `ConvBlock` for `seq` types.
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"""
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def __init__(self, in_chan, out_chan=None, mid_chan=None,
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seq='CBACBA'):
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super().__init__(in_chan, out_chan=out_chan,
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mid_chan=mid_chan,
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seq=seq[:-1] if seq[-1] == 'A' else seq)
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seq='CBACBA', last_act=True):
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if seq[-1] == 'A' and last_act:
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seq = seq[:-1]
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self.act = nn.LeakyReLU()
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else:
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self.act = None
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super().__init__(in_chan, out_chan=out_chan, mid_chan=mid_chan, seq=seq)
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if out_chan is None:
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self.skip = None
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@ -95,11 +107,6 @@ class ResBlock(ConvBlock):
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raise NotImplementedError('upsample and downsample layers '
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'not supported yet')
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if seq[-1] == 'A':
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self.act = nn.LeakyReLU()
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else:
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self.act = None
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def forward(self, x):
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y = x
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