pdarts implementation (export is not included) #1730
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| @@ -109,11 +112,12 @@ def forward(self, optional_inputs, semantic_labels=None): | |||
| "Length of the input list must be equal to number of candidates." | |||
| if semantic_labels is None: | |||
| semantic_labels = ["default_label"] * self.n_candidates | |||
| out, mask = self.mutator.on_forward(self, optional_inputs, semantic_labels) | |||
| out, mask = self.mutator.on_forward( | |||
| self, optional_inputs, semantic_labels) | |||
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Auto format. We can use same tool (vs code?), or have the same line width setting.
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You might need to set line width to 140, which is defined in our pylint.
| def __repr__(self): | ||
| return "{} ({})".format(self.name, self.key) | ||
| # def __repr__(self): | ||
| # return "{} ({})".format(self.name, self.key) |
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Can you do a better repr instead of delete it?
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the default repr is good enough, it's easy to compare with original network structure.
If we want some additional information, it can be another side method.
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Then delete it instead of commenting.
| from torch import nn as nn | ||
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| class RankedModule(nn.Module): |
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like cell, it marks difference rank/level of group. for example, in darts, cell is rank=1, and ops can be treat like rank=2. It can support macro/micro pattern better.
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Where is this rank/level used?
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I thought to update on existing network for pdarts implementation, so added it. But finally, to get exact implementation, the pdarts recreate network each time. So it's not used in this time, but I believe it's a good mark for future implementation.
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Looks "over-engineering" to me. I'm fine with it. Just make everything clear in the docstring. :)
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