Add assignment support for Sequential #4931
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torch/nn/modules/container.py
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| @@ -62,6 +60,9 @@ def __getitem__(self, idx): | |||
| next(it) | |||
| return next(it) | |||
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| def __setitem__(self, idx, module): | |||
| return setattr(self, str(idx), module) | |||
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Simply manipulate the variable returned by iterator only refers to a new module object, rather than modify the existing one.
torch/nn/modules/container.py
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| # Specify the module by index | ||
| model[1] = nn.Sigmoid() | ||
| # Specify the module by name if initialized with OrderedDict | ||
| model.relu1 = nn.LeakyReLU() |
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torch/nn/modules/container.py
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| def _get_item_by_idx(self, iterator, idx): | ||
| """Get the idx-th item of the iterator""" | ||
| size = len(self) | ||
| if not (-size <= idx < size): |
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torch/nn/modules/container.py
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| for i in range(idx): | ||
| next(it) | ||
| return next(it) | ||
| return self._get_item_by_idx(self._modules.items(), idx) |
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|
How do you think of using pure items = list(args)
for item in items:
if isinstance(item, tuple):
...
else:
... |
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@pytorchbot test this please |
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No, let's not complicate the API. This looks good as is. Thanks! |
Simply a copy from
ModuleList.I think the
Sequentialis just a forwardable version ofModuleList, it makes sense to combine both into one class.