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https://github.com/zebrajr/pytorch.git
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e7c1e6a8e3
Here's the command I used to invoke autopep8 (in parallel!):
git ls-files | grep '\.py$' | xargs -n1 -P`nproc` autopep8 -i
Several rules are ignored in setup.cfg. The goal is to let autopep8
handle everything which it can handle safely, and to disable any rules
which are tricky or controversial to address. We may want to come back
and re-enable some of these rules later, but I'm trying to make this
patch as safe as possible.
Also configures flake8 to match pep8's behavior.
Also configures TravisCI to check the whole project for lint.
31 lines
953 B
Python
31 lines
953 B
Python
import torch
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from ._utils import _range
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def split(tensor, split_size, dim=0):
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if dim < 0:
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dim += tensor.dim()
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dim_size = tensor.size(dim)
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num_splits = (dim_size + split_size - 1) // split_size
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last_split_size = split_size - (split_size * num_splits - dim_size)
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def get_split_size(i):
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return split_size if i < num_splits - 1 else last_split_size
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return tuple(tensor.narrow(int(dim), int(i * split_size), int(get_split_size(i))) for i
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in _range(0, num_splits))
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def chunk(tensor, n_chunks, dim=0):
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if dim < 0:
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dim += tensor.dim()
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split_size = (tensor.size(dim) + n_chunks - 1) // n_chunks
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return split(tensor, split_size, dim)
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def stack(sequence, dim=0):
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if len(sequence) == 0:
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raise TypeError("stack expects a non-empty sequence of tensors")
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if dim < 0:
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dim += sequence[0].dim()
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return torch.cat(list(t.unsqueeze(dim) for t in sequence), dim)
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