mirror of
https://github.com/zebrajr/pytorch.git
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c6f41ae01b
Summary: Fix https://github.com/pytorch/pytorch/issues/29712 #29668 , add arg checking, doc, and support for reflection and replication padding modes. Pull Request resolved: https://github.com/pytorch/pytorch/pull/31784 Differential Revision: D19301974 Pulled By: ezyang fbshipit-source-id: a0ed4815c0c22e416b16e256bba04324e376b2f8
33 lines
887 B
Python
33 lines
887 B
Python
from torch._six import container_abcs
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from itertools import repeat
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def _ntuple(n):
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def parse(x):
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if isinstance(x, container_abcs.Iterable):
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return x
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return tuple(repeat(x, n))
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return parse
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_single = _ntuple(1)
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_pair = _ntuple(2)
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_triple = _ntuple(3)
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_quadruple = _ntuple(4)
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def _repeat_tuple(t, n):
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r"""Repeat each element of `t` for `n` times.
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This can be used to translate padding arg used by Conv and Pooling modules
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to the ones used by `F.pad`.
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"""
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return tuple(x for x in t for _ in range(n))
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def _list_with_default(out_size, defaults):
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if isinstance(out_size, int):
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return out_size
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if len(defaults) <= len(out_size):
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raise ValueError('Input dimension should be at least {}'.format(len(out_size) + 1))
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return [v if v is not None else d for v, d in zip(out_size, defaults[-len(out_size):])]
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