mirror of
https://github.com/zebrajr/pytorch.git
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01b57e1810
Test Plan: revert-hammer
Differential Revision:
D25718705 (891759f860)
Original commit changeset: 6a9e3e6d17aa
fbshipit-source-id: 1a4ef0bfdec8eb8e7ce149bfbdb34a4ad8d964b6
36 lines
1000 B
Python
36 lines
1000 B
Python
from typing import List
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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 _reverse_repeat_tuple(t, n):
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r"""Reverse the order of `t` and repeat each element 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 reversed(t) for _ in range(n))
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def _list_with_default(out_size, defaults):
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# type: (List[int], List[int]) -> List[int]
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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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