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# Copyright (c) OpenMMLab. All rights reserved.
import collections.abc
import warnings
from itertools import repeat
import torch
from mmengine.utils import digit_version
def is_tracing() -> bool:
"""Determine whether the model is called during the tracing of code with
``torch.jit.trace``."""
if digit_version(torch.__version__) >= digit_version('1.6.0'):
on_trace = torch.jit.is_tracing()
# In PyTorch 1.6, torch.jit.is_tracing has a bug.
# Refers to https://github.com/pytorch/pytorch/issues/42448
if isinstance(on_trace, bool):
return on_trace
else:
return torch._C._is_tracing()
else:
warnings.warn(
'torch.jit.is_tracing is only supported after v1.6.0. '
'Therefore is_tracing returns False automatically. Please '
'set on_trace manually if you are using trace.', UserWarning)
return False
# From PyTorch internals
def _ntuple(n):
"""A `to_tuple` function generator.
It returns a function, this function will repeat the input to a tuple of
length ``n`` if the input is not an Iterable object, otherwise, return the
input directly.
Args:
n (int): The number of the target length.
"""
def parse(x):
if isinstance(x, collections.abc.Iterable):
return x
return tuple(repeat(x, n))
return parse
to_1tuple = _ntuple(1)
to_2tuple = _ntuple(2)
to_3tuple = _ntuple(3)
to_4tuple = _ntuple(4)
to_ntuple = _ntuple
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