pytorch/torch/nn/_reduction.py
David Riazati 10c4b98ade Remove weak script (#22212)
Summary:
* Deletes all weak script decorators / associated data structures / methods
   * In order to keep supporting the standard library in script, this enables recursive script on any function defined in `torch.nn`
   * Most changes in `torch/nn` are the result of `ag -Q "weak" torch/nn/ -l | xargs sed -i '/weak/d'`, only `rnn.py` needed manual editing to use the `ignore` and `export` to continue supporting the overloaded `forward` methods
* `Sequential`/`ModuleList` no longer need to be added to constants since they are compiled on demand

This should also fix https://github.com/pytorch/pytorch/issues/22212
Pull Request resolved: https://github.com/pytorch/pytorch/pull/22212

Differential Revision: D15988346

Pulled By: driazati

fbshipit-source-id: af223e3ad0580be895377312949997a70e988e4f
2019-07-03 17:28:25 -07:00

50 lines
1.5 KiB
Python

import warnings
# NB: Keep this file in sync with enums in aten/src/ATen/core/Reduction.h
def get_enum(reduction):
# type: (str) -> int
if reduction == 'none':
ret = 0
elif reduction == 'mean':
ret = 1
elif reduction == 'elementwise_mean':
warnings.warn("reduction='elementwise_mean' is deprecated, please use reduction='mean' instead.")
ret = 1
elif reduction == 'sum':
ret = 2
else:
ret = -1 # TODO: remove once JIT exceptions support control flow
raise ValueError("{} is not a valid value for reduction".format(reduction))
return ret
# In order to support previous versions, accept boolean size_average and reduce
# and convert them into the new constants for now
# We use these functions in torch/legacy as well, in which case we'll silence the warning
def legacy_get_string(size_average, reduce, emit_warning=True):
# type: (Optional[bool], Optional[bool], bool) -> str
warning = "size_average and reduce args will be deprecated, please use reduction='{}' instead."
if size_average is None:
size_average = True
if reduce is None:
reduce = True
if size_average and reduce:
ret = 'mean'
elif reduce:
ret = 'sum'
else:
ret = 'none'
if emit_warning:
warnings.warn(warning.format(ret))
return ret
def legacy_get_enum(size_average, reduce, emit_warning=True):
# type: (Optional[bool], Optional[bool], bool) -> int
return get_enum(legacy_get_string(size_average, reduce, emit_warning))