pytorch/caffe2/python/regularizer_context.py
Honghao Wei 6763c14e84 add base class ModifierContext, rewrite OptimizerContext, add RegularizerContext
Summary:
`ModifierContext` is the base class for `OptimizerContext` and `RegularizationContext`.
`UseModifierBase` is the base class for `UseRegularizer `and `UseOptimizer`

Most of codes in `OptimizerContext`, `RegularizationContext` and other potential Context class in future could be shared. We thus implemented a new base class, called `ModifierContext` to support it.

It happens to be the same for `UseRegularizer` and `UseOptimizer`, and we implemented a new base  class called `UseModifierBase`.

In this way, users only need to provide API for **get** and **has** operation. Also, they need to tell what's the **context class**.

**Note**
Mirrored code in fbandroid and fbobj would be added when finally check in.

Reviewed By: kittipatv, xianjiec

Differential Revision: D5724613

fbshipit-source-id: de19bb822dcd41ec5c459d65065603a0abe2fd20
2017-09-08 11:39:23 -07:00

39 lines
1.1 KiB
Python

# @package regularizer_context
# Module caffe2.python.regularizer_context
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from __future__ import unicode_literals
from caffe2.python import context
from caffe2.python.modifier_context import (
ModifierContext, UseModifierBase)
@context.define_context(allow_default=True)
class RegularizerContext(ModifierContext):
"""
provide context to allow param_info to have different regularizers
"""
def has_regularizer(self, name):
return self._has_modifier(name)
def get_regularizer(self, name):
assert self.has_regularizer(name), (
"{} regularizer is not provided!".format(name))
return self._get_modifier(name)
class UseRegularizer(UseModifierBase):
'''
context class to allow setting the current context.
Example useage with layer:
regularizers = {'reg1': reg1, 'reg2': reg2}
with Regularizers(regularizers):
reg = RegularizerContext.current().get_regularizer('reg1')
layer(reg=reg)
'''
def _context_class(self):
return RegularizerContext