pytorch/caffe2/python/layers/dropout.py
Yangqing Jia 8286ce1e3a Re-license to Apache
Summary: Closes https://github.com/caffe2/caffe2/pull/1260

Differential Revision: D5906739

Pulled By: Yangqing

fbshipit-source-id: e482ba9ba60b5337d9165f28f7ec68d4518a0902
2017-09-28 16:22:00 -07:00

64 lines
2.1 KiB
Python

# Copyright (c) 2016-present, Facebook, Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
##############################################################################
# Module caffe2.python.layers.dropout
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from __future__ import unicode_literals
from caffe2.python import schema
from caffe2.python.layers.layers import ModelLayer
class Dropout(ModelLayer):
def __init__(
self,
model,
input_record,
name='dropout',
ratio=0.5,
**kwargs):
super(Dropout, self).__init__(model, name, input_record, **kwargs)
assert isinstance(input_record, schema.Scalar), "Incorrect input type"
assert (ratio >= 0 and ratio < 1.0), \
"Expected 0 <= ratio < 1, but got ratio of %s" % ratio
self.output_schema = input_record.clone_schema()
self.output_schema.set_value(self.get_next_blob_reference('output'))
self.ratio = ratio
def _add_ops(self, net, is_test):
input_blob = self.input_record.field_blobs()
output_blobs = self.output_schema.field_blobs() \
+ [net.NextScopedBlob('d_mask')]
net.Dropout(input_blob,
output_blobs,
ratio=self.ratio,
is_test=is_test)
def add_train_ops(self, net):
self._add_ops(net, is_test=False)
def add_eval_ops(self, net):
self._add_ops(net, is_test=True)
def add_ops(self, net):
self.add_eval_ops(net)