# Copyright (c) 2020 Sony Corporation. All Rights Reserved.
#
# 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.
import nnabla.functions as F
from .module import Module
[docs]
class Dropout(Module):
r"""Dropout layer.
During training, randomly zeroes some of the elements of the input
tensor with probability :attr:`p` using samples from a Bernoulli
distribution. Each channel will be zeroed out independently on every
forward call.
Args:
drop_prob (:obj:`int`, optional): The probability of an element to be
zeroed. Defaults to 0.5.
name (string): the name of this module
"""
def __init__(self, drop_prob=0.5, name=''):
Module.__init__(self, name=name)
self._scope_name = f'<dropout at {hex(id(self))}>'
self._drop_prob = drop_prob
[docs]
def call(self, input):
if self._drop_prob == 0 or not self.training:
return input
return F.dropout(input, self._drop_prob)