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# Module caffe2.python.layers.dropout
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,
dropout_for_eval=False,
**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.dropout_for_eval = dropout_for_eval
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=(not self.dropout_for_eval))
def add_ops(self, net):
self.add_eval_ops(net)
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