FM / layers

/usr/local/lib64/python3.6/site-packages/caffe2/python/layers/

/usr/local/lib64/python3.6/site-packages/caffe2/python/layers

Name	Size	Mode	Actions
__pycache__/	-	0755	rm
adaptive_weight.py	5687	0644	edit dl rm
add_bias.py	1396	0644	edit dl rm
arc_cosine_feature_map.py	7345	0644	edit dl rm
batch_huber_loss.py	3523	0644	edit dl rm
batch_lr_loss.py	11577	0644	edit dl rm
batch_mse_loss.py	2333	0644	edit dl rm
batch_normalization.py	3823	0644	edit dl rm
batch_sigmoid_cross_entropy_loss.py	1483	0644	edit dl rm
batch_softmax_loss.py	4580	0644	edit dl rm
blob_weighted_sum.py	2219	0644	edit dl rm
bpr_loss.py	1499	0644	edit dl rm
bucket_weighted.py	2355	0644	edit dl rm
build_index.py	1937	0644	edit dl rm
concat.py	4849	0644	edit dl rm
constant_weight.py	1208	0644	edit dl rm
conv.py	5050	0644	edit dl rm
dropout.py	1410	0644	edit dl rm
fc.py	9296	0644	edit dl rm
fc_without_bias.py	1954	0644	edit dl rm
fc_with_bootstrap.py	12788	0644	edit dl rm
feature_sparse_to_dense.py	14361	0644	edit dl rm
functional.py	4875	0644	edit dl rm
gather_record.py	3260	0644	edit dl rm
homotopy_weight.py	4306	0644	edit dl rm
label_smooth.py	3507	0644	edit dl rm
last_n_window_collector.py	2392	0644	edit dl rm
layers.py	17412	0644	edit dl rm
layer_normalization.py	4291	0644	edit dl rm
margin_rank_loss.py	1951	0644	edit dl rm
merge_id_lists.py	1500	0644	edit dl rm
pairwise_similarity.py	3549	0644	edit dl rm
position_weighted.py	2066	0644	edit dl rm
random_fourier_features.py	3187	0644	edit dl rm
reservoir_sampling.py	3013	0644	edit dl rm
sampling_train.py	2210	0644	edit dl rm
sampling_trainable_mixin.py	1366	0644	edit dl rm
select_record_by_context.py	2381	0644	edit dl rm
semi_random_features.py	5809	0644	edit dl rm
sparse_dropout_with_replacement.py	3943	0644	edit dl rm
sparse_feature_hash.py	4618	0644	edit dl rm
sparse_itemwise_dropout_with_replacement.py	3944	0644	edit dl rm
sparse_lookup.py	22170	0644	edit dl rm
split.py	2257	0644	edit dl rm
tags.py	4114	0644	edit dl rm
uniform_sampling.py	2779	0644	edit dl rm
__init__.py	943	0644	edit dl rm

Edit: /usr/local/lib64/python3.6/site-packages/caffe2/python/layers/dropout.py (1410B)

# 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)

# 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)