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/sampling_trainable_mixin.py (1366B)

## @package sampling_trainable_mixin
# Module caffe2.python.layers.sampling_trainable_mixin

import abc

class SamplingTrainableMixin(metaclass=abc.ABCMeta):

def __init__(self, *args, **kwargs):
        super(SamplingTrainableMixin, self).__init__(*args, **kwargs)
        self._train_param_blobs = None
        self._train_param_blobs_frozen = False

@property
    @abc.abstractmethod
    def param_blobs(self):
        """
        List of parameter blobs for prediction net
        """
        pass

@property
    def train_param_blobs(self):
        """
        If train_param_blobs is not set before used, default to param_blobs
        """
        if self._train_param_blobs is None:
            self.train_param_blobs = self.param_blobs
        return self._train_param_blobs

@train_param_blobs.setter
    def train_param_blobs(self, blobs):
        assert not self._train_param_blobs_frozen
        assert blobs is not None
        self._train_param_blobs_frozen = True
        self._train_param_blobs = blobs

@abc.abstractmethod
    def _add_ops(self, net, param_blobs):
        """
        Add ops to the given net, using the given param_blobs
        """
        pass

def add_ops(self, net):
        self._add_ops(net, self.param_blobs)

def add_train_ops(self, net):
        self._add_ops(net, self.train_param_blobs)

## @package sampling_trainable_mixin # Module caffe2.python.layers.sampling_trainable_mixin import abc class SamplingTrainableMixin(metaclass=abc.ABCMeta): def __init__(self, *args, **kwargs): super(SamplingTrainableMixin, self).__init__(*args, **kwargs) self._train_param_blobs = None self._train_param_blobs_frozen = False @property @abc.abstractmethod def param_blobs(self): """ List of parameter blobs for prediction net """ pass @property def train_param_blobs(self): """ If train_param_blobs is not set before used, default to param_blobs """ if self._train_param_blobs is None: self.train_param_blobs = self.param_blobs return self._train_param_blobs @train_param_blobs.setter def train_param_blobs(self, blobs): assert not self._train_param_blobs_frozen assert blobs is not None self._train_param_blobs_frozen = True self._train_param_blobs = blobs @abc.abstractmethod def _add_ops(self, net, param_blobs): """ Add ops to the given net, using the given param_blobs """ pass def add_ops(self, net): self._add_ops(net, self.param_blobs) def add_train_ops(self, net): self._add_ops(net, self.train_param_blobs)