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/last_n_window_collector.py (2392B)

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

from caffe2.python import core, schema
from caffe2.python.layers.layers import ModelLayer

class LastNWindowCollector(ModelLayer):
    """
    Collect last-N samples from input record. If you have complex data,
    use PackRecords to pack it before using this layer.

This layer is not thread safe.
    """

def __init__(self, model, input_record, num_to_collect,
                 name='last_n_window_collector', **kwargs):
        super(LastNWindowCollector, self).__init__(
            model, name, input_record, **kwargs)
        assert num_to_collect > 0
        self.num_to_collect = num_to_collect
        assert isinstance(input_record, schema.Scalar), \
            "Got {!r}".format(input_record)

self.last_n = self.create_param(param_name='last_n',
                                        shape=[0],
                                        initializer=('ConstantFill', {}),
                                        optimizer=model.NoOptim)

self.next_blob = self.create_param(
            param_name='next',
            shape=[],
            initializer=('ConstantFill',
                         {'value': 0, 'dtype': core.DataType.INT32}),
            optimizer=model.NoOptim
        )

self.mutex = self.create_param(
            param_name='mutex',
            shape=[],
            initializer=('CreateMutex',),
            optimizer=model.NoOptim,
        )

self.num_visited_blob = self.create_param(
            param_name='num_visited',
            shape=[],
            initializer=('ConstantFill', {
                'value': 0,
                'dtype': core.DataType.INT64,
            }),
            optimizer=model.NoOptim,
        )

self.output_schema = schema.Struct(
            (
                'last_n',
                schema.from_blob_list(input_record, [self.last_n])
            ),
            ('num_visited', schema.Scalar(blob=self.num_visited_blob)),
            ('mutex', schema.Scalar(blob=self.mutex)),
        )

def add_ops(self, net):
        net.LastNWindowCollector(
            [self.last_n, self.next_blob, self.input_record(), self.mutex,
             self.num_visited_blob],
            [self.last_n, self.next_blob, self.num_visited_blob],
            num_to_collect=self.num_to_collect,
        )

## @package last_n_window_collector # Module caffe2.python.layers.last_n_window_collector from caffe2.python import core, schema from caffe2.python.layers.layers import ModelLayer class LastNWindowCollector(ModelLayer): """ Collect last-N samples from input record. If you have complex data, use PackRecords to pack it before using this layer. This layer is not thread safe. """ def __init__(self, model, input_record, num_to_collect, name='last_n_window_collector', **kwargs): super(LastNWindowCollector, self).__init__( model, name, input_record, **kwargs) assert num_to_collect > 0 self.num_to_collect = num_to_collect assert isinstance(input_record, schema.Scalar), \ "Got {!r}".format(input_record) self.last_n = self.create_param(param_name='last_n', shape=[0], initializer=('ConstantFill', {}), optimizer=model.NoOptim) self.next_blob = self.create_param( param_name='next', shape=[], initializer=('ConstantFill', {'value': 0, 'dtype': core.DataType.INT32}), optimizer=model.NoOptim ) self.mutex = self.create_param( param_name='mutex', shape=[], initializer=('CreateMutex',), optimizer=model.NoOptim, ) self.num_visited_blob = self.create_param( param_name='num_visited', shape=[], initializer=('ConstantFill', { 'value': 0, 'dtype': core.DataType.INT64, }), optimizer=model.NoOptim, ) self.output_schema = schema.Struct( ( 'last_n', schema.from_blob_list(input_record, [self.last_n]) ), ('num_visited', schema.Scalar(blob=self.num_visited_blob)), ('mutex', schema.Scalar(blob=self.mutex)), ) def add_ops(self, net): net.LastNWindowCollector( [self.last_n, self.next_blob, self.input_record(), self.mutex, self.num_visited_blob], [self.last_n, self.next_blob, self.num_visited_blob], num_to_collect=self.num_to_collect, )