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/merge_id_lists.py (1500B)

from caffe2.python import schema
from caffe2.python.layers.layers import (
    get_categorical_limit,
    ModelLayer,
    IdList
)

import numpy as np

class MergeIdLists(ModelLayer):
    """Merge multiple ID_LISTs into a single ID_LIST

Args:
        model: A layer model instance
        input_record: Tuple (Struct) of ID_LIST features to be
        merged

Returns:
        the merged ID_LIST feature
    """
    def __init__(self, model, input_record, name='merged'):
        super(MergeIdLists, self).__init__(model, name, input_record)
        assert all(schema.equal_schemas(x, IdList) for x in input_record), \
            "Inputs to MergeIdLists should all be IdLists."

assert all(record.items.metadata is not None
                   for record in self.input_record), \
            "Features without metadata are not supported"

merge_dim = max(get_categorical_limit(record)
                        for record in self.input_record)
        assert merge_dim is not None, "Unbounded features are not supported"

self.output_schema = schema.NewRecord(
            model.net, schema.List(
                schema.Scalar(
                    np.int64,
                    blob=model.net.NextBlob(name),
                    metadata=schema.Metadata(categorical_limit=merge_dim)
                )))

def add_ops(self, net):
        return net.MergeIdLists(self.input_record.field_blobs(),
                                self.output_schema.field_blobs())

from caffe2.python import schema from caffe2.python.layers.layers import ( get_categorical_limit, ModelLayer, IdList ) import numpy as np class MergeIdLists(ModelLayer): """Merge multiple ID_LISTs into a single ID_LIST Args: model: A layer model instance input_record: Tuple (Struct) of ID_LIST features to be merged Returns: the merged ID_LIST feature """ def __init__(self, model, input_record, name='merged'): super(MergeIdLists, self).__init__(model, name, input_record) assert all(schema.equal_schemas(x, IdList) for x in input_record), \ "Inputs to MergeIdLists should all be IdLists." assert all(record.items.metadata is not None for record in self.input_record), \ "Features without metadata are not supported" merge_dim = max(get_categorical_limit(record) for record in self.input_record) assert merge_dim is not None, "Unbounded features are not supported" self.output_schema = schema.NewRecord( model.net, schema.List( schema.Scalar( np.int64, blob=model.net.NextBlob(name), metadata=schema.Metadata(categorical_limit=merge_dim) ))) def add_ops(self, net): return net.MergeIdLists(self.input_record.field_blobs(), self.output_schema.field_blobs())