nsl.tools.build_graph

Like nsl.tools.build_graph_from_config, but with individual parameters.

nsl.tools.build_graph(
    embedding_files,
    output_graph_path,
    similarity_threshold=0.8,
    id_feature_name='id',
    embedding_feature_name='embedding',
    lsh_splits=0,
    lsh_rounds=2,
    random_seed=None
)

This API exists to maintain backward compatibility, but is deprecated in favor of using nsl.tools.build_graph_from_config instead.

Args
embedding_files	A list of names of TFRecord files containing tf.train.Example objects, which in turn contain dense embeddings.
output_graph_path	Name of the file to which the output graph in TSV format should be written.
similarity_threshold	Threshold used to determine which edges to retain in the resulting graph.
id_feature_name	The name of the feature in the input tf.train.Example objects representing the ID of examples.
embedding_feature_name	The name of the feature in the input tf.train.Example objects representing the embedding of examples.
lsh_splits	Determines the maximum number of LSH buckets into which input data points will be bucketed by the graph builder. See the nsl.tools.build_graph_from_config documentation for details.
lsh_rounds	The number of rounds of LSH bucketing to perform when lsh_splits > 0. This is also the number of LSH buckets each point will be hashed into.
random_seed	Value used to seed the random number generator used to perform randomized LSH bucketing of the inputs when lsh_splits > 0. By default, the generator will be initialized randomly, but setting this to any integer will initialize it deterministically.

Raises
ValueError	If lsh_splits < 0 or if lsh_splits > 0 and lsh_rounds < 1.