def __init__(self, categorical_column, dimension, combiner='mean', initializer=None, max_sequence_length=0): _TPUBaseEmbeddingColumn.__init__(self, categorical_column, max_sequence_length=max_sequence_length) self._key = None
def __init__(self, categorical_column, shared_embedding_column_creator, combiner='mean', initializer=None, shared_embedding_collection_name=None, max_sequence_length=0): _TPUBaseEmbeddingColumn.__init__(self, categorical_column, max_sequence_length=max_sequence_length) self._initializer = initializer self._shared_embedding_collection_name = shared_embedding_collection_name
def __init__(self, categorical_column, dimension, combiner='mean', initializer=None, max_sequence_length=0, learning_rate_fn=None, use_safe_embedding_lookup=True): _TPUBaseEmbeddingColumn.__init__( self, categorical_column, max_sequence_length=max_sequence_length, learning_rate_fn=learning_rate_fn) self._key = None
def __init__(self, categorical_column, shared_embedding_column_creator, combiner='mean', initializer=None, shared_embedding_collection_name=None, max_sequence_length=0, learning_rate_fn=None, use_safe_embedding_lookup=True): _TPUBaseEmbeddingColumn.__init__( self, categorical_column, max_sequence_length=max_sequence_length, learning_rate_fn=learning_rate_fn) self._initializer = initializer self._shared_embedding_collection_name = shared_embedding_collection_name
def __init__(self, categorical_column, dimension, combiner='mean', initializer=None, max_sequence_length=0, learning_rate_fn=None, use_safe_embedding_lookup=True, bypass_scope_validation=False): _TPUBaseEmbeddingColumn.__init__( self, categorical_column, max_sequence_length=max_sequence_length, learning_rate_fn=learning_rate_fn) self._key = None # If true, scope validation is skipped to allow the same column to be used # in multiple variable scopes. By default, this is False, and we expect a # 1:1 mapping between feature columns and scopes. self._bypass_scope_validation = bypass_scope_validation