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
