A generic hash table implementation.
tf.contrib.lookup.HashTable(
initializer, default_value, shared_name=None, name=None
)
Example usage:
table = tf.HashTable(
tf.KeyValueTensorInitializer(keys, values), -1)
out = table.lookup(input_tensor)
table.init.run()
print(out.eval())
Args |
initializer
|
The table initializer to use. See HashTable kernel for
supported key and value types.
|
default_value
|
The value to use if a key is missing in the table.
|
shared_name
|
If non-empty, this table will be shared under the given name
across multiple sessions.
|
name
|
A name for the operation (optional).
|
Attributes |
default_value
|
The default value of the table.
|
init
|
|
initializer
|
|
key_dtype
|
The table key dtype.
|
name
|
The name of the table.
|
resource_handle
|
Returns the resource handle associated with this Resource.
|
value_dtype
|
The table value dtype.
|
Methods
export
View source
export(
name=None
)
Returns tensors of all keys and values in the table.
Args |
name
|
A name for the operation (optional).
|
Returns |
A pair of tensors with the first tensor containing all keys and the
second tensors containing all values in the table.
|
lookup
View source
lookup(
keys, name=None
)
Looks up keys
in a table, outputs the corresponding values.
The default_value
is used for keys not present in the table.
Args |
keys
|
Keys to look up. May be either a SparseTensor or dense Tensor .
|
name
|
A name for the operation (optional).
|
Returns |
A SparseTensor if keys are sparse, otherwise a dense Tensor .
|
Raises |
TypeError
|
when keys or default_value doesn't match the table data
types.
|
size
View source
size(
name=None
)
Compute the number of elements in this table.
Args |
name
|
A name for the operation (optional).
|
Returns |
A scalar tensor containing the number of elements in this table.
|