A generic hash table that is immutable once initialized.
tf.lookup.StaticHashTable(
initializer, default_value, name=None
)
Example usage:
keys_tensor = tf.constant([1, 2])
vals_tensor = tf.constant([3, 4])
input_tensor = tf.constant([1, 5])
table = tf.lookup.StaticHashTable(
tf.lookup.KeyValueTensorInitializer(keys_tensor, vals_tensor), -1)
print(table.lookup(input_tensor))
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.
|
name
|
A name for the operation (optional).
|
Attributes |
default_value
|
The default value of the table.
|
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.
|