tf.lookup.StaticHashTable

TensorFlow 1 version View source on GitHub

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.