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tf.contrib.lookup.HashTable

A generic hash table implementation.

tf.contrib.lookup.HashTable(
    initializer, default_value, shared_name=None, name=None
)

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(
    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(
    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(
    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.