tf.contrib.lookup.MutableHashTable

Class MutableHashTable

Inherits From: LookupInterface

Defined in tensorflow/contrib/lookup/lookup_ops.py.

A generic mutable hash table implementation.

Data can be inserted by calling the insert method and removed by calling the remove method. It does not support initialization via the init method.

Example usage:

table = tf.contrib.lookup.MutableHashTable(key_dtype=tf.string,
                                           value_dtype=tf.int64,
                                           default_value=-1)
sess.run(table.insert(keys, values))
out = table.lookup(query_keys)
print(out.eval())

__init__

__init__(
    key_dtype,
    value_dtype,
    default_value,
    shared_name=None,
    name='MutableHashTable',
    checkpoint=True
)

Creates an empty MutableHashTable object.

Creates a table, the type of its keys and values are specified by key_dtype and value_dtype, respectively.

Args:

• key_dtype: the type of the key tensors.
• value_dtype: the type of the value tensors.
• 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).
• checkpoint: if True, the contents of the table are saved to and restored from checkpoints. If shared_name is empty for a checkpointed table, it is shared using the table node name.

Returns:

A MutableHashTable object.

Raises:

• ValueError: If checkpoint is True and no name was specified.

Properties

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

create_resource

create_resource()

A function that creates a resource handle.

export

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.

initialize

initialize()

A function that initializes the resource. Optional.

insert

insert(
    keys,
    values,
    name=None
)

Associates keys with values.

Args:

• keys: Keys to insert. Can be a tensor of any shape. Must match the table's key type.
• values: Values to be associated with keys. Must be a tensor of the same shape as keys and match the table's value type.
• name: A name for the operation (optional).

Returns:

The created Operation.

Raises:

• TypeError: when keys or values doesn't match the table data types.

lookup

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. Can be a tensor of any shape. Must match the table's key_dtype.
• name: A name for the operation (optional).

Returns:

A tensor containing the values in the same shape as keys using the table's value type.

Raises:

• TypeError: when keys do not match the table data types.

remove

remove(
    keys,
    name=None
)

Removes keys and its associated values from the table.

If a key is not present in the table, it is silently ignored.

Args:

• keys: Keys to remove. Can be a tensor of any shape. Must match the table's key type.
• name: A name for the operation (optional).

Returns:

The created Operation.

Raises:

• TypeError: when keys do not match the table data types.

size

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.