tf.contrib.lookup.MutableHashTable

class tf.contrib.lookup.MutableHashTable

A generic mutable hash table implementation.

Data can be inserted by calling the insert 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)
table.insert(keys, values)
out = table.lookup(query_keys)
print out.eval()

Properties

init

The table initialization op.

key_dtype

The table key dtype.

name

The name of the table.

value_dtype

The table value dtype.

Methods

__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.

check_table_dtypes(key_dtype, value_dtype)

Check that the given key_dtype and value_dtype matches the table dtypes.

Args:

• key_dtype: The key data type to check.
• value_dtype: The value data type to check.

Raises:

• TypeError: when 'key_dtype' or 'value_dtype' doesn't match the table data types.

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.

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(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.

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.

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