tf.lookup.StaticHashTable
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. |