tf.contrib.lookup.HashTable

A generic hash table implementation.

Example usage:

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

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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

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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

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.

© 2020 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r1.15/api_docs/python/tf/contrib/lookup/HashTable