tf.contrib.lookup.index_table_from_tensor(
mapping,
num_oov_buckets=0,
default_value=-1,
hasher_spec=tf.contrib.lookup.FastHashSpec,
dtype=tf.string,
name=None
)
Defined in tensorflow/contrib/lookup/lookup_ops.py.
Returns a lookup table that converts a string tensor into int64 IDs.
This operation constructs a lookup table to convert tensor of strings into int64 IDs. The mapping can be initialized from a string mapping 1-D tensor where each element is a key and corresponding index within the tensor is the value.
Any lookup of an out-of-vocabulary token will return a bucket ID based on its hash if num_oov_buckets is greater than zero. Otherwise it is assigned the default_value. The bucket ID range is [mapping size, mapping size + num_oov_buckets - 1].
The underlying table must be initialized by calling tf.tables_initializer.run() or table.init.run() once.
Elements in mapping cannot have duplicates, otherwise when executing the table initializer op, it will throw a FailedPreconditionError.
Sample Usages:
mapping_strings = tf.constant(["emerson", "lake", "palmer"])
table = tf.contrib.lookup.index_table_from_tensor(
mapping=mapping_strings, num_oov_buckets=1, default_value=-1)
features = tf.constant(["emerson", "lake", "and", "palmer"])
ids = table.lookup(features)
...
tf.tables_initializer().run()
ids.eval() ==> [0, 1, 3, 2]
mapping: A 1-D Tensor that specifies the mapping of keys to indices. The type of this object must be castable to dtype.num_oov_buckets: The number of out-of-vocabulary buckets.default_value: The value to use for out-of-vocabulary feature values. Defaults to -1.hasher_spec: A HasherSpec to specify the hash function to use for assignment of out-of-vocabulary buckets.dtype: The type of values passed to lookup. Only string and integers are supported.name: A name for this op (optional).The lookup table to map an input Tensor to index int64 Tensor.
ValueError: If mapping is invalid.ValueError: If num_oov_buckets is negative.
© 2018 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/api_docs/python/tf/contrib/lookup/index_table_from_tensor