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 | 
Creates a table initializer from a tf.data.Dataset.
tf.lookup.experimental.DatasetInitializer(
    dataset
)
Sample usage:
keys = tf.data.Dataset.range(100)values = tf.data.Dataset.range(100).map(lambda x: string_ops.as_string(x * 2))ds = tf.data.Dataset.zip((keys, values))init = tf.lookup.experimental.DatasetInitializer(ds)table = tf.lookup.StaticHashTable(init, "")table.lookup(tf.constant([0, 1, 2], dtype=tf.int64)).numpy()array([b'0', b'2', b'4'], dtype=object)
Raises: ValueError if dataset doesn't conform to specifications.
Args | |
|---|---|
dataset
 | 
A tf.data.Dataset object that produces tuples of scalars. The
first scalar is treated as a key and the second as value.
 | 
Attributes | |
|---|---|
dataset
 | 
A tf.data.Dataset object that produces tuples of scalars. The
first scalar is treated as a key and the second as value.
 | 
key_dtype
 | 
The expected table key dtype. | 
value_dtype
 | 
The expected table value dtype. | 
Methods
initialize
initialize(
    table
)
Returns the table initialization op.
    View source on GitHub