tf.keras.ops.vectorized_map  |  TensorFlow v2.16.1 (original) (raw)

tf.keras.ops.vectorized_map

Parallel map of function on axis 0 of tensor(s) elements.

tf.keras.ops.vectorized_map(
    function, elements
)

Schematically, vectorized_map implements the following, in the case of a single tensor input elements:

def vectorized_map(function, elements)
    outputs = []
    for e in elements:
        outputs.append(function(e))
    return stack(outputs)

In the case of an iterable of tensors elements, it implements the following:

def vectorized_map(function, elements)
    batch_size = elements[0].shape[0]
    outputs = []
    for index in range(batch_size):
        outputs.append(function([e[index] for e in elements]))
    return np.stack(outputs)

In this case, function is expected to take as input a single list of tensor arguments.

Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License, and code samples are licensed under the Apache 2.0 License. For details, see the Google Developers Site Policies. Java is a registered trademark of Oracle and/or its affiliates. Some content is licensed under the numpy license.

Last updated 2024-06-07 UTC.