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tf.contrib.framework.assign_from_checkpoint_fn

tf.contrib.framework.assign_from_checkpoint_fn

assign_from_checkpoint_fn(
    model_path,
    var_list,
    ignore_missing_vars=False,
    reshape_variables=False
)

Defined in tensorflow/contrib/framework/python/ops/variables.py.

See the guide: Framework (contrib) > Variables

Returns a function that assigns specific variables from a checkpoint.

If ignore_missing_vars is True and no variables are found in the checkpoint it returns None.

Args:

  • model_path: The full path to the model checkpoint. To get latest checkpoint use model_path = tf.train.latest_checkpoint(checkpoint_dir)
  • var_list: A list of Variable objects or a dictionary mapping names in the checkpoint to the corresponding variables to initialize. If empty or None, it would return no_op(), None.
  • ignore_missing_vars: Boolean, if True it would ignore variables missing in the checkpoint with a warning instead of failing.
  • reshape_variables: Boolean, if True it would automatically reshape variables which are of different shape then the ones stored in the checkpoint but which have the same number of elements.

Returns:

A function that takes a single argument, a tf.Session, that applies the assignment operation. If no matching variables were found in the checkpoint then None is returned.

Raises:

  • ValueError: If var_list is empty.

© 2017 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/framework/assign_from_checkpoint_fn