tf.contrib.framework.assign_from_checkpoint_fn
Returns a function that assigns specific variables from a checkpoint.
tf.contrib.framework.assign_from_checkpoint_fn( model_path, var_list, ignore_missing_vars=False, reshape_variables=False )
If ignore_missing_vars is True and no variables are found in the checkpoint it returns None.
Args | |
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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 | |
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A function that takes a single argument, a tf.compat.v1.Session , that applies the assignment operation. If no matching variables were found in the checkpoint then None is returned. |
Raises | |
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ValueError | If var_list is empty. |
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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/framework/assign_from_checkpoint_fn