tf.contrib.framework.assign_from_checkpoint_fn(model_path, var_list, ignore_missing_vars=False, reshape_variables=False)

tf.contrib.framework.assign_from_checkpoint_fn(model_path, var_list, ignore_missing_vars=False, reshape_variables=False)

See the guide: Framework (contrib) > Variables

Returns a function that assigns specific variables from a checkpoint.

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 correspoing 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.

Raises:

• ValueError: If the checkpoint specified at model_path is missing one of the variables in var_list.

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