tf.contrib.framework.assign_from_checkpoint_fn(model_path, var_list, ignore_missing_vars=False, reshape_variables=False)
Returns a function that assigns specific variables from a checkpoint.
Args:
-
model_path: The full path to the model checkpoint. To get latest checkpoint usemodel_path = tf.train.latest_checkpoint(checkpoint_dir) -
var_list: A list ofVariableobjects 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 atmodel_pathis missing one of the variables invar_list.
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