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
`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.compat.v1.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.

Args