tf.contrib.framework.assign_from_checkpoint_fn(
model_path,
var_list,
ignore_missing_vars=False,
reshape_variables=False
)
Defined in tensorflow/contrib/framework/python/ops/variables.py
.
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 usemodel_path = tf.train.latest_checkpoint(checkpoint_dir)
var_list
: A list ofVariable
objects or a dictionary mapping names in the checkpoint to the corresponding variables to initialize. If empty orNone
, it would returnno_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.