contrib.framework.assign_from_checkpoint_fn
tf.contrib.framework.assign_from_checkpoint_fn
tf.contrib.framework.assign_from_checkpoint_fn
assign_from_checkpoint_fn( model_path, var_list, ignore_missing_vars=False, reshape_variables=False )
Defined in tensorflow/contrib/framework/python/ops/variables.py
.
See the guide: Framework (contrib) > Variables
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.
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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/api_docs/python/tf/contrib/framework/assign_from_checkpoint_fn