tf.contrib.framework.assign_from_checkpoint

Creates an operation to assign specific variables from a checkpoint.

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

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 (possibly partitioned) `Variable` objects or a dictionary mapping names in the checkpoint to the corresponding variables or list of variables to initialize from that checkpoint value. For partitioned Variables, the name in the checkpoint must be the full variable, not the name of the partitioned variable, eg. "my_var" rather than "my_var/part_4". If empty, returns no_op(), {}.
`ignore_missing_vars`	Boolean, if True ignore variables missing in the checkpoint with a warning instead of failing.

Returns
the restore_op and the feed_dict that need to be run to restore var_list.

Raises
`ValueError`	If `ignore_missing_vars` is False and the checkpoint specified at `model_path` is missing one of the variables in `var_list`.

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Last updated 2020-10-01 UTC.

Args