880e57c9796c5f4ed79195bdd38bc4b0d3abf25f,finetune/saver.py,Saver,save,#Saver#Any#Any#Any#,46

Before Change

        return SaverHook()

    def save(self, finetune_obj, path, mkdir=True):
        if self.values is None:
            raise ValueError("No training has been run, cannot save")
        folder = os.path.dirname(path)
        if not os.path.exists(folder) and mkdir:
            os.mkdir(folder)
        if self.save_dtype is not None:
            self.values = [a.astype(self.save_dtype) for a in self.values]

        included, excluded = self.find_trainable_variables()
        vars_reduced, vals_reduced = self.remove_unchanged(included, self.values, self.fallback)
        var_names = [var.name for var in vars_reduced]
        var_dict = dict(zip(var_names, vals_reduced))
        assert len(vals_reduced) == len(var_names) == len(var_dict)
        joblib.dump((var_dict, finetune_obj), path)

After Change

        return self.fallback_

    def save(self, finetune_obj, path, mkdir=True):
        ckpt_reader = tf.train.load_checkpoint(finetune_obj.estimator_dir)
        variable_map = ckpt_reader.get_variable_to_shape_map()
        names = [name for name in variable_map.keys() if self.exclude_matches is None or self.exclude_matches not in name]
        names = [name if name.endswith(":0") else name for name in names]  // strip the :0 off the end
        values = [ckpt_reader.get_tensor(name) for name in names]
        names = [name + ":0" for name in names]

Instances