code: def tf_to_pt_weight_rename(self, tf_weight):
      if tf_weight == "lm_head.weight":
          return tf_weight, "model.embed_tokens.weight"
      else:
          return (tf_weight,)
  
imports: from __future__ import annotations
  import math
  import random
  from typing import Any, Optional, Tuple, Union
  import numpy
  import tensorflow
  from ...activations_tf import get_tf_activation
  from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward, replace_return_docstrings
  from ...modeling_tf_outputs import TFBaseModelOutputWithPastAndCrossAttentions, TFCausalLMOutputWithCrossAttentions
  from ...modeling_tf_utils import TFCausalLanguageModelingLoss, TFModelInputType, TFPreTrainedModel, TFSharedEmbeddings, get_initializer, keras_serializable, unpack_inputs
  from ...tf_utils import check_embeddings_within_bounds, shape_list, stable_softmax
  from ...utils import logging
  from .configuration_xglm import XGLMConfig
label_desc: Use image node_id 7 for calling the TFXGLMForCausalLM obj's underlying member method code with example usage: obj.tf_to_pt_weight_rename(tf_weight) and returns: tf_weight,  str, tf_weight