code: def prepare_tf_inputs_from_pt_inputs(self, pt_inputs_dict):
      tf_inputs_dict = {}
      for key, value in pt_inputs_dict.items():
          # skip key that does not exist in tf
          if isinstance(value, dict):
              tf_inputs_dict[
                  key
              ] = self.prepare_pt_inputs_from_tf_inputs(value)
          elif isinstance(value, (list, tuple)):
              tf_inputs_dict[key] = (
                  self.prepare_pt_inputs_from_tf_inputs(iter_value)
                  for iter_value in value
              )
          elif isinstance(value, bool):
              tf_inputs_dict[key] = value
          elif key == "input_values":
              tf_inputs_dict[key] = tf.convert_to_tensor(
                  value.cpu().numpy(), dtype=tf.float32
              )
          elif key == "pixel_values":
              tf_inputs_dict[key] = tf.convert_to_tensor(
                  value.cpu().numpy(), dtype=tf.float32
              )
          elif key == "input_features":
              tf_inputs_dict[key] = tf.convert_to_tensor(
                  value.cpu().numpy(), dtype=tf.float32
              )
          # other general float inputs
          elif value.is_floating_point():
              tf_inputs_dict[key] = tf.convert_to_tensor(
                  value.cpu().numpy(), dtype=tf.float32
              )
          else:
              tf_inputs_dict[key] = tf.convert_to_tensor(
                  value.cpu().numpy(), dtype=tf.int32
              )
  
      return tf_inputs_dict
  
imports: import copy
  import unittest
  import numpy
  from transformers import LxmertConfig, is_tf_available, is_torch_available
  from transformers.models.auto import get_values
  from transformers.testing_utils import require_torch, slow, torch_device
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_common import ModelTesterMixin, ids_tensor
  from ...test_pipeline_mixin import PipelineTesterMixin
label_desc: Use image node_id 12 for calling the LxmertModelTest obj's underlying member method code with example usage: obj.prepare_tf_inputs_from_pt_inputs(pt_inputs_dict) and returns: tf_inputs_dict