code: def get_config(self, gradient_checkpointing=False):
      return MptConfig(
          vocab_size=self.vocab_size,
          seq_length=self.seq_length,
          hidden_size=self.hidden_size,
          n_layers=self.num_hidden_layers,
          n_heads=self.num_attention_heads,
          hidden_dropout=self.hidden_dropout_prob,
          attention_dropout=self.attention_dropout_prob,
          n_positions=self.max_position_embeddings,
          type_vocab_size=self.type_vocab_size,
          initializer_range=self.initializer_range,
          use_cache=True,
          bos_token_id=self.bos_token_id,
          eos_token_id=self.eos_token_id,
          pad_token_id=self.pad_token_id,
          num_labels=self.num_labels,
          gradient_checkpointing=gradient_checkpointing,
          dtype="float32",
      )
  
imports: import math
  import unittest
  from transformers import MptConfig, is_torch_available
  from transformers.testing_utils import require_bitsandbytes, require_torch, require_torch_gpu, slow, torch_device
  from ...generation.test_utils import GenerationTesterMixin
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_common import ModelTesterMixin, ids_tensor, random_attention_mask
  from ...test_pipeline_mixin import PipelineTesterMixin
label_desc: Use image node_id 4 for calling the MptModelTester obj's underlying member method code with example usage: obj.get_config(gradient_checkpointing) and returns: MptConfig