code: def __init__(
      self,
      vocab_size=32000,
      hidden_size=4096,
      intermediate_size=14336,
      num_hidden_layers=32,
      num_attention_heads=32,
      num_key_value_heads=8,
      hidden_act="silu",
      max_position_embeddings=4096 * 32,
      initializer_range=0.02,
      rms_norm_eps=1e-5,
      use_cache=True,
      pad_token_id=None,
      bos_token_id=1,
      eos_token_id=2,
      tie_word_embeddings=False,
      rope_theta=1e6,
      sliding_window=None,
      attention_dropout=0.0,
      num_experts_per_tok=2,
      num_local_experts=8,
      output_router_logits=False,
      router_aux_loss_coef=0.001,
      **kwargs,
  ):
      self.vocab_size = vocab_size
      self.max_position_embeddings = max_position_embeddings
      self.hidden_size = hidden_size
      self.intermediate_size = intermediate_size
      self.num_hidden_layers = num_hidden_layers
      self.num_attention_heads = num_attention_heads
      self.sliding_window = sliding_window
  
      # for backward compatibility
      if num_key_value_heads is None:
          num_key_value_heads = num_attention_heads
  
      self.num_key_value_heads = num_key_value_heads
      self.hidden_act = hidden_act
      self.initializer_range = initializer_range
      self.rms_norm_eps = rms_norm_eps
      self.use_cache = use_cache
      self.rope_theta = rope_theta
      self.attention_dropout = attention_dropout
  
      self.num_experts_per_tok = num_experts_per_tok
      self.num_local_experts = num_local_experts
      self.output_router_logits = output_router_logits
      self.router_aux_loss_coef = router_aux_loss_coef
      super().__init__(
          pad_token_id=pad_token_id,
          bos_token_id=bos_token_id,
          eos_token_id=eos_token_id,
          tie_word_embeddings=tie_word_embeddings,
          **kwargs,
      )
  
imports: from ...configuration_utils import PretrainedConfig
  from ...utils import logging
label_desc: Use image node_id 1 to create a new MixtralConfig object from inherited base classes: PretrainedConfig with example: obj = MixtralConfig(vocab_size, hidden_size, intermediate_size, num_hidden_layers, num_attention_heads, num_key_value_heads, hidden_act, max_position_embeddings, initializer_range, rms_norm_eps, use_cache, pad_token_id, bos_token_id, eos_token_id, tie_word_embeddings, rope_theta, sliding_window, attention_dropout, num_experts_per_tok, num_local_experts, output_router_logits, router_aux_loss_coef)