code: def __init__(self, config):
      super().__init__()
      self.dense_h_to_4h = nn.Linear(
          config.hidden_size, config.intermediate_size
      )
      self.dense_4h_to_h = nn.Linear(
          config.intermediate_size, config.hidden_size
      )
      self.act = ACT2FN[config.hidden_act]
  
imports: import math
  from typing import List, Optional, Tuple, Union
  import torch
  import torch.utils.checkpoint
  from torch import nn
  from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
  from ...activations import ACT2FN
  from ...cache_utils import Cache, DynamicCache
  from ...modeling_attn_mask_utils import _prepare_4d_causal_attention_mask
  from ...modeling_outputs import BaseModelOutputWithPast, CausalLMOutputWithPast, SequenceClassifierOutputWithPast
  from ...modeling_utils import PreTrainedModel
  from ...utils import add_start_docstrings, add_start_docstrings_to_model_forward, logging, replace_return_docstrings
  from .configuration_persimmon import PersimmonConfig
label_desc: Use image node_id 1 to create a new PersimmonMLP object from inherited base classes: nn with example: obj = PersimmonMLP(config)