code: def __init__(self, config: SwiftFormerConfig):
      super().__init__(config)
      self.config = config
  
      self.patch_embed = SwiftFormerPatchEmbedding(config)
      self.encoder = SwiftFormerEncoder(config)
  
      # Initialize weights and apply final processing
      self.post_init()
  
imports: import collections.abc
  from typing import Optional, Tuple, Union
  import torch
  import torch.utils.checkpoint
  from torch import nn
  from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
  from ...activations import ACT2CLS
  from ...modeling_outputs import BaseModelOutputWithNoAttention, ImageClassifierOutputWithNoAttention
  from ...modeling_utils import PreTrainedModel
  from ...utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward, logging
  from .configuration_swiftformer import SwiftFormerConfig
label_desc: Use image node_id 1 to create a new SwiftFormerModel object from inherited base classes: SwiftFormerPreTrainedModel with example: obj = SwiftFormerModel(config)