code: def __init__(
      self,
      input_dim: int,
      output_dim: int,
      num_history: int = 1,
      *,
      bias: bool = True,
      encoder_settings: Optional[Dict[str, MLEncoderSettings]] = None,
      global_encoder_settings: Optional[MLGlobalEncoderSettings] = None,
  ):
      super().__init__(
          encoder_settings=encoder_settings,
          global_encoder_settings=global_encoder_settings,
      )
      if self.encoder is not None:
          input_dim += self.encoder.dim_increment
      input_dim *= num_history
      self.net = torch.nn.Linear(input_dim, output_dim, bias)
  
file_path: carefree-learn/cflearn/models/ml/linear.py
imports: import torch
  from typing import Dict
  from typing import Optional
  from .base import MLModel
  from ...schema import MLEncoderSettings
  from ...schema import MLGlobalEncoderSettings
label_desc: Use image node_id 1 to create a new Linear object from inherited base classes: MLModel with example: obj = Linear(input_dim, output_dim, num_history)