code: def __init__(self, img_size: int, context_length: int):
      super().__init__()
      self.img_size = img_size
      self.context_length = context_length
      self.logit_scale = nn.Parameter(torch.tensor(math.log(1 / 0.07)))
  
imports: import math
  import torch
  from abc import abstractmethod
  from abc import ABCMeta
  from torch import nn
  from torch import Tensor
  from typing import Any
  from typing import Tuple
  from typing import Optional
  from cftool.types import tensor_dict_type
  from .constants import TEXT_KEY
  from ...schema import TrainerState
  from ...schema import IDLModel
  from ...constants import INPUT_KEY
  from ...constants import PREDICTIONS_KEY
label_desc: Use image node_id 1 to create a new IPerceptor object from inherited base classes: IDLModel with example: obj = IPerceptor(img_size, context_length)