class_docstr: Apply grayscale operation.
  
  Args:
      initial_probability: the initial probability. If None, the augmentation will be randomly
          applied according to he augmentation sampling range.
      temperature: temperature for RelaxedBernoulli distribution used during training.
class_docstr_tok: ["Apply","grayscale","operation",".","Args",":","initial_probability",":","the","initial","probability",".","If","None",",","the","augmentation","will","be","randomly","applied","according","to","he","augmentation","sampling","range",".","temperature",":","temperature","for","RelaxedBernoulli","distribution","used","during","training","."]
code: def __init__(
      self, initial_probability: float = 0.5, temperature: float = 0.1
  ) -> None:
      super().__init__(
          K.RandomGrayscale(same_on_batch=False, p=initial_probability),
          initial_magnitude=None,
          temperature=temperature,
          symmetric_megnitude=False,
      )
  
imports: from typing import Optional, Tuple
  import kornia.augmentation
  from kornia.augmentation.auto.operations.base import OperationBase
  from kornia.core import Tensor
  from kornia.grad_estimator import STEFunction
label_desc: Use image node_id 1 to create a new Gray object from inherited base classes: OperationBase with example: obj = Gray(initial_probability, temperature)