class_docstr: Apply shear operation along y-axis.
  
  Args:
      initial_magnitude: the initial magnitude.
      initial_probability: the initial probability. If None, the augmentation will be randomly
          applied according to he augmentation sampling range.
      magnitude_range: the sampling range for random sampling and clamping the optimized magnitude.
      temperature: temperature for RelaxedBernoulli distribution used during training.
      symmetric_megnitude: if to randomly assign the magnitude as negative or not.
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code: def _process_magnitude(magnitude: Tensor) -> Tensor:
      # make it sign-agnostic
      return magnitude * 180
  
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 for calling the ShearY obj's underlying member method code with example usage: obj._process_magnitude(magnitude) and returns: unknown