class_docstr: Shear the tensor.
  
  Args:
      shear: tensor containing the angle to shear
        in the x and y direction. The tensor must have a shape of
        (B, 2), where B is batch size, last dimension contains shx shy.
      mode: interpolation mode to calculate output values
        ``'bilinear'`` | ``'nearest'``.
      padding_mode: padding mode for outside grid values
        ``'zeros'`` | ``'border'`` | ``'reflection'``.
      align_corners: interpolation flag.
  
  Returns:
      The skewed tensor with the same shape as the input.
  
  Example:
      >>> img = torch.rand(1, 3, 4, 4)
      >>> shear_factor = torch.tensor([[0.5, 0.0]])
      >>> out = Shear(shear_factor)(img)
      >>> print(out.shape)
      torch.Size([1, 3, 4, 4])
class_docstr_tok: ["Shear","the","tensor",".","Args",":","shear",":","tensor","containing","the","angle","to","shear","in","the","x","and","y","direction",".","The","tensor","must","have","a","shape","of","(","B",",","2",")",",","where","B","is","batch","size",",","last","dimension","contains","shx","shy",".","mode",":","interpolation","mode","to","calculate","output","values","``","'bilinear","'","``","|","``","'nearest","'","``",".","padding_mode",":","padding","mode","for","outside","grid","values","``","'zeros","'","``","|","``","'border","'","``","|","``","'reflection","'","``",".","align_corners",":","interpolation","flag",".","Returns",":","The","skewed","tensor","with","the","same","shape","as","the","input",".","Example",":",">",">",">","img","=","torch.rand","(","1",",","3",",","4",",","4",")",">",">",">","shear_factor","=","torch.tensor","(","[","[","0.5",",","0.0","]","]",")",">",">",">","out","=","Shear","(","shear_factor",")","(","img",")",">",">",">","print","(","out.shape",")","torch.Size","(","[","1",",","3",",","4",",","4","]",")"]
code: def __init__(
      self,
      shear: torch.Tensor,
      mode: str = "bilinear",
      padding_mode: str = "zeros",
      align_corners: bool = True,
  ) -> None:
      super().__init__()
      self.shear: torch.Tensor = shear
      self.mode: str = mode
      self.padding_mode: str = padding_mode
      self.align_corners: bool = align_corners
  
imports: from typing import Optional, Tuple, Union
  import torch
  from torch import nn
  from kornia.core import ones, ones_like, zeros
  from kornia.filters import gaussian_blur2d
  from kornia.utils import _extract_device_dtype
  from kornia.utils.image import perform_keep_shape_image
  from kornia.utils.misc import eye_like
  from .imgwarp import get_affine_matrix2d, get_projective_transform, get_rotation_matrix2d, warp_affine, warp_affine3d
label_desc: Use image node_id 1 to create a new Shear object from inherited base classes: nn with example: obj = Shear(shear, mode, padding_mode, align_corners)