class_docstr: Perform a special crop - one of the four corners or center crop
  
  :param size: (tuple or list):
      dimensions of the crop
  
  :param crop_type: (int in `{0,1,2,3,4}`):
      0 = center crop
      1 = top left crop
      2 = top right crop
      3 = bottom right crop
      4 = bottom left crop
code: def __call__(self, x, y=None):
      if self.crop_type == 0:
          # center crop
          x_diff = (x.size(1) - self.size[0]) / 2.0
          y_diff = (x.size(2) - self.size[1]) / 2.0
          ct_x = [
              int(math.ceil(x_diff)),
              x.size(1) - int(math.floor(x_diff)),
          ]
          ct_y = [
              int(math.ceil(y_diff)),
              x.size(2) - int(math.floor(y_diff)),
          ]
          indices = [ct_x, ct_y]
      elif self.crop_type == 1:
          # top left crop
          tl_x = [0, self.size[0]]
          tl_y = [0, self.size[1]]
          indices = [tl_x, tl_y]
      elif self.crop_type == 2:
          # top right crop
          tr_x = [0, self.size[0]]
          tr_y = [x.size(2) - self.size[1], x.size(2)]
          indices = [tr_x, tr_y]
      elif self.crop_type == 3:
          # bottom right crop
          br_x = [x.size(1) - self.size[0], x.size(1)]
          br_y = [x.size(2) - self.size[1], x.size(2)]
          indices = [br_x, br_y]
      elif self.crop_type == 4:
          # bottom left crop
          bl_x = [x.size(1) - self.size[0], x.size(1)]
          bl_y = [0, self.size[1]]
          indices = [bl_x, bl_y]
  
      x = x[
          :,
          indices[0][0] : indices[0][1],
          indices[1][0] : indices[1][1],
      ]
  
      if y is not None:
          y = y[
              :,
              indices[0][0] : indices[0][1],
              indices[1][0] : indices[1][1],
          ]
          return x, y
      return x
  
imports: import os
  import random
  import math
  import numpy
  import torch
label_desc: Use image node_id 2 for calling the SpecialCrop obj's underlying member method code with example usage: obj.__call__(x, y) and returns: x, x,  y