code: def _decorrelated_batch_normalization_1group(x, mean, projection):
      spatial_ndim = len(x.shape[2:])
      spatial_axis = tuple(range(2, 2 + spatial_ndim))
      b, C = x.shape[:2]
      x_hat = x.transpose((1, 0) + spatial_axis).reshape(C, -1)
      y_hat = projection.dot(x_hat - mean[:, None])
      y = y_hat.reshape((C, b) + x.shape[2:]).transpose(
          (1, 0) + spatial_axis
      )
      return y
  
imports: import contextlib
  import os
  import tempfile
  import unittest
  import numpy
  import chainer
  from chainer import links
  from chainer import testing
label_desc: Use image node_id 2 for calling a global function with example usage: _decorrelated_batch_normalization_1group(x, mean, projection) and returns: y