code: def DnPixelNorm(input_tensor, dim=3, backend="tensorflow"):
      if backend == "tensorflow":
          if dim == 2:
              return pixel_norm_2d(input_tensor)
          elif dim == 3:
              return pixel_norm_3d(input_tensor)
  
      if backend == "keras":
          raise NotImplementedError
  
file_path: DeepNeuro/deepneuro/models/dn_ops.py
imports: import tensorflow
  from keras.layers import UpSampling2D, UpSampling3D, Conv3D, MaxPooling3D, Conv2D, MaxPooling2D, Activation, BatchNormalization, Dropout, ZeroPadding2D, ZeroPadding3D
  from deepneuro.models.ops import pixel_norm_2d, pixel_norm_3d, conv2d, conv3d, deconv2d, deconv3d, upscale2d
label_desc: Use image node_id 8 for calling a global function with example usage: DnPixelNorm(input_tensor, dim, backend) and returns: pixel_norm_2d, pixel_norm_3d