code: def __call__(self, shape, dtype=None, partition_info=None):
      shape = tuple(shape)
      if len(shape) == 2:
          flat_shape = shape
      elif len(shape) == 4:  # assumes NHWC
          flat_shape = (np.prod(shape[:-1]), shape[-1])
      else:
          raise NotImplementedError
      a = np.random.normal(0.0, 1.0, flat_shape)
      u, _, v = np.linalg.svd(a, full_matrices=False)
      q = (
          u if u.shape == flat_shape else v
      )  # pick the one with the correct shape
      q = q.reshape(shape)
      return (self.gain * q[: shape[0], : shape[1]]).astype(np.float32)
  
imports: import numpy
  import tensorflow
  from tensorflow.python.ops.losses.losses_impl import Reduction
  from rl_coach.architectures.tensorflow_components.layers import Dense, convert_layer_class
  from rl_coach.base_parameters import AgentParameters
  from rl_coach.spaces import SpacesDefinition
  from rl_coach.utils import force_list
  from rl_coach.architectures.tensorflow_components.utils import squeeze_tensor
label_desc: Use image node_id 2 for calling the Orthogonal obj's underlying member method code with example usage: obj.__call__(shape, dtype, partition_info) and returns: unknown