code: def _binomial_kernel(
      num_channels: int, dtype: tf.DType = tf.float32
  ) -> tf.Tensor:
      """Creates a 5x5 binomial kernel.
  
      Args:
        num_channels: The number of channels of the image to filter.
        dtype: The type of an element in the kernel.
  
      Returns:
        A tensor of shape `[5, 5, num_channels, num_channels]`.
      """
      kernel = np.array(
          (1.0, 4.0, 6.0, 4.0, 1.0), dtype=dtype.as_numpy_dtype
      )
      kernel = np.outer(kernel, kernel)
      kernel /= np.sum(kernel)
      kernel = kernel[:, :, np.newaxis, np.newaxis]
      return tf.constant(kernel, dtype=dtype) * tf.eye(
          num_channels, dtype=dtype
      )
  
file_path: graphics/tensorflow_graphics/image/pyramid.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from typing import Callable, List, Optional, Tuple
  import numpy
  from six.moves import range
  import tensorflow
  from tensorflow_graphics.util import export_api
  from tensorflow_graphics.util import shape
  from tensorflow_graphics.util import type_alias
label_desc: Use image node_id 2 for calling a global function with example usage: _binomial_kernel(num_channels, dtype) and returns: unknown