code: def intrinsics_from_matrix(
      matrix: type_alias.TensorLike,
      name: str = "perspective_intrinsics_from_matrix",
  ) -> Tuple[tf.Tensor, tf.Tensor, tf.Tensor]:
      r"""Extracts intrinsic parameters from a calibration matrix.
  
    Extracts the focal length \\((f_x, f_y)\\), the principal point
    \\((c_x, c_y)\\) and the skew_coefficient(\\sc\\) from a camera calibration
    matrix
  
    $$
    \mathbf{C} =
    \begin{bmatrix}
    f_x & sc & c_x \\
    0  & f_y & c_y \\
    0  & 0  & 1 \\
    \end{bmatrix}.
    $$
  
    Note:
      In the following, A1 to An are optional batch dimensions.
  
    Args:
      matrix: A tensor of shape `[A1, ..., An, 3, 3]`, where the last two
        dimensions represent a camera calibration matrix.
      name: A name for this op that defaults to
        "perspective_intrinsics_from_matrix".
  
    Returns:
      Tuple of three tensors, the first two of shape `[A1, ..., An, 2]` and
      the third of shape `[A1, ..., An, 1]`. The first tensor represents the
      focal length, and the second one the principle point and the third one
      represents the skew coefficient.
  
    Raises:
      ValueError: If the shape of `matrix` is not supported.
    """
      with tf.name_scope(name):
          matrix = tf.convert_to_tensor(value=matrix)
  
          shape.check_static(
              tensor=matrix,
              tensor_name="matrix",
              has_rank_greater_than=1,
              has_dim_equals=((-1, 3), (-2, 3)),
          )
          fx = matrix[..., 0, 0]
          fy = matrix[..., 1, 1]
          cx = matrix[..., 0, 2]
          cy = matrix[..., 1, 2]
          skew = matrix[..., 0, 1]
          focal = tf.stack((fx, fy), axis=-1)
          principal_point = tf.stack((cx, cy), axis=-1)
          skew = tf.expand_dims(skew, axis=-1)
          return focal, principal_point, skew
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import math
  from typing import Tuple
  import tensorflow
  from tensorflow_graphics.geometry.representation import grid
  from tensorflow_graphics.util import asserts
  from tensorflow_graphics.util import export_api
  from tensorflow_graphics.util import safe_ops
  from tensorflow_graphics.util import shape
  from tensorflow_graphics.util import type_alias
label_desc: Use image node_id 3 for calling a global function with example usage: intrinsics_from_matrix(matrix, name) and returns: focal,  principal_point,  skew