parameters: (input, name=None)
return_statement: return tf.clip_by_value(value, 0, 1)
docstring: Convert a CIE XYZ image to RGB.
  
      Args:
        input: A 3-D (`[H, W, 3]`) or 4-D (`[N, H, W, 3]`) Tensor.
        name: A name for the operation (optional).
  
      Returns:
        A 3-D (`[H, W, 3]`) or 4-D (`[N, H, W, 3]`) Tensor.
docstring_summary: Convert a CIE XYZ image to RGB.
docstring_tokens: Convert a CIE XYZ image to RGB .
function: def xyz_to_rgb(input, name=None):
      """
      Convert a CIE XYZ image to RGB.
  
      Args:
        input: A 3-D (`[H, W, 3]`) or 4-D (`[N, H, W, 3]`) Tensor.
        name: A name for the operation (optional).
  
      Returns:
        A 3-D (`[H, W, 3]`) or 4-D (`[N, H, W, 3]`) Tensor.
      """
      input = tf.convert_to_tensor(input)
      assert input.dtype in (tf.float16, tf.float32, tf.float64)
  
      # inv of:
      # [[0.412453, 0.35758 , 0.180423],
      #  [0.212671, 0.71516 , 0.072169],
      #  [0.019334, 0.119193, 0.950227]]
      kernel = tf.constant(
          [
              [3.24048134, -1.53715152, -0.49853633],
              [-0.96925495, 1.87599, 0.04155593],
              [0.05564664, -0.20404134, 1.05731107],
          ],
          input.dtype,
      )
      value = tf.tensordot(input, tf.transpose(kernel), axes=((-1,), (0,)))
      value = tf.where(
          tf.math.greater(value, 0.0031308),
          tf.math.pow(value, 1.0 / 2.4) * 1.055 - 0.055,
          value * 12.92,
      )
      return tf.clip_by_value(value, 0, 1)
function_tokens: def xyz_to_rgb ( input , name = None ) : input = tf . convert_to_tensor ( input ) assert input . dtype in ( tf . float16 , tf . float32 , tf . float64 ) # inv of: # [[0.412453, 0.35758 , 0.180423], #  [0.212671, 0.71516 , 0.072169], #  [0.019334, 0.119193, 0.950227]] kernel = tf . constant ( [ [ 3.24048134 , - 1.53715152 , - 0.49853633 ] , [ - 0.96925495 , 1.87599 , 0.04155593 ] , [ 0.05564664 , - 0.20404134 , 1.05731107 ] , ] , input . dtype , ) value = tf . tensordot ( input , tf . transpose ( kernel ) , axes = ( ( - 1 , ) , ( 0 , ) ) ) value = tf . where ( tf . math . greater ( value , 0.0031308 ) , tf . math . pow ( value , 1.0 / 2.4 ) * 1.055 - 0.055 , value * 12.92 , ) return tf . clip_by_value ( value , 0 , 1 )