message: Corrected the tf.linalg.diag_part examples
  This fixes
diff: @@ -2431,16 +2431,16 @@ def matrix_diag_part(
  [5, 6, 7, 8]]])
  # A main diagonal from each batch.
  - tf.matrix_diag_part(input) ==> [[1, 6, 7], # Output shape: (2, 3)
  + tf.linalg.diag_part(input) ==> [[1, 6, 7], # Output shape: (2, 3)
  [5, 2, 7]]
  # A superdiagonal from each batch.
  - tf.matrix_diag_part(input, k = 1)
  + tf.linalg.diag_part(input, k = 1)
  ==> [[2, 7, 6], # Output shape: (2, 3)
  [4, 3, 8]]
  # A band from each batch.
  - tf.matrix_diag_part(input, k = (-1, 2))
  + tf.linalg.diag_part(input, k = (-1, 2))
  ==> [[[3, 8, 0], # Output shape: (2, 4, 3)
  [2, 7, 6],
  [1, 6, 7],
  @@ -2451,7 +2451,7 @@ def matrix_diag_part(
  [0, 1, 6]]]
  # RIGHT_LEFT alignment.
  - tf.matrix_diag_part(input, k = (-1, 2), align="RIGHT_LEFT")
  + tf.linalg.diag_part(input, k = (-1, 2), align="RIGHT_LEFT")
  ==> [[[0, 3, 8], # Output shape: (2, 4, 3)
  [2, 7, 6],
  [1, 6, 7],
  @@ -2462,14 +2462,14 @@ def matrix_diag_part(
  [1, 6, 0]]]
  # max_diag_len can be shorter than the main diagonal.
  - tf.matrix_diag_part(input, k = (-2, -1))
  + tf.linalg.diag_part(input, k = (-2, -1))
  ==> [[[5, 8],
  [0, 9]],
  [[1, 6],
  [0, 5]]]
  # padding_value = 9
  - tf.matrix_diag_part(input, k = (1, 3), padding_value = 9)
  + tf.linalg.diag_part(input, k = (1, 3), padding_value = 9)
  ==> [[[4, 9, 9], # Output shape: (2, 3, 3)
  [3, 8, 9],
  [2, 7, 6]],
  