message: Fix the render on tensorflow.org
diff: @@ -1726,18 +1726,12 @@ def batch_dot(x, y, axes=None):
  If the final rank is 1, we reshape it to `(batch_size, 1)`.
  Examples:
  - Assume `x = [[1, 2], [3, 4]]` and `y = [[5, 6], [7, 8]]`
  - `batch_dot(x, y, axes=1) = [[17], [53]]` which is the main diagonal
  - of `x.dot(y.T)`, although we never have to calculate the off-diagonal
  - elements.
  -
  - Pseudocode:
  - ```
  - inner_products = []
  - for xi, yi in zip(x, y):
  - inner_products.append(xi.dot(yi))
  - result = stack(inner_products)
  - ```
  +
  + >>> x_batch = tf.keras.backend.ones(shape=(32, 20, 1))
  + >>> y_batch = tf.keras.backend.ones(shape=(32, 30, 20))
  + >>> xy_batch_dot = tf.keras.backend.batch_dot(x_batch, y_batch, axes=(1, 2))
  + >>> tf.keras.backend.int_shape(xy_batch_dot)
  + (32, 1, 30)
  Shape inference:
  Let `x`'s shape be `(100, 20)` and `y`'s shape be `(100, 30, 20)`.
  @@ -1752,12 +1746,6 @@ def batch_dot(x, y, axes=None):
  * `y.shape[2]` : 20 : do not append to output shape,
  dimension 2 of `y` has been summed over. (`dot_axes[1]` = 2)
  `output_shape` = `(100, 30)`
  -
  - >>> x_batch = tf.keras.backend.ones(shape=(32, 20, 1))
  - >>> y_batch = tf.keras.backend.ones(shape=(32, 30, 20))
  - >>> xy_batch_dot = tf.keras.backend.batch_dot(x_batch, y_batch, axes=(1, 2))
  - >>> tf.keras.backend.int_shape(xy_batch_dot)
  - (32, 1, 30)
  """
  x_shape = int_shape(x)
  y_shape = int_shape(y)
  @@ -1929,8 +1917,6 @@ def transpose(x):
  >>> input_transposed = tf.keras.backend.transpose(input)
  >>> input_transposed
  <tf.Tensor 'Transpose_...' shape=(3, 2) dtype=float32>
  -
  -
  """
  return array_ops.transpose(x)
  