import tensorflow as tf

    name: (Optional) A name for this operation.
    output_dtype: (Optional) If not None, casts the output tensor to this type.

  Returns:
    A `Tensor` containing the mean. If `x` is floating point, the mean will have
    the same type as `x`. If `x` is integral, the output is cast to float32.
    NaNs and infinite input values are ignored.

  Raises:
    TypeError: If the type of `x` is not supported.
  """
  with tf.compat.v1.name_scope(name, 'mean'):
    return _mean_and_var(x, reduce_instance_dims, output_dtype)[0]


@common.log_api_use(common.ANALYZER_COLLECTION)
def var(x: common_types.TensorType,
        reduce_instance_dims: bool = True,
        name: Optional[str] = None,
        output_dtype: Optional[tf.DType] = None) -> tf.Tensor:
  """Computes the variance of the values of a `Tensor` over the whole dataset.

