code: def top_1(x, reduced_dim, dtype=tf.int32, name=None):
    
    reduced_dim = convert_to_dimension(reduced_dim)
    with tf.name_scope(name, default_name="top_1"):
      max_val = reduce_max(x, reduced_dim=reduced_dim)
      is_max = to_float(equal(x, max_val))
      pos = mtf_range(x.mesh, reduced_dim, tf.float32)
      ret = reduce_max(is_max * pos, reduced_dim=reduced_dim)
      ret = cast(ret, dtype)
      return ret, max_val
docs: Argmax and Max.
  
    Args:
      x: a Tensor
      reduced_dim: a Dimension in x.shape.dims
      dtype: a tf.dtype (for the output)
      name: an optional string
    Returns:
      indices: a Tensor with given dtype
      values: optional Tensor equal to mtf.reduce_max(x, reduced_dim=reduced_dim)