expand_dims:
  description: |
    Adds an additional dimension to `input_x` at the given axis, the dimension
    of `input_x` should be greater than or equal to 1.

    Note:
        If the specified axis is a negative number, the index is counted
        backward from the end and starts at 1.

    Args:
        input_x (Tensor): The shape of tensor is :math:`(x_1, x_2, ..., x_R)`.
        axis (int): Specifies the dimension index at which to expand
            the shape of `input_x`. The value of axis must be in the range
            `[-input_x.ndim-1, input_x.ndim]`. Only constant value is allowed.

    Returns:
        Tensor, the shape of tensor is :math:`(1, x_1, x_2, ..., x_R)` if the
        value of `axis` is 0. It has the same data type as `input_x`.

    Raises:
        TypeError: If `axis` is not an int.
        ValueError: If `axis` is not in the valid range :math:`[-a.ndim-1, a.ndim]`.

    Supported Platforms:
        ``Ascend`` ``GPU`` ``CPU``

    Examples:
        >>> import mindspore
        >>> import numpy as np
        >>> from mindspore import Tensor, ops
        >>> input_tensor = Tensor(np.array([[2, 2], [2, 2]]), mindspore.float32)
        >>> output = ops.expand_dims(input_tensor, 0)
        >>> print(output)
        [[[2. 2.]
          [2. 2.]]]