gather_nd:
  description: |
      Gathers slices from a tensor by indices.

      Using given indices to gather slices from a tensor with a specified shape.

      `indices` is an K-dimensional integer tensor.
      Supposes it as a (K-1)-dimensional tensor and each element of it defines a slice of `input_x`:

      .. math::

          output[(i_0, ..., i_{K-2})] = input\_x[indices[(i_0, ..., i_{K-2})]]

      The last dimension of `indices` can not more than the rank of `input_x`:

      :math:`indices.shape[-1] <= input\_x.rank`.

      Args:
          input_x (Tensor): The target tensor to gather values.
          indices (Tensor): The index tensor, with int32 or int64 data type.

      Returns:
          Tensor, has the same type as `input_x` and the shape is
          :math:`indices\_shape[:-1] + input\_x\_shape[indices\_shape[-1]:]`.

      Raises:
          ValueError: If length of shape of `input_x` is less than the last dimension of `indices`.

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

      Examples:
          >>> import mindspore
          >>> import numpy as np
          >>> from mindspore import Tensor, ops
          >>> input_x = Tensor(np.array([[-0.1, 0.3, 3.6], [0.4, 0.5, -3.2]]), mindspore.float32)
          >>> indices = Tensor(np.array([[0, 0], [1, 1]]), mindspore.int32)
          >>> output = ops.gather_nd(input_x, indices)
          >>> print(output)
          [-0.1  0.5]