def resize_images_3d(x, output_shape):
    'Resize images to the given shape.\n    This function resizes 3D data to :obj:`output_shape`.\n    Currently, only bilinear interpolation is supported as the sampling method.\n    Notatition: here is a notation for dimensionalities.\n    - :math:`n` is the batch size.\n    - :math:`c_I` is the number of the input channels.\n    - :math:`h`, :math:`w` and :math:`d` are the height, width and depth of the\n        input image, respectively.\n    - :math:`h_O`, :math:`w_O` and :math:`d_0` are the height, width and depth\n        of the output image.\n    Args:\n        x (~chainer.Variable):\n        Input variable of shape :math:`(n, c_I, h, w, d)`.\n        output_shape (tuple):\n        This is a tuple of length 3 whose values are :obj:`(h_O, w_O, d_O)`.\n    Returns:\n        ~chainer.Variable: Resized image whose shape is             :math:`(n, c_I, h_O, w_O, d_O)`.\n    '
    return ResizeImages3D(output_shape).apply((x,))[0]
Resize images to the given shape.
This function resizes 3D data to :obj:`output_shape`.
Currently, only bilinear interpolation is supported as the sampling method.
Notatition: here is a notation for dimensionalities.
- :math:`n` is the batch size.
- :math:`c_I` is the number of the input channels.
- :math:`h`, :math:`w` and :math:`d` are the height, width and depth of the
    input image, respectively.
- :math:`h_O`, :math:`w_O` and :math:`d_0` are the height, width and depth
    of the output image.
Args:
    x (~chainer.Variable):
    Input variable of shape :math:`(n, c_I, h, w, d)`.
    output_shape (tuple):
    This is a tuple of length 3 whose values are :obj:`(h_O, w_O, d_O)`.
Returns:
    ~chainer.Variable: Resized image whose shape is             :math:`(n, c_I, h_O, w_O, d_O)`.
def resize_images_3d(x, output_shape):
    'Resize images to the given shape.\n    This function resizes 3D data to :obj:`output_shape`.\n    Currently, only bilinear interpolation is supported as the sampling method.\n    Notatition: here is a notation for dimensionalities.\n    - :math:`n` is the batch size.\n    - :math:`c_I` is the number of the input channels.\n    - :math:`h`, :math:`w` and :math:`d` are the height, width and depth of the\n        input image, respectively.\n    - :math:`h_O`, :math:`w_O` and :math:`d_0` are the height, width and depth\n        of the output image.\n    Args:\n        x (~chainer.Variable):\n        Input variable of shape :math:`(n, c_I, h, w, d)`.\n        output_shape (tuple):\n        This is a tuple of length 3 whose values are :obj:`(h_O, w_O, d_O)`.\n    Returns:\n        ~chainer.Variable: Resized image whose shape is             :math:`(n, c_I, h_O, w_O, d_O)`.\n    '
    return ResizeImages3D(output_shape).apply((x,))[0]