# Buggy code
def affine_transform(
    input,
    matrix,
    offset=0.0,
    output_shape=None,
    output=None,
    order=None,
    mode="constant",
    cval=0.0,
    prefilter=True,
):
    """Apply an affine transformation.

    Given an output image pixel index vector ``o``, the pixel value is
    determined from the input image at position
    ``cupy.dot(matrix, o) + offset``.

    Args:
        input (cupy.ndarray): The input array.
        matrix (cupy.ndarray): The inverse coordinate transformation matrix,
            mapping output coordinates to input coordinates. If ``ndim`` is the
            number of dimensions of ``input``, the given matrix must have one
            of the following shapes:

                - ``(ndim, ndim)``: the linear transformation matrix for each
                  output coordinate.
                - ``(ndim,)``: assume that the 2D transformation matrix is
                  diagonal, with the diagonal specified by the given value.
                - ``(ndim + 1, ndim + 1)``: assume that the transformation is
                  specified using homogeneous coordinates. In this case, any
                  value passed to ``offset`` is ignored.
                - ``(ndim, ndim + 1)``: as above, but the bottom row of a
                  homogeneous transformation matrix is always
                  ``[0, 0, ..., 1]``, and may be omitted.

        offset (float or sequence): The offset into the array where the
            transform is applied. If a float, ``offset`` is the same for each
            axis. If a sequence, ``offset`` should contain one value for each
            axis.
        output_shape (tuple of ints): Shape tuple.
        output (cupy.ndarray or ~cupy.dtype): The array in which to place the
            output, or the dtype of the returned array.
        order (int): The order of the spline interpolation. If it is not given,
            order 1 is used. It is different from :mod:`scipy.ndimage` and can
            change in the future. Currently it supports only order 0 and 1.
        mode (str): Points outside the boundaries of the input are filled
            according to the given mode (``'constant'``, ``'nearest'``,
            ``'mirror'`` or ``'opencv'``). Default is ``'constant'``.
        cval (scalar): Value used for points outside the boundaries of
            the input if ``mode='constant'`` or ``mode='opencv'``. Default is
            0.0
        prefilter (bool): It is not used yet. It just exists for compatibility
            with :mod:`scipy.ndimage`.

    Returns:
        cupy.ndarray or None:
            The transformed input. If ``output`` is given as a parameter,
            ``None`` is returned.

    .. seealso:: :func:`scipy.ndimage.affine_transform`
    """

    _check_parameter("affine_transform", order, mode)

    offset = _util._fix_sequence_arg(offset, input.ndim, "offset", float)

    if matrix.ndim not in [1, 2] or matrix.shape[0] < 1:
        raise RuntimeError("no proper affine matrix provided")
    if matrix.ndim == 2:
        if matrix.shape[0] == matrix.shape[1] - 1:
            offset = matrix[:, -1]
            matrix = matrix[:, :-1]
        elif matrix.shape[0] == input.ndim + 1:
            offset = matrix[:-1, -1]
            matrix = matrix[:-1, :-1]
        if matrix.shape != (input.ndim, input.ndim):
            raise RuntimeError("improper affine shape")

    if mode == "opencv":
        m = cupy.zeros((input.ndim + 1, input.ndim + 1))
        m[:-1, :-1] = matrix
        m[:-1, -1] = offset
        m[-1, -1] = 1
        m = cupy.linalg.inv(m)
        m[:2] = cupy.roll(m[:2], 1, axis=0)
        m[:2, :2] = cupy.roll(m[:2, :2], 1, axis=1)
        matrix = m[:-1, :-1]
        offset = m[:-1, -1]

    if output_shape is None:
        output_shape = input.shape

    matrix = matrix.astype(cupy.float64, copy=False)
    if order is None:
        order = 1
    ndim = input.ndim
    output = _util._get_output(output, input, shape=output_shape)
    if input.dtype.kind in "iu":
        input = input.astype(cupy.float32)

    integer_output = output.dtype.kind in "iu"
    large_int = max(_prod(input.shape), _prod(output_shape)) > 1 << 31
    if matrix.ndim == 1:
        offset = cupy.asarray(offset, dtype=cupy.float64)
        offset = -offset / matrix
        kern = _interp_kernels._get_zoom_shift_kernel(
            ndim,
            large_int,
            output_shape,
            mode,
            cval=cval,
            order=order,
            integer_output=integer_output,
        )
        kern(input, offset, matrix, output)
    else:
        kern = _interp_kernels._get_affine_kernel(
            ndim,
            large_int,
            output_shape,
            mode,
            cval=cval,
            order=order,
            integer_output=integer_output,
        )
        m = cupy.zeros((ndim, ndim + 1), dtype=cupy.float64)
        m[:, :-1] = matrix
        m[:, -1] = cupy.asarray(offset, dtype=cupy.float64)
        kern(input, m, output)
    return output


# Traceback (cupy_backends.cuda.libs.nvrtc.NVRTCError)
/home/croat/.local/share/virtualenvs/starmap-T47byR32/lib/python3.8/site-packages/cupyx/scipy/ndimage/interpolation.py:15: UserWarning: In the current feature the default order of shift is 1. It is different from scipy.ndimage and can change in the future.
warnings.warn('In the current feature the default order of {} is 1. '
Traceback (most recent call last):
File "/home/croat/.local/share/virtualenvs/starmap-T47byR32/lib/python3.8/site-packages/cupy/cuda/compiler.py", line 516, in compile
nvrtc.compileProgram(self.ptr, options)
File "cupy_backends/cuda/libs/nvrtc.pyx", line 108, in cupy_backends.cuda.libs.nvrtc.compileProgram
File "cupy_backends/cuda/libs/nvrtc.pyx", line 120, in cupy_backends.cuda.libs.nvrtc.compileProgram
File "cupy_backends/cuda/libs/nvrtc.pyx", line 58, in cupy_backends.cuda.libs.nvrtc.check_status
cupy_backends.cuda.libs.nvrtc.NVRTCError: NVRTC_ERROR_COMPILATION (6)

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/croat/.local/share/virtualenvs/starmap-T47byR32/lib/python3.8/site-packages/cupyx/scipy/ndimage/interpolation.py", line 379, in shift
kern(input, shift, output)
File "cupy/core/_kernel.pyx", line 821, in cupy.core._kernel.ElementwiseKernel.__call__
File "cupy/core/_kernel.pyx", line 846, in cupy.core._kernel.ElementwiseKernel._get_elementwise_kernel
File "cupy/_util.pyx", line 103, in cupy._util.memoize.decorator.ret
File "cupy/core/_kernel.pyx", line 639, in cupy.core._kernel._get_elementwise_kernel
File "cupy/core/_kernel.pyx", line 37, in cupy.core._kernel._get_simple_elementwise_kernel
File "cupy/core/_kernel.pyx", line 60, in cupy.core._kernel._get_simple_elementwise_kernel
File "cupy/core/core.pyx", line 1937, in cupy.core.core.compile_with_cache
File "/home/croat/.local/share/virtualenvs/starmap-T47byR32/lib/python3.8/site-packages/cupy/cuda/compiler.py", line 335, in compile_with_cache
return _compile_with_cache_cuda(
File "/home/croat/.local/share/virtualenvs/starmap-T47byR32/lib/python3.8/site-packages/cupy/cuda/compiler.py", line 402, in _compile_with_cache_cuda
ptx, mapping = compile_using_nvrtc(
File "/home/croat/.local/share/virtualenvs/starmap-T47byR32/lib/python3.8/site-packages/cupy/cuda/compiler.py", line 173, in compile_using_nvrtc
return _compile(source, options, cu_path,
File "/home/croat/.local/share/virtualenvs/starmap-T47byR32/lib/python3.8/site-packages/cupy/cuda/compiler.py", line 157, in _compile
ptx, mapping = prog.compile(options, log_stream)
File "/home/croat/.local/share/virtualenvs/starmap-T47byR32/lib/python3.8/site-packages/cupy/cuda/compiler.py", line 527, in compile
raise CompileException(log, self.src, self.name, options,
cupy.cuda.compiler.CompileException: /tmp/tmpbp6idobr/064ead033e63783c4dfe62433771dbed_2.cubin.cu(28): error: invalid type conversion

/tmp/tmpbp6idobr/064ead033e63783c4dfe62433771dbed_2.cubin.cu(20): warning: variable "s" was declared but never referenced

/tmp/tmpbp6idobr/064ead033e63783c4dfe62433771dbed_2.cubin.cu(20): warning: variable "t" was declared but never referenced

1 error detected in the compilation of "/tmp/tmpbp6idobr/064ead033e63783c4dfe62433771dbed_2.cubin.cu".

# Fixed code
def affine_transform(
    input,
    matrix,
    offset=0.0,
    output_shape=None,
    output=None,
    order=None,
    mode="constant",
    cval=0.0,
    prefilter=True,
):
    """Apply an affine transformation.

    Given an output image pixel index vector ``o``, the pixel value is
    determined from the input image at position
    ``cupy.dot(matrix, o) + offset``.

    Args:
        input (cupy.ndarray): The input array.
        matrix (cupy.ndarray): The inverse coordinate transformation matrix,
            mapping output coordinates to input coordinates. If ``ndim`` is the
            number of dimensions of ``input``, the given matrix must have one
            of the following shapes:

                - ``(ndim, ndim)``: the linear transformation matrix for each
                  output coordinate.
                - ``(ndim,)``: assume that the 2D transformation matrix is
                  diagonal, with the diagonal specified by the given value.
                - ``(ndim + 1, ndim + 1)``: assume that the transformation is
                  specified using homogeneous coordinates. In this case, any
                  value passed to ``offset`` is ignored.
                - ``(ndim, ndim + 1)``: as above, but the bottom row of a
                  homogeneous transformation matrix is always
                  ``[0, 0, ..., 1]``, and may be omitted.

        offset (float or sequence): The offset into the array where the
            transform is applied. If a float, ``offset`` is the same for each
            axis. If a sequence, ``offset`` should contain one value for each
            axis.
        output_shape (tuple of ints): Shape tuple.
        output (cupy.ndarray or ~cupy.dtype): The array in which to place the
            output, or the dtype of the returned array.
        order (int): The order of the spline interpolation. If it is not given,
            order 1 is used. It is different from :mod:`scipy.ndimage` and can
            change in the future. Currently it supports only order 0 and 1.
        mode (str): Points outside the boundaries of the input are filled
            according to the given mode (``'constant'``, ``'nearest'``,
            ``'mirror'`` or ``'opencv'``). Default is ``'constant'``.
        cval (scalar): Value used for points outside the boundaries of
            the input if ``mode='constant'`` or ``mode='opencv'``. Default is
            0.0
        prefilter (bool): It is not used yet. It just exists for compatibility
            with :mod:`scipy.ndimage`.

    Returns:
        cupy.ndarray or None:
            The transformed input. If ``output`` is given as a parameter,
            ``None`` is returned.

    .. seealso:: :func:`scipy.ndimage.affine_transform`
    """

    _check_parameter("affine_transform", order, mode)

    offset = _util._fix_sequence_arg(offset, input.ndim, "offset", float)

    if matrix.ndim not in [1, 2] or matrix.shape[0] < 1:
        raise RuntimeError("no proper affine matrix provided")
    if matrix.ndim == 2:
        if matrix.shape[0] == matrix.shape[1] - 1:
            offset = matrix[:, -1]
            matrix = matrix[:, :-1]
        elif matrix.shape[0] == input.ndim + 1:
            offset = matrix[:-1, -1]
            matrix = matrix[:-1, :-1]
        if matrix.shape != (input.ndim, input.ndim):
            raise RuntimeError("improper affine shape")

    if mode == "opencv":
        m = cupy.zeros((input.ndim + 1, input.ndim + 1))
        m[:-1, :-1] = matrix
        m[:-1, -1] = offset
        m[-1, -1] = 1
        m = cupy.linalg.inv(m)
        m[:2] = cupy.roll(m[:2], 1, axis=0)
        m[:2, :2] = cupy.roll(m[:2, :2], 1, axis=1)
        matrix = m[:-1, :-1]
        offset = m[:-1, -1]

    if output_shape is None:
        output_shape = input.shape

    matrix = matrix.astype(cupy.float64, copy=False)
    if order is None:
        order = 1
    ndim = input.ndim
    output = _util._get_output(output, input, shape=output_shape)
    if input.dtype.kind in "iu":
        input = input.astype(cupy.float32)

    integer_output = output.dtype.kind in "iu"
    _util._check_cval(mode, cval, integer_output)
    large_int = max(_prod(input.shape), _prod(output_shape)) > 1 << 31
    if matrix.ndim == 1:
        offset = cupy.asarray(offset, dtype=cupy.float64)
        offset = -offset / matrix
        kern = _interp_kernels._get_zoom_shift_kernel(
            ndim,
            large_int,
            output_shape,
            mode,
            cval=cval,
            order=order,
            integer_output=integer_output,
        )
        kern(input, offset, matrix, output)
    else:
        kern = _interp_kernels._get_affine_kernel(
            ndim,
            large_int,
            output_shape,
            mode,
            cval=cval,
            order=order,
            integer_output=integer_output,
        )
        m = cupy.zeros((ndim, ndim + 1), dtype=cupy.float64)
        m[:, :-1] = matrix
        m[:, -1] = cupy.asarray(offset, dtype=cupy.float64)
        kern(input, m, output)
    return output