Fix FFT negative strides case (#2202)

* Fix issue with negative strides

* Apply suggestions from code review

Co-authored-by: Anton <100830759+antonwolfy@users.noreply.github.com>

---------

Co-authored-by: Anton <100830759+antonwolfy@users.noreply.github.com>

dpnp/fft/dpnp_utils_fft.py

@@ -78,11 +78,13 @@ def _commit_descriptor(a, forward, in_place, c2c, a_strides, index, batch_fft):
     shape = a_shape[index:]
     strides = (0,) + a_strides[index:]
     if c2c:  # c2c FFT
+        assert dpnp.issubdtype(a.dtype, dpnp.complexfloating)
         if a.dtype == dpnp.complex64:
             dsc = fi.Complex64Descriptor(shape)
         else:
             dsc = fi.Complex128Descriptor(shape)
     else:  # r2c/c2r FFT
+        assert dpnp.issubdtype(a.dtype, dpnp.inexact)
         if a.dtype in [dpnp.float32, dpnp.complex64]:
             dsc = fi.Real32Descriptor(shape)
         else:
@@ -262,12 +264,14 @@ def _copy_array(x, complex_input):
     in-place FFT can be performed.
     """
     dtype = x.dtype
+    copy_flag = False
     if numpy.min(x.strides) < 0:
         # negative stride is not allowed in OneMKL FFT
         # TODO: support for negative strides will be added in the future
         # versions of OneMKL, see discussion in MKLD-17597
         copy_flag = True
-    elif complex_input and not dpnp.issubdtype(dtype, dpnp.complexfloating):
+
+    if complex_input and not dpnp.issubdtype(dtype, dpnp.complexfloating):
         # c2c/c2r FFT, if input is not complex, convert to complex
         copy_flag = True
         if dtype in [dpnp.float16, dpnp.float32]:
@@ -279,8 +283,6 @@ def _copy_array(x, complex_input):
         # float32 or float64 depending on device capabilities
         copy_flag = True
         dtype = map_dtype_to_device(dpnp.float64, x.sycl_device)
-    else:
-        copy_flag = False
 
     if copy_flag:
         x_copy = dpnp.empty_like(x, dtype=dtype, order="C")

tests/test_fft.py

@@ -379,6 +379,16 @@ def test_fft_validate_out(self):
         out = dpnp.empty((10,), dtype=dpnp.float32)
         assert_raises(TypeError, dpnp.fft.fft, a, out=out)
 
+    @pytest.mark.parametrize(
+        "dtype", get_all_dtypes(no_none=True, no_bool=True)
+    )
+    def test_negative_stride(self, dtype):
+        a = dpnp.arange(10, dtype=dtype)
+        result = dpnp.fft.fft(a[::-1])
+        expected = numpy.fft.fft(a.asnumpy()[::-1])
+
+        assert_dtype_allclose(result, expected, check_only_type_kind=True)
+
 
 class TestFft2:
     def setup_method(self):