Add casting for input strides and none buffer

Author: antonwolfy

dpnp/dpnp_array.py

@@ -102,15 +102,19 @@ def __init__(
 
             if dtype is None and hasattr(buffer, "dtype"):
                 dtype = buffer.dtype
-
-            if not (strides is None or dtype is None):
-                # dpctl expects strides as elements displacement in memory,
-                # while dpnp (and numpy as well) relies on bytes displacement
-                it_sz = dpnp.dtype(dtype).itemsize
-                strides = tuple(el // it_sz for el in strides)
         else:
             buffer = usm_type
 
+        if strides is not None:
+            # dpctl expects strides as elements displacement in memory,
+            # while dpnp (and numpy as well) relies on bytes displacement
+            if dtype is None:
+                dtype = dpnp.default_float_type(
+                    device=device, sycl_queue=sycl_queue
+                )
+            it_sz = dpnp.dtype(dtype).itemsize
+            strides = tuple(el // it_sz for el in strides)
+
         sycl_queue_normalized = dpnp.get_normalized_queue_device(
             device=device, sycl_queue=sycl_queue
         )

dpnp/dpnp_iface_arraycreation.py

@@ -105,7 +105,7 @@ def _get_empty_array(
         elif a.flags.c_contiguous:
             order = "C"
         else:
-            strides = _get_strides_for_order_k(a, _shape)
+            strides = _get_strides_for_order_k(a, _dtype, shape=_shape)
             order = "C"
     elif order not in "cfCF":
         raise ValueError(
@@ -122,15 +122,15 @@ def _get_empty_array(
     )
 
 
-def _get_strides_for_order_k(x, shape=None):
+def _get_strides_for_order_k(x, dtype, shape=None):
     """
     Calculate strides when order='K' for empty_like, ones_like, zeros_like,
     and full_like where `shape` is ``None`` or len(shape) == x.ndim.
 
     """
     stride_and_index = sorted([(abs(s), -i) for i, s in enumerate(x.strides)])
     strides = [0] * x.ndim
-    stride = 1
+    stride = dpnp.dtype(dtype).itemsize
     for _, i in stride_and_index:
         strides[-i] = stride
         stride *= shape[-i] if shape else x.shape[-i]

dpnp/fft/dpnp_utils_fft.py

@@ -224,6 +224,10 @@ def _compute_result(dsc, a, out, forward, c2c, out_strides):
                         if a.dtype == dpnp.complex64
                         else dpnp.float64
                     )
+            # cast to expected strides format
+            out_strides = tuple(
+                el * dpnp.dtype(out_dtype).itemsize for el in out_strides
+            )
             result = dpnp_array(
                 out_shape,
                 dtype=out_dtype,

dpnp/tests/test_ndarray.py

@@ -290,7 +290,7 @@ def test_flags_strides(dtype, order, strides):
         (4, 4), dtype=dtype, order=order, strides=strides
     )
     a = numpy.ndarray((4, 4), dtype=dtype, order=order, strides=numpy_strides)
-    ia = dpnp.ndarray((4, 4), dtype=dtype, order=order, strides=strides)
+    ia = dpnp.ndarray((4, 4), dtype=dtype, order=order, strides=numpy_strides)
     assert usm_array.flags == ia.flags
     assert a.flags.c_contiguous == ia.flags.c_contiguous
     assert a.flags.f_contiguous == ia.flags.f_contiguous