Merge pull request #1786 from IntelPython/fix-gh-1769

Fix gh-1769 - setting shape by a scalar

dpctl/tensor/_usmarray.pyx

@@ -563,6 +563,22 @@ cdef class usm_ndarray:
 
     @shape.setter
     def shape(self, new_shape):
+        """
+        Modifies usm_ndarray instance in-place by changing its metadata
+        about the shape and the strides of the array, or raises
+        `AttributeError` exception if in-place change is not possible.
+
+        Args:
+            new_shape: (tuple, int)
+                New shape. Only non-negative values are supported.
+                The new shape may not lead to the change in the
+                number of elements in the array.
+
+        Whether the array can be reshape in-place depends on its
+        strides. Use :func:`dpctl.tensor.reshape` function which
+        always succeeds to reshape the array by performing a copy
+        if necessary.
+        """
         cdef int new_nd = -1
         cdef Py_ssize_t nelems = -1
         cdef int err = 0
@@ -576,7 +592,11 @@ cdef class usm_ndarray:
 
         from ._reshape import reshaped_strides
 
-        new_nd = len(new_shape)
+        try:
+            new_nd = len(new_shape)
+        except TypeError:
+            new_nd = 1
+            new_shape = (new_shape,)
         try:
             new_shape = tuple(operator.index(dim) for dim in new_shape)
         except TypeError:

dpctl/tests/test_usm_ndarray_ctor.py

@@ -16,6 +16,7 @@
 
 import ctypes
 import numbers
+from math import prod
 
 import numpy as np
 import pytest
@@ -1102,7 +1103,7 @@ def test_setitem_same_dtype(dtype, src_usm_type, dst_usm_type):
     skip_if_dtype_not_supported(dtype, q)
     shape = (2, 4, 3)
     Xnp = (
-        np.random.randint(-10, 10, size=np.prod(shape))
+        np.random.randint(-10, 10, size=prod(shape))
         .astype(dtype)
         .reshape(shape)
     )
@@ -1307,6 +1308,10 @@ def relaxed_strides_equal(st1, st2, sh):
     X = dpt.usm_ndarray(sh_s, dtype="?")
     X.shape = sh_f
     assert relaxed_strides_equal(X.strides, cc_strides(sh_f), sh_f)
+    sz = X.size
+    X.shape = sz
+    assert X.shape == (sz,)
+    assert relaxed_strides_equal(X.strides, (1,), (sz,))
 
     X = dpt.usm_ndarray(sh_s, dtype="u4")
     with pytest.raises(TypeError):
@@ -2077,11 +2082,9 @@ def test_tril(dtype):
     skip_if_dtype_not_supported(dtype, q)
 
     shape = (2, 3, 4, 5, 5)
-    X = dpt.reshape(
-        dpt.arange(np.prod(shape), dtype=dtype, sycl_queue=q), shape
-    )
+    X = dpt.reshape(dpt.arange(prod(shape), dtype=dtype, sycl_queue=q), shape)
     Y = dpt.tril(X)
-    Xnp = np.arange(np.prod(shape), dtype=dtype).reshape(shape)
+    Xnp = np.arange(prod(shape), dtype=dtype).reshape(shape)
     Ynp = np.tril(Xnp)
     assert Y.dtype == Ynp.dtype
     assert np.array_equal(Ynp, dpt.asnumpy(Y))
@@ -2093,11 +2096,9 @@ def test_triu(dtype):
     skip_if_dtype_not_supported(dtype, q)
 
     shape = (4, 5)
-    X = dpt.reshape(
-        dpt.arange(np.prod(shape), dtype=dtype, sycl_queue=q), shape
-    )
+    X = dpt.reshape(dpt.arange(prod(shape), dtype=dtype, sycl_queue=q), shape)
     Y = dpt.triu(X, k=1)
-    Xnp = np.arange(np.prod(shape), dtype=dtype).reshape(shape)
+    Xnp = np.arange(prod(shape), dtype=dtype).reshape(shape)
     Ynp = np.triu(Xnp, k=1)
     assert Y.dtype == Ynp.dtype
     assert np.array_equal(Ynp, dpt.asnumpy(Y))
@@ -2110,7 +2111,7 @@ def test_tri_usm_type(tri_fn, usm_type):
     dtype = dpt.uint16
 
     shape = (2, 3, 4, 5, 5)
-    size = np.prod(shape)
+    size = prod(shape)
     X = dpt.reshape(
         dpt.arange(size, dtype=dtype, usm_type=usm_type, sycl_queue=q), shape
     )
@@ -2129,11 +2130,11 @@ def test_tril_slice():
     q = get_queue_or_skip()
 
     shape = (6, 10)
-    X = dpt.reshape(
-        dpt.arange(np.prod(shape), dtype="int", sycl_queue=q), shape
-    )[1:, ::-2]
+    X = dpt.reshape(dpt.arange(prod(shape), dtype="int", sycl_queue=q), shape)[
+        1:, ::-2
+    ]
     Y = dpt.tril(X)
-    Xnp = np.arange(np.prod(shape), dtype="int").reshape(shape)[1:, ::-2]
+    Xnp = np.arange(prod(shape), dtype="int").reshape(shape)[1:, ::-2]
     Ynp = np.tril(Xnp)
     assert Y.dtype == Ynp.dtype
     assert np.array_equal(Ynp, dpt.asnumpy(Y))
@@ -2144,14 +2145,12 @@ def test_triu_permute_dims():
 
     shape = (2, 3, 4, 5)
     X = dpt.permute_dims(
-        dpt.reshape(
-            dpt.arange(np.prod(shape), dtype="int", sycl_queue=q), shape
-        ),
+        dpt.reshape(dpt.arange(prod(shape), dtype="int", sycl_queue=q), shape),
         (3, 2, 1, 0),
     )
     Y = dpt.triu(X)
     Xnp = np.transpose(
-        np.arange(np.prod(shape), dtype="int").reshape(shape), (3, 2, 1, 0)
+        np.arange(prod(shape), dtype="int").reshape(shape), (3, 2, 1, 0)
     )
     Ynp = np.triu(Xnp)
     assert Y.dtype == Ynp.dtype
@@ -2189,12 +2188,12 @@ def test_triu_order_k(order, k):
 
     shape = (3, 3)
     X = dpt.reshape(
-        dpt.arange(np.prod(shape), dtype="int", sycl_queue=q),
+        dpt.arange(prod(shape), dtype="int", sycl_queue=q),
         shape,
         order=order,
     )
     Y = dpt.triu(X, k=k)
-    Xnp = np.arange(np.prod(shape), dtype="int").reshape(shape, order=order)
+    Xnp = np.arange(prod(shape), dtype="int").reshape(shape, order=order)
     Ynp = np.triu(Xnp, k=k)
     assert Y.dtype == Ynp.dtype
     assert X.flags == Y.flags
@@ -2210,12 +2209,12 @@ def test_tril_order_k(order, k):
         pytest.skip("Queue could not be created")
     shape = (3, 3)
     X = dpt.reshape(
-        dpt.arange(np.prod(shape), dtype="int", sycl_queue=q),
+        dpt.arange(prod(shape), dtype="int", sycl_queue=q),
         shape,
         order=order,
     )
     Y = dpt.tril(X, k=k)
-    Xnp = np.arange(np.prod(shape), dtype="int").reshape(shape, order=order)
+    Xnp = np.arange(prod(shape), dtype="int").reshape(shape, order=order)
     Ynp = np.tril(Xnp, k=k)
     assert Y.dtype == Ynp.dtype
     assert X.flags == Y.flags