Fixed example for @antonwolfy, added tests based on it

Also added comment to explain the logic of the code.

Author: oleksandr-pavlyk

dpctl/tensor/_copy_utils.py

@@ -302,9 +302,27 @@ def _copy_from_usm_ndarray_to_usm_ndarray(dst, src):
         src_same_shape = dpt.usm_ndarray(
             common_shape, dtype=src.dtype, buffer=src, strides=new_src_strides
         )
+    elif src.ndim == len(common_shape):
+        new_src_strides = _broadcast_strides(
+            src.shape, src.strides, len(common_shape)
+        )
+        src_same_shape = dpt.usm_ndarray(
+            common_shape, dtype=src.dtype, buffer=src, strides=new_src_strides
+        )
     else:
-        src_same_shape = src
-        src_same_shape.shape = common_shape
+        # since broadcasting succeeded, src.ndim is greater because of
+        # leading sequence of ones, so we trim it
+        n = len(common_shape)
+        new_src_strides = _broadcast_strides(
+            src.shape[-n:], src.strides[-n:], n
+        )
+        src_same_shape = dpt.usm_ndarray(
+            common_shape,
+            dtype=src.dtype,
+            buffer=src.usm_data,
+            strides=new_src_strides,
+            offset=src._element_offset,
+        )
 
     _copy_same_shape(dst, src_same_shape)
 

dpctl/tests/test_usm_ndarray_ctor.py

@@ -1039,6 +1039,26 @@ def test_setitem_broadcasting_empty_dst_edge_case():
     dst[...] = src
 
 
+def test_setitem_broadcasting_src_ndim_equal_dst_ndim():
+    get_queue_or_skip()
+    dst = dpt.ones((2, 3, 4), dtype="i4")
+    src = dpt.zeros((2, 1, 4), dtype="i4")
+    dst[...] = src
+
+    expected = np.zeros(dst.shape, dtype=dst.dtype)
+    assert np.array_equal(dpt.asnumpy(dst), expected)
+
+
+def test_setitem_broadcasting_src_ndim_greater_than_dst_ndim():
+    get_queue_or_skip()
+    dst = dpt.ones((2, 3, 4), dtype="i4")
+    src = dpt.zeros((1, 2, 1, 4), dtype="i4")
+    dst[...] = src
+
+    expected = np.zeros(dst.shape, dtype=dst.dtype)
+    assert np.array_equal(dpt.asnumpy(dst), expected)
+
+
 @pytest.mark.parametrize(
     "dtype",
     _all_dtypes,