Disallow scalar conversation for non-0D arrays

CHANGELOG.md

@@ -10,6 +10,8 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ### Changed
 
+* Disallowed scalar conversion for non-0D `tensor.usm_ndarray` per Python Array API specification [gh-2223](https://github.com/IntelPython/dpctl/pull/2223)
+
 ### Fixed
 
 ### Maintenance

dpctl/tensor/_usmarray.pyx

@@ -124,6 +124,14 @@ cdef object _as_zero_dim_ndarray(object usm_ary):
     return view
 
 
+cdef inline void _check_0d_scalar_conversion(object usm_ary) except *:
+    "Raise TypeError if array cannot be converted to a Python scalar"
+    if (usm_ary.ndim != 0):
+        raise TypeError(
+            "only 0-dimensional arrays can be converted to Python scalars"
+        )
+
+
 cdef int _copy_writable(int lhs_flags, int rhs_flags):
     "Copy the WRITABLE flag to lhs_flags from rhs_flags"
     return (lhs_flags & ~USM_ARRAY_WRITABLE) | (rhs_flags & USM_ARRAY_WRITABLE)
@@ -1132,6 +1140,7 @@ cdef class usm_ndarray:
 
     def __bool__(self):
         if self.size == 1:
+            _check_0d_scalar_conversion(self)
             view = _as_zero_dim_ndarray(self)
             return view.__bool__()
 
@@ -1147,6 +1156,7 @@ cdef class usm_ndarray:
 
     def __float__(self):
         if self.size == 1:
+            _check_0d_scalar_conversion(self)
             view = _as_zero_dim_ndarray(self)
             return view.__float__()
 
@@ -1156,6 +1166,7 @@ cdef class usm_ndarray:
 
     def __complex__(self):
         if self.size == 1:
+            _check_0d_scalar_conversion(self)
             view = _as_zero_dim_ndarray(self)
             return view.__complex__()
 
@@ -1165,6 +1176,7 @@ cdef class usm_ndarray:
 
     def __int__(self):
         if self.size == 1:
+            _check_0d_scalar_conversion(self)
             view = _as_zero_dim_ndarray(self)
             return view.__int__()
 

dpctl/tests/test_usm_ndarray_ctor.py

@@ -20,6 +20,7 @@
 
 import numpy as np
 import pytest
+from numpy.testing import assert_raises_regex
 
 import dpctl
 import dpctl.memory as dpm
@@ -282,34 +283,42 @@ def test_properties(dt):
         V.mT
 
 
-@pytest.mark.parametrize("func", [bool, float, int, complex])
-@pytest.mark.parametrize("shape", [tuple(), (1,), (1, 1), (1, 1, 1)])
-@pytest.mark.parametrize("dtype", ["|b1", "|u2", "|f4", "|i8"])
-def test_copy_scalar_with_func(func, shape, dtype):
-    try:
-        X = dpt.usm_ndarray(shape, dtype=dtype)
-    except dpctl.SyclDeviceCreationError:
-        pytest.skip("No SYCL devices available")
-    Y = np.arange(1, X.size + 1, dtype=dtype)
-    X.usm_data.copy_from_host(Y.view("|u1"))
-    Y.shape = tuple()
-    assert func(X) == func(Y)
-
-
-@pytest.mark.parametrize(
-    "method", ["__bool__", "__float__", "__int__", "__complex__"]
-)
 @pytest.mark.parametrize("shape", [tuple(), (1,), (1, 1), (1, 1, 1)])
 @pytest.mark.parametrize("dtype", ["|b1", "|u2", "|f4", "|i8"])
-def test_copy_scalar_with_method(method, shape, dtype):
-    try:
-        X = dpt.usm_ndarray(shape, dtype=dtype)
-    except dpctl.SyclDeviceCreationError:
-        pytest.skip("No SYCL devices available")
-    Y = np.arange(1, X.size + 1, dtype=dtype)
-    X.usm_data.copy_from_host(Y.view("|u1"))
-    Y.shape = tuple()
-    assert getattr(X, method)() == getattr(Y, method)()
+class TestCopyScalar:
+    @pytest.mark.parametrize("func", [bool, float, int, complex])
+    def test_copy_scalar_with_func(self, func, shape, dtype):
+        try:
+            X = dpt.usm_ndarray(shape, dtype=dtype)
+        except dpctl.SyclDeviceCreationError:
+            pytest.skip("No SYCL devices available")
+        Y = np.arange(1, X.size + 1, dtype=dtype)
+        X.usm_data.copy_from_host(Y.view("|u1"))
+        Y = Y.reshape(())
+        # Non-0D numeric arrays must not be convertible to Python scalars
+        if len(shape) != 0:
+            assert_raises_regex(TypeError, "only 0-dimensional arrays", func, X)
+        else:
+            # 0D arrays are allowed to convert
+            assert func(X) == func(Y)
+
+    @pytest.mark.parametrize(
+        "method", ["__bool__", "__float__", "__int__", "__complex__"]
+    )
+    def test_copy_scalar_with_method(self, method, shape, dtype):
+        try:
+            X = dpt.usm_ndarray(shape, dtype=dtype)
+        except dpctl.SyclDeviceCreationError:
+            pytest.skip("No SYCL devices available")
+        Y = np.arange(1, X.size + 1, dtype=dtype)
+        X.usm_data.copy_from_host(Y.view("|u1"))
+        Y = Y.reshape(())
+        if len(shape) != 0:
+            assert_raises_regex(
+                TypeError, "only 0-dimensional arrays", getattr(X, method)
+            )
+        else:
+            assert getattr(X, method)() == getattr(Y, method)()
 
 
 @pytest.mark.parametrize("func", [bool, float, int, complex])

dpctl/tests/test_usm_ndarray_indexing.py

@@ -1430,11 +1430,12 @@ def test_nonzero_f_contig():
     mask = dpt.zeros((5, 5), dtype="?", order="F")
     mask[2, 3] = True
 
-    expected_res = (2, 3)
-    res = dpt.nonzero(mask)
+    expected_res = np.nonzero(dpt.asnumpy(mask))
+    result = dpt.nonzero(mask)
 
-    assert expected_res == res
-    assert mask[res]
+    for exp, res in zip(expected_res, result):
+        assert_array_equal(dpt.asnumpy(res), exp)
+    assert dpt.asnumpy(mask[result]).all()
 
 
 def test_nonzero_compacting():
@@ -1448,11 +1449,12 @@ def test_nonzero_compacting():
     mask[3, 2, 1] = True
     mask_view = mask[..., :3]
 
-    expected_res = (3, 2, 1)
-    res = dpt.nonzero(mask_view)
+    expected_res = np.nonzero(dpt.asnumpy(mask_view))
+    result = dpt.nonzero(mask_view)
 
-    assert expected_res == res
-    assert mask_view[res]
+    for exp, res in zip(expected_res, result):
+        assert_array_equal(dpt.asnumpy(res), exp)
+    assert dpt.asnumpy(mask_view[result]).all()
 
 
 def test_assign_scalar():

dpctl/tests/test_usm_ndarray_manipulation.py

@@ -1438,11 +1438,11 @@ def test_tile_size_1():
     # test for gh-1627 behavior
     res = dpt.tile(x1, reps)
     assert x1.shape == res.shape
-    assert x1 == res
+    assert_array_equal(dpt.asnumpy(x1), dpt.asnumpy(res))
 
     res = dpt.tile(x2, reps)
     assert x2.shape == res.shape
-    assert x2 == res
+    assert_array_equal(dpt.asnumpy(x2), dpt.asnumpy(res))
 
 
 def test_tile_prepends_axes():

dpctl/tests/test_usm_ndarray_operators.py

@@ -129,7 +129,7 @@ def test_mat_ops(namespace):
 @pytest.mark.parametrize("namespace", [dpt, Dummy()])
 def test_comp_ops(namespace):
     try:
-        X = dpt.ones(1, dtype="u8")
+        X = dpt.asarray(1, dtype="u8")
     except dpctl.SyclDeviceCreationError:
         pytest.skip("No SYCL devices available")
     X._set_namespace(namespace)

dpctl/tests/test_usm_ndarray_sorting.py

@@ -18,6 +18,7 @@
 
 import numpy as np
 import pytest
+from numpy.testing import assert_array_equal
 
 import dpctl.tensor as dpt
 from dpctl.tests.helper import get_queue_or_skip, skip_if_dtype_not_supported
@@ -345,19 +346,19 @@ def test_radix_sort_size_1_axis():
 
     x1 = dpt.ones((), dtype="i1")
     r1 = dpt.sort(x1, kind="radixsort")
-    assert r1 == x1
+    assert_array_equal(dpt.asnumpy(r1), dpt.asnumpy(x1))
 
     x2 = dpt.ones([1], dtype="i1")
     r2 = dpt.sort(x2, kind="radixsort")
-    assert r2 == x2
+    assert_array_equal(dpt.asnumpy(r2), dpt.asnumpy(x2))
 
     x3 = dpt.reshape(dpt.arange(10, dtype="i1"), (10, 1))
     r3 = dpt.sort(x3, kind="radixsort")
-    assert dpt.all(r3 == x3)
+    assert dpt.asnumpy(r3 == x3).all()
 
     x4 = dpt.reshape(dpt.arange(10, dtype="i1"), (1, 10))
     r4 = dpt.sort(x4, axis=0, kind="radixsort")
-    assert dpt.all(r4 == x4)
+    assert dpt.asnumpy(r4 == x4).all()
 
 
 def test_radix_argsort_size_1_axis():
@@ -369,12 +370,12 @@ def test_radix_argsort_size_1_axis():
 
     x2 = dpt.ones([1], dtype="i1")
     r2 = dpt.argsort(x2, kind="radixsort")
-    assert r2 == 0
+    assert dpt.asnumpy(r2 == 0).all()
 
     x3 = dpt.reshape(dpt.arange(10, dtype="i1"), (10, 1))
     r3 = dpt.argsort(x3, kind="radixsort")
-    assert dpt.all(r3 == 0)
+    assert dpt.asnumpy(r3 == 0).all()
 
     x4 = dpt.reshape(dpt.arange(10, dtype="i1"), (1, 10))
     r4 = dpt.argsort(x4, axis=0, kind="radixsort")
-    assert dpt.all(r4 == 0)
+    assert dpt.asnumpy(r4 == 0).all()