Adding tests for dpt.divide

Author: oleksandr-pavlyk

dpctl/tests/elementwise/test_divide.py

@@ -0,0 +1,173 @@
+import ctypes
+
+import numpy as np
+import pytest
+
+import dpctl
+import dpctl.tensor as dpt
+from dpctl.tests.helper import get_queue_or_skip, skip_if_dtype_not_supported
+
+from .utils import _all_dtypes, _compare_dtypes, _usm_types
+
+
+@pytest.mark.parametrize("op1_dtype", _all_dtypes)
+@pytest.mark.parametrize("op2_dtype", _all_dtypes)
+def test_divide_dtype_matrix(op1_dtype, op2_dtype):
+    q = get_queue_or_skip()
+    skip_if_dtype_not_supported(op1_dtype, q)
+    skip_if_dtype_not_supported(op2_dtype, q)
+
+    sz = 127
+    ar1 = dpt.ones(sz, dtype=op1_dtype)
+    ar2 = dpt.ones_like(ar1, dtype=op2_dtype)
+
+    r = dpt.divide(ar1, ar2)
+    assert isinstance(r, dpt.usm_ndarray)
+    expected = np.divide(
+        np.ones(1, dtype=op1_dtype), np.ones(1, dtype=op2_dtype)
+    )
+    assert _compare_dtypes(r.dtype, expected.dtype, sycl_queue=q)
+    assert r.shape == ar1.shape
+    assert (dpt.asnumpy(r) == expected.astype(r.dtype)).all()
+    assert r.sycl_queue == ar1.sycl_queue
+
+    ar3 = dpt.ones(sz, dtype=op1_dtype)
+    ar4 = dpt.ones(2 * sz, dtype=op2_dtype)
+
+    r = dpt.divide(ar3[::-1], ar4[::2])
+    assert isinstance(r, dpt.usm_ndarray)
+    expected = np.divide(
+        np.ones(1, dtype=op1_dtype), np.ones(1, dtype=op2_dtype)
+    )
+    assert _compare_dtypes(r.dtype, expected.dtype, sycl_queue=q)
+    assert r.shape == ar3.shape
+    assert (dpt.asnumpy(r) == expected.astype(r.dtype)).all()
+
+
+@pytest.mark.parametrize("op1_usm_type", _usm_types)
+@pytest.mark.parametrize("op2_usm_type", _usm_types)
+def test_divide_usm_type_matrix(op1_usm_type, op2_usm_type):
+    get_queue_or_skip()
+
+    sz = 128
+    ar1 = dpt.ones(sz, dtype="i4", usm_type=op1_usm_type)
+    ar2 = dpt.ones_like(ar1, dtype="i4", usm_type=op2_usm_type)
+
+    r = dpt.divide(ar1, ar2)
+    assert isinstance(r, dpt.usm_ndarray)
+    expected_usm_type = dpctl.utils.get_coerced_usm_type(
+        (op1_usm_type, op2_usm_type)
+    )
+    assert r.usm_type == expected_usm_type
+
+
+def test_divide_order():
+    get_queue_or_skip()
+
+    ar1 = dpt.ones((20, 20), dtype="i4", order="C")
+    ar2 = dpt.ones((20, 20), dtype="i4", order="C")
+    r1 = dpt.divide(ar1, ar2, order="C")
+    assert r1.flags.c_contiguous
+    r2 = dpt.divide(ar1, ar2, order="F")
+    assert r2.flags.f_contiguous
+    r3 = dpt.divide(ar1, ar2, order="A")
+    assert r3.flags.c_contiguous
+    r4 = dpt.divide(ar1, ar2, order="K")
+    assert r4.flags.c_contiguous
+
+    ar1 = dpt.ones((20, 20), dtype="i4", order="F")
+    ar2 = dpt.ones((20, 20), dtype="i4", order="F")
+    r1 = dpt.divide(ar1, ar2, order="C")
+    assert r1.flags.c_contiguous
+    r2 = dpt.divide(ar1, ar2, order="F")
+    assert r2.flags.f_contiguous
+    r3 = dpt.divide(ar1, ar2, order="A")
+    assert r3.flags.f_contiguous
+    r4 = dpt.divide(ar1, ar2, order="K")
+    assert r4.flags.f_contiguous
+
+    ar1 = dpt.ones((40, 40), dtype="i4", order="C")[:20, ::-2]
+    ar2 = dpt.ones((40, 40), dtype="i4", order="C")[:20, ::-2]
+    r4 = dpt.divide(ar1, ar2, order="K")
+    assert r4.strides == (20, -1)
+
+    ar1 = dpt.ones((40, 40), dtype="i4", order="C")[:20, ::-2].mT
+    ar2 = dpt.ones((40, 40), dtype="i4", order="C")[:20, ::-2].mT
+    r4 = dpt.divide(ar1, ar2, order="K")
+    assert r4.strides == (-1, 20)
+
+
+def test_divide_broadcasting():
+    get_queue_or_skip()
+
+    m = dpt.ones((100, 5), dtype="i4")
+    v = dpt.arange(1, 6, dtype="i4")
+
+    r = dpt.divide(m, v)
+
+    expected = np.divide(
+        np.ones((100, 5), dtype="i4"), np.arange(1, 6, dtype="i4")
+    )
+    assert (dpt.asnumpy(r) == expected.astype(r.dtype)).all()
+
+    r2 = dpt.divide(v, m)
+    expected2 = np.divide(
+        np.arange(1, 6, dtype="i4"), np.ones((100, 5), dtype="i4")
+    )
+    assert (dpt.asnumpy(r2) == expected2.astype(r2.dtype)).all()
+
+
+@pytest.mark.parametrize("arr_dt", _all_dtypes)
+def test_divide_python_scalar(arr_dt):
+    q = get_queue_or_skip()
+    skip_if_dtype_not_supported(arr_dt, q)
+
+    X = dpt.ones((10, 10), dtype=arr_dt, sycl_queue=q)
+    py_ones = (
+        bool(1),
+        int(1),
+        float(1),
+        complex(1),
+        np.float32(1),
+        ctypes.c_int(1),
+    )
+    for sc in py_ones:
+        R = dpt.divide(X, sc)
+        assert isinstance(R, dpt.usm_ndarray)
+        R = dpt.divide(sc, X)
+        assert isinstance(R, dpt.usm_ndarray)
+
+
+class MockArray:
+    def __init__(self, arr):
+        self.data_ = arr
+
+    @property
+    def __sycl_usm_array_interface__(self):
+        return self.data_.__sycl_usm_array_interface__
+
+
+def test_divide_mock_array():
+    get_queue_or_skip()
+    a = dpt.arange(10)
+    b = dpt.ones(10)
+    c = MockArray(b)
+    r = dpt.divide(a, c)
+    assert isinstance(r, dpt.usm_ndarray)
+
+
+def test_divide_canary_mock_array():
+    get_queue_or_skip()
+    a = dpt.arange(10)
+
+    class Canary:
+        def __init__(self):
+            pass
+
+        @property
+        def __sycl_usm_array_interface__(self):
+            return None
+
+    c = Canary()
+    with pytest.raises(ValueError):
+        dpt.divide(a, c)