Merge 3a8cb9b into cb801da

Author: antonwolfy

.github/workflows/conda-package.yml

@@ -63,10 +63,11 @@ env:
       third_party/cupy/math_tests
       third_party/cupy/padding_tests
       third_party/cupy/sorting_tests
-      third_party/cupy/statistics_tests/test_histogram.py
-      third_party/cupy/statistics_tests/test_meanvar.py
+      third_party/cupy/statistics_tests
       third_party/cupy/test_ndim.py
+      third_party/cupy/test_numpy_interop.py
       third_party/cupy/test_type_routines.py
+      third_party/cupy/test_typing.py
   VER_JSON_NAME: 'version.json'
   VER_SCRIPT1: "import json; f = open('version.json', 'r'); j = json.load(f); f.close(); "
   VER_SCRIPT2: "d = j['dpnp'][0]; print('='.join((d[s] for s in ('version', 'build'))))"

tests/skipped_tests.tbl

@@ -309,46 +309,3 @@ tests/third_party/cupy/random_tests/test_sample.py::TestRandomIntegers2::test_bo
 tests/third_party/cupy/random_tests/test_sample.py::TestRandomIntegers2::test_bound_2
 tests/third_party/cupy/random_tests/test_sample.py::TestRandomIntegers2::test_goodness_of_fit
 tests/third_party/cupy/random_tests/test_sample.py::TestRandomIntegers2::test_goodness_of_fit_2
-
-tests/third_party/cupy/statistics_tests/test_correlation.py::TestCorrcoef::test_corrcoef
-tests/third_party/cupy/statistics_tests/test_correlation.py::TestCorrcoef::test_corrcoef_diag_exception
-tests/third_party/cupy/statistics_tests/test_correlation.py::TestCorrcoef::test_corrcoef_rowvar
-tests/third_party/cupy/statistics_tests/test_correlation.py::TestCorrcoef::test_corrcoef_y
-
-tests/third_party/cupy/statistics_tests/test_order.py::TestOrder::test_percentile_defaults[linear]
-tests/third_party/cupy/statistics_tests/test_order.py::TestOrder::test_percentile_defaults[lower]
-tests/third_party/cupy/statistics_tests/test_order.py::TestOrder::test_percentile_defaults[higher]
-tests/third_party/cupy/statistics_tests/test_order.py::TestOrder::test_percentile_defaults[midpoint]
-tests/third_party/cupy/statistics_tests/test_order.py::TestOrder::test_percentile_q_list[linear]
-tests/third_party/cupy/statistics_tests/test_order.py::TestOrder::test_percentile_q_list[lower]
-tests/third_party/cupy/statistics_tests/test_order.py::TestOrder::test_percentile_q_list[higher]
-tests/third_party/cupy/statistics_tests/test_order.py::TestOrder::test_percentile_q_list[midpoint]
-tests/third_party/cupy/statistics_tests/test_order.py::TestOrder::test_percentile_no_axis[linear]
-tests/third_party/cupy/statistics_tests/test_order.py::TestOrder::test_percentile_no_axis[lower]
-tests/third_party/cupy/statistics_tests/test_order.py::TestOrder::test_percentile_no_axis[higher]
-tests/third_party/cupy/statistics_tests/test_order.py::TestOrder::test_percentile_no_axis[midpoint]
-tests/third_party/cupy/statistics_tests/test_order.py::TestOrder::test_percentile_neg_axis[linear]
-tests/third_party/cupy/statistics_tests/test_order.py::TestOrder::test_percentile_neg_axis[lower]
-tests/third_party/cupy/statistics_tests/test_order.py::TestOrder::test_percentile_neg_axis[higher]
-tests/third_party/cupy/statistics_tests/test_order.py::TestOrder::test_percentile_neg_axis[midpoint]
-tests/third_party/cupy/statistics_tests/test_order.py::TestOrder::test_percentile_tuple_axis[linear]
-tests/third_party/cupy/statistics_tests/test_order.py::TestOrder::test_percentile_tuple_axis[lower]
-tests/third_party/cupy/statistics_tests/test_order.py::TestOrder::test_percentile_tuple_axis[higher]
-tests/third_party/cupy/statistics_tests/test_order.py::TestOrder::test_percentile_tuple_axis[midpoint]
-tests/third_party/cupy/statistics_tests/test_order.py::TestOrder::test_percentile_scalar_q[linear]
-tests/third_party/cupy/statistics_tests/test_order.py::TestOrder::test_percentile_scalar_q[lower]
-tests/third_party/cupy/statistics_tests/test_order.py::TestOrder::test_percentile_scalar_q[higher]
-tests/third_party/cupy/statistics_tests/test_order.py::TestOrder::test_percentile_scalar_q[midpoint]
-tests/third_party/cupy/statistics_tests/test_order.py::TestOrder::test_percentile_keepdims[linear]
-tests/third_party/cupy/statistics_tests/test_order.py::TestOrder::test_percentile_keepdims[lower]
-tests/third_party/cupy/statistics_tests/test_order.py::TestOrder::test_percentile_keepdims[higher]
-tests/third_party/cupy/statistics_tests/test_order.py::TestOrder::test_percentile_keepdims[midpoint]
-tests/third_party/cupy/statistics_tests/test_order.py::TestOrder::test_percentile_out[linear]
-tests/third_party/cupy/statistics_tests/test_order.py::TestOrder::test_percentile_out[lower]
-tests/third_party/cupy/statistics_tests/test_order.py::TestOrder::test_percentile_out[higher]
-tests/third_party/cupy/statistics_tests/test_order.py::TestOrder::test_percentile_out[midpoint]
-tests/third_party/cupy/statistics_tests/test_order.py::TestOrder::test_percentile_bad_q[linear]
-tests/third_party/cupy/statistics_tests/test_order.py::TestOrder::test_percentile_bad_q[lower]
-tests/third_party/cupy/statistics_tests/test_order.py::TestOrder::test_percentile_bad_q[higher]
-tests/third_party/cupy/statistics_tests/test_order.py::TestOrder::test_percentile_bad_q[midpoint]
-tests/third_party/cupy/statistics_tests/test_order.py::TestOrder::test_percentile_unxpected_method

tests/skipped_tests_gpu.tbl

@@ -319,46 +319,3 @@ tests/third_party/cupy/random_tests/test_sample.py::TestRandomIntegers2::test_bo
 tests/third_party/cupy/random_tests/test_sample.py::TestRandomIntegers2::test_bound_2
 tests/third_party/cupy/random_tests/test_sample.py::TestRandomIntegers2::test_goodness_of_fit
 tests/third_party/cupy/random_tests/test_sample.py::TestRandomIntegers2::test_goodness_of_fit_2
-
-tests/third_party/cupy/statistics_tests/test_correlation.py::TestCorrcoef::test_corrcoef
-tests/third_party/cupy/statistics_tests/test_correlation.py::TestCorrcoef::test_corrcoef_diag_exception
-tests/third_party/cupy/statistics_tests/test_correlation.py::TestCorrcoef::test_corrcoef_rowvar
-tests/third_party/cupy/statistics_tests/test_correlation.py::TestCorrcoef::test_corrcoef_y
-
-tests/third_party/cupy/statistics_tests/test_order.py::TestOrder::test_percentile_defaults[linear]
-tests/third_party/cupy/statistics_tests/test_order.py::TestOrder::test_percentile_defaults[lower]
-tests/third_party/cupy/statistics_tests/test_order.py::TestOrder::test_percentile_defaults[higher]
-tests/third_party/cupy/statistics_tests/test_order.py::TestOrder::test_percentile_defaults[midpoint]
-tests/third_party/cupy/statistics_tests/test_order.py::TestOrder::test_percentile_q_list[linear]
-tests/third_party/cupy/statistics_tests/test_order.py::TestOrder::test_percentile_q_list[lower]
-tests/third_party/cupy/statistics_tests/test_order.py::TestOrder::test_percentile_q_list[higher]
-tests/third_party/cupy/statistics_tests/test_order.py::TestOrder::test_percentile_q_list[midpoint]
-tests/third_party/cupy/statistics_tests/test_order.py::TestOrder::test_percentile_no_axis[linear]
-tests/third_party/cupy/statistics_tests/test_order.py::TestOrder::test_percentile_no_axis[lower]
-tests/third_party/cupy/statistics_tests/test_order.py::TestOrder::test_percentile_no_axis[higher]
-tests/third_party/cupy/statistics_tests/test_order.py::TestOrder::test_percentile_no_axis[midpoint]
-tests/third_party/cupy/statistics_tests/test_order.py::TestOrder::test_percentile_neg_axis[linear]
-tests/third_party/cupy/statistics_tests/test_order.py::TestOrder::test_percentile_neg_axis[lower]
-tests/third_party/cupy/statistics_tests/test_order.py::TestOrder::test_percentile_neg_axis[higher]
-tests/third_party/cupy/statistics_tests/test_order.py::TestOrder::test_percentile_neg_axis[midpoint]
-tests/third_party/cupy/statistics_tests/test_order.py::TestOrder::test_percentile_tuple_axis[linear]
-tests/third_party/cupy/statistics_tests/test_order.py::TestOrder::test_percentile_tuple_axis[lower]
-tests/third_party/cupy/statistics_tests/test_order.py::TestOrder::test_percentile_tuple_axis[higher]
-tests/third_party/cupy/statistics_tests/test_order.py::TestOrder::test_percentile_tuple_axis[midpoint]
-tests/third_party/cupy/statistics_tests/test_order.py::TestOrder::test_percentile_scalar_q[linear]
-tests/third_party/cupy/statistics_tests/test_order.py::TestOrder::test_percentile_scalar_q[lower]
-tests/third_party/cupy/statistics_tests/test_order.py::TestOrder::test_percentile_scalar_q[higher]
-tests/third_party/cupy/statistics_tests/test_order.py::TestOrder::test_percentile_scalar_q[midpoint]
-tests/third_party/cupy/statistics_tests/test_order.py::TestOrder::test_percentile_keepdims[linear]
-tests/third_party/cupy/statistics_tests/test_order.py::TestOrder::test_percentile_keepdims[lower]
-tests/third_party/cupy/statistics_tests/test_order.py::TestOrder::test_percentile_keepdims[higher]
-tests/third_party/cupy/statistics_tests/test_order.py::TestOrder::test_percentile_keepdims[midpoint]
-tests/third_party/cupy/statistics_tests/test_order.py::TestOrder::test_percentile_out[linear]
-tests/third_party/cupy/statistics_tests/test_order.py::TestOrder::test_percentile_out[lower]
-tests/third_party/cupy/statistics_tests/test_order.py::TestOrder::test_percentile_out[higher]
-tests/third_party/cupy/statistics_tests/test_order.py::TestOrder::test_percentile_out[midpoint]
-tests/third_party/cupy/statistics_tests/test_order.py::TestOrder::test_percentile_bad_q[linear]
-tests/third_party/cupy/statistics_tests/test_order.py::TestOrder::test_percentile_bad_q[lower]
-tests/third_party/cupy/statistics_tests/test_order.py::TestOrder::test_percentile_bad_q[higher]
-tests/third_party/cupy/statistics_tests/test_order.py::TestOrder::test_percentile_bad_q[midpoint]
-tests/third_party/cupy/statistics_tests/test_order.py::TestOrder::test_percentile_unxpected_method

tests/third_party/cupy/__init__.py

@@ -1,16 +1,16 @@
-import sys
 import unittest
 
 import numpy
 import pytest
-from dpctl import select_default_device
 
 import dpnp as cupy
 from tests.helper import has_support_aspect64
 from tests.third_party.cupy import testing
 
 
+@pytest.mark.skip("dpnp.corrcoef() is not implemented yet")
 class TestCorrcoef(unittest.TestCase):
+
     @testing.for_all_dtypes()
     @testing.numpy_cupy_allclose()
     def test_corrcoef(self, xp, dtype):
@@ -37,10 +37,16 @@ def test_corrcoef_rowvar(self, xp, dtype):
         y = testing.shaped_arange((2, 3), xp, dtype)
         return xp.corrcoef(a, y=y, rowvar=False)
 
+    @testing.with_requires("numpy>=1.20")
+    @testing.for_all_dtypes()
+    @testing.numpy_cupy_allclose(accept_error=True)
+    def test_corrcoef_dtype(self, xp, dtype):
+        a = testing.shaped_arange((2, 3), xp, dtype)
+        y = testing.shaped_arange((2, 3), xp, dtype)
+        return xp.corrcoef(a, y=y, dtype=dtype)
+
 
 class TestCov(unittest.TestCase):
-    # resulting dtype will differ with numpy if no fp64 support by a default device
-    _has_fp64 = select_default_device().has_aspect_fp64
 
     def generate_input(self, a_shape, y_shape, xp, dtype):
         a = testing.shaped_arange(a_shape, xp, dtype)
@@ -50,7 +56,9 @@ def generate_input(self, a_shape, y_shape, xp, dtype):
         return a, y
 
     @testing.for_all_dtypes()
-    @testing.numpy_cupy_allclose(type_check=_has_fp64, accept_error=True)
+    @testing.numpy_cupy_allclose(
+        type_check=has_support_aspect64(), accept_error=True
+    )
     def check(
         self,
         a_shape,
@@ -153,6 +161,7 @@ def test_cov_empty(self):
 )
 @pytest.mark.usefixtures("allow_fall_back_on_numpy")
 class TestCorrelateShapeCombination(unittest.TestCase):
+
     @testing.for_all_dtypes(no_float16=True)
     @testing.numpy_cupy_allclose(rtol=1e-4)
     def test_correlate(self, xp, dtype):
@@ -161,34 +170,36 @@ def test_correlate(self, xp, dtype):
         return xp.correlate(a, b, mode=self.mode)
 
 
-@testing.parameterize(*testing.product({"mode": ["valid", "full", "same"]}))
+@pytest.mark.parametrize("mode", ["valid", "full", "same"])
 @pytest.mark.usefixtures("allow_fall_back_on_numpy")
-class TestCorrelate(unittest.TestCase):
+class TestCorrelate:
+
     @testing.for_all_dtypes()
     @testing.numpy_cupy_allclose(rtol=1e-5)
-    def test_correlate_non_contiguous(self, xp, dtype):
+    def test_correlate_non_contiguous(self, xp, dtype, mode):
         a = testing.shaped_arange((300,), xp, dtype)
         b = testing.shaped_arange((100,), xp, dtype)
-        return xp.correlate(a[::200], b[10::70], mode=self.mode)
+        return xp.correlate(a[::200], b[10::70], mode=mode)
 
     @testing.for_all_dtypes(no_float16=True)
     @testing.numpy_cupy_allclose(rtol=1e-4)
-    def test_correlate_large_non_contiguous(self, xp, dtype):
+    def test_correlate_large_non_contiguous(self, xp, dtype, mode):
         a = testing.shaped_arange((10000,), xp, dtype)
         b = testing.shaped_arange((1000,), xp, dtype)
-        return xp.correlate(a[200::], b[10::700], mode=self.mode)
+        return xp.correlate(a[200::], b[10::700], mode=mode)
 
     @testing.for_all_dtypes_combination(names=["dtype1", "dtype2"])
     @testing.numpy_cupy_allclose(rtol=1e-2, type_check=has_support_aspect64())
-    def test_correlate_diff_types(self, xp, dtype1, dtype2):
+    def test_correlate_diff_types(self, xp, dtype1, dtype2, mode):
         a = testing.shaped_random((200,), xp, dtype1)
         b = testing.shaped_random((100,), xp, dtype2)
-        return xp.correlate(a, b, mode=self.mode)
+        return xp.correlate(a, b, mode=mode)
 
 
 @testing.parameterize(*testing.product({"mode": ["valid", "same", "full"]}))
 @pytest.mark.usefixtures("allow_fall_back_on_numpy")
 class TestCorrelateInvalid(unittest.TestCase):
+
     @testing.with_requires("numpy>=1.18")
     @testing.for_all_dtypes()
     def test_correlate_empty(self, dtype):

tests/third_party/cupy/statistics_tests/test_correlation.py

@@ -42,6 +42,7 @@ def for_all_dtypes_combination_bincount(names):
 
 
 class TestHistogram(unittest.TestCase):
+
     @testing.for_all_dtypes(no_bool=True, no_complex=True)
     @testing.numpy_cupy_allclose(atol=1e-6, type_check=has_support_aspect64())
     def test_histogram(self, xp, dtype):
@@ -94,7 +95,7 @@ def test_histogram_range_with_density(self, xp, dtype):
         return h
 
     @testing.for_float_dtypes()
-    @testing.numpy_cupy_allclose(atol=1e-6, type_check=False)
+    @testing.numpy_cupy_allclose(atol=1e-6, type_check=has_support_aspect64())
     def test_histogram_range_with_weights_and_density(self, xp, dtype):
         a = xp.arange(10, dtype=dtype) + 0.5
         w = xp.arange(10, dtype=dtype) + 0.5
@@ -135,7 +136,9 @@ def test_histogram_int_weights_dtype(self, xp, dtype):
     def test_histogram_float_weights_dtype(self, xp, dtype):
         # Check the type of the returned histogram
         a = xp.arange(10, dtype=dtype)
-        h, b = xp.histogram(a, weights=xp.ones(10, dtype=xp.float32))
+        h, b = xp.histogram(
+            a, weights=xp.ones(10, dtype=cupy.default_float_type())
+        )
         assert xp.issubdtype(h.dtype, xp.floating)
         return h
 
@@ -363,6 +366,7 @@ def test_bincount_too_small_minlength(self, dtype):
     )
 )
 class TestDigitize:
+
     @testing.for_all_dtypes(no_bool=True, no_complex=True)
     @testing.numpy_cupy_array_equal()
     def test_digitize(self, xp, dtype):
@@ -377,6 +381,7 @@ def test_digitize(self, xp, dtype):
 
 @testing.parameterize({"right": True}, {"right": False})
 class TestDigitizeNanInf(unittest.TestCase):
+
     @testing.numpy_cupy_array_equal()
     def test_digitize_nan(self, xp):
         x = testing.shaped_arange((14,), xp, xp.float32)
@@ -446,6 +451,7 @@ def test_searchsorted_minf(self, xp):
 
 
 class TestDigitizeInvalid(unittest.TestCase):
+
     def test_digitize_complex(self):
         for xp in (numpy, cupy):
             x = testing.shaped_arange((14,), xp, xp.complex64)
@@ -462,6 +468,7 @@ def test_digitize_nd_bins(self):
 
 
 @pytest.mark.skip("histogramdd() is not implemented yet")
+# @pytest.mark.skip(reason="XXX: NP2.0: histogramdd dtype")
 @testing.parameterize(
     *testing.product(
         {
@@ -481,6 +488,7 @@ def test_digitize_nd_bins(self):
     )
 )
 class TestHistogramdd:
+
     @testing.for_all_dtypes(no_bool=True, no_complex=True)
     @testing.numpy_cupy_allclose(atol=1e-7, rtol=1e-7)
     def test_histogramdd(self, xp, dtype):
@@ -507,6 +515,7 @@ def test_histogramdd(self, xp, dtype):
 
 @pytest.mark.skip("histogramdd() is not implemented yet")
 class TestHistogramddErrors(unittest.TestCase):
+
     def test_histogramdd_invalid_bins(self):
         for xp in (numpy, cupy):
             x = testing.shaped_random((16, 2), xp, scale=100)
@@ -552,6 +561,7 @@ def test_histogramdd_disallow_arraylike_bins(self):
 
 
 @pytest.mark.skip("histogram2d() is not implemented yet")
+# @pytest.mark.skip(reason="XXX: NP2.0: histogram2d dtype")
 @testing.parameterize(
     *testing.product(
         {
@@ -564,11 +574,13 @@ def test_histogramdd_disallow_arraylike_bins(self):
     )
 )
 class TestHistogram2d:
+
     @testing.for_all_dtypes(no_bool=True, no_complex=True)
-    @testing.numpy_cupy_allclose(atol=1e-7, rtol=1e-7)
+    @testing.numpy_cupy_allclose(atol=1e-2, rtol=1e-7)
     def test_histogram2d(self, xp, dtype):
         x = testing.shaped_random((100,), xp, dtype, scale=100)
         y = testing.shaped_random((100,), xp, dtype, scale=100)
+
         if self.bins == "array_list":
             bins = [xp.arange(0, 100, 4), xp.arange(0, 100, 10)]
         elif self.bins == "array":
@@ -592,6 +604,7 @@ def test_histogram2d(self, xp, dtype):
 
 @pytest.mark.skip("histogram2d() is not implemented yet")
 class TestHistogram2dErrors(unittest.TestCase):
+
     def test_histogram2d_disallow_arraylike_bins(self):
         x = testing.shaped_random((16,), cupy, scale=100)
         y = testing.shaped_random((16,), cupy, scale=100)