Get rid of fallback on numpy in dpnp.asfarray

dpnp/dpnp_iface_manipulation.py

@@ -46,7 +46,6 @@
 import dpnp
 from dpnp.dpnp_algo import *
 from dpnp.dpnp_array import dpnp_array
-from dpnp.dpnp_iface_arraycreation import array
 from dpnp.dpnp_utils import *
 
 __all__ = [
@@ -78,27 +77,45 @@
 ]
 
 
-def asfarray(a, dtype=None):
+def asfarray(a, dtype=None, *, device=None, usm_type=None, sycl_queue=None):
     """
     Return an array converted to a float type.
 
     For full documentation refer to :obj:`numpy.asfarray`.
 
     Notes
     -----
-    This function works exactly the same as :obj:`dpnp.array`.
-    If dtype is `None`, `bool` or one of the `int` dtypes, it is replaced with
-    the default floating type in DPNP depending on device capabilities.
+    If `dtype` is ``None``, :obj:`dpnp.bool` or one of the `int` dtypes,
+    it is replaced with the default floating type (:obj:`dpnp.float64`
+    if a device supports it, or :obj:`dpnp.float32` type otherwise).
+
+    Returns
+    -------
+    y : dpnp.ndarray
+        The input a as a float ndarray.
+
+    Examples
+    --------
+    >>> import dpnp as np
+    >>> np.asfarray([2, 3])
+    array([2.,  3.])
+    >>> np.asfarray([2, 3], dtype='float')
+    array([2.,  3.])
+    >>> np.asfarray([2, 3], dtype='int8')
+    array([2.,  3.])
 
     """
 
+    _sycl_queue = dpnp.get_normalized_queue_device(
+        a, sycl_queue=sycl_queue, device=device
+    )
+
     if dtype is None or not numpy.issubdtype(dtype, dpnp.inexact):
-        if dpnp.is_supported_array_type(a):
-            dtype = dpnp.default_float_type(sycl_queue=a.sycl_queue)
-        else:
-            dtype = dpnp.default_float_type()
+        dtype = dpnp.default_float_type(sycl_queue=_sycl_queue)
 
-    return array(a, dtype=dtype)
+    return dpnp.array(
+        a, dtype=dtype, copy=False, usm_type=usm_type, sycl_queue=_sycl_queue
+    )
 
 
 def atleast_1d(*arys):

tests/skipped_tests.tbl

@@ -483,6 +483,15 @@ tests/third_party/cupy/manipulation_tests/test_shape.py::TestRavel::test_ravel
 tests/third_party/cupy/manipulation_tests/test_shape.py::TestReshape::test_reshape_zerosize
 tests/third_party/cupy/manipulation_tests/test_shape.py::TestReshape::test_reshape_zerosize2
 
+tests/third_party/cupy/manipulation_tests/test_kind.py::TestKind::test_asarray_chkfinite
+tests/third_party/cupy/manipulation_tests/test_kind.py::TestKind::test_asarray_chkfinite_non_finite_vals
+tests/third_party/cupy/manipulation_tests/test_kind.py::TestKind::test_require_C_and_F_flags
+tests/third_party/cupy/manipulation_tests/test_kind.py::TestKind::test_require_empty_requirements
+tests/third_party/cupy/manipulation_tests/test_kind.py::TestKind::test_require_flag_check
+tests/third_party/cupy/manipulation_tests/test_kind.py::TestKind::test_require_incorrect_dtype
+tests/third_party/cupy/manipulation_tests/test_kind.py::TestKind::test_require_incorrect_requirments
+tests/third_party/cupy/manipulation_tests/test_kind.py::TestKind::test_require_owndata
+
 tests/third_party/cupy/manipulation_tests/test_tiling.py::TestRepeatRepeatsNdarray::test_func
 tests/third_party/cupy/manipulation_tests/test_tiling.py::TestRepeatRepeatsNdarray::test_method
 tests/third_party/cupy/manipulation_tests/test_tiling.py::TestTileFailure_param_0_{reps=-1}::test_tile_failure

tests/skipped_tests_gpu.tbl

@@ -641,6 +641,15 @@ tests/third_party/cupy/manipulation_tests/test_tiling.py::TestTile_param_3_{reps
 tests/third_party/cupy/manipulation_tests/test_tiling.py::TestTile_param_4_{reps=(2, 3)}::test_array_tile
 tests/third_party/cupy/manipulation_tests/test_tiling.py::TestTile_param_5_{reps=(2, 3, 4, 5)}::test_array_tile
 
+tests/third_party/cupy/manipulation_tests/test_kind.py::TestKind::test_asarray_chkfinite
+tests/third_party/cupy/manipulation_tests/test_kind.py::TestKind::test_asarray_chkfinite_non_finite_vals
+tests/third_party/cupy/manipulation_tests/test_kind.py::TestKind::test_require_C_and_F_flags
+tests/third_party/cupy/manipulation_tests/test_kind.py::TestKind::test_require_empty_requirements
+tests/third_party/cupy/manipulation_tests/test_kind.py::TestKind::test_require_flag_check
+tests/third_party/cupy/manipulation_tests/test_kind.py::TestKind::test_require_incorrect_dtype
+tests/third_party/cupy/manipulation_tests/test_kind.py::TestKind::test_require_incorrect_requirments
+tests/third_party/cupy/manipulation_tests/test_kind.py::TestKind::test_require_owndata
+
 tests/third_party/cupy/math_tests/test_arithmetic.py::TestArithmeticRaisesWithNumpyInput_param_3_{name='angle', nargs=1}::test_raises_with_numpy_input
 
 tests/third_party/cupy/math_tests/test_explog.py::TestExplog::test_logaddexp

tests/test_arraymanipulation.py

@@ -13,7 +13,6 @@
 from .helper import get_all_dtypes, get_float_complex_dtypes
 
 
-@pytest.mark.usefixtures("allow_fall_back_on_numpy")
 @pytest.mark.parametrize("dtype", get_all_dtypes())
 @pytest.mark.parametrize(
     "data", [[1, 2, 3], [1.0, 2.0, 3.0]], ids=["[1, 2, 3]", "[1., 2., 3.]"]

tests/test_sycl_queue.py

@@ -1020,7 +1020,14 @@ def test_to_device(device_from, device_to):
 )
 @pytest.mark.parametrize(
     "func",
-    ["array", "asarray", "asanyarray", "ascontiguousarray", "asfortranarray"],
+    [
+        "array",
+        "asarray",
+        "asanyarray",
+        "ascontiguousarray",
+        "asfarray",
+        "asfortranarray",
+    ],
 )
 @pytest.mark.parametrize(
     "device_param", ["", "None", "sycl_device"], ids=["Empty", "None", "device"]

tests/test_usm_type.py

@@ -159,7 +159,14 @@ def test_array_creation(func, args, usm_type_x, usm_type_y):
 
 @pytest.mark.parametrize(
     "func",
-    ["array", "asarray", "asanyarray", "ascontiguousarray", "asfortranarray"],
+    [
+        "array",
+        "asarray",
+        "asanyarray",
+        "ascontiguousarray",
+        "asfarray",
+        "asfortranarray",
+    ],
 )
 @pytest.mark.parametrize("usm_type_x", list_of_usm_types, ids=list_of_usm_types)
 @pytest.mark.parametrize("usm_type_y", list_of_usm_types, ids=list_of_usm_types)

tests/third_party/cupy/manipulation_tests/test_kind.py

@@ -0,0 +1,126 @@
+import unittest
+
+import numpy
+import pytest
+
+import dpnp as cupy
+from tests.third_party.cupy import testing
+
+
+class TestKind(unittest.TestCase):
+    @testing.for_orders("CFAK")
+    @testing.for_all_dtypes()
+    @testing.numpy_cupy_array_equal()
+    def test_asarray_chkfinite(self, xp, dtype, order):
+        a = [0, 4, 0, 5]
+        return xp.asarray_chkfinite(a, dtype=dtype, order=order)
+
+    @testing.for_orders("CFAK")
+    @testing.for_all_dtypes(no_bool=True)
+    def test_asarray_chkfinite_non_finite_vals(self, dtype, order):
+        a = [-numpy.inf, 0.0, numpy.inf, numpy.nan]
+        for xp in (numpy, cupy):
+            if xp.issubdtype(dtype, xp.integer):
+                error = OverflowError
+            else:
+                error = ValueError
+            with pytest.raises(error):
+                xp.asarray_chkfinite(a, dtype=dtype, order=order)
+
+    @testing.for_all_dtypes()
+    def test_asfarray(self, dtype):
+        a = cupy.asarray([1, 2, 3])
+        a_gpu = cupy.asfarray(a, dtype)
+        a_cpu = numpy.asfarray(a, dtype)
+        assert a_cpu.dtype == a_gpu.dtype
+
+    @testing.for_all_dtypes()
+    def test_asfortranarray1(self, dtype):
+        def func(xp):
+            x = xp.zeros((2, 3), dtype=dtype)
+            ret = xp.asfortranarray(x)
+            assert x.flags.c_contiguous
+            assert ret.flags.f_contiguous
+
+        assert func(numpy) == func(cupy)
+
+    @testing.for_all_dtypes()
+    def test_asfortranarray2(self, dtype):
+        def func(xp):
+            x = xp.zeros((2, 3, 4), dtype=dtype)
+            ret = xp.asfortranarray(x)
+            assert x.flags.c_contiguous
+            assert ret.flags.f_contiguous
+
+        assert func(numpy) == func(cupy)
+
+    @testing.for_all_dtypes()
+    def test_asfortranarray3(self, dtype):
+        def func(xp):
+            x = xp.zeros((2, 3, 4), dtype=dtype)
+            ret = xp.asfortranarray(xp.asfortranarray(x))
+            assert x.flags.c_contiguous
+            assert ret.flags.f_contiguous
+
+        assert func(numpy) == func(cupy)
+
+    @testing.for_all_dtypes()
+    def test_asfortranarray4(self, dtype):
+        def func(xp):
+            x = xp.zeros((2, 3), dtype=dtype)
+            x = xp.transpose(x, (1, 0))
+            ret = xp.asfortranarray(x)
+            assert ret.flags.f_contiguous
+
+        assert func(numpy) == func(cupy)
+
+    @testing.for_all_dtypes()
+    def test_asfortranarray5(self, dtype):
+        def func(xp):
+            x = testing.shaped_arange((2, 3), xp, dtype)
+            ret = xp.asfortranarray(x)
+            assert x.flags.c_contiguous
+            assert ret.flags.f_contiguous
+
+        assert func(numpy) == func(cupy)
+
+    @testing.for_all_dtypes()
+    def test_require_flag_check(self, dtype):
+        possible_flags = [["C_CONTIGUOUS"], ["F_CONTIGUOUS"]]
+        x = cupy.zeros((2, 3, 4), dtype=dtype)
+        for flags in possible_flags:
+            arr = cupy.require(x, dtype, flags)
+            for parameter in flags:
+                assert arr.flags[parameter]
+                assert arr.dtype == dtype
+
+    @testing.for_all_dtypes()
+    def test_require_owndata(self, dtype):
+        x = cupy.zeros((2, 3, 4), dtype=dtype)
+        arr = x.view()
+        arr = cupy.require(arr, dtype, ["O"])
+        assert arr.flags["OWNDATA"]
+
+    @testing.for_all_dtypes()
+    def test_require_C_and_F_flags(self, dtype):
+        x = cupy.zeros((2, 3, 4), dtype=dtype)
+        with pytest.raises(ValueError):
+            cupy.require(x, dtype, ["C", "F"])
+
+    @testing.for_all_dtypes()
+    def test_require_incorrect_requirments(self, dtype):
+        x = cupy.zeros((2, 3, 4), dtype=dtype)
+        with pytest.raises(ValueError):
+            cupy.require(x, dtype, ["W"])
+
+    @testing.for_all_dtypes()
+    def test_require_incorrect_dtype(self, dtype):
+        x = cupy.zeros((2, 3, 4), dtype=dtype)
+        with pytest.raises(ValueError):
+            cupy.require(x, "random", "C")
+
+    @testing.for_all_dtypes()
+    def test_require_empty_requirements(self, dtype):
+        x = cupy.zeros((2, 3, 4), dtype=dtype)
+        x = cupy.require(x, dtype, [])
+        assert x.flags["C_CONTIGUOUS"]