Use empty() function from dpctl.tensor module for empty_like() function

dpnp/dpnp_container.py

@@ -102,12 +102,17 @@ def asarray(x1,
 
 
 def empty(shape,
-          dtype="f4",
+          *,
+          dtype=None,
           order="C",
           device=None,
           usm_type="device",
           sycl_queue=None):
-    sycl_queue_normalized = dpnp.get_normalized_queue_device(device=device, sycl_queue=sycl_queue)
+    """Validate input parameters before passing them into `dpctl.tensor` module"""
+    dpu.validate_usm_type(usm_type, allow_none=False)
+    sycl_queue_normalized = dpnp.get_normalized_queue_device(sycl_queue=sycl_queue, device=device)
+    if order is None:
+        order = 'C'
 
     """Creates `dpnp_array` from uninitialized USM allocation."""
     array_obj = dpt.empty(shape,

dpnp/dpnp_iface_arraycreation.py

@@ -464,7 +464,8 @@ def diagflat(x1, k=0):
 
 
 def empty(shape,
-          dtype="f8",
+          *,
+          dtype=None,
           order="C",
           like=None,
           device=None,
@@ -477,7 +478,9 @@ def empty(shape,
 
     Limitations
     -----------
+    Parameter ``order`` is supported only with values ``"C"`` and ``"F"``.
     Parameter ``like`` is supported only with default value ``None``.
+    Otherwise the function will be executed sequentially on CPU.
 
     See Also
     --------
@@ -497,6 +500,8 @@ def empty(shape,
 
     if like is not None:
         pass
+    elif order not in ('C', 'c', 'F', 'f', None):
+        pass
     else:
         return dpnp_container.empty(shape,
                                     dtype=dtype,
@@ -508,16 +513,27 @@ def empty(shape,
     return call_origin(numpy.empty, shape, dtype=dtype, order=order, like=like)
 
 
-def empty_like(prototype, dtype=None, order='C', subok=False, shape=None):
+def empty_like(x1,
+               /,
+               *,
+               dtype=None,
+               order="C",
+               subok=False,
+               shape=None,
+               device=None,
+               usm_type=None,
+               sycl_queue=None):
     """
     Return a new array with the same shape and type as a given array.
 
     For full documentation refer to :obj:`numpy.empty_like`.
 
     Limitations
     -----------
-    Parameter ``order`` is supported only with default value ``"C"``.
+    Parameters ``x1`` is supported only as :class:`dpnp.dpnp_array`.
+    Parameter ``order`` is supported with values ``"C"`` or ``"F"``.
     Parameter ``subok`` is supported only with default value ``False``.
+    Otherwise the function will be executed sequentially on CPU.
 
     See Also
     --------
@@ -529,26 +545,31 @@ def empty_like(prototype, dtype=None, order='C', subok=False, shape=None):
     Examples
     --------
     >>> import dpnp as np
-    >>> prototype = np.array([1, 2, 3])
-    >>> x = np.empty_like(prototype)
+    >>> a = np.array([1, 2, 3])
+    >>> x = np.empty_like(a)
     >>> [i for i in x]
     [0, 0, 0]
 
     """
 
-    if (not use_origin_backend()):
-        if order not in ('C', 'c', None):
-            pass
-        elif subok is not False:
-            pass
-        else:
-            _shape = shape if shape is not None else prototype.shape
-            _dtype = dtype if dtype is not None else prototype.dtype.type
-
-            result = create_output_descriptor_py(_object_to_tuple(_shape), _dtype, None).get_pyobj()
-            return result
+    if not isinstance(x1, dpnp.ndarray):
+        pass
+    elif order not in ('C', 'c', 'F', 'f', None):
+        pass
+    elif subok is not False:
+        pass
+    else:
+        _shape = x1.shape if shape is None else shape
+        _dtype = x1.dtype if dtype is None else dtype
+        _usm_type = x1.usm_type if usm_type is None else usm_type
+        _sycl_queue = dpnp.get_normalized_queue_device(x1, sycl_queue=sycl_queue, device=device)
+        return dpnp_container.empty(_shape,
+                                    dtype=_dtype,
+                                    order=order,
+                                    usm_type=_usm_type,
+                                    sycl_queue=_sycl_queue)
 
-    return call_origin(numpy.empty_like, prototype, dtype, order, subok, shape)
+    return call_origin(numpy.empty_like, x1, dtype, order, subok, shape)
 
 
 def eye(N, M=None, k=0, dtype=None, order='C', **kwargs):

tests/skipped_tests.tbl

@@ -282,20 +282,11 @@ tests/third_party/cupy/core_tests/test_ndarray_reduction.py::TestCubReduction_pa
 tests/third_party/cupy/core_tests/test_ndarray_reduction.py::TestCubReduction_param_6_{order='F', shape=(10, 20, 30)}::test_cub_min
 tests/third_party/cupy/core_tests/test_ndarray_reduction.py::TestCubReduction_param_7_{order='F', shape=(10, 20, 30, 40)}::test_cub_max
 tests/third_party/cupy/core_tests/test_ndarray_reduction.py::TestCubReduction_param_7_{order='F', shape=(10, 20, 30, 40)}::test_cub_min
-tests/third_party/cupy/creation_tests/test_basic.py::TestBasic::test_empty
-tests/third_party/cupy/creation_tests/test_basic.py::TestBasic::test_empty_int
-tests/third_party/cupy/creation_tests/test_basic.py::TestBasic::test_empty_like
 tests/third_party/cupy/creation_tests/test_basic.py::TestBasic::test_empty_like_contiguity
-tests/third_party/cupy/creation_tests/test_basic.py::TestBasic::test_empty_scalar
-tests/third_party/cupy/creation_tests/test_basic.py::TestBasicReshape_param_0_{shape=4}::test_empty_like_reshape
 tests/third_party/cupy/creation_tests/test_basic.py::TestBasicReshape_param_0_{shape=4}::test_empty_like_reshape_contiguity
-tests/third_party/cupy/creation_tests/test_basic.py::TestBasicReshape_param_1_{shape=(4,)}::test_empty_like_reshape
 tests/third_party/cupy/creation_tests/test_basic.py::TestBasicReshape_param_1_{shape=(4,)}::test_empty_like_reshape_contiguity
-tests/third_party/cupy/creation_tests/test_basic.py::TestBasicReshape_param_2_{shape=(4, 2)}::test_empty_like_reshape
 tests/third_party/cupy/creation_tests/test_basic.py::TestBasicReshape_param_2_{shape=(4, 2)}::test_empty_like_reshape_contiguity
-tests/third_party/cupy/creation_tests/test_basic.py::TestBasicReshape_param_3_{shape=(4, 2, 3)}::test_empty_like_reshape
 tests/third_party/cupy/creation_tests/test_basic.py::TestBasicReshape_param_3_{shape=(4, 2, 3)}::test_empty_like_reshape_contiguity
-tests/third_party/cupy/creation_tests/test_basic.py::TestBasicReshape_param_4_{shape=(5, 4, 2, 3)}::test_empty_like_reshape
 tests/third_party/cupy/creation_tests/test_basic.py::TestBasicReshape_param_4_{shape=(5, 4, 2, 3)}::test_empty_like_reshape_contiguity
 tests/third_party/cupy/creation_tests/test_basic.py::TestBasicReshape_param_0_{shape=4}::test_empty_like_K_strides_reshape
 tests/third_party/cupy/creation_tests/test_basic.py::TestBasicReshape_param_0_{shape=4}::test_empty_like_reshape_contiguity2

tests/skipped_tests_gpu.tbl

@@ -458,20 +458,11 @@ tests/third_party/cupy/core_tests/test_ndarray_reduction.py::TestCubReduction_pa
 tests/third_party/cupy/core_tests/test_ndarray_reduction.py::TestCubReduction_param_6_{order='F', shape=(10, 20, 30)}::test_cub_min
 tests/third_party/cupy/core_tests/test_ndarray_reduction.py::TestCubReduction_param_7_{order='F', shape=(10, 20, 30, 40)}::test_cub_max
 tests/third_party/cupy/core_tests/test_ndarray_reduction.py::TestCubReduction_param_7_{order='F', shape=(10, 20, 30, 40)}::test_cub_min
-tests/third_party/cupy/creation_tests/test_basic.py::TestBasic::test_empty
-tests/third_party/cupy/creation_tests/test_basic.py::TestBasic::test_empty_int
-tests/third_party/cupy/creation_tests/test_basic.py::TestBasic::test_empty_like
 tests/third_party/cupy/creation_tests/test_basic.py::TestBasic::test_empty_like_contiguity
-tests/third_party/cupy/creation_tests/test_basic.py::TestBasic::test_empty_scalar
-tests/third_party/cupy/creation_tests/test_basic.py::TestBasicReshape_param_0_{shape=4}::test_empty_like_reshape
 tests/third_party/cupy/creation_tests/test_basic.py::TestBasicReshape_param_0_{shape=4}::test_empty_like_reshape_contiguity
-tests/third_party/cupy/creation_tests/test_basic.py::TestBasicReshape_param_1_{shape=(4,)}::test_empty_like_reshape
 tests/third_party/cupy/creation_tests/test_basic.py::TestBasicReshape_param_1_{shape=(4,)}::test_empty_like_reshape_contiguity
-tests/third_party/cupy/creation_tests/test_basic.py::TestBasicReshape_param_2_{shape=(4, 2)}::test_empty_like_reshape
 tests/third_party/cupy/creation_tests/test_basic.py::TestBasicReshape_param_2_{shape=(4, 2)}::test_empty_like_reshape_contiguity
-tests/third_party/cupy/creation_tests/test_basic.py::TestBasicReshape_param_3_{shape=(4, 2, 3)}::test_empty_like_reshape
 tests/third_party/cupy/creation_tests/test_basic.py::TestBasicReshape_param_3_{shape=(4, 2, 3)}::test_empty_like_reshape_contiguity
-tests/third_party/cupy/creation_tests/test_basic.py::TestBasicReshape_param_4_{shape=(5, 4, 2, 3)}::test_empty_like_reshape
 tests/third_party/cupy/creation_tests/test_basic.py::TestBasicReshape_param_4_{shape=(5, 4, 2, 3)}::test_empty_like_reshape_contiguity
 tests/third_party/cupy/creation_tests/test_basic.py::TestBasicReshape_param_0_{shape=4}::test_empty_like_K_strides_reshape
 tests/third_party/cupy/creation_tests/test_basic.py::TestBasicReshape_param_0_{shape=4}::test_empty_like_reshape_contiguity2

tests/test_arraycreation.py

@@ -580,6 +580,45 @@ def test_zeros_like(array, dtype, order):
     assert_array_equal(expected, result)
 
 
+@pytest.mark.parametrize("shape",
+                         [(), 0, (0,), (2, 0, 3), (3, 2)],
+                         ids=['()', '0', '(0,)', '(2, 0, 3)', '(3, 2)'])
+@pytest.mark.parametrize("dtype",
+                         [None, numpy.complex128, numpy.complex64, numpy.float64, numpy.float32,
+                          numpy.float16, numpy.int64, numpy.int32, numpy.bool],
+                         ids=['None', 'complex128', 'complex64', 'float64', 'float32',
+                              'float16', 'int64', 'int32', 'bool'])
+@pytest.mark.parametrize("order",
+                         [None, "C", "F"],
+                         ids=['None', 'C', 'F'])
+def test_empty(shape, dtype, order):
+    expected = numpy.empty(shape, dtype=dtype, order=order)
+    result = dpnp.empty(shape, dtype=dtype, order=order)
+
+    assert expected.shape == result.shape
+
+
+@pytest.mark.parametrize("array",
+                         [[], 0,  [1, 2, 3], [[1, 2], [3, 4]]],
+                         ids=['[]', '0',  '[1, 2, 3]', '[[1, 2], [3, 4]]'])
+@pytest.mark.parametrize("dtype",
+                         [None, numpy.complex128, numpy.complex64, numpy.float64, numpy.float32,
+                          numpy.float16, numpy.int64, numpy.int32, numpy.bool],
+                         ids=['None', 'complex128', 'complex64', 'float64', 'float32',
+                              'float16', 'int64', 'int32', 'bool'])
+@pytest.mark.parametrize("order",
+                         [None, "C", "F"],
+                         ids=['None', 'C', 'F'])
+def test_empty_like(array, dtype, order):
+    a = numpy.array(array)
+    ia = dpnp.array(array)
+
+    expected = numpy.empty_like(a, dtype=dtype, order=order)
+    result = dpnp.empty_like(ia, dtype=dtype, order=order)
+
+    assert expected.shape == result.shape
+
+
 @pytest.mark.parametrize("shape",
                          [(), 0, (0,), (2, 0, 3), (3, 2)],
                          ids=['()', '0', '(0,)', '(2, 0, 3)', '(3, 2)'])

tests/test_sycl_queue.py

@@ -102,6 +102,28 @@ def test_array_creation(func, arg, kwargs, device):
     assert dpnp_array.sycl_device == device
 
 
+@pytest.mark.parametrize("device",
+                          valid_devices,
+                          ids=[device.filter_string for device in valid_devices])
+def test_empty(device):
+    dpnp_array = dpnp.empty((2, 2), device=device)
+    assert dpnp_array.sycl_device == device
+
+
+@pytest.mark.parametrize("device_x",
+                          valid_devices,
+                          ids=[device.filter_string for device in valid_devices])
+@pytest.mark.parametrize("device_y",
+                          valid_devices,
+                          ids=[device.filter_string for device in valid_devices])
+def test_empty_like(device_x, device_y):
+    x = dpnp.ndarray([1, 2, 3], device=device_x)
+    y = dpnp.empty_like(x)
+    assert_sycl_queue_equal(y.sycl_queue, x.sycl_queue)
+    y = dpnp.empty_like(x, device=device_y)
+    assert_sycl_queue_equal(y.sycl_queue, x.to_device(device_y).sycl_queue)
+
+
 @pytest.mark.parametrize(
     "func, kwargs",
     [

tests/test_usm_type.py

@@ -47,6 +47,8 @@ def test_coerced_usm_types_mul(usm_type_x, usm_type_y):
                      ['x0']),
         pytest.param("ones_like",
                      ['x0']),
+        pytest.param("empty_like",
+                     ['x0']),
     ])
 @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/creation_tests/test_basic.py

@@ -39,7 +39,7 @@ def test_empty_huge_size_fill0(self):
     @testing.for_all_dtypes()
     @testing.numpy_cupy_array_equal()
     def test_empty_scalar(self, xp, dtype, order):
-        a = xp.empty(None, dtype=dtype, order=order)
+        a = xp.empty((), dtype=dtype, order=order)
         a.fill(0)
         return a