Use tril() function from dpctl.tensor

Author: npolina4

dpnp/backend/include/dpnp_iface_fptr.hpp

@@ -370,7 +370,6 @@ enum class DPNPFuncName : size_t
     DPNP_FN_TRI,                          /**< Used in numpy.tri() impl  */
     DPNP_FN_TRI_EXT,                      /**< Used in numpy.tri() impl, requires extra parameters */
     DPNP_FN_TRIL,                         /**< Used in numpy.tril() impl  */
-    DPNP_FN_TRIL_EXT,                     /**< Used in numpy.tril() impl, requires extra parameters */
     DPNP_FN_TRIU,                         /**< Used in numpy.triu() impl  */
     DPNP_FN_TRIU_EXT,                     /**< Used in numpy.triu() impl, requires extra parameters */
     DPNP_FN_TRUNC,                        /**< Used in numpy.trunc() impl  */

dpnp/backend/kernels/dpnp_krnl_arraycreation.cpp

@@ -1055,17 +1055,6 @@ void (*dpnp_tril_default_c)(void*,
                             const size_t,
                             const size_t) = dpnp_tril_c<_DataType>;
 
-template <typename _DataType>
-DPCTLSyclEventRef (*dpnp_tril_ext_c)(DPCTLSyclQueueRef,
-                                     void*,
-                                     void*,
-                                     const int,
-                                     shape_elem_type*,
-                                     shape_elem_type*,
-                                     const size_t,
-                                     const size_t,
-                                     const DPCTLEventVectorRef) = dpnp_tril_c<_DataType>;
-
 template <typename _DataType>
 DPCTLSyclEventRef dpnp_triu_c(DPCTLSyclQueueRef q_ref,
                               void* array_in,
@@ -1439,11 +1428,6 @@ void func_map_init_arraycreation(func_map_t& fmap)
     fmap[DPNPFuncName::DPNP_FN_TRIL][eft_FLT][eft_FLT] = {eft_FLT, (void*)dpnp_tril_default_c<float>};
     fmap[DPNPFuncName::DPNP_FN_TRIL][eft_DBL][eft_DBL] = {eft_DBL, (void*)dpnp_tril_default_c<double>};
 
-    fmap[DPNPFuncName::DPNP_FN_TRIL_EXT][eft_INT][eft_INT] = {eft_INT, (void*)dpnp_tril_ext_c<int32_t>};
-    fmap[DPNPFuncName::DPNP_FN_TRIL_EXT][eft_LNG][eft_LNG] = {eft_LNG, (void*)dpnp_tril_ext_c<int64_t>};
-    fmap[DPNPFuncName::DPNP_FN_TRIL_EXT][eft_FLT][eft_FLT] = {eft_FLT, (void*)dpnp_tril_ext_c<float>};
-    fmap[DPNPFuncName::DPNP_FN_TRIL_EXT][eft_DBL][eft_DBL] = {eft_DBL, (void*)dpnp_tril_ext_c<double>};
-
     fmap[DPNPFuncName::DPNP_FN_TRIU][eft_INT][eft_INT] = {eft_INT, (void*)dpnp_triu_default_c<int32_t>};
     fmap[DPNPFuncName::DPNP_FN_TRIU][eft_LNG][eft_LNG] = {eft_LNG, (void*)dpnp_triu_default_c<int64_t>};
     fmap[DPNPFuncName::DPNP_FN_TRIU][eft_FLT][eft_FLT] = {eft_FLT, (void*)dpnp_triu_default_c<float>};

dpnp/dpnp_algo/dpnp_algo_arraycreation.pyx

@@ -45,7 +45,6 @@ __all__ += [
     "dpnp_ptp",
     "dpnp_trace",
     "dpnp_tri",
-    "dpnp_tril",
     "dpnp_triu",
     "dpnp_vander",
 ]
@@ -426,50 +425,6 @@ cpdef utils.dpnp_descriptor dpnp_tri(N, M=None, k=0, dtype=dpnp.float):
     return result
 
 
-cpdef utils.dpnp_descriptor dpnp_tril(utils.dpnp_descriptor m, int k):
-    cdef shape_type_c input_shape = m.shape
-    cdef shape_type_c result_shape
-
-    if m.ndim == 1:
-        result_shape = (m.shape[0], m.shape[0])
-    else:
-        result_shape = m.shape
-
-    cdef DPNPFuncType param1_type = dpnp_dtype_to_DPNPFuncType(m.dtype)
-    cdef DPNPFuncData kernel_data = get_dpnp_function_ptr(DPNP_FN_TRIL_EXT, param1_type, param1_type)
-
-    m_obj = m.get_array()
-
-    # ceate result array with type given by FPTR data
-    cdef utils.dpnp_descriptor result = utils.create_output_descriptor(result_shape,
-                                                                       kernel_data.return_type,
-                                                                       None,
-                                                                       device=m_obj.sycl_device,
-                                                                       usm_type=m_obj.usm_type,
-                                                                       sycl_queue=m_obj.sycl_queue)
-
-    result_sycl_queue = result.get_array().sycl_queue
-
-    cdef c_dpctl.SyclQueue q = <c_dpctl.SyclQueue> result_sycl_queue
-    cdef c_dpctl.DPCTLSyclQueueRef q_ref = q.get_queue_ref()
-
-    cdef custom_1in_1out_func_ptr_t func = <custom_1in_1out_func_ptr_t > kernel_data.ptr
-    cdef c_dpctl.DPCTLSyclEventRef event_ref = func(q_ref,
-                                                    m.get_data(),
-                                                    result.get_data(),
-                                                    k,
-                                                    input_shape.data(),
-                                                    result_shape.data(),
-                                                    m.ndim,
-                                                    result.ndim,
-                                                    NULL)  # dep_events_ref
-
-    with nogil: c_dpctl.DPCTLEvent_WaitAndThrow(event_ref)
-    c_dpctl.DPCTLEvent_Delete(event_ref)
-
-    return result
-
-
 cpdef utils.dpnp_descriptor dpnp_triu(utils.dpnp_descriptor m, int k):
     cdef shape_type_c input_shape = m.shape
     cdef shape_type_c result_shape

dpnp/dpnp_container.py

@@ -48,6 +48,7 @@
     "eye",
     "full",
     "ones"
+    "tril"
     "zeros",
 ]
 
@@ -200,6 +201,12 @@ def ones(shape,
     return dpnp_array(array_obj.shape, buffer=array_obj, order=order)
 
 
+def tril(x1, /, *, k=0):
+    """"Creates `dpnp_array` as lower triangle of an input array."""
+    array_obj = dpt.tril(x1.get_array() if isinstance(x1, dpnp_array) else x1, k)
+    return dpnp_array(array_obj.shape, buffer=array_obj)
+
+
 def zeros(shape,
           *,
           dtype=None,

dpnp/dpnp_iface.py

@@ -66,7 +66,8 @@
     "dpnp_queue_is_cpu",
     "get_dpnp_descriptor",
     "get_include",
-    "get_normalized_queue_device"
+    "get_normalized_queue_device",
+    "isarray"
 ]
 
 from dpnp import (
@@ -338,3 +339,13 @@ def get_normalized_queue_device(obj=None,
     if hasattr(dpt._device, 'normalize_queue_device'):
         return dpt._device.normalize_queue_device(sycl_queue=sycl_queue, device=device)
     return sycl_queue
+
+
+def isarray(obj):
+    """
+    Return True if:
+      `obj` has a supported array type
+    Return False if:
+      `obj` has an unsupported array type or other data type
+    """
+    return isinstance(obj, (dpnp_array, dpt.usm_ndarray))

dpnp/dpnp_iface_arraycreation.py

@@ -1331,14 +1331,20 @@ def tri(N, M=None, k=0, dtype=dpnp.float, **kwargs):
     return call_origin(numpy.tri, N, M, k, dtype, **kwargs)
 
 
-def tril(x1, k=0):
+def tril(x1, /, *, k=0):
     """
     Lower triangle of an array.
 
     Return a copy of an array with elements above the `k`-th diagonal zeroed.
 
     For full documentation refer to :obj:`numpy.tril`.
 
+    Limitations
+    -----------
+    Parameter ``x1`` is supported only as :class:`dpnp.dpnp_array` with two or more dimensions.
+    Parameter ``k`` is supported only as int data type.
+    Otherwise the function will be executed sequentially on CPU.
+
     Examples
     --------
     >>> import dpnp as np
@@ -1350,12 +1356,14 @@ def tril(x1, k=0):
 
     """
 
-    x1_desc = dpnp.get_dpnp_descriptor(x1, copy_when_nondefault_queue=False)
-    if x1_desc:
-        if not isinstance(k, int):
-            pass
-        else:
-            return dpnp_tril(x1_desc, k).get_pyobj()
+    if not dpnp.isarray(x1):
+        pass
+    elif x1.ndim < 2:
+        pass
+    elif not isinstance(k, int):
+        pass
+    else:
+        return dpnp_container.tril(x1, k=k)
 
     return call_origin(numpy.tril, x1, k)
 

tests/skipped_tests.tbl

@@ -430,6 +430,9 @@ tests/third_party/cupy/creation_tests/test_ranges.py::TestRanges::test_linspace_
 tests/third_party/cupy/creation_tests/test_ranges.py::TestRanges::test_linspace_mixed_start_stop
 tests/third_party/cupy/creation_tests/test_ranges.py::TestRanges::test_linspace_mixed_start_stop2
 tests/third_party/cupy/creation_tests/test_ranges.py::TestRanges::test_linspace_start_stop_list
+tests/third_party/cupy/creation_tests/test_matrix.py::TestTriLowerAndUpper_param_0_{shape=(2,)}::test_tril
+tests/third_party/cupy/creation_tests/test_matrix.py::TestTriLowerAndUpper_param_0_{shape=(2,)}::test_tril_nega
+tests/third_party/cupy/creation_tests/test_matrix.py::TestTriLowerAndUpper_param_0_{shape=(2,)}::test_tril_posi
 tests/third_party/cupy/indexing_tests/test_generate.py::TestAxisConcatenator::test_AxisConcatenator_init1
 tests/third_party/cupy/indexing_tests/test_generate.py::TestAxisConcatenator::test_len
 tests/third_party/cupy/indexing_tests/test_generate.py::TestC_::test_c_1

tests/skipped_tests_gpu.tbl

@@ -190,6 +190,9 @@ tests/third_party/cupy/creation_tests/test_matrix.py::TestMatrix::test_diag_cons
 tests/third_party/cupy/creation_tests/test_matrix.py::TestMatrix::test_diag_construction_from_tuple
 tests/third_party/cupy/creation_tests/test_matrix.py::TestMatrix::test_diag_extraction_from_nested_list
 tests/third_party/cupy/creation_tests/test_matrix.py::TestMatrix::test_diag_extraction_from_nested_tuple
+tests/third_party/cupy/creation_tests/test_matrix.py::TestTriLowerAndUpper_param_0_{shape=(2,)}::test_tril
+tests/third_party/cupy/creation_tests/test_matrix.py::TestTriLowerAndUpper_param_0_{shape=(2,)}::test_tril_nega
+tests/third_party/cupy/creation_tests/test_matrix.py::TestTriLowerAndUpper_param_0_{shape=(2,)}::test_tril_posi
 
 tests/third_party/cupy/indexing_tests/test_insert.py::TestFillDiagonal_param_4_{shape=(3, 3), val=(2,), wrap=True}::test_1darray
 tests/third_party/cupy/indexing_tests/test_insert.py::TestFillDiagonal_param_4_{shape=(3, 3), val=(2,), wrap=True}::test_fill_diagonal

tests/test_arraycreation.py

@@ -258,28 +258,25 @@ def test_tri_default_dtype():
 
 
 @pytest.mark.parametrize("k",
-                         [-6, -5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5, 6],
-                         ids=['-6', '-5', '-4', '-3', '-2', '-1', '0', '1', '2', '3', '4', '5', '6'])
+                         [-3, -2, -1, 0, 1, 2, 3, 4, 5],
+                         ids=['-3', '-2', '-1', '0', '1', '2', '3', '4', '5'])
 @pytest.mark.parametrize("m",
-                         [[0, 1, 2, 3, 4],
-                          [1, 1, 1, 1, 1],
-                          [[0, 0], [0, 0]],
+                         [[[0, 0], [0, 0]],
                           [[1, 2], [1, 2]],
                           [[1, 2], [3, 4]],
                           [[0, 1, 2], [3, 4, 5], [6, 7, 8]],
                           [[0, 1, 2, 3, 4], [5, 6, 7, 8, 9]]],
-                         ids=['[0, 1, 2, 3, 4]',
-                              '[1, 1, 1, 1, 1]',
-                              '[[0, 0], [0, 0]]',
+                         ids=['[[0, 0], [0, 0]]',
                               '[[1, 2], [1, 2]]',
                               '[[1, 2], [3, 4]]',
                               '[[0, 1, 2], [3, 4, 5], [6, 7, 8]]',
                               '[[0, 1, 2, 3, 4], [5, 6, 7, 8, 9]]'])
-def test_tril(m, k):
-    a = numpy.array(m)
+@pytest.mark.parametrize("dtype", get_all_dtypes(no_float16=False))
+def test_tril(m, k, dtype):
+    a = numpy.array(m, dtype=dtype)
     ia = dpnp.array(a)
-    expected = numpy.tril(a, k)
-    result = dpnp.tril(ia, k)
+    expected = numpy.tril(a, k=k)
+    result = dpnp.tril(ia, k=k)
     assert_array_equal(expected, result)
 
 

tests/third_party/cupy/creation_tests/test_matrix.py

@@ -157,13 +157,13 @@ def test_tril_array_like(self, xp):
     @testing.numpy_cupy_array_equal()
     def test_tril_nega(self, xp, dtype):
         m = testing.shaped_arange(self.shape, xp, dtype)
-        return xp.tril(m, -1)
+        return xp.tril(m, k=-1)
 
     @testing.for_all_dtypes(no_complex=True)
     @testing.numpy_cupy_array_equal()
     def test_tril_posi(self, xp, dtype):
         m = testing.shaped_arange(self.shape, xp, dtype)
-        return xp.tril(m, 1)
+        return xp.tril(m, k=1)
 
     @testing.for_all_dtypes(no_complex=True)
     @testing.numpy_cupy_array_equal()