Implemented ndarray flag helper class

Author: ndgrigorian

dpctl/tensor/_copy_utils.py

@@ -261,18 +261,18 @@ def copy(usm_ary, order="K"):
     elif order == "F":
         copy_order = order
     elif order == "A":
-        if usm_ary.flags & 2:
+        if usm_ary.flags.f_contiguous:
             copy_order = "F"
     elif order == "K":
-        if usm_ary.flags & 2:
+        if usm_ary.flags.f_contiguous:
             copy_order = "F"
     else:
         raise ValueError(
             "Unrecognized value of the order keyword. "
             "Recognized values are 'A', 'C', 'F', or 'K'"
         )
-    c_contig = usm_ary.flags & 1
-    f_contig = usm_ary.flags & 2
+    c_contig = usm_ary.flags.c_contiguous
+    f_contig = usm_ary.flags.f_contiguous
     R = dpt.usm_ndarray(
         usm_ary.shape,
         dtype=usm_ary.dtype,
@@ -325,8 +325,8 @@ def astype(usm_ary, newdtype, order="K", casting="unsafe", copy=True):
                 ary_dtype, newdtype, casting
             )
         )
-    c_contig = usm_ary.flags & 1
-    f_contig = usm_ary.flags & 2
+    c_contig = usm_ary.flags.c_contiguous
+    f_contig = usm_ary.flags.f_contiguous
     needs_copy = copy or not (ary_dtype == target_dtype)
     if not needs_copy and (order != "K"):
         needs_copy = (c_contig and order not in ["A", "C"]) or (
@@ -339,10 +339,10 @@ def astype(usm_ary, newdtype, order="K", casting="unsafe", copy=True):
         elif order == "F":
             copy_order = order
         elif order == "A":
-            if usm_ary.flags & 2:
+            if usm_ary.flags.f_contiguous:
                 copy_order = "F"
         elif order == "K":
-            if usm_ary.flags & 2:
+            if usm_ary.flags.f_contiguous:
                 copy_order = "F"
         else:
             raise ValueError(

dpctl/tensor/_ctors.py

@@ -133,9 +133,9 @@ def _asarray_from_usm_ndarray(
     #    sycl_queue is unchanged
     can_zero_copy = can_zero_copy and copy_q is usm_ndary.sycl_queue
     #    order is unchanged
-    c_contig = usm_ndary.flags & 1
-    f_contig = usm_ndary.flags & 2
-    fc_contig = usm_ndary.flags & 3
+    c_contig = usm_ndary.flags.c_contiguous
+    f_contig = usm_ndary.flags.f_contiguous
+    fc_contig = usm_ndary.flags.forc
     if can_zero_copy:
         if order == "C" and c_contig:
             pass
@@ -1130,7 +1130,7 @@ def tril(X, k=0):
     k = operator.index(k)
 
     # F_CONTIGUOUS = 2
-    order = "F" if (X.flags & 2) else "C"
+    order = "F" if (X.flags.f_contiguous) else "C"
 
     shape = X.shape
     nd = X.ndim
@@ -1171,7 +1171,7 @@ def triu(X, k=0):
     k = operator.index(k)
 
     # F_CONTIGUOUS = 2
-    order = "F" if (X.flags & 2) else "C"
+    order = "F" if (X.flags.f_contiguous) else "C"
 
     shape = X.shape
     nd = X.ndim

dpctl/tensor/_flags.pyx

@@ -0,0 +1,85 @@
+#                       Data Parallel Control (dpctl)
+#
+#  Copyright 2020-2022 Intel Corporation
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+
+# distutils: language = c++
+# cython: language_level=3
+# cython: linetrace=True
+
+from dpctl.tensor._usmarray cimport (
+    USM_ARRAY_C_CONTIGUOUS,
+    USM_ARRAY_F_CONTIGUOUS,
+    USM_ARRAY_WRITEABLE,
+)
+
+
+class Flags:
+
+    def __init__(self, arr, flags):
+        self.arr_ = arr
+        self.flags_ = flags
+
+    @property
+    def flags(self):
+        return self.flags_
+
+    @property
+    def c_contiguous(self):
+        return ((self.flags_ & USM_ARRAY_C_CONTIGUOUS)
+                == USM_ARRAY_C_CONTIGUOUS)
+
+    @property
+    def f_contiguous(self):
+        return ((self.flags_ & USM_ARRAY_F_CONTIGUOUS)
+                == USM_ARRAY_F_CONTIGUOUS)
+
+    @property
+    def writable(self):
+        return False if ((self.flags & USM_ARRAY_WRITEABLE)
+                        == USM_ARRAY_WRITEABLE) else True
+
+    @property
+    def forc(self):
+        return True if (((self.flags_ & USM_ARRAY_F_CONTIGUOUS)
+                        == USM_ARRAY_F_CONTIGUOUS)
+                        or ((self.flags_ & USM_ARRAY_C_CONTIGUOUS)
+                        == USM_ARRAY_C_CONTIGUOUS)) else False
+
+    @property
+    def fnc(self):
+        return True if (((self.flags_ & USM_ARRAY_F_CONTIGUOUS)
+                        == USM_ARRAY_F_CONTIGUOUS)
+                        and not ((self.flags_ & USM_ARRAY_C_CONTIGUOUS)
+                        == USM_ARRAY_C_CONTIGUOUS)) else False
+
+    @property
+    def contiguous(self):
+        return self.forc
+
+    def __getitem__(self, name):
+        if name in ["C_CONTIGUOUS", "C"]:
+            return self.c_contiguous
+        elif name in ["F_CONTIGUOUS", "F"]:
+            return self.f_contiguous
+        elif name == "WRITABLE":
+            return self.writable
+        elif name == "CONTIGUOUS":
+            return self.forc
+
+    def __repr__(self):
+        out = []
+        for name in "C_CONTIGUOUS", "F_CONTIGUOUS", "WRITABLE":
+            out.append("  {} : {}".format(name, self[name]))
+        return '\n'.join(out)

dpctl/tensor/_usmarray.pyx

@@ -33,6 +33,7 @@ from cpython.tuple cimport PyTuple_New, PyTuple_SetItem
 cimport dpctl as c_dpctl
 cimport dpctl.memory as c_dpmem
 cimport dpctl.tensor._dlpack as c_dlpack
+import dpctl.tensor._flags as _flags
 
 include "_stride_utils.pxi"
 include "_types.pxi"
@@ -503,9 +504,9 @@ cdef class usm_ndarray:
     @property
     def flags(self):
         """
-        Currently returns integer whose bits correspond to the flags.
+        Returns dpctl.tensor._flags object.
         """
-        return self.flags_
+        return _flags.Flags(self, self.flags_)
 
     @property
     def usm_type(self):
@@ -663,7 +664,7 @@ cdef class usm_ndarray:
                 strides=self.strides,
                 offset=self.get_offset()
             )
-            res.flags_ = self.flags
+            res.flags_ = self.flags.flags
             return res
         else:
             nbytes = self.usm_data.nbytes
@@ -678,7 +679,7 @@ cdef class usm_ndarray:
                 strides=self.strides,
                 offset=self.get_offset()
             )
-            res.flags_ = self.flags
+            res.flags_ = self.flags.flags
             return res
 
     def _set_namespace(self, mod):

dpctl/tests/test_usm_ndarray_ctor.py

@@ -59,13 +59,13 @@ def test_allocate_usm_ndarray(shape, usm_type):
 
 
 def test_usm_ndarray_flags():
-    assert dpt.usm_ndarray((5,)).flags == 3
-    assert dpt.usm_ndarray((5, 2)).flags == 1
-    assert dpt.usm_ndarray((5, 2), order="F").flags == 2
-    assert dpt.usm_ndarray((5, 1, 2), order="F").flags == 2
-    assert dpt.usm_ndarray((5, 1, 2), strides=(2, 0, 1)).flags == 1
-    assert dpt.usm_ndarray((5, 1, 2), strides=(1, 0, 5)).flags == 2
-    assert dpt.usm_ndarray((5, 1, 1), strides=(1, 0, 1)).flags == 3
+    assert dpt.usm_ndarray((5,)).flags.flags == 3
+    assert dpt.usm_ndarray((5, 2)).flags.flags == 1
+    assert dpt.usm_ndarray((5, 2), order="F").flags.flags == 2
+    assert dpt.usm_ndarray((5, 1, 2), order="F").flags.flags == 2
+    assert dpt.usm_ndarray((5, 1, 2), strides=(2, 0, 1)).flags.flags == 1
+    assert dpt.usm_ndarray((5, 1, 2), strides=(1, 0, 5)).flags.flags == 2
+    assert dpt.usm_ndarray((5, 1, 1), strides=(1, 0, 1)).flags.flags == 3
 
 
 @pytest.mark.parametrize(
@@ -326,7 +326,7 @@ def test_usm_ndarray_props():
     Xusm = dpt.usm_ndarray((10, 5), dtype="c16", order="F")
     Xusm.ndim
     repr(Xusm)
-    Xusm.flags
+    Xusm.flags.flags
     Xusm.__sycl_usm_array_interface__
     Xusm.device
     Xusm.strides
@@ -465,7 +465,7 @@ def test_pyx_capi_get_flags():
         fn_restype=ctypes.c_int,
     )
     flags = get_flags_fn(X)
-    assert type(flags) is int and flags == X.flags
+    assert type(flags) is int and flags == X.flags.flags
 
 
 def test_pyx_capi_get_offset():
@@ -753,7 +753,7 @@ def relaxed_strides_equal(st1, st2, sh):
     X.shape = sh_f
     assert X.shape == sh_f
     assert relaxed_strides_equal(X.strides, cc_strides(sh_f), sh_f)
-    assert X.flags & 1, "reshaped array expected to be C-contiguous"
+    assert X.flags.c_contiguous, "reshaped array expected to be C-contiguous"
 
     sh_s = (
         2,
@@ -919,7 +919,7 @@ def test_reshape():
 
     X = dpt.usm_ndarray((1,))
     Y = dpt.reshape(X, X.shape)
-    assert Y.flags == X.flags
+    assert Y.flags.flags == X.flags.flags
 
     A = dpt.usm_ndarray((0,), "i4")
     A1 = dpt.reshape(A, (0,))
@@ -1402,7 +1402,7 @@ def test_triu_order_k(order, k):
     Xnp = np.arange(np.prod(shape), dtype="int").reshape(shape, order=order)
     Ynp = np.triu(Xnp, k)
     assert Y.dtype == Ynp.dtype
-    assert X.flags == Y.flags
+    assert X.flags.flags == Y.flags.flags
     assert np.array_equal(Ynp, dpt.asnumpy(Y))
 
 
@@ -1423,7 +1423,7 @@ def test_tril_order_k(order, k):
     Xnp = np.arange(np.prod(shape), dtype="int").reshape(shape, order=order)
     Ynp = np.tril(Xnp, k)
     assert Y.dtype == Ynp.dtype
-    assert X.flags == Y.flags
+    assert X.flags.flags == Y.flags.flags
     assert np.array_equal(Ynp, dpt.asnumpy(Y))