Release 0.11.2

CHANGELOG.md

@@ -4,6 +4,11 @@ All notable changes to this project will be documented in this file.
 The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
 and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
 
+## [0.11.2] - 11/xx/2021
+
+## Fixed
+- Fix/gh #649 transpose (#653)
+
 ## [0.11.1] - 11/10/2021
 
 ### Changed

dpctl/tensor/_usmarray.pyx

@@ -1014,31 +1014,62 @@ cdef usm_ndarray _real_view(usm_ndarray ary):
     """
     View into real parts of a complex type array
     """
-    cdef usm_ndarray r = ary._clone()
+    cdef int r_typenum_ = -1
+    cdef usm_ndarray r = None
+    cdef Py_ssize_t offset_elems = 0
+
     if (ary.typenum_ == UAR_CFLOAT):
-        r.typenum_ = UAR_FLOAT
+        r_typenum_ = UAR_FLOAT
     elif (ary.typenum_ == UAR_CDOUBLE):
-        r.typenum_ = UAR_DOUBLE
+        r_typenum_ = UAR_DOUBLE
     else:
         raise InternalUSMArrayError(
             "_real_view call on array of non-complex type.")
+
+    offset_elems = ary.get_offset() * 2
+    r = usm_ndarray.__new__(
+        usm_ndarray,
+        _make_int_tuple(ary.nd_, ary.shape_),
+        dtype=_make_typestr(r_typenum_),
+        strides=tuple(2 * si for si in ary.strides),
+        buffer=ary.base_,
+        offset=offset_elems,
+        order=('C' if (ary.flags_ & USM_ARRAY_C_CONTIGUOUS) else 'F')
+    )
+    r.flags_ = ary.flags_
+    r.array_namespace_ = ary.array_namespace_
     return r
 
 
 cdef usm_ndarray _imag_view(usm_ndarray ary):
     """
     View into imaginary parts of a complex type array
     """
-    cdef usm_ndarray r = ary._clone()
+    cdef int r_typenum_ = -1
+    cdef usm_ndarray r = None
+    cdef Py_ssize_t offset_elems = 0
+
     if (ary.typenum_ == UAR_CFLOAT):
-        r.typenum_ = UAR_FLOAT
+        r_typenum_ = UAR_FLOAT
     elif (ary.typenum_ == UAR_CDOUBLE):
-        r.typenum_ = UAR_DOUBLE
+        r_typenum_ = UAR_DOUBLE
     else:
         raise InternalUSMArrayError(
-            "_real_view call on array of non-complex type.")
+            "_imag_view call on array of non-complex type.")
+
     # displace pointer to imaginary part
-    r.data_ = r.data_ + type_bytesize(r.typenum_)
+    offset_elems = 2 * ary.get_offset() + 1
+    r = usm_ndarray.__new__(
+        usm_ndarray,
+        _make_int_tuple(ary.nd_, ary.shape_),
+        dtype=_make_typestr(r_typenum_),
+        strides=tuple(2 * si for si in ary.strides),
+        buffer=ary.base_,
+        offset=offset_elems,
+        order=('C' if (ary.flags_ & USM_ARRAY_C_CONTIGUOUS) else 'F')
+    )
+    r.flags_ = ary.flags_
+    r.array_namespace_ = ary.array_namespace_
     return r
 
 
@@ -1054,7 +1085,8 @@ cdef usm_ndarray _transpose(usm_ndarray ary):
             _make_reversed_int_tuple(ary.nd_, ary.strides_)
             if (ary.strides_) else None),
         buffer=ary.base_,
-        order=('F' if (ary.flags_ & USM_ARRAY_C_CONTIGUOUS) else 'C')
+        order=('F' if (ary.flags_ & USM_ARRAY_C_CONTIGUOUS) else 'C'),
+        offset=ary.get_offset()
     )
     r.flags_ |= (ary.flags_ & USM_ARRAY_WRITEABLE)
     return r

dpctl/tests/test_usm_ndarray_ctor.py

@@ -841,3 +841,25 @@ def test_reshape():
         dpt.reshape(Z, Z.shape, order="invalid")
     W = dpt.reshape(Z, (-1,), order="C")
     assert W.shape == (Z.size,)
+
+
+def test_transpose():
+    n, m = 2, 3
+    X = dpt.usm_ndarray((n, m), "f4")
+    Xnp = np.arange(n * m, dtype="f4").reshape((n, m))
+    X[:] = Xnp
+    assert np.array_equal(dpt.to_numpy(X.T), Xnp.T)
+    assert np.array_equal(dpt.to_numpy(X[1:].T), Xnp[1:].T)
+
+
+def test_real_imag_views():
+    n, m = 2, 3
+    X = dpt.usm_ndarray((n, m), "c8")
+    Xnp_r = np.arange(n * m, dtype="f4").reshape((n, m))
+    Xnp_i = np.arange(n * m, 2 * n * m, dtype="f4").reshape((n, m))
+    Xnp = Xnp_r + 1j * Xnp_i
+    X[:] = Xnp
+    assert np.array_equal(dpt.to_numpy(X.real), Xnp.real)
+    assert np.array_equal(dpt.to_numpy(X.imag), Xnp.imag)
+    assert np.array_equal(dpt.to_numpy(X[1:].real), Xnp[1:].real)
+    assert np.array_equal(dpt.to_numpy(X[1:].imag), Xnp[1:].imag)