Add copy_when_nondefault_queue=False to call of get_dpnp_descriptor

Author: densmirn

dpnp/dpnp_algo/dpnp_algo_manipulation.pyx

@@ -227,7 +227,8 @@ cpdef utils.dpnp_descriptor dpnp_reshape(utils.dpnp_descriptor array1, newshape,
                                                order=order,
                                                device=array1_obj.sycl_device,
                                                usm_type=array1_obj.usm_type,
-                                               sycl_queue=array1_obj.sycl_queue))
+                                               sycl_queue=array1_obj.sycl_queue),
+                                    copy_when_nondefault_queue=False)
 
 
 cpdef utils.dpnp_descriptor dpnp_transpose(utils.dpnp_descriptor array1, axes=None):

dpnp/dpnp_algo/dpnp_algo_statistics.pyx

@@ -570,7 +570,8 @@ cpdef utils.dpnp_descriptor dpnp_min(utils.dpnp_descriptor x1, axis):
 
 cpdef utils.dpnp_descriptor dpnp_nanvar(utils.dpnp_descriptor arr, ddof):
     # dpnp_isnan does not support USM array as input in comparison to dpnp.isnan
-    cdef utils.dpnp_descriptor mask_arr = dpnp.get_dpnp_descriptor(dpnp.isnan(arr.get_pyobj()))
+    cdef utils.dpnp_descriptor mask_arr = dpnp.get_dpnp_descriptor(dpnp.isnan(arr.get_pyobj()),
+                                                                   copy_when_nondefault_queue=False)
     n = dpnp.count_nonzero(mask_arr.get_pyobj())
     res_size = int(arr.size - n)
     cdef DPNPFuncType param1_type = dpnp_dtype_to_DPNPFuncType(arr.dtype)

dpnp/dpnp_iface_arraycreation.py

@@ -431,7 +431,7 @@ def diag(x1, k=0):
 
     """
 
-    x1_desc = dpnp.get_dpnp_descriptor(x1)
+    x1_desc = dpnp.get_dpnp_descriptor(x1, copy_when_nondefault_queue=False)
     if x1_desc:
         if not isinstance(k, int):
             pass
@@ -465,10 +465,10 @@ def diagflat(x1, k=0):
 
     """
 
-    x1_desc = dpnp.get_dpnp_descriptor(x1)
+    x1_desc = dpnp.get_dpnp_descriptor(x1, copy_when_nondefault_queue=False)
     if x1_desc:
         input_ravel = dpnp.ravel(x1)
-        input_ravel_desc = dpnp.get_dpnp_descriptor(input_ravel)
+        input_ravel_desc = dpnp.get_dpnp_descriptor(input_ravel, copy_when_nondefault_queue=False)
 
         return dpnp_diag(input_ravel_desc, k).get_pyobj()
 
@@ -1138,7 +1138,7 @@ def ones_like(x1, dtype=None, order='C', subok=False, shape=None):
 
     """
 
-    x1_desc = dpnp.get_dpnp_descriptor(x1)
+    x1_desc = dpnp.get_dpnp_descriptor(x1, copy_when_nondefault_queue=False)
     if x1_desc:
         if order not in ('C', 'c', None):
             pass
@@ -1164,7 +1164,7 @@ def ptp(arr, axis=None, out=None, keepdims=numpy._NoValue):
     Input array is supported as :obj:`dpnp.ndarray`.
     Parameters ``out`` and ``keepdims`` are supported only with default values.
     """
-    arr_desc = dpnp.get_dpnp_descriptor(arr)
+    arr_desc = dpnp.get_dpnp_descriptor(arr, copy_when_nondefault_queue=False)
     if not arr_desc:
         pass
     elif axis is not None and not isinstance(axis, int):
@@ -1194,7 +1194,7 @@ def trace(x1, offset=0, axis1=0, axis2=1, dtype=None, out=None):
        Parameters ``axis1``, ``axis2``, ``out`` and ``dtype`` are supported only with default values.
        """
 
-    x1_desc = dpnp.get_dpnp_descriptor(x1)
+    x1_desc = dpnp.get_dpnp_descriptor(x1, copy_when_nondefault_queue=False)
     if x1_desc:
         if x1_desc.size == 0:
             pass
@@ -1271,7 +1271,7 @@ def tril(x1, k=0):
 
     """
 
-    x1_desc = dpnp.get_dpnp_descriptor(x1)
+    x1_desc = dpnp.get_dpnp_descriptor(x1, copy_when_nondefault_queue=False)
     if x1_desc:
         if not isinstance(k, int):
             pass
@@ -1301,7 +1301,7 @@ def triu(x1, k=0):
 
     """
 
-    x1_desc = dpnp.get_dpnp_descriptor(x1)
+    x1_desc = dpnp.get_dpnp_descriptor(x1, copy_when_nondefault_queue=False)
     if x1_desc:
         if not isinstance(k, int):
             pass
@@ -1340,7 +1340,7 @@ def vander(x1, N=None, increasing=False):
            [  1,   5,  25, 125]])
     """
 
-    x1_desc = dpnp.get_dpnp_descriptor(x1)
+    x1_desc = dpnp.get_dpnp_descriptor(x1, copy_when_nondefault_queue=False)
     if x1_desc:
         if x1.ndim != 1:
             pass
@@ -1425,7 +1425,7 @@ def zeros_like(x1, dtype=None, order='C', subok=False, shape=None):
 
     """
 
-    x1_desc = dpnp.get_dpnp_descriptor(x1)
+    x1_desc = dpnp.get_dpnp_descriptor(x1, copy_when_nondefault_queue=False)
     if x1_desc:
         if order not in ('C', 'c', None):
             pass

dpnp/dpnp_iface_bitwise.py

@@ -63,10 +63,10 @@ def _check_nd_call(origin_func, dpnp_func, x1, x2, dtype=None, out=None, where=T
 
     x1_is_scalar = dpnp.isscalar(x1)
     x2_is_scalar = dpnp.isscalar(x2)
-    x1_desc = dpnp.get_dpnp_descriptor(x1)
-    x2_desc = dpnp.get_dpnp_descriptor(x2)
-    x1_desc = dpnp.get_dpnp_descriptor(x1, copy_when_strides=False)
-    x2_desc = dpnp.get_dpnp_descriptor(x2, copy_when_strides=False)
+    x1_desc = dpnp.get_dpnp_descriptor(x1, copy_when_nondefault_queue=False)
+    x2_desc = dpnp.get_dpnp_descriptor(x2, copy_when_nondefault_queue=False)
+    x1_desc = dpnp.get_dpnp_descriptor(x1, copy_when_strides=False, copy_when_nondefault_queue=False)
+    x2_desc = dpnp.get_dpnp_descriptor(x2, copy_when_strides=False, copy_when_nondefault_queue=False)
 
     if x1_desc and x2_desc and not kwargs:
         if not x1_desc and not x1_is_scalar:
@@ -90,7 +90,7 @@ def _check_nd_call(origin_func, dpnp_func, x1, x2, dtype=None, out=None, where=T
         elif not where:
             pass
         else:
-            out_desc = dpnp.get_dpnp_descriptor(out) if out is not None else None
+            out_desc = dpnp.get_dpnp_descriptor(out, copy_when_nondefault_queue=False) if out is not None else None
             return dpnp_func(x1_desc, x2_desc, dtype, out_desc, where).get_pyobj()
 
     return call_origin(origin_func, x1, x2, dtype=dtype, out=out, where=where, **kwargs)
@@ -228,7 +228,7 @@ def invert(x, **kwargs):
 
     """
 
-    x1_desc = dpnp.get_dpnp_descriptor(x)
+    x1_desc = dpnp.get_dpnp_descriptor(x, copy_when_nondefault_queue=False)
     if x1_desc and not kwargs:
         return dpnp_invert(x1_desc).get_pyobj()
 

dpnp/dpnp_iface_counting.py

@@ -75,7 +75,7 @@ def count_nonzero(x1, axis=None, *, keepdims=False):
     5
 
     """
-    x1_desc = dpnp.get_dpnp_descriptor(x1)
+    x1_desc = dpnp.get_dpnp_descriptor(x1, copy_when_nondefault_queue=False)
     if x1_desc:
         if axis is not None:
             pass

dpnp/dpnp_iface_indexing.py

@@ -81,11 +81,11 @@ def choose(x1, choices, out=None, mode='raise'):
     --------
     :obj:`take_along_axis` : Preferable if choices is an array.
     """
-    x1_desc = dpnp.get_dpnp_descriptor(x1)
+    x1_desc = dpnp.get_dpnp_descriptor(x1, copy_when_nondefault_queue=False)
 
     choices_list = []
     for choice in choices:
-        choices_list.append(dpnp.get_dpnp_descriptor(choice))
+        choices_list.append(dpnp.get_dpnp_descriptor(choice, copy_when_nondefault_queue=False))
 
     if x1_desc:
         if any(not desc for desc in choices_list):
@@ -186,7 +186,7 @@ def diag_indices_from(x1):
 
     """
 
-    x1_desc = dpnp.get_dpnp_descriptor(x1)
+    x1_desc = dpnp.get_dpnp_descriptor(x1, copy_when_nondefault_queue=False)
     if x1_desc:
         # original limitation
         if not x1_desc.ndim >= 2:
@@ -216,7 +216,7 @@ def diagonal(x1, offset=0, axis1=0, axis2=1):
     Otherwise the function will be executed sequentially on CPU.
     """
 
-    x1_desc = dpnp.get_dpnp_descriptor(x1)
+    x1_desc = dpnp.get_dpnp_descriptor(x1, copy_when_nondefault_queue=False)
     if x1_desc:
         if not isinstance(offset, int):
             pass
@@ -248,7 +248,7 @@ def fill_diagonal(x1, val, wrap=False):
     :obj:`dpnp.diag_indices_from` : Return the indices to access the main diagonal of an n-dimensional array.
     """
 
-    x1_desc = dpnp.get_dpnp_descriptor(x1, copy_when_strides=False)
+    x1_desc = dpnp.get_dpnp_descriptor(x1, copy_when_strides=False, copy_when_nondefault_queue=False)
     if x1_desc:
         if not dpnp.isscalar(val):
             pass
@@ -329,7 +329,7 @@ def nonzero(x1):
 
     """
 
-    x1_desc = dpnp.get_dpnp_descriptor(x1)
+    x1_desc = dpnp.get_dpnp_descriptor(x1, copy_when_nondefault_queue=False)
     if x1_desc:
         return dpnp_nonzero(x1_desc)
 
@@ -347,9 +347,9 @@ def place(x1, mask, vals):
     Parameter ``vals`` is supported as 1-D sequence.
     """
 
-    x1_desc = dpnp.get_dpnp_descriptor(x1)
-    mask_desc = dpnp.get_dpnp_descriptor(mask)
-    vals_desc = dpnp.get_dpnp_descriptor(vals)
+    x1_desc = dpnp.get_dpnp_descriptor(x1, copy_when_nondefault_queue=False)
+    mask_desc = dpnp.get_dpnp_descriptor(mask, copy_when_nondefault_queue=False)
+    vals_desc = dpnp.get_dpnp_descriptor(vals, copy_when_nondefault_queue=False)
     if x1_desc and mask_desc and vals_desc:
         return dpnp_place(x1_desc, mask, vals_desc)
 
@@ -367,7 +367,7 @@ def put(x1, ind, v, mode='raise'):
     Not supported parameter mode.
     """
 
-    x1_desc = dpnp.get_dpnp_descriptor(x1, copy_when_strides=False)
+    x1_desc = dpnp.get_dpnp_descriptor(x1, copy_when_strides=False, copy_when_nondefault_queue=False)
     if x1_desc:
         if mode != 'raise':
             pass
@@ -391,9 +391,9 @@ def put_along_axis(x1, indices, values, axis):
     :obj:`take_along_axis` : Take values from the input array by matching 1d index and data slices.
     """
 
-    x1_desc = dpnp.get_dpnp_descriptor(x1)
-    indices_desc = dpnp.get_dpnp_descriptor(indices)
-    values_desc = dpnp.get_dpnp_descriptor(values)
+    x1_desc = dpnp.get_dpnp_descriptor(x1, copy_when_nondefault_queue=False)
+    indices_desc = dpnp.get_dpnp_descriptor(indices, copy_when_nondefault_queue=False)
+    values_desc = dpnp.get_dpnp_descriptor(values, copy_when_nondefault_queue=False)
     if x1_desc and indices_desc and values_desc:
         if x1_desc.ndim != indices_desc.ndim:
             pass
@@ -419,9 +419,9 @@ def putmask(x1, mask, values):
     Input arrays ``arr``, ``mask`` and ``values``  are supported as :obj:`dpnp.ndarray`.
     """
 
-    x1_desc = dpnp.get_dpnp_descriptor(x1, copy_when_strides=False)
-    mask_desc = dpnp.get_dpnp_descriptor(mask)
-    values_desc = dpnp.get_dpnp_descriptor(values)
+    x1_desc = dpnp.get_dpnp_descriptor(x1, copy_when_strides=False, copy_when_nondefault_queue=False)
+    mask_desc = dpnp.get_dpnp_descriptor(mask, copy_when_nondefault_queue=False)
+    values_desc = dpnp.get_dpnp_descriptor(values, copy_when_nondefault_queue=False)
     if x1_desc and mask_desc and values_desc:
         return dpnp_putmask(x1_desc, mask_desc, values_desc)
 
@@ -477,8 +477,8 @@ def take(x1, indices, axis=None, out=None, mode='raise'):
     :obj:`take_along_axis` : Take elements by matching the array and the index arrays.
     """
 
-    x1_desc = dpnp.get_dpnp_descriptor(x1)
-    indices_desc = dpnp.get_dpnp_descriptor(indices)
+    x1_desc = dpnp.get_dpnp_descriptor(x1, copy_when_nondefault_queue=False)
+    indices_desc = dpnp.get_dpnp_descriptor(indices, copy_when_nondefault_queue=False)
     if x1_desc and indices_desc:
         if axis is not None:
             pass
@@ -503,8 +503,8 @@ def take_along_axis(x1, indices, axis):
     :obj:`put_along_axis` : Put values into the destination array by matching 1d index and data slices.
     """
 
-    x1_desc = dpnp.get_dpnp_descriptor(x1)
-    indices_desc = dpnp.get_dpnp_descriptor(indices)
+    x1_desc = dpnp.get_dpnp_descriptor(x1, copy_when_nondefault_queue=False)
+    indices_desc = dpnp.get_dpnp_descriptor(indices, copy_when_nondefault_queue=False)
     if x1_desc and indices_desc:
         if x1_desc.ndim != indices_desc.ndim:
             pass
@@ -578,7 +578,7 @@ def tril_indices_from(x1, k=0):
         Diagonal offset (see `tril` for details).
     """
 
-    x1_desc = dpnp.get_dpnp_descriptor(x1)
+    x1_desc = dpnp.get_dpnp_descriptor(x1, copy_when_nondefault_queue=False)
     if x1_desc:
         if isinstance(k, int):
             return dpnp_tril_indices_from(x1_desc, k)
@@ -635,7 +635,7 @@ def triu_indices_from(x1, k=0):
         Diagonal offset (see `tril` for details).
     """
 
-    x1_desc = dpnp.get_dpnp_descriptor(x1)
+    x1_desc = dpnp.get_dpnp_descriptor(x1, copy_when_nondefault_queue=False)
     if x1_desc:
         if isinstance(k, int):
             return dpnp_triu_indices_from(x1_desc, k)

dpnp/dpnp_iface_linearalgebra.py

@@ -91,8 +91,8 @@ def dot(x1, x2, **kwargs):
 
     """
 
-    x1_desc = dpnp.get_dpnp_descriptor(x1, copy_when_strides=False)
-    x2_desc = dpnp.get_dpnp_descriptor(x2, copy_when_strides=False)
+    x1_desc = dpnp.get_dpnp_descriptor(x1, copy_when_strides=False, copy_when_nondefault_queue=False)
+    x2_desc = dpnp.get_dpnp_descriptor(x2, copy_when_strides=False, copy_when_nondefault_queue=False)
     if x1_desc and x2_desc and not kwargs:
         # TODO: remove fallback with scalars when muliply backend func will support strides
         if(x1_desc.ndim == 0 and x2_desc.strides is not None
@@ -183,8 +183,8 @@ def inner(x1, x2, **kwargs):
 
     """
 
-    x1_desc = dpnp.get_dpnp_descriptor(x1)
-    x2_desc = dpnp.get_dpnp_descriptor(x2)
+    x1_desc = dpnp.get_dpnp_descriptor(x1, copy_when_nondefault_queue=False)
+    x2_desc = dpnp.get_dpnp_descriptor(x2, copy_when_nondefault_queue=False)
     if x1_desc and x2_desc and not kwargs:
         return dpnp_inner(x1_desc, x2_desc).get_pyobj()
 
@@ -201,8 +201,8 @@ def kron(x1, x2):
 
     """
 
-    x1_desc = dpnp.get_dpnp_descriptor(x1)
-    x2_desc = dpnp.get_dpnp_descriptor(x2)
+    x1_desc = dpnp.get_dpnp_descriptor(x1, copy_when_nondefault_queue=False)
+    x2_desc = dpnp.get_dpnp_descriptor(x2, copy_when_nondefault_queue=False)
     if x1_desc and x2_desc:
         return dpnp_kron(x1_desc, x2_desc).get_pyobj()
 
@@ -277,7 +277,7 @@ def matmul(x1, x2, out=None, **kwargs):
                 if (array1_size > cost_size) and (array2_size > cost_size):
                     return dpnp_matmul(x1_desc, x2_desc, out)
             else:
-                out_desc = dpnp.get_dpnp_descriptor(out) if out is not None else None
+                out_desc = dpnp.get_dpnp_descriptor(out, copy_when_nondefault_queue=False) if out is not None else None
                 return dpnp_matmul(x1_desc, x2_desc, out_desc).get_pyobj()
 
     return call_origin(numpy.matmul, x1, x2, out=out, **kwargs)
@@ -312,8 +312,8 @@ def outer(x1, x2, **kwargs):
 
     """
 
-    x1_desc = dpnp.get_dpnp_descriptor(x1)
-    x2_desc = dpnp.get_dpnp_descriptor(x2)
+    x1_desc = dpnp.get_dpnp_descriptor(x1, copy_when_nondefault_queue=False)
+    x2_desc = dpnp.get_dpnp_descriptor(x2, copy_when_nondefault_queue=False)
     if x1_desc and x2_desc and not kwargs:
         return dpnp_outer(x1_desc, x2_desc).get_pyobj()
 
@@ -350,8 +350,8 @@ def tensordot(x1, x2, axes=2):
 
     """
 
-    x1_desc = dpnp.get_dpnp_descriptor(x1)
-    x2_desc = dpnp.get_dpnp_descriptor(x2)
+    x1_desc = dpnp.get_dpnp_descriptor(x1, copy_when_nondefault_queue=False)
+    x2_desc = dpnp.get_dpnp_descriptor(x2, copy_when_nondefault_queue=False)
     if x1_desc and x2_desc and (axes == 1):
         return dpnp_tensordot_not_implemented(x1_desc, x2_desc)  # dpnp_matmul
 

dpnp/dpnp_iface_logic.py

@@ -108,7 +108,7 @@ def all(x1, axis=None, out=None, keepdims=False):
 
     """
 
-    x1_desc = dpnp.get_dpnp_descriptor(x1)
+    x1_desc = dpnp.get_dpnp_descriptor(x1, copy_when_nondefault_queue=False)
     if x1_desc:
         if axis is not None:
             pass
@@ -148,8 +148,8 @@ def allclose(x1, x2, rtol=1.e-5, atol=1.e-8, **kwargs):
 
     rtol_is_scalar = dpnp.isscalar(rtol)
     atol_is_scalar = dpnp.isscalar(atol)
-    x1_desc = dpnp.get_dpnp_descriptor(x1)
-    x2_desc = dpnp.get_dpnp_descriptor(x2)
+    x1_desc = dpnp.get_dpnp_descriptor(x1, copy_when_nondefault_queue=False)
+    x2_desc = dpnp.get_dpnp_descriptor(x2, copy_when_nondefault_queue=False)
 
     if x1_desc and x2_desc and not kwargs:
         if not rtol_is_scalar or not atol_is_scalar:
@@ -202,7 +202,7 @@ def any(x1, axis=None, out=None, keepdims=False):
 
     """
 
-    x1_desc = dpnp.get_dpnp_descriptor(x1)
+    x1_desc = dpnp.get_dpnp_descriptor(x1, copy_when_nondefault_queue=False)
     if x1_desc:
         if axis is not None:
             pass