Merge pull request #886 from IntelPython/master

Merge master to gold

Author: Alexander-Makaryev

dpnp/config.py

@@ -43,7 +43,12 @@
 Explicitly use NumPy.ndarray as return type for creation functions
 '''
 
-__DPNP_DPCTL_AVAILABLE__ = False
+__DPNP_OUTPUT_DPCTL__ = int(os.getenv('DPNP_OUTPUT_DPCTL', 0))
 '''
-Availability of the DPCtl package in the environment
+Explicitly use DPCtl package container as return type for creation functions
+'''
+
+__DPNP_OUTPUT_DPCTL_DEFAULT_SHARED__ = int(os.getenv('DPNP_OUTPUT_DPCTL_DEFAULT_SHARED', 0))
+'''
+Explicitly use SYCL shared memory parameter in DPCtl array constructor for creation functions
 '''

dpnp/dpnp_algo/dpnp_algo.pyx

@@ -36,6 +36,8 @@ from libc.time cimport time, time_t
 import dpnp
 import dpnp.config as config
 import dpnp.dpnp_utils as utils_py
+from dpnp.dpnp_container import container_copy
+
 import numpy
 
 cimport cpython
@@ -118,7 +120,7 @@ cpdef utils.dpnp_descriptor dpnp_array(object obj, object dtype=None):
         else:
             result = utils_py.create_output_descriptor_py(obj_shape, obj_dtype, None)
 
-    utils.container_copy(result.get_pyobj(), obj)
+    container_copy(result.get_pyobj(), obj)
 
     return result
 

dpnp/dpnp_container.py

@@ -40,21 +40,18 @@
 import numpy
 
 
-try:
-    """
-    Detect DPCtl availability to use data container
-    """
-    import dpctl.tensor as dpctl
-
-    config.__DPNP_DPCTL_AVAILABLE__ = True
-
-except ImportError:
-    """
-    No DPCtl data container available
-    """
-    config.__DPNP_DPCTL_AVAILABLE__ = False
+if config.__DPNP_OUTPUT_DPCTL__:
+    try:
+        """
+        Detect DPCtl availability to use data container
+        """
+        import dpctl.tensor as dpctl
 
-# config.__DPNP_DPCTL_AVAILABLE__ = False
+    except ImportError:
+        """
+        No DPCtl data container available
+        """
+        config.__DPNP_OUTPUT_DPCTL__ = 0
 
 
 __all__ = [
@@ -67,11 +64,38 @@ def create_output_container(shape, type):
         """ Create NumPy ndarray """
         # TODO need to use "buffer=" parameter to use SYCL aware memory
         result = numpy.ndarray(shape, dtype=type)
-    elif config.__DPNP_DPCTL_AVAILABLE__:
+    elif config.__DPNP_OUTPUT_DPCTL__:
         """ Create DPCTL array """
-        result = dpctl.usm_ndarray(shape, dtype=numpy.dtype(type).name)
+        if config.__DPNP_OUTPUT_DPCTL_DEFAULT_SHARED__:
+            """
+            From DPCtrl documentation:
+            'buffer can be strings ('device'|'shared'|'host' to allocate new memory)'
+            """
+            result = dpctl.usm_ndarray(shape, dtype=numpy.dtype(type).name, buffer='shared')
+        else:
+            """
+            Can't pass 'None' as buffer= parameter to allow DPCtrl uses it's default
+            """
+            result = dpctl.usm_ndarray(shape, dtype=numpy.dtype(type).name)
     else:
         """ Create DPNP array """
         result = dparray(shape, dtype=type)
 
     return result    
+
+
+def container_copy(dst_obj, src_obj, dst_idx = 0):
+    """
+    Copy values to `dst` by iterating element by element in `input_obj`
+    """
+
+    for elem_value in src_obj:
+        if isinstance(elem_value, (list, tuple)):
+            dst_idx = container_copy(dst_obj, elem_value, dst_idx)
+        elif issubclass(type(elem_value), (numpy.ndarray, dparray)):
+            dst_idx = container_copy(dst_obj, elem_value, dst_idx)
+        else:
+            dst_obj.flat[dst_idx] = elem_value
+            dst_idx += 1
+
+    return dst_idx

dpnp/dpnp_iface_arraycreation.py

@@ -195,7 +195,7 @@ def array(x1, dtype=None, copy=True, order='C', subok=False, ndmin=0, like=None)
 
     if not dpnp.is_type_supported(dtype) and dtype is not None:
         pass
-    elif config.__DPNP_DPCTL_AVAILABLE__:
+    elif config.__DPNP_OUTPUT_DPCTL__:
         # TODO this is workaround becasue
         # usm_array has no element wise assignment (aka []) and
         # has no "flat" property and

dpnp/dpnp_utils/dpnp_algo_utils.pxd

@@ -98,10 +98,6 @@ cpdef find_common_type(object x1_obj, object x2_obj)
 Find common type of 2 input objects
 """
 
-cdef long container_copy(object dst_obj, object src_obj, size_t dst_idx=*) except -1
-"""
-Copy values to `dst` by iterating element by element in `input_obj`
-"""
 
 cpdef long _get_linear_index(key, tuple shape, int ndim)
 """

dpnp/dpnp_utils/dpnp_algo_utils.pyx

@@ -35,12 +35,10 @@ import numpy
 import dpnp.config as config
 import dpnp
 from dpnp.dpnp_algo cimport dpnp_DPNPFuncType_to_dtype, dpnp_dtype_to_DPNPFuncType, get_dpnp_function_ptr
-from dpnp.dpnp_container import create_output_container
+from dpnp.dpnp_container import create_output_container, container_copy
 from libcpp cimport bool as cpp_bool
 from libcpp.complex cimport complex as cpp_complex
 
-from dpnp.dparray import dparray
-
 cimport cpython
 cimport cython
 cimport numpy
@@ -194,21 +192,6 @@ cpdef dpnp_descriptor create_output_descriptor_py(shape_type_c output_shape, obj
     return create_output_descriptor(output_shape, c_type, requested_out)
 
 
-cdef long container_copy(object dst_obj, object src_obj, size_t dst_idx = 0) except -1:
-    cdef elem_dtype = dst_obj.dtype
-
-    for elem_value in src_obj:
-        if isinstance(elem_value, (list, tuple)):
-            dst_idx = container_copy(dst_obj, elem_value, dst_idx)
-        elif issubclass(type(elem_value), (numpy.ndarray, dparray)):
-            dst_idx = container_copy(dst_obj, elem_value, dst_idx)
-        else:
-            dst_obj.flat[dst_idx] = elem_value
-            dst_idx += 1
-
-    return dst_idx
-
-
 cpdef tuple get_axis_indeces(idx, shape):
     """
     Compute axis indices of an element in array from array linear index

tests/skipped_tests_gpu.tbl

@@ -1,3 +1,4 @@
+tests/third_party/intel/test_zero_copy_test1.py::test_dpnp_interaction_with_dpctl_memory
 tests/test_arraymanipulation.py::TestHstack::test_generator
 tests/test_arraymanipulation.py::TestVstack::test_generator
 tests/test_fft.py::test_fft[complex128]