using container.flat instead explicit datatype casting in dpnp_array() (#863)

Author: shssf

dpnp/dpnp_algo/dpnp_algo.pyx

@@ -108,7 +108,7 @@ cpdef utils.dpnp_descriptor dpnp_array(object obj, object dtype=None):
     if not cpython.PySequence_Check(obj):
         raise TypeError(f"DPNP dpnp_array(): Unsupported non-sequence obj={type(obj)}")
 
-    obj_shape, elem_dtype = utils.get_shape_dtype(obj)
+    obj_shape, obj_dtype = utils.get_shape_dtype(obj)
     if dtype is not None:
         """ Set type from parameter. result might be empty array """
         result = utils_py.create_output_descriptor_py(obj_shape, dtype, None)
@@ -117,7 +117,7 @@ cpdef utils.dpnp_descriptor dpnp_array(object obj, object dtype=None):
             """ Empty object (ex. empty list) and no type provided """
             result = utils_py.create_output_descriptor_py(obj_shape, None, None)
         else:
-            result = utils_py.create_output_descriptor_py(obj_shape, elem_dtype, None)
+            result = utils_py.create_output_descriptor_py(obj_shape, obj_dtype, None)
 
     utils.container_copy(result.get_pyobj(), obj)
 

dpnp/dpnp_utils/dpnp_algo_utils.pxd

@@ -99,7 +99,7 @@ cpdef find_common_type(object x1_obj, object x2_obj)
 Find common type of 2 input objects
 """
 
-cdef long container_copy(dparray dst, input_obj, size_t dst_idx=*) except -1
+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`
 """

dpnp/dpnp_utils/dpnp_algo_utils.pyx

@@ -175,32 +175,16 @@ cpdef dp2nd_array(arr):
     """Convert dparray to ndarray"""
     return dpnp.asnumpy(arr) if isinstance(arr, dparray) else arr
 
-cdef long container_copy(dparray dst, input_obj, size_t dst_idx=0) except -1:
-    cdef elem_dtype = dst.dtype
+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 input_obj:
+    for elem_value in src_obj:
         if isinstance(elem_value, (list, tuple)):
-            dst_idx = container_copy(dst, elem_value, dst_idx)
+            dst_idx = container_copy(dst_obj, elem_value, dst_idx)
         elif issubclass(type(elem_value), (numpy.ndarray, dparray)):
-            dst_idx = container_copy(dst, elem_value, dst_idx)
+            dst_idx = container_copy(dst_obj, elem_value, dst_idx)
         else:
-            if elem_dtype == numpy.float64:
-                ( < double * > dst.get_data())[dst_idx] = elem_value
-            elif elem_dtype == numpy.float32:
-                ( < float * > dst.get_data())[dst_idx] = elem_value
-            elif elem_dtype == numpy.int64:
-                ( < long * > dst.get_data())[dst_idx] = elem_value
-            elif elem_dtype == numpy.int32:
-                ( < int * > dst.get_data())[dst_idx] = elem_value
-            elif elem_dtype == numpy.bool_ or elem_dtype == numpy.bool:
-                (< cpp_bool * > dst.get_data())[dst_idx] = elem_value
-            elif elem_dtype == numpy.complex64:
-                (< cpp_complex[float] * > dst.get_data())[dst_idx] = elem_value
-            elif elem_dtype == numpy.complex128:
-                (< cpp_complex[double] * > dst.get_data())[dst_idx] = elem_value
-            else:
-                checker_throw_type_error("container_copy", elem_dtype)
-
+            dst_obj.flat[dst_idx] = elem_value
             dst_idx += 1
 
     return dst_idx