remove C kernel imports to cython

Author: shssf

dpnp/backend.pxd

@@ -120,16 +120,6 @@ cdef extern from "backend/backend_iface.hpp":
     void custom_elemwise_tan_c[_DataType_input, _DataType_output](void * array1, void * result1, size_t size)
     void custom_elemwise_tanh_c[_DataType_input, _DataType_output](void * array1, void * result1, size_t size)
 
-    # Mathematical part
-    void custom_elemwise_add_c[_DataType_input1, _DataType_input2, _DataType_output](void * array1, void * array2, void * result1, size_t size)
-    void custom_elemwise_arctan2_c[_DataType_input1, _DataType_input2, _DataType_output](void * array1, void * array2, void * result1, size_t size)
-    void custom_elemwise_divide_c[_DataType_input1, _DataType_input2, _DataType_output](void * array1, void * array2, void * result1, size_t size)
-    void custom_elemwise_hypot_c[_DataType_input1, _DataType_input2, _DataType_output](void * array1, void * array2, void * result1, size_t size)
-    void custom_elemwise_multiply_c[_DataType_input1, _DataType_input2, _DataType_output](void * array1, void * array2, void * result1, size_t size)
-    void custom_elemwise_power_c[_DataType_input1, _DataType_input2, _DataType_output](void * array1, void * array2, void * result1, size_t size)
-    void custom_elemwise_subtract_c[_DataType_input1, _DataType_input2, _DataType_output](void * array1, void * array2, void * result1, size_t size)
-    void custom_sum_c[_DataType](void * array, void * result, size_t size)
-
     # array manipulation routines
     void custom_elemwise_transpose_c[_DataType](void * array1_in, dparray_shape_type & input_shape, dparray_shape_type & result_shape, dparray_shape_type & permute_axes, void * result1, size_t size)
 

dpnp/backend_statistics.pyx

@@ -36,7 +36,7 @@ and the rest of the library
 import dpnp
 import numpy
 import dpnp
-from dpnp.dpnp_utils cimport checker_throw_type_error, normalize_axis
+from dpnp.dpnp_utils cimport *
 from dpnp.backend cimport *
 
 
@@ -50,23 +50,13 @@ __all__ += [
 ]
 
 
-cpdef dpnp_average(dparray array):
-    call_type = array.dtype
-    return_type = numpy.float32 if call_type == numpy.float32 else numpy.float64
-    cdef dparray result = dparray((1), dtype=call_type)
+cpdef dpnp_average(dparray x1):
+    array_sum = dpnp_sum(x1)
 
-    if call_type == numpy.float64:
-        custom_sum_c[double](array.get_data(), result.get_data(), array.size)
-    elif call_type == numpy.float32:
-        custom_sum_c[float](array.get_data(), result.get_data(), array.size)
-    elif call_type == numpy.int64:
-        custom_sum_c[long](array.get_data(), result.get_data(), array.size)
-    elif call_type == numpy.int32:
-        custom_sum_c[int](array.get_data(), result.get_data(), array.size)
-    else:
-        checker_throw_type_error("dpnp_average", call_type)
+    """ Numpy interface inconsistency """
+    return_type = numpy.float32 if (x1.dtype == numpy.float32) else numpy.float64
 
-    return return_type(result[0] / array.size)
+    return (return_type(array_sum / x1.size))
 
 
 cpdef dparray dpnp_cov(dparray array1):