Merge branch 'master' into gold/2021

Author: Alexander-Makaryev

dpnp/__init__.py

@@ -40,7 +40,8 @@
 if "numpy" in sys.modules:
     warnings.warn("\nDPNP: Module NumPy found. Please load DPNP module before NumPy.\n")
 
-from dpnp.dparray import dparray as ndarray
+# from dpnp.dparray import dparray as ndarray
+from dpnp.dpnp_array import dpnp_array as ndarray
 from dpnp.dpnp_iface import *
 from dpnp.dpnp_iface import __all__ as _iface__all__
 from dpnp.dpnp_iface_types import *

dpnp/backend/kernels/dpnp_krnl_random.cpp

@@ -974,7 +974,7 @@ void dpnp_rng_shuffle_c(
         return;
     }
 
-    DPNPC_ptr_adapter<char> result1_ptr(result, size, true, true);
+    DPNPC_ptr_adapter<char> result1_ptr(result, size * itemsize, true, true);
     char* result1 = result1_ptr.get_ptr();
 
     size_t uvec_size = high_dim_size - 1;

dpnp/backend/kernels/dpnp_krnl_statistics.cpp

@@ -760,7 +760,7 @@ void func_map_init_statistics(func_map_t& fmap)
     fmap[DPNPFuncName::DPNP_FN_CORRELATE][eft_DBL][eft_DBL] = {eft_DBL,
                                                                (void*)dpnp_correlate_c<double, double, double>};
 
-    fmap[DPNPFuncName::DPNP_FN_COUNT_NONZERO][eft_BLN][eft_BLN] = {eft_BLN, (void*)dpnp_count_nonzero_c<bool, long>};
+    fmap[DPNPFuncName::DPNP_FN_COUNT_NONZERO][eft_BLN][eft_BLN] = {eft_LNG, (void*)dpnp_count_nonzero_c<bool, long>};
     fmap[DPNPFuncName::DPNP_FN_COUNT_NONZERO][eft_INT][eft_INT] = {eft_LNG, (void*)dpnp_count_nonzero_c<int, long>};
     fmap[DPNPFuncName::DPNP_FN_COUNT_NONZERO][eft_LNG][eft_LNG] = {eft_LNG, (void*)dpnp_count_nonzero_c<long, long>};
     fmap[DPNPFuncName::DPNP_FN_COUNT_NONZERO][eft_FLT][eft_FLT] = {eft_LNG, (void*)dpnp_count_nonzero_c<float, long>};

dpnp/dpnp_algo/dpnp_algo_linearalgebra.pyx

@@ -305,6 +305,6 @@ cpdef utils.dpnp_descriptor dpnp_outer(utils.dpnp_descriptor array1, utils.dpnp_
 
     for idx1 in range(array1.size):
         for idx2 in range(array2.size):
-            result.get_pyobj()[idx1 * array2.size + idx2] = array1.get_pyobj()[idx1] * array2.get_pyobj()[idx2]
+            result.get_pyobj()[numpy.unravel_index(idx1 * array2.size + idx2, result.shape)] = array1.get_pyobj()[numpy.unravel_index(idx1, array1.shape)] * array2.get_pyobj()[numpy.unravel_index(idx2, array2.shape)]
 
     return result

dpnp/dpnp_algo/dpnp_algo_manipulation.pyx

@@ -148,7 +148,8 @@ cpdef utils.dpnp_descriptor dpnp_repeat(utils.dpnp_descriptor array1, repeats, a
 
 cpdef utils.dpnp_descriptor dpnp_reshape(utils.dpnp_descriptor array1, newshape, order=None):
     # return dpnp.get_dpnp_descriptor(dpctl.tensor.usm_ndarray(newshape, dtype=numpy.dtype(array1.dtype).name, buffer=array1.get_pyobj()))
-    return dpnp.get_dpnp_descriptor(dpctl.tensor.reshape(array1.get_pyobj(), newshape))
+    # return dpnp.get_dpnp_descriptor(dpctl.tensor.reshape(array1.get_pyobj(), newshape))
+    return dpnp.get_dpnp_descriptor(dpctl.tensor.reshape(array1.get_pyobj()._array_obj, newshape))
 
 
 cpdef utils.dpnp_descriptor dpnp_transpose(utils.dpnp_descriptor array1, axes=None):

dpnp/dpnp_algo/dpnp_algo_sorting.pyx

@@ -47,7 +47,10 @@ ctypedef void(*fptr_dpnp_searchsorted_t)(void * , const void * , const void * ,
 
 
 cpdef utils.dpnp_descriptor dpnp_argsort(utils.dpnp_descriptor x1):
-    return call_fptr_1in_1out(DPNP_FN_ARGSORT, x1, x1.shape)
+    cdef shape_type_c result_shape = x1.shape
+    if result_shape == ():
+        result_shape = (1,)
+    return call_fptr_1in_1out(DPNP_FN_ARGSORT, x1, result_shape)
 
 
 cpdef utils.dpnp_descriptor dpnp_partition(utils.dpnp_descriptor arr, int kth, axis=-1, kind='introselect', order=None):