Add support of numpy 1.24

Author: antonwolfy

conda-recipe/meta.yaml

@@ -8,7 +8,7 @@ requirements:
     host:
       - python
       - setuptools
-      - numpy >=1.19,<1.23a0
+      - numpy >=1.19,<1.25a0
       - cython
       - cmake >=3.19
       - dpctl >=0.13

dpnp/backend/include/dpnp_iface_fptr.hpp

@@ -1,5 +1,5 @@
 //*****************************************************************************
-// Copyright (c) 2016-2022, Intel Corporation
+// Copyright (c) 2016-2023, Intel Corporation
 // All rights reserved.
 //
 // Redistribution and use in source and binary forms, with or without
@@ -391,7 +391,7 @@ enum class DPNPFuncType : size_t
     DPNP_FT_DOUBLE,   /**< analog of numpy.float32 or double */
     DPNP_FT_CMPLX64,  /**< analog of numpy.complex64 or std::complex<float> */
     DPNP_FT_CMPLX128, /**< analog of numpy.complex128 or std::complex<double> */
-    DPNP_FT_BOOL      /**< analog of numpy.bool or numpy.bool_ or bool */
+    DPNP_FT_BOOL      /**< analog of numpy.bool_ or bool */
 };
 
 /**

dpnp/backend/kernels/dpnp_krnl_arraycreation.cpp

@@ -1,5 +1,5 @@
 //*****************************************************************************
-// Copyright (c) 2016-2023, Intel Corporation
+// Copyright (c) 2016-2022, Intel Corporation
 // All rights reserved.
 //
 // Redistribution and use in source and binary forms, with or without

dpnp/backend/src/dpnpc_memory_adapter.hpp

@@ -30,9 +30,6 @@
 #include "queue_sycl.hpp"
 #include "dpnp_utils.hpp"
 
-static_assert(__SYCL_COMPILER_VERSION >= __SYCL_COMPILER_VERSION_REQUIRED,
-              "The compiler does not meet minimum version requirement");
-
 /**
  * @ingroup BACKEND_UTILS
  * @brief Adapter for the memory given by parameters in the DPNPC functions

dpnp/backend/src/queue_sycl.cpp

@@ -31,9 +31,6 @@
 #include "queue_sycl.hpp"
 #include "dpnp_utils.hpp"
 
-static_assert(__SYCL_COMPILER_VERSION >= __SYCL_COMPILER_VERSION_REQUIRED,
-              "The compiler does not meet minimum version requirement");
-
 #if defined(DPNP_LOCAL_QUEUE)
 sycl::queue* backend_sycl::queue = nullptr;
 #endif

dpnp/dparray.pyx

@@ -1,7 +1,7 @@
 # cython: language_level=3
 # -*- coding: utf-8 -*-
 # *****************************************************************************
-# Copyright (c) 2016-2022, Intel Corporation
+# Copyright (c) 2016-2023, Intel Corporation
 # All rights reserved.
 #
 # Redistribution and use in source and binary forms, with or without
@@ -462,7 +462,7 @@ cdef class dparray:
             return ( < long * > self._dparray_data)[lin_idx]
         elif self.dtype == numpy.int32:
             return ( < int * > self._dparray_data)[lin_idx]
-        elif self.dtype == numpy.bool:
+        elif self.dtype == numpy.bool_:
             return ( < cpp_bool * > self._dparray_data)[lin_idx]
         elif self.dtype == numpy.complex128:
             return ( < double complex * > self._dparray_data)[lin_idx]
@@ -489,7 +489,7 @@ cdef class dparray:
             ( < long * > self._dparray_data)[lin_idx] = <long > value
         elif self.dtype == numpy.int32:
             ( < int * > self._dparray_data)[lin_idx] = <int > value
-        elif self.dtype == numpy.bool:
+        elif self.dtype == numpy.bool_:
             ( < cpp_bool * > self._dparray_data)[lin_idx] = < cpp_bool > value
         elif self.dtype == numpy.complex64:
             ( < float complex * > self._dparray_data)[lin_idx] = <float complex > value
@@ -876,7 +876,7 @@ cdef class dparray:
 
         """
 
-        if not numpy.issubsctype(self.dtype, numpy.complex):
+        if not numpy.issubsctype(self.dtype, numpy.complex_):
             return self
         else:
             return conjugate(self)
@@ -889,7 +889,7 @@ cdef class dparray:
 
         """
 
-        if not numpy.issubsctype(self.dtype, numpy.complex):
+        if not numpy.issubsctype(self.dtype, numpy.complex_):
             return self
         else:
             return conjugate(self)

dpnp/dpnp_algo/dpnp_algo.pyx

@@ -276,7 +276,7 @@ cdef dpnp_DPNPFuncType_to_dtype(size_t type):
     elif type == <size_t > DPNP_FT_CMPLX128:
         return numpy.complex128
     elif type == <size_t > DPNP_FT_BOOL:
-        return numpy.bool
+        return numpy.bool_
     else:
         utils.checker_throw_type_error("dpnp_DPNPFuncType_to_dtype", type)
 

dpnp/dpnp_algo/dpnp_algo_arraycreation.pyx

@@ -1,7 +1,7 @@
 # cython: language_level=3
 # -*- coding: utf-8 -*-
 # *****************************************************************************
-# Copyright (c) 2016-2022, Intel Corporation
+# Copyright (c) 2016-2023, Intel Corporation
 # All rights reserved.
 #
 # Redistribution and use in source and binary forms, with or without
@@ -434,7 +434,7 @@ cpdef utils.dpnp_descriptor dpnp_trace(utils.dpnp_descriptor arr, offset=0, axis
     return result
 
 
-cpdef utils.dpnp_descriptor dpnp_tri(N, M=None, k=0, dtype=numpy.float):
+cpdef utils.dpnp_descriptor dpnp_tri(N, M=None, k=0, dtype=dpnp.float):
     if M is None:
         M = N
 

dpnp/dpnp_array.py

@@ -1,6 +1,6 @@
 # -*- coding: utf-8 -*-
 # *****************************************************************************
-# Copyright (c) 2016-2022, Intel Corporation
+# Copyright (c) 2016-2023, Intel Corporation
 # All rights reserved.
 #
 # Redistribution and use in source and binary forms, with or without
@@ -493,7 +493,7 @@ def conj(self):
 
         """
 
-        if not numpy.issubsctype(self.dtype, numpy.complex):
+        if not numpy.issubsctype(self.dtype, numpy.complex_):
             return self
         else:
             return dpnp.conjugate(self)
@@ -506,7 +506,7 @@ def conjugate(self):
 
         """
 
-        if not numpy.issubsctype(self.dtype, numpy.complex):
+        if not numpy.issubsctype(self.dtype, numpy.complex_):
             return self
         else:
             return dpnp.conjugate(self)

dpnp/dpnp_iface_arraycreation.py

@@ -2,7 +2,7 @@
 # distutils: language = c++
 # -*- coding: utf-8 -*-
 # *****************************************************************************
-# Copyright (c) 2016-2022, Intel Corporation
+# Copyright (c) 2016-2023, Intel Corporation
 # All rights reserved.
 #
 # Redistribution and use in source and binary forms, with or without
@@ -1280,7 +1280,7 @@ def trace(x1, offset=0, axis1=0, axis2=1, dtype=None, out=None):
     return call_origin(numpy.trace, x1, offset, axis1, axis2, dtype, out)
 
 
-def tri(N, M=None, k=0, dtype=numpy.float, **kwargs):
+def tri(N, M=None, k=0, dtype=dpnp.float, **kwargs):
     """
     An array with ones at and below the given diagonal and zeros elsewhere.
 
@@ -1315,7 +1315,7 @@ def tri(N, M=None, k=0, dtype=numpy.float, **kwargs):
         elif not isinstance(k, int):
             pass
         else:
-            if dtype is numpy.float:
+            if dtype is dpnp.float:
                 sycl_queue = dpnp.get_normalized_queue_device(sycl_queue=None, device=None)
                 dtype = map_dtype_to_device(dpnp.float64, sycl_queue.sycl_device)
             return dpnp_tri(N, M, k, dtype).get_pyobj()