Get rid of unsupported types in array creation tests (#1283)

Author: antonwolfy

dpnp/dpnp_iface.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
@@ -61,6 +61,7 @@
     "asnumpy",
     "astype",
     "convert_single_elem_array_to_scalar",
+    "default_float_type",
     "dpnp_queue_initialize",
     "dpnp_queue_is_cpu",
     "get_dpnp_descriptor",
@@ -69,7 +70,8 @@
 ]
 
 from dpnp import (
-    isscalar
+    isscalar,
+    float64
 )
 
 from dpnp.dpnp_iface_arraycreation import *
@@ -191,6 +193,35 @@ def convert_single_elem_array_to_scalar(obj, keepdims=False):
     return obj
 
 
+def default_float_type(device=None, sycl_queue=None):
+    """
+    Return a floating type used by default in DPNP depending on device capabilities.
+
+    Parameters
+    ----------
+    device : {None, string, SyclDevice, SyclQueue}, optional
+        An array API concept of device where an array of default floating type might be created.
+        The `device` can be ``None`` (the default), an OneAPI filter selector string,
+        an instance of :class:`dpctl.SyclDevice` corresponding to a non-partitioned SYCL device,
+        an instance of :class:`dpctl.SyclQueue`, or a `Device` object returned by
+        :obj:`dpnp.dpnp_array.dpnp_array.device` property.
+        The value ``None`` is interpreted as to use a default device.
+    sycl_queue : {None, SyclQueue}, optional
+        A SYCL queue which might be used to create an array of default floating type.
+        The `sycl_queue` can be ``None`` (the default), which is interpreted as
+        to get the SYCL queue from `device` keyword if present or to use a default queue.
+
+    Returns
+    -------
+    dt : dtype
+        A default DPNP floating type.
+
+    """
+
+    _sycl_queue = get_normalized_queue_device(device=device, sycl_queue=sycl_queue)
+    return map_dtype_to_device(float64, _sycl_queue.sycl_device)
+
+
 def get_dpnp_descriptor(ext_obj,
                         copy_when_strides=True,
                         copy_when_nondefault_queue=True,

dpnp/dpnp_iface_arraycreation.py

@@ -871,10 +871,8 @@ def identity(n, dtype=None, *, like=None):
         elif n < 0:
             pass
         else:
-            if dtype is None:
-                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_identity(n, dtype).get_pyobj()
+            _dtype = dpnp.default_float_type() if dtype is None else dtype
+            return dpnp_identity(n, _dtype).get_pyobj()
 
     return call_origin(numpy.identity, n, dtype=dtype, like=like)
 
@@ -1327,10 +1325,8 @@ def tri(N, M=None, k=0, dtype=dpnp.float, **kwargs):
         elif not isinstance(k, int):
             pass
         else:
-            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()
+            _dtype = dpnp.default_float_type() if dtype in (dpnp.float, None) else dtype
+            return dpnp_tri(N, M, k, _dtype).get_pyobj()
 
     return call_origin(numpy.tri, N, M, k, dtype, **kwargs)
 

dpnp/dpnp_iface_types.py

@@ -36,12 +36,12 @@
 
 import numpy
 
+
 __all__ = [
     "bool",
     "bool_",
     "complex128",
     "complex64",
-    "default_float_type",
     "dtype",
     "float",
     "float16",
@@ -75,10 +75,6 @@
 longcomplex = numpy.longcomplex
 
 
-def default_float_type():
-    return float64
-
-
 def isscalar(obj):
     """
     Returns True if the type of `obj` is a scalar type.

dpnp/dpnp_utils/dpnp_algo_utils.pyx

@@ -165,7 +165,7 @@ def call_origin(function, *args, **kwargs):
 
     exec_q = dpctl.utils.get_execution_queue(alloc_queues)
     if exec_q is None:
-        exec_q = sycl_queue
+        exec_q = dpnp.get_normalized_queue_device(sycl_queue=sycl_queue)
     # print(f"DPNP call_origin(): bakend called. \n\t function={function}, \n\t args_new={args_new}, \n\t kwargs_new={kwargs_new}, \n\t dpnp_inplace={dpnp_inplace}")
     # TODO need to put array memory into NumPy call
     result_origin = function(*args_new, **kwargs_new)

tests/helper.py

@@ -0,0 +1,39 @@
+import dpctl
+import dpnp
+
+
+def get_all_dtypes(no_bool=False,
+                   no_float16=True,
+                   no_complex=False,
+                   no_none=False,
+                   device=None):
+    """
+    Build a list of types supported by DPNP based on input flags and device capabilities.
+    """
+
+    dev = dpctl.select_default_device() if device is None else device
+
+    # add boolean type
+    dtypes = [dpnp.bool] if not no_bool else []
+
+    # add integer types
+    dtypes.extend([dpnp.int32, dpnp.int64])
+
+    # add floating types
+    if not no_float16 and dev.has_aspect_fp16:
+        dtypes.append(dpnp.float16)
+
+    dtypes.append(dpnp.float32)
+    if dev.has_aspect_fp64:
+        dtypes.append(dpnp.float64)
+
+    # add complex types
+    if not no_complex:
+        dtypes.append(dpnp.complex64)
+        if dev.has_aspect_fp64:
+            dtypes.append(dpnp.complex128)
+    
+    # add None value to validate a default dtype
+    if not no_none:
+        dtypes.append(None)
+    return dtypes