numpy.core.tests.test_simd._Test_Utility

class documentation

class _Test_Utility: (source)

Known subclasses: numpy.core.tests.test_simd._SIMD_ALL, numpy.core.tests.test_simd._SIMD_BOOL, numpy.core.tests.test_simd._SIMD_FP, numpy.core.tests.test_simd._SIMD_FP32, numpy.core.tests.test_simd._SIMD_FP64, numpy.core.tests.test_simd._SIMD_INT

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Undocumented

Method __getattr__ To call NPV intrinsics without the attribute 'npyv' and auto suffixing intrinsics according to class attribute 'sfx'
Class Variable npyv Undocumented
Class Variable sfx Undocumented
Class Variable target_name Undocumented
Method _cpu_features Undocumented
Method _data Create list of consecutive numbers according to number of vector's lanes.
Method _int_clip Undocumented
Method _int_max Undocumented
Method _int_min Undocumented
Method _is_fp Undocumented
Method _is_signed Undocumented
Method _is_unsigned Undocumented
Method _nan Undocumented
Method _ninfinity Undocumented
Method _pinfinity Undocumented
Method _scalar_size Undocumented
Method _to_unsigned Undocumented
Method _true_mask Undocumented
def __getattr__(self, attr): (source)

To call NPV intrinsics without the attribute 'npyv' and auto suffixing intrinsics according to class attribute 'sfx'

npyv = (source)

Undocumented

sfx = (source)

Undocumented

target_name = (source)

Undocumented

def _cpu_features(self): (source)

Undocumented

def _data(self, start=None, count=None, reverse=False): (source)
overridden in numpy.core.tests.test_simd._SIMD_BOOL

Create list of consecutive numbers according to number of vector's lanes.

def _int_clip(self, seq): (source)

Undocumented

def _int_max(self): (source)

Undocumented

def _int_min(self): (source)

Undocumented

def _is_fp(self): (source)

Undocumented

def _is_signed(self): (source)

Undocumented

def _is_unsigned(self): (source)

Undocumented

def _nan(self): (source)

Undocumented

def _ninfinity(self): (source)

Undocumented

def _pinfinity(self): (source)

Undocumented

def _scalar_size(self): (source)

Undocumented

def _to_unsigned(self, vector): (source)

Undocumented

def _true_mask(self): (source)

Undocumented