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Function run_gpu_only

tensorflow/python/framework/test_util.py:1320–1350  ·  view source on GitHub ↗

Execute the decorated test only if a GPU is available. This function is intended to be applied to tests that require the presence of a GPU. If a GPU is absent, it will simply be skipped. Args: func: function to be annotated. If `func` is None, this method returns a decorator the ca

(func=None)

Source from the content-addressed store, hash-verified

1318
1319
1320def run_gpu_only(func=None):
1321 """Execute the decorated test only if a GPU is available.
1322
1323 This function is intended to be applied to tests that require the presence
1324 of a GPU. If a GPU is absent, it will simply be skipped.
1325
1326 Args:
1327 func: function to be annotated. If `func` is None, this method returns a
1328 decorator the can be applied to a function. If `func` is not None this
1329 returns the decorator applied to `func`.
1330
1331 Returns:
1332 Returns a decorator that will conditionally skip the decorated test method.
1333 """
1334
1335 def decorator(f):
1336 if tf_inspect.isclass(f):
1337 raise ValueError("`run_gpu_only` only supports test methods.")
1338
1339 def decorated(self, *args, **kwargs):
1340 if not is_gpu_available():
1341 self.skipTest("Test requires GPU")
1342
1343 return f(self, *args, **kwargs)
1344
1345 return decorated
1346
1347 if func is not None:
1348 return decorator(func)
1349
1350 return decorator
1351
1352
1353def run_cuda_only(func=None):

Callers

nothing calls this directly

Calls 1

decoratorFunction · 0.70

Tested by

no test coverage detected