def check_network(self, suffix):
"""
Checks whether the provided network is accurate compared to golden values.
Returns:
OrderedDict[str, OutputCompareResult]:
A mapping of output names to an object describing whether they matched, and what the
required tolerances were.
"""
from polygraphy.comparator import Comparator, CompareFunc, DataLoader
from polygraphy.backend.trt import EngineFromNetwork, TrtRunner, ModifyNetwork, SaveEngine
with G_LOGGER.verbosity(severity=G_LOGGER.severity if self.args.
show_output else G_LOGGER.CRITICAL):
data_loader = tool_util.get_data_loader(self.args)
self.args.strict_types = True # HACK: Override strict types so things actually run in the right precision.
config = tool_util.get_trt_config_loader(self.args,
data_loader)(self.builder,
self.network)
suffix = "-{:}-{:}".format(suffix, self.precision)
engine_path = misc.insert_suffix(self.args.save_engine, suffix)
self.builder, self.network, self.parser = ModifyNetwork(
(self.builder, self.network, self.parser),
outputs=self.args.trt_outputs)()
engine_loader = SaveEngine(EngineFromNetwork(
(self.builder, self.network, self.parser), config),
path=engine_path)
runners = [TrtRunner(engine_loader)]
results = Comparator.run(runners, data_loader=data_loader)
if self.args.validate:
Comparator.validate(results)
results.update(self.golden)
compare_func = CompareFunc.basic_compare_func(
atol=self.args.atol,
rtol=self.args.rtol,
check_shapes=not self.args.no_shape_check)
accuracy_result = Comparator.compare_accuracy(
results, compare_func=compare_func)
tolerances = list(accuracy_result.values())[0][
0] # First iteration of first runner pair
for name, req_tol in tolerances.items():
if bool(req_tol):
G_LOGGER.success(
"PASSED | Output: {:} | Required Tolerances: {:}".format(
name, req_tol))
else:
G_LOGGER.error(
"FAILED | Output: {:} | Required Tolerances: {:}".format(
name, req_tol))
return accuracy_result
def test_validate_inf(self):
run_results = RunResults()
run_results["fake-runner"] = [
IterationResult(outputs={"x": np.array(np.inf)})
]
assert not Comparator.validate(run_results, check_finite=True)
def test_validate_nan(self):
run_results = RunResults()
run_results["fake-runner"] = [
IterationResult(outputs={"x": np.array(np.nan)})
]
assert not Comparator.validate(run_results)