def test_basic(self):
model = TF_MODELS["identity"]
with TfRunner(SessionFromGraph(model.loader)) as runner:
assert runner.is_active
model.check_runner(runner)
assert not runner.is_active
assert runner._cached_input_metadata is None
def test_basic(self):
model = TF_MODELS["identity"]
with TfRunner(SessionFromGraph(model.loader)) as runner:
assert runner.is_active
model.check_runner(runner)
assert runner.last_inference_time() is not None
assert not runner.is_active
def test_save_timeline(self):
model = TF_MODELS["identity"]
with tempfile.NamedTemporaryFile() as outpath:
with TfRunner(SessionFromGraph(model.loader),
allow_growth=True,
save_timeline=outpath.name) as runner:
model.check_runner(runner)
check_file_non_empty(outpath.name)
def test_error_on_wrong_dtype_feed_dict(self):
model = TF_MODELS["identity"]
with TfRunner(SessionFromGraph(model.loader)) as runner:
with pytest.raises(PolygraphyException, match="unexpected dtype."):
runner.infer({
"Input:0":
np.ones(shape=(1, 15, 25, 30), dtype=np.int32)
})
def test_error_on_wrong_name_feed_dict(self, names, err):
model = TF_MODELS["identity"]
with TfRunner(SessionFromGraph(model.loader)) as runner:
with pytest.raises(PolygraphyException, match=err):
runner.infer({
name: np.ones(shape=(1, 15, 25, 30), dtype=np.float32)
for name in names
})
def test_multiple_runners(self):
load_tf = TF_MODELS["identity"].loader
build_tf_session = SessionFromGraph(load_tf)
load_serialized_onnx = BytesFromOnnx(OnnxFromTfGraph(load_tf))
build_onnxrt_session = SessionFromOnnxBytes(load_serialized_onnx)
load_engine = EngineFromNetwork(NetworkFromOnnxBytes(load_serialized_onnx))
runners = [
TfRunner(build_tf_session),
OnnxrtRunner(build_onnxrt_session),
TrtRunner(load_engine),
]
run_results = Comparator.run(runners)
compare_func = CompareFunc.basic_compare_func(check_shapes=version(trt.__version__) >= version("7.0"))
assert bool(Comparator.compare_accuracy(run_results, compare_func=compare_func))
assert len(list(run_results.values())[0]) == 1 # Default number of iterations