example Namespace Reference

Functions
def	load_network (builder, network, parser)
def	load_config (config)
def	calib_data ()
def	create_network (builder, network)

Variables
	X = gs.Variable(name="X", dtype=np.float32, shape=(1, 3, 5, 5))
	Y = gs.Variable(name="Y", dtype=np.float32, shape=(1, 3, 1, 1))
	node = gs.Node(op="GlobalLpPool", attrs={"p": 2}, inputs=[X], outputs=[Y])
	graph = gs.Graph(nodes=[node], inputs=[X], outputs=[Y])
	W = gs.Constant(name="W", values=np.ones(shape=(5, 3, 3, 3), dtype=np.float32))
	MODEL = os.path.join(os.path.dirname(__file__), os.path.pardir, os.path.pardir, "models", "identity.onnx")
	load_serialized_onnx = BytesFromPath(MODEL)
	build_onnxrt_session = SessionFromOnnxBytes(load_serialized_onnx)
	build_engine = EngineFromNetwork(NetworkFromOnnxBytes(load_serialized_onnx))
list	runners
	run_results = Comparator.run(runners)
tuple	INPUT_SHAPE = (1, 1, 2, 2)
list	REAL_DATASET
list	GOLDEN_VALUES = REAL_DATASET
	outputs = runner.infer(feed_dict={"x": data})
	calibrator = Calibrator(data_loader=calib_data(), cache="identity-calib.cache")
dictionary	feed_dict = {"x": np.ones(shape=INPUT_SHAPE, dtype=np.float32)}
string	INPUT_NAME = "input"
string	OUTPUT_NAME = "output"

Function Documentation

load_network()

def example.load_network	(		builder,
			network,
			parser
	)

load_config()

def example.load_config

(

config

)

calib_data()

def example.calib_data

(

)

create_network()

def example.create_network	(		builder,
			network
	)

Variable Documentation

X

example.X = gs.Variable(name="X", dtype=np.float32, shape=(1, 3, 5, 5))

Y

example.Y = gs.Variable(name="Y", dtype=np.float32, shape=(1, 3, 1, 1))

node

example.node = gs.Node(op="GlobalLpPool", attrs={"p": 2}, inputs=[X], outputs=[Y])

graph

example.graph = gs.Graph(nodes=[node], inputs=[X], outputs=[Y])

W

example.W = gs.Constant(name="W", values=np.ones(shape=(5, 3, 3, 3), dtype=np.float32))

MODEL

example.MODEL = os.path.join(os.path.dirname(__file__), os.path.pardir, os.path.pardir, "models", "identity.onnx")

load_serialized_onnx

example.load_serialized_onnx = BytesFromPath(MODEL)

build_onnxrt_session

example.build_onnxrt_session = SessionFromOnnxBytes(load_serialized_onnx)

build_engine

example.build_engine = EngineFromNetwork(NetworkFromOnnxBytes(load_serialized_onnx))

runners

list example.runners

Initial value:

=  [
    TrtRunner(build_engine),
    OnnxrtRunner(build_onnxrt_session),
]

run_results

example.run_results = Comparator.run(runners)

INPUT_SHAPE

tuple example.INPUT_SHAPE = (1, 1, 2, 2)

REAL_DATASET

list example.REAL_DATASET

Initial value:

=  [ # Definitely real data
    np.ones(INPUT_SHAPE, dtype=np.float32),
    np.zeros(INPUT_SHAPE, dtype=np.float32),
    np.ones(INPUT_SHAPE, dtype=np.float32),
    np.zeros(INPUT_SHAPE, dtype=np.float32),
]

GOLDEN_VALUES

list example.GOLDEN_VALUES = REAL_DATASET

outputs

example.outputs = runner.infer(feed_dict={"x": data})

calibrator

example.calibrator = Calibrator(data_loader=calib_data(), cache="identity-calib.cache")

feed_dict

dictionary example.feed_dict = {"x": np.ones(shape=INPUT_SHAPE, dtype=np.float32)}

INPUT_NAME

string example.INPUT_NAME = "input"

OUTPUT_NAME

string example.OUTPUT_NAME = "output"