def test_case6(self):
paddle.disable_static()
model = ModelCase2()
predictor = TableLatencyPredictor(f'./{opt_tool}',
hardware='845',
threads=4,
power_mode=3,
batchsize=1)
pbmodel_file = predictor.opt_model(model,
input_shape=[1, 3, 224, 224],
save_dir='./model',
data_type='int8',
task_type='det')
assert os.path.exists(pbmodel_file)
latency = predictor.predict_latency(model,
input_shape=[1, 3, 224, 224],
save_dir='./model',
data_type='fp32',
task_type='det')
assert latency > 0
def test_case10(self):
paddle.disable_static()
model = ModelCase1()
predictor = TableLatencyPredictor(f'./{opt_tool}',
hardware='845',
threads=4,
power_mode=3,
batchsize=1)
pbmodel_file = predictor.opt_model(model,
input_shape=[1, 116, 28, 28],
save_dir='./model',
data_type='int8',
task_type='seg')
paddle.enable_static()
with open(pbmodel_file, "rb") as f:
program_desc_str = f.read()
fluid_program = paddle.fluid.framework.Program.parse_from_string(
program_desc_str)
graph = paddleslim.core.GraphWrapper(fluid_program)
graph_keys = predictor._get_key_info_from_graph(graph=graph)
assert len(graph_keys) > 0