def estimate(args):
"""Estimate example function
Args:
network name (str): network name
Returns:
float: estimated time in ms
"""
model = AnnetteGraph(
args.network, get_database('graphs', 'annette',
args.network + '.json'))
if args.mapping != "none":
opt = Mapping_model.from_json(
get_database('models', 'mapping', args.mapping + '.json'))
opt.run_optimization(model)
# LOAD MODELS
mod = Layer_model.from_json(
get_database('models', 'layer', args.layer + '.json'))
# APPLY ESTIMATION
res = mod.estimate_model(model)
write_result(args.network, res, args.mapping, args.layer,
get_database('results'))
return res[0], res[2]
def test_annette_to_model(network="cf_reid"):
json_file = Path('database', 'graphs', 'annette', network + '.json')
annette_graph = AnnetteGraph(network, json_file)
# execute the function under test
generator.generate_tf_model(annette_graph)
assert True
def test_regression_estimation():
network_list = [
'cf_cityscapes', 'cf_resnet50', 'cf_openpose', 'tf_mobilenetv1',
'tf_mobilenetv2'
]
json_file = Path('database', 'models', 'mapping', 'ov.json')
ncs2_opt = Mapping_model.from_json(json_file)
# LOAD MODELS
ncs2_mod = {}
json_file = Path('database', 'models', 'layer', 'ov.json')
ncs2_mod['roofline'] = Layer_model.from_json(
"database/models/layer/ncs2-roofline.json")
ncs2_mod['ref_roofline'] = Layer_model.from_json(
"database/models/layer/ncs2-ref_roofline.json")
ncs2_mod['statistical'] = Layer_model.from_json(
"database/models/layer/ncs2-statistical.json")
ncs2_mod['mixed'] = Layer_model.from_json(
"database/models/layer/ncs2-mixed.json")
for network in network_list:
json_file = Path('database', 'graphs', 'annette', network + '.json')
model = AnnetteGraph(network, json_file)
ncs2_opt.run_optimization(model)
# APPLY ESTIMATION
ncs2_res = {}
ncs2_res['mixed'] = ncs2_mod['mixed'].estimate_model(model)
ncs2_res['roofline'] = ncs2_mod['roofline'].estimate_model(model)
ncs2_res['ref_roofline'] = ncs2_mod['ref_roofline'].estimate_model(
model)
ncs2_res['statistical'] = ncs2_mod['statistical'].estimate_model(model)
assert True
def test_estimation(network="cf_resnet50"):
json_file = Path('database', 'graphs', 'annette', network + '.json')
model = AnnetteGraph(network, json_file)
json_file = Path('database', 'models', 'mapping', 'ov.json')
ncs2_opt = Mapping_model.from_json(json_file)
ncs2_opt.run_optimization(model)
# LOAD MODELS
ncs2_mod = {}
json_file = Path('database', 'models', 'layer', 'ov.json')
ncs2_mod['roofline'] = Layer_model.from_json(
"database/models/layer/ncs2-roofline.json")
ncs2_mod['ref_roofline'] = Layer_model.from_json(
"database/models/layer/ncs2-ref_roofline.json")
ncs2_mod['statistical'] = Layer_model.from_json(
"database/models/layer/ncs2-statistical.json")
ncs2_mod['mixed'] = Layer_model.from_json(
"database/models/layer/ncs2-mixed.json")
# APPLY ESTIMATION
ncs2_res = {}
ncs2_res['mixed'] = ncs2_mod['mixed'].estimate_model(model)
ncs2_res['roofline'] = ncs2_mod['roofline'].estimate_model(model)
ncs2_res['ref_roofline'] = ncs2_mod['ref_roofline'].estimate_model(model)
ncs2_res['statistical'] = ncs2_mod['statistical'].estimate_model(model)
assert True
return model
def test_optimization(network="cf_resnet50"):
json_file = Path('database', 'graphs', 'annette', network + '.json')
model = AnnetteGraph(network, json_file)
json_file = Path('database', 'models', 'mapping', 'ov.json')
ncs2_opt = Mapping_model.from_json(json_file)
ncs2_opt.run_optimization(model)
assert True
return model
def __init__(self, network):
#load graphstruct
json_file = get_database('graphs', 'annette', network + '.json')
self.graph = AnnetteGraph(network, json_file)
print(self.graph)