def profile_net(network,
inputnode=None,
outputnode=None,
nshaves=1,
inputsize=None,
weights=None,
device_no=None):
file_init()
args = Arguments(network, inputnode, outputnode, inputsize, nshaves,
weights, device_no)
myriad_config = MyriadParam(0, nshaves - 1)
filetype = network.split(".")[-1]
if args.conf_file is not None:
get_myriad_info(args, myriad_config)
if filetype in ["prototxt"]:
from Controllers.CaffeParser import parse_caffe
net = parse_caffe(args, myriad_config, file_gen=True)
elif filetype in ["pb", "protobuf", "meta"]:
from Controllers.TensorFlowParser import parse_tensor
net = parse_tensor(args, myriad_config, file_gen=True)
else:
throw_error(ErrorTable.ParserNotSupported)
net.finalize()
net.optimize()
graph_file = Blob(major_version, net.name, '', myriad_config, net, "graph")
graph_file.generate()
timings, myriad_output = run_myriad(graph_file, args, file_gen=False)
net.gather_metrics(timings)
print_summary_of_network(graph_file)
generate_graphviz(net, graph_file, filename=args.outputs_name)
def create_graph(network, inputnode = None, outputnode = None, outfile = 'graph', nshaves = 1, inputsize = None, weights = None, explicit_concat = None, ma2480 = None, scheduler = True, model_dir='', extargs = None):
file_init()
args = Arguments(network, inputnode, outputnode, outfile, inputsize, nshaves, weights, explicit_concat, model_dir, extargs)
args.ma2480 = ma2480
args.scheduler = scheduler
GLOBALS.USING_MA2480 = args.ma2480
GLOBALS.OPT_SCHEDULER = args.scheduler is None
ppInit(args.scheduler)
myriad_config = load_myriad_config(args.number_of_shaves)
if args.conf_file is not None:
get_myriad_info(args, myriad_config)
filetype = network.split(".")[-1]
parser = None
if filetype in ["prototxt"]:
parser = Parser.Caffe
elif filetype in ["pb", "protobuf", "meta"]:
parser = Parser.TensorFlow
else:
throw_error(ErrorTable.ParserNotSupported)
file_gen = True
load_ret = load_network(args, parser, myriad_config,debug=True)
net = load_ret['network']
if args.new_parser:
graph_file = load_ret['graph']
else:
graph_file = Blob([GLOBALS.BLOB_MAJOR_VERSION, GLOBALS.BLOB_MINOR_VERSION, GLOBALS.BLOB_PATCH_VERSION], net.name, '', myriad_config, net, outfile)
graph_file.generate_v2(args)
expected = load_ret['expected']
if file_gen:
np.save(args.outputs_name + "_expected.npy", expected.astype(dtype=np.float16))
def create_graph(network,
inputnode=None,
outputnode=None,
outfile='graph',
nshaves=1,
inputsize=None,
weights=None):
file_init()
args = Arguments(network, inputnode, outputnode, outfile, inputsize,
nshaves, weights)
myriad_config = MyriadParam(0, nshaves - 1)
if args.conf_file is not None:
get_myriad_info(args, myriad_config)
filetype = network.split(".")[-1]
if filetype in ["prototxt"]:
from Controllers.CaffeParser import parse_caffe
net = parse_caffe(args, myriad_config)
elif filetype in ["pb", "protobuf", "meta"]:
from Controllers.TensorFlowParser import parse_tensor
net = parse_tensor(args, myriad_config)
else:
throw_error(ErrorTable.ParserNotSupported)
net.finalize()
net.optimize()
graph_file = Blob(major_version, net.name, '', myriad_config, net, outfile)
graph_file.generate()
def profile_net(network,
inputnode=None,
outputnode=None,
nshaves=1,
inputsize=None,
weights=None,
device_no=None,
explicit_concat=None,
ma2480=None,
scheduler=True,
model_dir='',
extargs=None):
file_init()
args = Arguments(network, inputnode, outputnode, inputsize, nshaves,
weights, device_no, explicit_concat, ma2480, scheduler,
model_dir, extargs)
GLOBALS.USING_MA2480 = args.ma2480
GLOBALS.OPT_SCHEDULER = args.scheduler is None
ppInit(args.scheduler)
myriad_config = load_myriad_config(args.number_of_shaves)
if args.conf_file is not None:
get_myriad_info(args, myriad_config)
filetype = network.split(".")[-1]
parser = None
if filetype in ["prototxt"]:
parser = Parser.Caffe
elif filetype in ["pb", "protobuf", "meta"]:
parser = Parser.TensorFlow
else:
throw_error(ErrorTable.ParserNotSupported)
load_ret = load_network(args, parser, myriad_config, debug=True)
net = load_ret['network']
if args.new_parser:
graph_file = load_ret['graph']
else:
graph_file = Blob([
GLOBALS.BLOB_MAJOR_VERSION, GLOBALS.BLOB_MINOR_VERSION,
GLOBALS.BLOB_PATCH_VERSION
], net.name, '', myriad_config, net, model_dir + "graph")
graph_file.generate_v2(args)
timings, myriad_output = run_myriad(graph_file, args)
net.gather_metrics(timings)
print_summary_of_network(graph_file)
if not args.new_parser:
generate_graphviz(net, graph_file, filename=args.outputs_name)
def check_net(network,
image,
inputnode=None,
outputnode=None,
nshaves=1,
inputsize=None,
weights=None,
extargs=None):
file_init()
args = Arguments(network, image, inputnode, outputnode, inputsize, nshaves,
weights, extargs)
myriad_config = MyriadParam(0, nshaves - 1)
if args.conf_file is not None:
get_myriad_info(args, myriad_config)
filetype = network.split(".")[-1]
if filetype in ["prototxt"]:
from Controllers.CaffeParser import parse_caffe
net = parse_caffe(args, myriad_config, file_gen=True)
elif filetype in ["pb", "protobuf", "meta"]:
from Controllers.TensorFlowParser import parse_tensor
net = parse_tensor(args, myriad_config, file_gen=True)
else:
throw_error(ErrorTable.ParserNotSupported)
net.finalize()
net.optimize()
graph_file = Blob(major_version, net.name, '', myriad_config, net, "graph")
graph_file.generate()
timings, myriad_output = run_myriad(graph_file, args, file_gen=True)
expected = np.load(args.outputs_name + "_expected.npy")
result = np.load(args.outputs_name + "_result.npy")
filename = str(args.outputs_name) + "_val.csv"
quit_code = validation(myriad_output, expected, args.exp_id,
ValidationStatistic[extargs.metric], filename, args)
return quit_code
def check_net(network,
image,
inputnode=None,
outputnode=None,
nshaves=1,
inputsize=None,
weights=None,
extargs=None,
debug=False):
file_init()
args = Arguments(network, image, inputnode, outputnode, inputsize, nshaves,
weights, extargs)
GLOBALS.USING_MA2480 = args.ma2480
GLOBALS.OPT_SCHEDULER = args.scheduler is None
ppInit(args.scheduler)
myriad_config = load_myriad_config(args.number_of_shaves)
if args.conf_file is not None:
get_myriad_info(args, myriad_config)
filetype = network.split(".")[-1]
parser = None
if filetype in ["prototxt"]:
parser = Parser.Caffe
elif filetype in ["pb", "protobuf", "meta"]:
parser = Parser.TensorFlow
else:
throw_error(ErrorTable.ParserNotSupported)
file_gen = True
load_ret = load_network(args, parser, myriad_config, debug=True)
net = load_ret['network']
if args.new_parser:
graph_file = load_ret['graph']
else:
graph_file = Blob([
GLOBALS.BLOB_MAJOR_VERSION, GLOBALS.BLOB_MINOR_VERSION,
GLOBALS.BLOB_PATCH_VERSION
], net.name, '', myriad_config, net, "graph")
graph_file.generate_v2(args)
timings, myriad_output = run_myriad(graph_file, args)
report_filename = str(args.outputs_name) + "_val.csv"
expected = load_ret['expected']
expected_layout = load_ret['expected_layout']
# Bring myriad layout to the layout of the expected output, in order to allow comparison
# between the two
if not args.new_parser:
myriad_output = storage_order_convert(myriad_output,
net.outputTensorLayout,
expected_layout)
if file_gen:
np.save(args.outputs_name + "_result.npy", myriad_output)
np.save(args.outputs_name + "_expected.npy",
expected.astype(dtype=np.float16))
quit_code = validation(myriad_output, expected, args.exp_id,
ValidationStatistic[extargs.metric],
report_filename, args)
return quit_code