def __call__(self, path, input_shapes=None):
compressed = os.path.splitext(path) in ['tgz', 'gz'
] and not os.path.isdir(path)
folder = None
try:
if compressed:
folder = tempfile.mkdtemp(prefix="nnef_")
tgz_extract(path, folder)
path = folder
if not os.path.isdir(path):
raise IOError(
"NNEF model must be a (compressed) folder, but an uncompressed file was provided"
)
nnef_graph = nnef.load_graph(path,
stdlib=self._stdlib,
lowered=self._decomposed)
if self._infer_shapes:
nnef.infer_shapes(nnef_graph,
external_shapes=input_shapes or {},
custom_shapes=self._custom_shapes or {})
return _build_graph(nnef_graph)
finally:
if folder is not None:
shutil.rmtree(folder)
def nnef2ir(inputFolder, outputFolder):
nnef_graph = nnef.load_graph(inputFolder)
nnef.infer_shapes(nnef_graph)
graph = nnef_graph_to_ir_graph(nnef_graph)
graph.toFile(outputFolder)
action="store_true",
help='perform shape validation as well')
args = ap.parse_args()
stdlib = ''
if args.stdlib:
try:
with open(args.stdlib) as file:
stdlib = file.read()
except FileNotFoundError as e:
print('Could not open file: ' + args.stdlib)
exit(-1)
try:
graph = nnef.load_graph(args.path,
stdlib=stdlib,
lowered=args.lower.split(','))
except nnef.Error as err:
print('Parse error: ' + str(err))
exit(-1)
if args.shapes:
try:
nnef.infer_shapes(graph)
except nnef.Error as err:
print('Shape error: ' + str(err))
exit(-1)
print(
nnef.format_graph(graph.name, graph.inputs, graph.outputs,
graph.operations))
def load_graph(self, path):
return nnef.load_graph(path=path,
stdlib=self._source,
lowered=self._expand)
def load_graph(self, path):
return nnef.load_graph(path=path,
stdlib=self.fragments,
lowered=self.lowered)
def load_graph(self, path):
return nnef.load_graph(path=path,
stdlib=self.custom_ops,
lowered=self.expand)
