def main():
args = convert.get_args()
convert.main()
onnx_model = onnx.load(args.output)
verify_outputs(args, onnx_model)
onnx.save(onnx_model, args.output)
def run_test_case(args):
""" run case and clean up """
sys.argv = args
convert.main()
ret = os.path.exists(args[-1])
if ret:
os.remove(args[-1])
return ret
def convert_onnx(**kwargs):
# https://github.com/onnx/tensorflow-onnx
# sys.argv = ['checkpoint2onnx.py',
# "--inputs", FLAGS.input_nodes,
# "--outputs", FLAGS.output_nodes]
sys.argv = ["convert.py", "--opset", FLAGS.opset]
# add specific arguments for conversions from different source format
for k, v in kwargs.items():
sys.argv.extend(["--%s" % k, "%s" % v])
convert.main()
def run_test_case(args, paths_to_check=None):
""" run case and clean up """
if paths_to_check is None:
paths_to_check = [args[-1]]
sys.argv = args
convert.main()
ret = True
for p in paths_to_check:
if os.path.exists(p):
os.remove(p)
else:
ret = False
return ret
def tfonnxconvert(config, paths_to_check=None):
args = [
'', '--saved-model', config['savedmodel'], '--output',
config['onnxmodel']
]
""" run case and clean up """
if paths_to_check is None:
paths_to_check = [args[-1]]
sys.argv = args
convert.main()
ret = True
for p in paths_to_check:
if os.path.exists(p):
os.remove(p)
else:
ret = False
return ret
