def release_wrapper(self,
config,
model_path,
storage,
image,
destination,
optimization_level=None,
gpuid=0,
push_model=True):
local_config = self._finalize_config(config, training=False)
objects = self.release(
local_config,
model_path,
optimization_level=optimization_level,
gpuid=gpuid)
bundle_dependencies(objects, config, local_config)
model_id = config['model'] + '_release'
config['model'] = model_id
config['modelType'] = 'release'
config['imageTag'] = image
for name in ("parent_model", "build", "data"):
if name in config:
del config[name]
inference_options = config.get('inference_options')
if inference_options is not None:
schema = config_util.validate_inference_options(inference_options, config)
options_path = os.path.join(self._output_dir, 'options.json')
with open(options_path, 'w') as options_file:
json.dump(schema, options_file)
objects[os.path.basename(options_path)] = options_path
objects_dir = os.path.join(self._models_dir, model_id)
build_model_dir(objects_dir, objects, config, should_check_integrity)
if push_model:
storage.push(objects_dir, storage.join(destination, model_id))
def test_inference_options_invalid_shema():
opt = copy.deepcopy(_test_inference_options)
opt["json_schema"]["type"] = "objects"
with pytest.raises(jsonschema.SchemaError):
config.validate_inference_options(opt, _test_config)
def test_inference_options_validation():
schema = config.validate_inference_options(_test_inference_options,
_test_config)
assert isinstance(schema, dict)