def __init__(self, config):
dg.MultiSlotDataGenerator.__init__(self)
if os.path.isfile(config):
with open(config, 'r') as rb:
_config = yaml.load(rb.read(), Loader=yaml.FullLoader)
else:
raise ValueError("reader config only support yaml")
envs.set_global_envs(_config)
envs.update_workspace()
def create(config):
_config = None
if os.path.isfile(config):
with open(config, 'r') as rb:
_config = yaml.load(rb.read(), Loader=yaml.FullLoader)
else:
raise ValueError("paddlerec's config only support yaml")
envs.set_global_envs(_config)
envs.update_workspace()
trainer = TrainerFactory._build_trainer(config)
return trainer
def __init__(self, config=None):
super(TranspileTrainer, self).__init__(config)
self._env = self._config
self.processor_register()
self._model = {}
self._dataset = {}
envs.set_global_envs(self._config)
envs.update_workspace()
self._runner_name = envs.get_global_env("mode")
device = envs.get_global_env("runner." + self._runner_name + ".device")
if device == 'gpu':
self._place = fluid.CUDAPlace(0)
elif device == 'cpu':
self._place = fluid.CPUPlace()
self._exe = fluid.Executor(self._place)
def create(config):
_config = envs.load_yaml(config)
envs.set_global_envs(_config)
envs.update_workspace()
trainer = TrainerFactory._build_trainer(config)
return trainer
def __init__(self, config):
dg.MultiSlotDataGenerator.__init__(self)
_config = envs.load_yaml(config)
envs.set_global_envs(_config)
envs.update_workspace()