def __init__(self, config):
"""R
"""
Trainer.__init__(self, config)
config['output_path'] = util.get_absolute_path(
config['output_path'], config['io']['afs'])
self.global_config = config
self._metrics = {}
self._path_generator = util.PathGenerator({
'templates': [
{'name': 'xbox_base_done', 'template': config['output_path'] + '/xbox_base_done.txt'},
{'name': 'xbox_delta_done', 'template': config['output_path'] + '/xbox_patch_done.txt'},
{'name': 'xbox_base', 'template': config['output_path'] + '/xbox/{day}/base/'},
{'name': 'xbox_delta', 'template': config['output_path'] + '/xbox/{day}/delta-{pass_id}/'},
{'name': 'batch_model', 'template': config['output_path'] + '/batch_model/{day}/{pass_id}/'}
]
})
if 'path_generator' in config:
self._path_generator.add_path_template(config['path_generator'])
self.regist_context_processor('uninit', self.init)
self.regist_context_processor('startup', self.startup)
self.regist_context_processor('begin_day', self.begin_day)
self.regist_context_processor('train_pass', self.train_pass)
self.regist_context_processor('end_day', self.end_day)
def __init__(self, config):
"""R
"""
Trainer.__init__(self, config)
self.global_config = config
self._metrics = {}
self.processor_register()
def __init__(self, config=None):
Trainer.__init__(self, config)
device = envs.get_global_env("train.device", "cpu")
if device == 'gpu':
self._place = fluid.CUDAPlace(0)
self._exe = fluid.Executor(self._place)
self.processor_register()
self.model = None
self.inference_models = []
self.increment_models = []
def __init__(self, config=None):
Trainer.__init__(self, config)
self.processor_register()
self.abs_dir = os.path.dirname(os.path.abspath(__file__))
self.runner_env_name = "runner." + self._context["runner_name"]