From 6f402b9cddb3eda5f740aad97a94a04c58a70564 Mon Sep 17 00:00:00 2001 From: yh_cc Date: Fri, 6 May 2022 00:50:37 +0800 Subject: [PATCH] =?UTF-8?q?=E4=BC=98=E5=8C=96=E9=83=A8=E5=88=86warning?= =?UTF-8?q?=E6=98=BE=E7=A4=BA?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- fastNLP/core/callbacks/has_monitor_callback.py | 6 +++--- fastNLP/core/callbacks/topk_saver.py | 2 +- fastNLP/core/controllers/evaluator.py | 2 +- fastNLP/core/controllers/trainer.py | 4 ++-- .../drivers/paddle_driver/initialize_paddle_driver.py | 4 ++-- fastNLP/core/drivers/paddle_driver/paddle_driver.py | 8 ++++---- fastNLP/core/drivers/paddle_driver/utils.py | 2 +- fastNLP/core/drivers/torch_driver/torch_driver.py | 4 ++-- fastNLP/core/drivers/torch_driver/utils.py | 4 ++-- fastNLP/core/log/logger.py | 7 +++++-- fastNLP/core/utils/cache_results.py | 3 ++- fastNLP/core/utils/utils.py | 2 +- 12 files changed, 26 insertions(+), 22 deletions(-) diff --git a/fastNLP/core/callbacks/has_monitor_callback.py b/fastNLP/core/callbacks/has_monitor_callback.py index c5c5edde..8e5eb0aa 100644 --- a/fastNLP/core/callbacks/has_monitor_callback.py +++ b/fastNLP/core/callbacks/has_monitor_callback.py @@ -78,11 +78,11 @@ class MonitorUtility: return monitor_value # 第一次运行 if isinstance(self.monitor, str) and self._real_monitor == self.monitor and use_monitor != self.monitor: - logger.warning(f"We can not find `{self.monitor}` in the evaluation result (with keys as {list(results.keys())}), " - f"we use the `{use_monitor}` as the monitor for `{self.__class__.__name__}`.") + logger.rank_zero_warning(f"We can not find `{self.monitor}` in the evaluation result (with keys as " + f"{list(results.keys())}), we use the `{use_monitor}` as the monitor.", once=True) # 检测到此次和上次不同。 elif isinstance(self.monitor, str) and self._real_monitor != self.monitor and use_monitor != self._real_monitor: - logger.warning(f"Change of monitor detected for `{self.__class__.__name__}`. " + logger.rank_zero_warning(f"Change of monitor detected for `{self.__class__.__name__}`. " f"The expected monitor is:`{self.monitor}`, last used monitor is:" f"`{self._real_monitor}` and current monitor is:`{use_monitor}`. Please consider using a " f"customized monitor function when the evaluation results are varying between validation.") diff --git a/fastNLP/core/callbacks/topk_saver.py b/fastNLP/core/callbacks/topk_saver.py index 25e66cb9..bd630836 100644 --- a/fastNLP/core/callbacks/topk_saver.py +++ b/fastNLP/core/callbacks/topk_saver.py @@ -32,7 +32,7 @@ class Saver: :param kwargs: 更多需要传递给 Trainer.save() 或者 Trainer.save_model() 接口的参数。 """ if folder is None: - logger.warning( + logger.rank_zero_warning( "Parameter `folder` is None, and we will use the current work directory to find and load your model.") folder = Path.cwd() folder = Path(folder) diff --git a/fastNLP/core/controllers/evaluator.py b/fastNLP/core/controllers/evaluator.py index 4dba8a4c..70c7fbd0 100644 --- a/fastNLP/core/controllers/evaluator.py +++ b/fastNLP/core/controllers/evaluator.py @@ -221,7 +221,7 @@ class Evaluator: @evaluate_batch_loop.setter def evaluate_batch_loop(self, loop: Loop): if self.evaluate_batch_step_fn is not None: - logger.warning("`evaluate_batch_step_fn` was customized in the Evaluator initialization, it will be ignored " + logger.rank_zero_warning("`evaluate_batch_step_fn` was customized in the Evaluator initialization, it will be ignored " "when the `evaluate_batch_loop` is also customized.") self._evaluate_batch_loop = loop diff --git a/fastNLP/core/controllers/trainer.py b/fastNLP/core/controllers/trainer.py index f720fe5b..8fd3c65e 100644 --- a/fastNLP/core/controllers/trainer.py +++ b/fastNLP/core/controllers/trainer.py @@ -305,7 +305,7 @@ class Trainer(TrainerEventTrigger): else: if self.driver.is_distributed(): if catch_KeyboardInterrupt: - logger.warning("Parameter `catch_KeyboardInterrupt` can only be False when you are using multi-device " + logger.rank_zero_warning("Parameter `catch_KeyboardInterrupt` can only be False when you are using multi-device " "driver. And we are gonna to set it to False.") catch_KeyboardInterrupt = False @@ -535,7 +535,7 @@ class Trainer(TrainerEventTrigger): _not_called_callback_fns.append(each_callback_fn) if check_mode: - logger.warning("You have customized your 'batch_step_fn' in the 'train_batch_loop' and also use these " + logger.rank_zero_warning("You have customized your 'batch_step_fn' in the 'train_batch_loop' and also use these " f"callback_fns: {_not_called_callback_fns}, but it seems that" "you don't call the corresponding callback hook explicitly in your 'batch_step_fn'.") # 对于 'batch_step_fn' 来讲，其只需要在第一次的 step 后进行检测即可，因此在第一次检测后将 check_batch_step_fn 置为 pass diff --git a/fastNLP/core/drivers/paddle_driver/initialize_paddle_driver.py b/fastNLP/core/drivers/paddle_driver/initialize_paddle_driver.py index 46f51b9c..66da8cf1 100644 --- a/fastNLP/core/drivers/paddle_driver/initialize_paddle_driver.py +++ b/fastNLP/core/drivers/paddle_driver/initialize_paddle_driver.py @@ -69,7 +69,7 @@ def initialize_paddle_driver(driver: str, device: Optional[Union[str, int, List[ if not isinstance(device, List): return PaddleSingleDriver(model, device, **kwargs) else: - logger.warning("Notice you are using `paddle` driver but your chosen `device` are multi gpus, we will use" + logger.rank_zero_warning("Notice you are using `paddle` driver but your chosen `device` are multi gpus, we will use" "`Fleetriver` by default. But if you mean using `PaddleFleetDriver`, you should choose parameter" "`driver` as `PaddleFleetDriver`.") return PaddleFleetDriver(model, device, **kwargs) @@ -77,7 +77,7 @@ def initialize_paddle_driver(driver: str, device: Optional[Union[str, int, List[ if not isinstance(device, List): if device == "cpu": raise ValueError("You are using `fleet` driver, but your chosen `device` is 'cpu'.") - logger.warning("Notice you are using `fleet` driver, but your chosen `device` is only one gpu, we will" + logger.rank_zero_warning("Notice you are using `fleet` driver, but your chosen `device` is only one gpu, we will" "still use `PaddleFleetDriver` for you, but if you mean using `PaddleSingleDriver`, you should " "choose `paddle` driver.") return PaddleFleetDriver(model, [device], **kwargs) diff --git a/fastNLP/core/drivers/paddle_driver/paddle_driver.py b/fastNLP/core/drivers/paddle_driver/paddle_driver.py index 48ff9de1..795cb7bf 100644 --- a/fastNLP/core/drivers/paddle_driver/paddle_driver.py +++ b/fastNLP/core/drivers/paddle_driver/paddle_driver.py @@ -72,7 +72,7 @@ class PaddleDriver(Driver): :param set_to_none: 用来判断是否需要将梯度直接置为 None；Paddle中这个参数无效。 """ if set_to_none: - logger.warning_once("Parameter `set_to_none` does nothing in paddle since grad cannot be set directly.") + logger.rank_zero_warning("Parameter `set_to_none` does nothing in paddle since grad cannot be set directly.") for optimizer in self.optimizers: optimizer.clear_grad() @@ -256,7 +256,7 @@ class PaddleDriver(Driver): if dataloader_args.batch_size is not None: num_consumed_batches = num_consumed_batches * dataloader_args.batch_size else: # 有可能 batch_size 为 None，就只有损失精度了 - logger.warning("fastNLP cannot get batch_size, we have to save based on `num_consumed_samples`, " + logger.rank_zero_warning("fastNLP cannot get batch_size, we have to save based on `num_consumed_samples`, " "it may cause missing some samples when reload.") num_consumed_batches = sampler_states['num_consumed_samples'] sampler_states['num_consumed_samples'] = num_consumed_samples_array[num_consumed_batches] @@ -266,7 +266,7 @@ class PaddleDriver(Driver): sampler_states['num_consumed_samples'] = sampler.num_replicas * dataloader_args.batch_size \ * num_consumed_batches else: - logger.warning("fastNLP cannot get batch_size, we have to save based on `num_consumed_samples`, " + logger.rank_zero_warning("fastNLP cannot get batch_size, we have to save based on `num_consumed_samples`, " "it may cause missing some samples when reload.") else: raise RuntimeError( @@ -329,7 +329,7 @@ class PaddleDriver(Driver): self.grad_scaler.load_state_dict(grad_scaler_state_dict) logger.debug("Load grad_scaler state dict...") elif not isinstance(self.grad_scaler, DummyGradScaler): - logger.warning(f"Checkpoint {folder} is not trained with fp16=True, while resume to a fp16=True training, " + logger.rank_zero_warning(f"Checkpoint {folder} is not trained with fp16=True, while resume to a fp16=True training, " f"the training process may be unstable.") # 4. 恢复 sampler 的状态； diff --git a/fastNLP/core/drivers/paddle_driver/utils.py b/fastNLP/core/drivers/paddle_driver/utils.py index 60d243e7..6362193e 100644 --- a/fastNLP/core/drivers/paddle_driver/utils.py +++ b/fastNLP/core/drivers/paddle_driver/utils.py @@ -51,7 +51,7 @@ def paddle_seed_everything(seed: Optional[int] = None, workers: bool = False) -> seed = int(seed) if not (min_seed_value <= seed <= max_seed_value): - logger.warning("Your seed value is two big or two small for numpy, we will choose a random seed for " + logger.rank_zero_warning("Your seed value is two big or two small for numpy, we will choose a random seed for " "you.") # rank_zero_warn(f"{seed} is not in bounds, numpy accepts from {min_seed_value} to {max_seed_value}") diff --git a/fastNLP/core/drivers/torch_driver/torch_driver.py b/fastNLP/core/drivers/torch_driver/torch_driver.py index 8c332251..382ac2c1 100644 --- a/fastNLP/core/drivers/torch_driver/torch_driver.py +++ b/fastNLP/core/drivers/torch_driver/torch_driver.py @@ -197,7 +197,7 @@ class TorchDriver(Driver): if dataloader_args.batch_size is not None: num_consumed_batches = num_consumed_batches * dataloader_args.batch_size else: # 有可能 batch_size 为 None，就只有损失精度了 - logger.warning("fastNLP cannot get batch_size, we have to save based on `num_consumed_samples`, " + logger.rank_zero_warning("fastNLP cannot get batch_size, we have to save based on `num_consumed_samples`, " "it may cause missing some samples when reload.") num_consumed_batches = sampler_states['num_consumed_samples'] sampler_states['num_consumed_samples'] = num_consumed_samples_array[num_consumed_batches] @@ -207,7 +207,7 @@ class TorchDriver(Driver): sampler_states['num_consumed_samples'] = sampler.num_replicas * dataloader_args.batch_size \ * num_consumed_batches else: - logger.warning("fastNLP cannot get batch_size, we have to save based on `num_consumed_samples`, " + logger.rank_zero_warning("fastNLP cannot get batch_size, we have to save based on `num_consumed_samples`, " "it may cause missing some samples when reload.") states['sampler_states'] = sampler_states diff --git a/fastNLP/core/drivers/torch_driver/utils.py b/fastNLP/core/drivers/torch_driver/utils.py index 941e4445..d756cf77 100644 --- a/fastNLP/core/drivers/torch_driver/utils.py +++ b/fastNLP/core/drivers/torch_driver/utils.py @@ -60,7 +60,7 @@ def torch_seed_everything(seed: Optional[int] = None, workers: bool = False) -> seed = int(seed) if not (min_seed_value <= seed <= max_seed_value): - logger.warning("Your seed value is two big or two small for numpy, we will choose a random seed for you.") + logger.rank_zero_warning("Your seed value is two big or two small for numpy, we will choose a random seed for you.") seed = _select_seed_randomly(min_seed_value, max_seed_value) @@ -162,7 +162,7 @@ def _build_fp16_env(dummy=False): if not torch.cuda.is_available(): raise RuntimeError("No cuda") if torch.cuda.get_device_capability(0)[0] < 7: - logger.warning( + logger.rank_zero_warning( "NOTE: your device does NOT support faster training with fp16, " "please switch to FP32 which is likely to be faster" ) diff --git a/fastNLP/core/log/logger.py b/fastNLP/core/log/logger.py index 6610b30c..eea54f36 100644 --- a/fastNLP/core/log/logger.py +++ b/fastNLP/core/log/logger.py @@ -124,18 +124,21 @@ class FastNLPLogger(logging.Logger, metaclass=LoggerSingleton): self._log(WARNING, msg, args, **kwargs) self._warning_msgs.add(msg) - def rank_zero_warning(self, msg, *args, **kwargs): + def rank_zero_warning(self, msg, *args, once=False, **kwargs): """ 只在 rank 0 上 warning 。 :param msg: :param args: + :param once: 是否只 warning 一次 :param kwargs: :return: """ if os.environ.get(FASTNLP_GLOBAL_RANK, '0') == '0': + if once and msg in self._warning_msgs: + return if self.isEnabledFor(WARNING): - # kwargs = self._add_rank_info(kwargs) + kwargs = self._add_rank_info(kwargs) self._log(WARNING, msg, args, **kwargs) def warn(self, msg, *args, **kwargs): diff --git a/fastNLP/core/utils/cache_results.py b/fastNLP/core/utils/cache_results.py index f8d34bc9..cde4a51e 100644 --- a/fastNLP/core/utils/cache_results.py +++ b/fastNLP/core/utils/cache_results.py @@ -15,6 +15,7 @@ __all__ = [ from fastNLP.core.log.logger import logger from fastNLP.core.log.highlighter import ColorHighlighter +from .utils import _get_fun_msg class FuncCallVisitor(ast.NodeVisitor): @@ -306,7 +307,7 @@ def cache_results(_cache_fp, _hash_param=True, _refresh=False, _verbose=1, _chec if verbose == 1: logger.info("Read cache from {} (Saved on {}).".format(cache_filepath, save_time)) if check_hash and old_hash_code != new_hash_code: - logger.warning(f"The function `{func.__name__}` is different from its last cache (Save on {save_time}). The " + logger.warning(f"The function {_get_fun_msg(func)} is different from its last cache (Save on {save_time}). The " f"difference may caused by the sourcecode change.", extra={'highlighter': ColorHighlighter('red')}) refresh_flag = False diff --git a/fastNLP/core/utils/utils.py b/fastNLP/core/utils/utils.py index 93f38e2a..c894131d 100644 --- a/fastNLP/core/utils/utils.py +++ b/fastNLP/core/utils/utils.py @@ -239,7 +239,7 @@ def check_user_specific_params(user_params: Dict, fn: Callable): fn_arg_names = get_fn_arg_names(fn) for arg_name, arg_value in user_params.items(): if arg_name not in fn_arg_names: - logger.warning(f"Notice your specific parameter `{arg_name}` is not used by function `{fn.__name__}`.") + logger.rank_zero_warning(f"Notice your specific parameter `{arg_name}` is not used by function `{fn.__name__}`.") return user_params