fix test

fastNLP/core/callbacks/callback_events.py

@@ -4,8 +4,6 @@ from types import DynamicClassAttribute
 from functools import wraps
 
 
-import fastNLP
-
 __all__ = [
     'Events',
     'EventsList',

fastNLP/core/callbacks/callback_manager.py

@@ -11,6 +11,7 @@ from .callback import Callback
 from fastNLP.core.log import logger
 from .progress_callback import ProgressCallback, choose_progress_callback
 from fastNLP.envs import rank_zero_call
+from fastNLP.core.utils.utils import _get_fun_msg
 
 
 def _transfer(func):
@@ -21,10 +22,12 @@ def _transfer(func):
 
     def wrapper(manager, *arg, **kwargs):
         manager.callback_counter[func.__name__] += 1  # 给实际被调用的 callback_fn 的计数加 1；
-        returns = []
         for callback_fn in manager.callback_fns[func.__name__]:
-            returns.append(callback_fn(*arg, **kwargs))
-        return returns
+            try:
+                callback_fn(*arg, **kwargs)
+            except BaseException as e:
+                logger.error(f"The following callback_fn raise exception:{_get_fun_msg(callback_fn)}.")
+                raise e
     return wrapper
 
 

tests/core/controllers/test_trainer_paddle.py

@@ -11,7 +11,6 @@ from paddle.io import DataLoader
 
 from tests.helpers.models.paddle_model import PaddleNormalModel_Classification_1
 from tests.helpers.datasets.paddle_data import PaddleRandomMaxDataset
-from tests.helpers.callbacks.helper_callbacks import RecordLossCallback, RecordMetricCallback
 from tests.helpers.utils import magic_argv_env_context
 
 @dataclass

tests/core/controllers/test_trainer_w_evaluator_torch.py

@@ -100,17 +100,16 @@ def model_and_optimizers(request):
 # 测试一下普通的情况；
 @pytest.mark.torch
 @pytest.mark.parametrize("driver,device", [("torch", "cpu"), ("torch", 1), ("torch", [0, 1])])  #  ("torch", "cpu"), ("torch", 1), ("torch", [0, 1])
-@pytest.mark.parametrize("callbacks", [[RecordMetricCallback(monitor="acc", metric_threshold=0.2, larger_better=True)]])
 @pytest.mark.parametrize("evaluate_every", [-3, -1, 100])
 @magic_argv_env_context
 def test_trainer_torch_with_evaluator(
         model_and_optimizers: TrainerParameters,
         driver,
         device,
-        callbacks,
         evaluate_every,
         n_epochs=10,
 ):
+    callbacks = [RecordMetricCallback(monitor="acc", metric_threshold=0.2, larger_better=True)]
     trainer = Trainer(
         model=model_and_optimizers.model,
         driver=driver,
@@ -172,7 +171,7 @@ def test_trainer_torch_with_evaluator_fp16_accumulation_steps(
     if dist.is_initialized():
         dist.destroy_process_group()
 
-
+@pytest.mark.torch
 @pytest.mark.parametrize("driver,device", [("torch", 1)])  # ("torch", [0, 1]),("torch", 1)
 @magic_argv_env_context
 def test_trainer_validate_every(
@@ -184,9 +183,7 @@ def test_trainer_validate_every(
 
     def validate_every(trainer):
         if trainer.global_forward_batches % 10 == 0:
-            print(trainer)
             print("\nfastNLP test validate every.\n")
-            print(trainer.global_forward_batches)
             return True
 
     trainer = Trainer(

tests/helpers/callbacks/helper_callbacks.py

@@ -36,12 +36,10 @@ class RecordMetricCallback(Callback):
         self.larger_better = larger_better
         self.metric = None
         self.metric_threshold = metric_threshold
-        self.metric_begin_value = None
+        self.metric_begin_value = float('-inf') if larger_better else float('inf')
 
     def on_evaluate_end(self, trainer, results):
         self.metric = results[self.monitor]
-        if self.metric_begin_value is None:
-            self.metric_begin_value = self.metric
 
     def on_train_end(self, trainer):
         if self.larger_better:

tests/helpers/utils.py

@@ -30,12 +30,12 @@ def recover_logger(fn):
     return wrapper
 
 
-def magic_argv_env_context(fn=None, timeout=600):
+def magic_argv_env_context(fn=None, timeout=300):
     """
     用来在测试时包裹每一个单独的测试函数，使得 ddp 测试正确；
     会丢掉 pytest 中的 arg 参数。
 
-    :param timeout: 表示一个测试如果经过多久还没有通过的话就主动将其 kill 掉，默认为 10 分钟，单位为秒；
+    :param timeout: 表示一个测试如果经过多久还没有通过的话就主动将其 kill 掉，默认为 5 分钟，单位为秒；
     :return:
     """
     # 说明是通过 @magic_argv_env_context(timeout=600) 调用；