将 Events 修改为小写

fastNLP/core/callbacks/callback_events.py

@@ -74,30 +74,30 @@ class EventEnum(_SingleEventState, Enum):
 
 @unique
 class Events(EventEnum):
-    ON_AFTER_TRAINER_INITIALIZED = "on_after_trainer_initialized"
-    ON_SANITY_CHECK_BEGIN = "on_sanity_check_begin"
-    ON_SANITY_CHECK_END = "on_sanity_check_end"
-    ON_TRAIN_BEGIN = "on_train_begin"
-    ON_TRAIN_END = "on_train_end"
-    ON_TRAIN_EPOCH_BEGIN = "on_train_epoch_begin"
-    ON_TRAIN_EPOCH_END = "on_train_epoch_end"
-    ON_FETCH_DATA_BEGIN = "on_fetch_data_begin"
-    ON_FETCH_DATA_END = "on_fetch_data_end"
-    ON_TRAIN_BATCH_BEGIN = "on_train_batch_begin"
-    ON_TRAIN_BATCH_END = "on_train_batch_end"
-    ON_EXCEPTION = "on_exception"
-    ON_SAVE_MODEL = "on_save_model"
-    ON_LOAD_MODEL = "on_load_model"
-    ON_SAVE_CHECKPOINT = "on_save_checkpoint"
-    ON_LOAD_CHECKPOINT = "on_load_checkpoint"
-    ON_BEFORE_BACKWARD = "on_before_backward"
-    ON_AFTER_BACKWARD = "on_after_backward"
-    ON_BEFORE_OPTIMIZERS_STEP = "on_before_optimizers_step"
-    ON_AFTER_OPTIMIZERS_STEP = "on_after_optimizers_step"
-    ON_BEFORE_ZERO_GRAD = "on_before_zero_grad"
-    ON_AFTER_ZERO_GRAD = "on_after_zero_grad"
-    ON_VALIDATE_BEGIN = "on_validate_begin"
-    ON_VALIDATE_END = "on_validate_end"
+    on_after_trainer_initialized = "on_after_trainer_initialized"
+    on_sanity_check_begin = "on_sanity_check_begin"
+    on_sanity_check_end = "on_sanity_check_end"
+    on_train_begin = "on_train_begin"
+    on_train_end = "on_train_end"
+    on_train_epoch_begin = "on_train_epoch_begin"
+    on_train_epoch_end = "on_train_epoch_end"
+    on_fetch_data_begin = "on_fetch_data_begin"
+    on_fetch_data_end = "on_fetch_data_end"
+    on_train_batch_begin = "on_train_batch_begin"
+    on_train_batch_end = "on_train_batch_end"
+    on_exception = "on_exception"
+    on_save_model = "on_save_model"
+    on_load_model = "on_load_model"
+    on_save_checkpoint = "on_save_checkpoint"
+    on_load_checkpoint = "on_load_checkpoint"
+    on_before_backward = "on_before_backward"
+    on_after_backward = "on_after_backward"
+    on_before_optimizers_step = "on_before_optimizers_step"
+    on_after_optimizers_step = "on_after_optimizers_step"
+    on_before_zero_grad = "on_before_zero_grad"
+    on_after_zero_grad = "on_after_zero_grad"
+    on_validate_begin = "on_validate_begin"
+    on_validate_end = "on_validate_end"
 
 
 class EventsList:

tests/core/callbacks/test_checkpoint_callback_torch.py

@@ -238,7 +238,7 @@ def test_model_checkpoint_callback_2(
 
     from fastNLP.core.callbacks.callback_events import Events
 
-    @Trainer.on(Events.ON_TRAIN_EPOCH_END)
+    @Trainer.on(Events.on_train_epoch_end)
     def raise_exception(trainer):
         if trainer.driver.get_local_rank() == 0 and trainer.cur_epoch_idx == 4:
             raise NotImplementedError

tests/core/controllers/test_trainer_wo_evaluator_torch.py

@@ -254,7 +254,7 @@ def test_trainer_on_exception(
 ):
     from fastNLP.core.callbacks.callback_events import Events
 
-    @Trainer.on(Events.ON_TRAIN_EPOCH_END)
+    @Trainer.on(Events.on_train_epoch_end)
     def raise_exception(trainer):
         if trainer.driver.get_local_rank() == cur_rank:
             raise NotImplementedError