添加了测试 函数式 callback 的test

tests/core/controllers/test_trainer_event_trigger.py

@@ -67,7 +67,7 @@ def model_and_optimizers():
 @pytest.mark.parametrize("callbacks", [[RecordTrainerEventTriggerCallback()]])
 @pytest.mark.torch
 @magic_argv_env_context
-def test_trainer_event_trigger(
+def test_trainer_event_trigger_1(
         model_and_optimizers: TrainerParameters,
         driver,
         device,
@@ -101,5 +101,126 @@ def test_trainer_event_trigger(
             assert member.value in output[0]
 
 
+@pytest.mark.parametrize("driver,device", [("torch", "cpu"),("torch", 6), ("torch", [6, 7])])  # , ("torch", 6), ("torch", [6, 7])
+@pytest.mark.torch
+@magic_argv_env_context
+def test_trainer_event_trigger_2(
+        model_and_optimizers: TrainerParameters,
+        driver,
+        device,
+        n_epochs=2,
+):
+
+    @Trainer.on(Events.on_after_trainer_initialized)
+    def on_after_trainer_initialized(trainer, driver):
+        print("on_after_trainer_initialized")
+
+    @Trainer.on(Events.on_sanity_check_begin)
+    def on_sanity_check_begin(trainer):
+        print("on_sanity_check_begin")
+
+    @Trainer.on(Events.on_sanity_check_end)
+    def on_sanity_check_end(trainer, sanity_check_res):
+        print("on_sanity_check_end")
+
+    @Trainer.on(Events.on_train_begin)
+    def on_train_begin(trainer):
+        print("on_train_begin")
+
+    @Trainer.on(Events.on_train_end)
+    def on_train_end(trainer):
+        print("on_train_end")
+
+    @Trainer.on(Events.on_train_epoch_begin)
+    def on_train_epoch_begin(trainer):
+        if trainer.cur_epoch_idx >= 1:
+            # 触发 on_exception；
+            raise Exception
+        print("on_train_epoch_begin")
+
+    @Trainer.on(Events.on_train_epoch_end)
+    def on_train_epoch_end(trainer):
+        print("on_train_epoch_end")
+
+    @Trainer.on(Events.on_fetch_data_begin)
+    def on_fetch_data_begin(trainer):
+        print("on_fetch_data_begin")
+
+    @Trainer.on(Events.on_fetch_data_end)
+    def on_fetch_data_end(trainer):
+        print("on_fetch_data_end")
+
+    @Trainer.on(Events.on_train_batch_begin)
+    def on_train_batch_begin(trainer, batch, indices=None):
+        print("on_train_batch_begin")
+
+    @Trainer.on(Events.on_train_batch_end)
+    def on_train_batch_end(trainer):
+        print("on_train_batch_end")
+
+    @Trainer.on(Events.on_exception)
+    def on_exception(trainer, exception):
+        print("on_exception")
+
+    @Trainer.on(Events.on_before_backward)
+    def on_before_backward(trainer, outputs):
+        print("on_before_backward")
+
+    @Trainer.on(Events.on_after_backward)
+    def on_after_backward(trainer):
+        print("on_after_backward")
+
+    @Trainer.on(Events.on_before_optimizers_step)
+    def on_before_optimizers_step(trainer, optimizers):
+        print("on_before_optimizers_step")
+
+    @Trainer.on(Events.on_after_optimizers_step)
+    def on_after_optimizers_step(trainer, optimizers):
+        print("on_after_optimizers_step")
+
+    @Trainer.on(Events.on_before_zero_grad)
+    def on_before_zero_grad(trainer, optimizers):
+        print("on_before_zero_grad")
+
+    @Trainer.on(Events.on_after_zero_grad)
+    def on_after_zero_grad(trainer, optimizers):
+        print("on_after_zero_grad")
+
+    @Trainer.on(Events.on_evaluate_begin)
+    def on_evaluate_begin(trainer):
+        print("on_evaluate_begin")
+
+    @Trainer.on(Events.on_evaluate_end)
+    def on_evaluate_end(trainer, results):
+        print("on_evaluate_end")
+
+    with pytest.raises(Exception):
+        with Capturing() as output:
+            trainer = Trainer(
+                model=model_and_optimizers.model,
+                driver=driver,
+                device=device,
+                optimizers=model_and_optimizers.optimizers,
+                train_dataloader=model_and_optimizers.train_dataloader,
+                evaluate_dataloaders=model_and_optimizers.evaluate_dataloaders,
+                input_mapping=model_and_optimizers.input_mapping,
+                output_mapping=model_and_optimizers.output_mapping,
+                metrics=model_and_optimizers.metrics,
+
+                n_epochs=n_epochs,
+            )
+
+            trainer.run()
+
+            if dist.is_initialized():
+                dist.destroy_process_group()
+
+        for name, member in Events.__members__.items():
+            assert member.value in output[0]
+
+
+
+
+