- release the wait if training is ended

mindspore/ccsrc/minddata/dataset/callback/py_ds_callback.cc

@@ -53,7 +53,11 @@ Status PyDSCallback::ExecutePyfunc(py::function f, const CallbackParam &cb_param
     if (Py_IsInitialized() == 0) {
       return Status(StatusCode::kPythonInterpreterFailure, "Python Interpreter is finalized");
     }
+    try {
       f(cb_param);
+    } catch (const py::error_already_set &e) {
+      return Status(StatusCode::kPyFuncException, e.what());
+    }
   }
   return Status::OK();
 }

mindspore/dataset/callback/ds_callback.py

@@ -144,6 +144,8 @@ class WaitedDSCallback(Callback, DSCallback):
         self.epoch_event = threading.Event()
         self.epoch_run_context = None
 
+        self.training_ended = False
+
     def sync_epoch_begin(self, train_run_context, ds_run_context):
         """
         Called before a new dataset epoch is started and after the previous training epoch is ended.
@@ -180,6 +182,7 @@ class WaitedDSCallback(Callback, DSCallback):
           ds_run_context: Include some information of the pipeline.
         """
         if ds_run_context.cur_epoch_num > 1:
+            if not self.training_ended:
                 success = self.epoch_event.wait(timeout=ds.config.get_callback_timeout())
                 self.epoch_event.clear()
                 if not success:
@@ -205,6 +208,7 @@ class WaitedDSCallback(Callback, DSCallback):
             ds_run_context: Include some information of the pipeline.
         """
         if ds_run_context.cur_step_num > self.step_size:
+            if not self.training_ended:
                 success = self.step_event.wait(timeout=ds.config.get_callback_timeout())
                 self.step_event.clear()
                 if not success:
@@ -233,3 +237,8 @@ class WaitedDSCallback(Callback, DSCallback):
             raise AttributeError("Provided Callback class did not override any of the 2 callback methods.")
 
         return c_cb
+
+    def end(self, run_context):
+        self.epoch_end(run_context)
+        self.step_end(run_context)
+        self.training_ended = True

tests/ut/python/dataset/test_callbacks.py

@@ -410,6 +410,22 @@ def test_callbacks_exceptions():
         assert "RuntimeError: Bad begin" in str(err.value)
 
 
+def test_callbacks_train_end():
+    logger.info("test_callback_sink_simulation")
+    # No asserts are needed, just test there is no deadlock or exceptions
+    events = []
+    epochs = 2
+
+    my_cb = MyWaitedCallback(events, 1)
+    data = ds.NumpySlicesDataset([1, 2, 3, 4], shuffle=False)
+    data = data.map(operations=(lambda x: x), callbacks=[my_cb])
+    data = data.to_device()
+    data.send(num_epochs=epochs)
+    time.sleep(0.5)
+    my_cb.end(run_context={})
+    time.sleep(0.5)
+
+
 def test_callbacks_one_cb():
     logger.info("test_callbacks_one_cb")
 
@@ -458,3 +474,4 @@ if __name__ == '__main__':
     test_callbacks_non_sink()
     test_callbacks_one_cb()
     test_callbacks_non_sink_mismatch_size()
+    test_callbacks_train_end()