modify 0.7

mindspore/train/model.py

@@ -37,6 +37,16 @@ from .dataset_helper import DatasetHelper
 from . import amp
 
 
+def _transfer_tensor_to_tuple(inputs):
+    """
+    If the input is a tensor, convert it to a tuple. If not, the output is unchanged.
+    """
+    if isinstance(inputs, Tensor):
+        return (inputs,)
+
+    return inputs
+
+
 class Model:
     """
     High-Level API for Training or Testing.
@@ -386,15 +396,6 @@ class Model:
 
         return [callbacks]
 
-    def _transfer_tensor_to_tuple(self, inputs):
-        """
-        If the input is a tensor, convert it to a tuple. If not, the output is unchanged.
-        """
-        if isinstance(inputs, Tensor):
-            return (inputs,)
-
-        return inputs
-
     def _train_dataset_sink_process(self, epoch, train_dataset, list_callback=None, cb_params=None, sink_size=-1):
         """
         Training process. The data would be passed to network through dataset channel.
@@ -437,7 +438,6 @@ class Model:
 
             # for data sink dataset_helper only iter once, other wise iter epoch_size times.
             for inputs in dataset_helper:
-                inputs = self._transfer_tensor_to_tuple(inputs)
                 if _need_to_full() and context.get_context("device_target") == "GPU":
                     inputs = _to_full_tensor(inputs, self._device_number, self._global_rank)
                 list_callback.step_begin(run_context)
@@ -485,7 +485,7 @@ class Model:
             list_callback.epoch_begin(run_context)
 
             for next_element in dataset_helper:
-                next_element = self._transfer_tensor_to_tuple(next_element)
+                next_element = _transfer_tensor_to_tuple(next_element)
                 len_element = len(next_element)
                 if self._loss_fn and len_element != 2:
                     raise ValueError("when loss_fn is not None, train_dataset should"
@@ -603,7 +603,6 @@ class Model:
         list_callback.begin(run_context)
 
         for inputs in dataset_helper:
-            inputs = self._transfer_tensor_to_tuple(inputs)
             cb_params.cur_step_num += 1
             list_callback.step_begin(run_context)
 
@@ -642,7 +641,7 @@ class Model:
         for next_element in dataset_helper:
             cb_params.cur_step_num += 1
             list_callback.step_begin(run_context)
-            next_element = self._transfer_tensor_to_tuple(next_element)
+            next_element = _transfer_tensor_to_tuple(next_element)
             outputs = self._eval_network(*next_element)
             cb_params.net_outputs = outputs
             list_callback.step_end(run_context)