fix single card dist (#1889)

* fix single card logit

* fix distillation yaml files

ppcls/configs/ImageNet/Distillation/mv3_large_x1_0_distill_mv3_small_x1_0.yaml

@@ -49,9 +49,8 @@ Loss:
         model_name_pairs:
         - ["Student", "Teacher"]
   Eval:
-    - DistillationGTCELoss:
+    - CELoss:
         weight: 1.0
-        model_names: ["Student"]
         
 
 Optimizer:

ppcls/configs/ImageNet/Distillation/resnet34_distill_resnet18_afd.yaml

@@ -88,10 +88,8 @@ Loss:
         s_shapes: *s_shapes
         t_shapes: *t_shapes
   Eval:
-    - DistillationGTCELoss:
+    - CELoss:
         weight: 1.0
-        model_names: ["Student"]
-        
 
 Optimizer:
   name: Momentum

ppcls/engine/evaluation/classification.py

@@ -80,22 +80,17 @@ def classification_eval(engine, epoch_id=0):
         current_samples = batch_size * paddle.distributed.get_world_size()
         accum_samples += current_samples
 
+        if isinstance(out, dict) and "Student" in out:
+            out = out["Student"]
+        if isinstance(out, dict) and "logits" in out:
+            out = out["logits"]
+
         # gather Tensor when distributed
         if paddle.distributed.get_world_size() > 1:
             label_list = []
             paddle.distributed.all_gather(label_list, batch[1])
             labels = paddle.concat(label_list, 0)
 
-            if isinstance(out, dict):
-                if "Student" in out:
-                    out = out["Student"]
-                    if isinstance(out, dict):
-                        out = out["logits"]
-                elif "logits" in out:
-                    out = out["logits"]
-                else:
-                    msg = "Error: Wrong key in out!"
-                    raise Exception(msg)
             if isinstance(out, list):
                 preds = []
                 for x in out:

ppcls/optimizer/__init__.py

@@ -118,8 +118,6 @@ def build_optimizer(config, epochs, step_each_epoch, model_list=None):
                     if hasattr(model_list[i], optim_scope):
                         optim_model.append(getattr(model_list[i], optim_scope))
 
-        assert len(optim_model) == 1, \
-            "Invalid optim model for optim scope({}), number of optim_model={}".format(optim_scope, len(optim_model))
         optim = getattr(optimizer, optim_name)(
             learning_rate=lr, grad_clip=grad_clip,
             **optim_cfg)(model_list=optim_model)