[MNT] only check output shape for classification, regression and feature extraction

learnware/market/easy.py

@@ -122,19 +122,20 @@ class EasyMarket(BaseMarket):
             inputs = np.random.randn(10, *input_shape)
             outputs = learnware.predict(inputs)
 
-            # check output type
-            if isinstance(outputs, torch.Tensor):
-                outputs = outputs.detach().cpu().numpy()
-            if not isinstance(outputs, np.ndarray):
-                logger.warning(f"The learnware [{learnware.id}] output must be np.ndarray or torch.Tensor")
-                return cls.NONUSABLE_LEARNWARE
-
-            # check output shape
+            # check output
             if outputs.ndim == 1:
                 outputs = outputs.reshape(-1, 1)
                 pass
             
             if semantic_spec['Task']['Values'][0] in ('Classification', 'Regression', 'Feature Extraction'):
+                # check output type
+                if isinstance(outputs, torch.Tensor):
+                    outputs = outputs.detach().cpu().numpy()
+                if not isinstance(outputs, np.ndarray):
+                    logger.warning(f"The learnware [{learnware.id}] output must be np.ndarray or torch.Tensor")
+                    return cls.NONUSABLE_LEARNWARE
+                
+                # check output shape
                 output_dim = int(semantic_spec['Output']['Dimension'])
                 if outputs[0].shape[0] != output_dim:
                     logger.warning(f"The learnware [{learnware.id}] input and output dimention is error")