fix googlenet infer

ppcls/engine/trainer.py

@@ -555,6 +555,8 @@ class Trainer(object):
             if len(batch_data) >= batch_size or idx == len(image_list) - 1:
                 batch_tensor = paddle.to_tensor(batch_data)
                 out = self.model(batch_tensor)
+                if isinstance(out, list):
+                    out = out[0]
                 result = postprocess_func(out, image_file_list)
                 print(result)
                 batch_data.clear()

tools/export_model.py

@@ -38,6 +38,7 @@ class ExportModel(nn.Layer):
 
     def __init__(self, config):
         super().__init__()
+        print (config)
         self.base_model = build_model(config)
 
         # we should choose a final model to export
@@ -63,6 +64,8 @@ class ExportModel(nn.Layer):
 
     def forward(self, x):
         x = self.base_model(x)
+        if isinstance(x, list):
+            x = x[0]
         if self.infer_model_name is not None:
             x = x[self.infer_model_name]
         if self.infer_output_key is not None:
@@ -76,7 +79,6 @@ if __name__ == "__main__":
     args = config.parse_args()
     config = config.get_config(
         args.config, overrides=args.override, show=False)
-
     log_file = os.path.join(config['Global']['output_dir'],
                             config["Arch"]["name"], "export.log")
     init_logger(name='root', log_file=log_file)
@@ -86,7 +88,6 @@ if __name__ == "__main__":
     assert config["Global"]["device"] in ["cpu", "gpu", "xpu"]
     device = paddle.set_device(config["Global"]["device"])
     model = ExportModel(config["Arch"])
-
     if config["Global"]["pretrained_model"] is not None:
         load_dygraph_pretrain(model.base_model,
                               config["Global"]["pretrained_model"])