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@@ -220,28 +220,7 @@ class Main(object):
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self.train_result_dict["speed"].append(epoch_speed)
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model_dir = "{}/{}".format(save_model_path, epoch)
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- if paddle.distributed.get_rank() == 0:
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- # 1. 确保所有 worker 同步
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- fleet.barrier_worker()
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-
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- # 2. 获取主程序
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- main_program = paddle.static.default_main_program()
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-
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- # 3. 使用 paddle.static.save_inference_model 替代 fleet.save_inference_model
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- paddle.static.save_inference_model(
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- model_dir,
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- [feed.name for feed in self.inference_feed_var],
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- self.inference_target_var,
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- self.exe,
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- program=main_program, # 使用 fleet 的主程序
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- export_for_deployment=True # 保存为新格式
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- )
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-
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- # 4. 再次同步确保保存完成
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- fleet.barrier_worker()
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-
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- """
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if is_distributed_env():
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fleet.save_inference_model(
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self.exe, model_dir,
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@@ -253,7 +232,7 @@ class Main(object):
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model_dir,
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[feed.name for feed in self.inference_feed_var],
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[self.inference_target_var], self.exe)
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- """
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+
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if reader_type == "InmemoryDataset":
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self.reader.release_memory()
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often