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seq_tag #54
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seq_tag #54
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guoshengCS
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Apr 26, 2020
| test_generator = create_lexnet_data_generator( | ||
| args, reader=dataset, file_name=test_path, place=place, mode="test") | ||
| feed_list = None if args.dynamic else [ | ||
| x.forward() for x in inputs + labels |
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No need to set feed_list anymore, maybe delete this later.
| param_attr=fluid.ParamAttr( | ||
| initializer=fluid.initializer.UniformInitializer( | ||
| low=-init_bound, high=init_bound), | ||
| regularizer=fluid.regularizer.L2DecayRegularizer( |
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Should we make initializer and regularizer optional, maybe we can expose param_attr=None, bias_attr=None as other layers
| self.reset() | ||
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| def add_metric_op(self, *args): | ||
| def add_metric_op(self, *args): |
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Can we use fluid.layers.chunk_eval here, is there any specific purpose to wrap a Chunk_eval class
guoshengCS
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Apr 26, 2020
jinyuKING
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Apr 27, 2020
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1、升级sequence_tagging中rnn模型
2、更新Dataloader;
3、新增模型；