示例#1
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文件: train.py 项目: RunOrVeith/FGG
    def modify_config(self, config: FaceGroupingConfig, i):
        if i < self.num_runs / 2:
            config.dataset = self.bf
        else:
            config.dataset = self.bbt

        return super().modify_config(config, i)
示例#2
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    def modify_config(self, config: FaceGroupingConfig, i):
        if i < 6:
            config.dataset = BigBangTheory(episode_index_test=i)
        else:
            config.dataset = Buffy(episode_index_test=i - 6)

        return super().modify_config(config, i)
示例#3
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 def modify_config(self, config: FaceGroupingConfig, i):
     from FGG.dataset.split_strategy import SplitEveryXFrames
     x = 10
     config.graph_builder_params["split_strategy"] = SplitEveryXFrames(x=x)
     config.pool_before_clustering = True
     config.dataset = Buffy(episode_index_val=None,
                            episode_index_train=None,
                            episode_index_test=i)
     return (str(x), *super().modify_config(config, i))
示例#4
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文件: train.py 项目: RunOrVeith/FGG
 def modify_config(self, config: FaceGroupingConfig, i):
     config.dataset = self.accio
     config.model_params["sparse_adjacency"] = True
     return (str(self.num_clusters), *super().modify_config(config, i))
示例#5
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文件: train.py 项目: RunOrVeith/FGG
 def modify_config(self, config: FaceGroupingConfig, i):
     config.dataset = self.bf
     return super().create_model_name(config, i)
示例#6
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 def modify_config(self, config: FaceGroupingConfig, i):
     config.dataset = self.dataset
     return super().modify_config(config, i)
示例#7
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 def modify_config(self, config: FaceGroupingConfig, i):
     config.dataset = Buffy(episode_index_test=i)
     return super().modify_config(config, i)
示例#8
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 def modify_config(self, config: FaceGroupingConfig, i):
     config.dataset = Accio()
     config.model_params["sparse_adjacency"] = True
     return super().modify_config(config, i)