From c67be2a42cb43b35255d994133c68a4a71d2f9c4 Mon Sep 17 00:00:00 2001 From: chengmo Date: Mon, 18 May 2020 20:37:58 +0800 Subject: [PATCH] update doc --- core/trainers/tdm_cluster_trainer.py | 16 +-- core/trainers/tdm_single_trainer.py | 20 ++-- doc/distributed_train.md | 5 +- doc/imgs/overview.png | Bin 549496 -> 749651 bytes doc/ps_background.md | 141 ++------------------------- readme.md | 88 +++++++++++------ 6 files changed, 81 insertions(+), 189 deletions(-) diff --git a/core/trainers/tdm_cluster_trainer.py b/core/trainers/tdm_cluster_trainer.py index 95d75971..f4edc62a 100755 --- a/core/trainers/tdm_cluster_trainer.py +++ b/core/trainers/tdm_cluster_trainer.py @@ -67,7 +67,7 @@ class TDMClusterTrainer(ClusterTrainer): # covert tree to tensor, set it into Fluid's variable. for param_name in special_param: param_t = fluid.global_scope().find_var(param_name).get_tensor() - param_array = self.tdm_prepare(param_name) + param_array = self._tdm_prepare(param_name) param_t.set(param_array.astype('int32'), self._place) if save_init_model: @@ -78,27 +78,27 @@ class TDMClusterTrainer(ClusterTrainer): context['status'] = 'train_pass' - def tdm_prepare(self, param_name): + def _tdm_prepare(self, param_name): if param_name == "TDM_Tree_Travel": - travel_array = self.tdm_travel_prepare() + travel_array = self._tdm_travel_prepare() return travel_array elif param_name == "TDM_Tree_Layer": - layer_array, _ = self.tdm_layer_prepare() + layer_array, _ = self._tdm_layer_prepare() return layer_array elif param_name == "TDM_Tree_Info": - info_array = self.tdm_info_prepare() + info_array = self._tdm_info_prepare() return info_array else: raise " {} is not a special tdm param name".format(param_name) - def tdm_travel_prepare(self): + def _tdm_travel_prepare(self): """load tdm tree param from npy/list file""" travel_array = np.load(self.tree_travel_path) logger.info("TDM Tree leaf node nums: {}".format( travel_array.shape[0])) return travel_array - def tdm_layer_prepare(self): + def _tdm_layer_prepare(self): """load tdm tree param from npy/list file""" layer_list = [] layer_list_flat = [] @@ -118,7 +118,7 @@ class TDMClusterTrainer(ClusterTrainer): [len(i) for i in layer_list])) return layer_array, layer_list - def tdm_info_prepare(self): + def _tdm_info_prepare(self): """load tdm tree param from list file""" info_array = np.load(self.tree_info_path) return info_array diff --git a/core/trainers/tdm_single_trainer.py b/core/trainers/tdm_single_trainer.py index 82819393..dce3c8d5 100755 --- a/core/trainers/tdm_single_trainer.py +++ b/core/trainers/tdm_single_trainer.py @@ -70,7 +70,7 @@ class TDMSingleTrainer(SingleTrainer): # covert tree to tensor, set it into Fluid's variable. for param_name in special_param: param_t = fluid.global_scope().find_var(param_name).get_tensor() - param_array = self.tdm_prepare(param_name) + param_array = self._tdm_prepare(param_name) if param_name == 'TDM_Tree_Emb': param_t.set(param_array.astype('float32'), self._place) else: @@ -84,37 +84,37 @@ class TDMSingleTrainer(SingleTrainer): context['status'] = 'train_pass' - def tdm_prepare(self, param_name): + def _tdm_prepare(self, param_name): if param_name == "TDM_Tree_Travel": - travel_array = self.tdm_travel_prepare() + travel_array = self._tdm_travel_prepare() return travel_array elif param_name == "TDM_Tree_Layer": - layer_array, _ = self.tdm_layer_prepare() + layer_array, _ = self._tdm_layer_prepare() return layer_array elif param_name == "TDM_Tree_Info": - info_array = self.tdm_info_prepare() + info_array = self._tdm_info_prepare() return info_array elif param_name == "TDM_Tree_Emb": - emb_array = self.tdm_emb_prepare() + emb_array = self._tdm_emb_prepare() return emb_array else: raise " {} is not a special tdm param name".format(param_name) - def tdm_travel_prepare(self): + def _tdm_travel_prepare(self): """load tdm tree param from npy/list file""" travel_array = np.load(self.tree_travel_path) logger.info("TDM Tree leaf node nums: {}".format( travel_array.shape[0])) return travel_array - def tdm_emb_prepare(self): + def _tdm_emb_prepare(self): """load tdm tree param from npy/list file""" emb_array = np.load(self.tree_emb_path) logger.info("TDM Tree node nums from emb: {}".format( emb_array.shape[0])) return emb_array - def tdm_layer_prepare(self): + def _tdm_layer_prepare(self): """load tdm tree param from npy/list file""" layer_list = [] layer_list_flat = [] @@ -134,7 +134,7 @@ class TDMSingleTrainer(SingleTrainer): [len(i) for i in layer_list])) return layer_array, layer_list - def tdm_info_prepare(self): + def _tdm_info_prepare(self): """load tdm tree param from list file""" info_array = np.load(self.tree_info_path) return info_array diff --git a/doc/distributed_train.md b/doc/distributed_train.md index c28425f7..425f141a 100644 --- a/doc/distributed_train.md +++ b/doc/distributed_train.md @@ -4,10 +4,7 @@ > 占位 ### 本地模拟分布式 > 占位 -### 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