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alibaba · May 7, 2022 · d6bab16 · d6bab16
2 parents 94f93db + 2f5e41c
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diff --git a/federatedscope/__init__.py b/federatedscope/__init__.py
@@ -2,7 +2,7 @@
 from __future__ import print_function
 from __future__ import division
 
-__version__ = '0.0.1'
+__version__ = '0.1.0'
 
 
 def _setup_logger():

diff --git a/federatedscope/core/configs/__init__.py b/federatedscope/core/configs/__init__.py
@@ -13,10 +13,19 @@
 if "config" in all_sub_configs:
     all_sub_configs.remove('config')
 
+
+from federatedscope.core.configs.config import CN, init_global_cfg
+__all__ = __all__ + \
+          [
+              'CN',
+              'init_global_cfg'
+          ]
+
 # reorder the config to ensure the base config will be registered first
 base_configs = [
     'cfg_data', 'cfg_fl_setting', 'cfg_model', 'cfg_training', 'cfg_evaluation'
 ]
 for base_config in base_configs:
     all_sub_configs.pop(all_sub_configs.index(base_config))
     all_sub_configs.insert(0, base_config)
+
diff --git a/federatedscope/core/monitors/__init__.py b/federatedscope/core/monitors/__init__.py
@@ -0,0 +1,5 @@
+from federatedscope.core.monitors.early_stopper import EarlyStopper
+from federatedscope.core.monitors.metric_calculator import MetricCalculator
+from federatedscope.core.monitors.monitor import Monitor
+
+__all__ = ['EarlyStopper', 'MetricCalculator', 'Monitor']
diff --git a/federatedscope/core/trainers/__init__.py b/federatedscope/core/trainers/__init__.py
@@ -1,10 +1,14 @@
 from federatedscope.core.trainers.trainer import Trainer, GeneralTorchTrainer
+from federatedscope.core.trainers.trainer_multi_model import GeneralMultiModelTrainer
 from federatedscope.core.trainers.trainer_pFedMe import wrap_pFedMeTrainer
+from federatedscope.core.trainers.trainer_Ditto import wrap_DittoTrainer
+from federatedscope.core.trainers.trainer_FedEM import FedEMTrainer
 from federatedscope.core.trainers.context import Context
 from federatedscope.core.trainers.trainer_fedprox import wrap_fedprox_trainer
 from federatedscope.core.trainers.trainer_nbafl import wrap_nbafl_trainer, wrap_nbafl_server
 
 __all__ = [
-    'Trainer', 'Context', 'GeneralTorchTrainer', 'wrap_pFedMeTrainer',
+    'Trainer', 'Context', 'GeneralTorchTrainer', 'GeneralMultiModelTrainer',
+    'wrap_pFedMeTrainer', 'wrap_DittoTrainer', 'FedEMTrainer',
     'wrap_fedprox_trainer', 'wrap_nbafl_trainer', 'wrap_nbafl_server'
-]
+]
diff --git a/materials/paper_list/FL-Attacker/README.md b/materials/paper_list/FL-Attacker/README.md
@@ -0,0 +1 @@
+The paper list goes here.
diff --git a/materials/paper_list/FL-Database/README.md b/materials/paper_list/FL-Database/README.md
@@ -0,0 +1 @@
+The paper list goes here.
diff --git a/materials/paper_list/FL-Incentive/README.md b/materials/paper_list/FL-Incentive/README.md
@@ -0,0 +1 @@
+The paper list goes here.
diff --git a/materials/paper_list/FL-NLP/README.md b/materials/paper_list/FL-NLP/README.md
@@ -0,0 +1 @@
+## The paper list of Federated Learning in NLP will go here.
diff --git a/materials/paper_list/FL-Recommendation/README.md b/materials/paper_list/FL-Recommendation/README.md
@@ -0,0 +1,18 @@
+## Federated Learning for Recommendation
+
+### 2021
+| Title | Venue | Link |  
+| --- | --- | --- | 
+| Efficient-FedRec: Efficient Federated Learning Framework for Privacy-Preserving News Recommendation | EMNLP |  [pdf](https://aclanthology.org/2021.emnlp-main.223), [code](https://github.com/yjw1029/Efficient-FedRec) |
+
+### 2020
+| Title | Venue | Link |  
+| --- | --- | --- | 
+| Secure Federated Matrix Factorization | IEEE Intelligent Systems | [pdf](https://ieeexplore.ieee.org/abstract/document/9162459), [code](https://github.com/Di-Chai/FedMF) | 
+| Privacy-Preserving News Recommendation Model Learning | EMNLP | [pdf](https://aclanthology.org/2020.findings-emnlp.128/), [code](https://github.com/taoqi98/FedNewsRec) |
+
+### 2019
+| Title | Venue | Link |  
+| --- | --- | --- | 
+| Federated Collaborative Filtering for Privacy-Preserving Personalized Recommendation System | arXiv | [pdf](https://arxiv.org/abs/1901.09888) |
+
diff --git a/materials/paper_list/Federated_Graph_Learning/README.md b/materials/paper_list/Federated_Graph_Learning/README.md
@@ -0,0 +1,24 @@
+## Federated Learning for Graph
+
+### 2021
+
+| Title                                                        | Venue      | Link                                                         |
+| ------------------------------------------------------------ | ---------- | ------------------------------------------------------------ |
+| Federated Graph Classification over Non-IID Graphs           | NeurIPS    | [pdf](https://proceedings.neurips.cc//paper/2021/file/9c6947bd95ae487c81d4e19d3ed8cd6f-Paper.pdf), [code](https://github.com/Oxfordblue7/GCFL) |
+| Subgraph Federated Learning with Missing Neighbor Generation | NeurIPS    | [pdf](http://proceedings.neurips.cc/paper/2021/file/34adeb8e3242824038aa65460a47c29e-Paper.pdf), [code](https://github.com/zkhku/fedsage) |
+| Cross-Node Federated Graph Neural Network for Spatio-Temporal Data Modeling | KDD        | [pdf](https://arxiv.org/pdf/2106.05223v1.pdf), [code](https://github.com/mengcz13/KDD2021_CNFGNN) |
+| Glint: Decentralized Federated Graph Learning with Traffic Throttling and Flow Scheduling | IEEE IWQoS | [pdf](https://ieeexplore.ieee.org/abstract/document/9521331) |
+| Differentially Private Federated Knowledge Graphs Embedding  | CIKM       | [pdf](https://arxiv.org/pdf/2105.07615v2.pdf), [code](https://github.com/HKUST-KnowComp/FKGE) |
+
+### 2020
+
+| Title                                                 | Venue | Link                                                         |
+| ----------------------------------------------------- | ----- | ------------------------------------------------------------ |
+| FedE: Embedding Knowledge Graphs in Federated Setting | IJCKG | [pdf](https://dl.acm.org/doi/fullHtml/10.1145/3502223.3502233), [code](https://github.com/zjukg/FedE) |
+
+### 2019
+
+| Title                                                        | Venue | Link                                          |
+| ------------------------------------------------------------ | ----- | --------------------------------------------- |
+| Towards Federated Graph Learning for Collaborative Financial Crimes Detection | Arxiv | [pdf](https://arxiv.org/pdf/1909.12946v2.pdf) |
+
diff --git a/materials/paper_list/Federated_HPO/README.md b/materials/paper_list/Federated_HPO/README.md
@@ -0,0 +1,25 @@
+## Federated Hyperparameter Optimization
+
+### 2022
+Coming soon!
+
+### 2021
+
+| Title | Venue | Link |
+| --- | --- | --- |
+| Federated Hyperparameter Tuning: Challenges, Baselines, and Connections to Weight-Sharing | NeurIPS | [pdf](https://openreview.net/forum?id=p99rWde9fVJ), [code](https://github.com/mkhodak/FedEx) |
+| FLoRA: Single-shot Hyper-parameter Optimization for Federated Learning | NeurIPS workshop | [pdf](https://neurips2021workshopfl.github.io/NFFL-2021/papers/2021/Zhou2021.pdf) |
+| FedTune: Automatic Tuning of Federated Learning Hyper-Parameters from System Perspective | Arxiv | [pdf](https://arxiv.org/pdf/2110.03061.pdf) |
+
+### 2020
+
+| Title | Venue | Link |
+| --- | --- | --- |
+| Federated Bayesian Optimization via Thompson Sampling | NeurIPS | [pdf](https://proceedings.neurips.cc/paper/2020/file/6dfe08eda761bd321f8a9b239f6f4ec3-Paper.pdf) |
+
+### 2019
+
+| Title | Venue | Link |
+| --- | --- | --- |
+| Learning Rate Adaptation for Differentially Private Learning | AISTATS | [pdf](http://proceedings.mlr.press/v108/koskela20a.html) |
+| Robust Federated Learning Through Representation Matching and Adaptive Hyper-parameters | Arxiv | [pdf](https://arxiv.org/pdf/1912.13075.pdf) |
diff --git a/materials/paper_list/Personalized_FL/README.md b/materials/paper_list/Personalized_FL/README.md
@@ -0,0 +1 @@
+## The paper list of Personalized Federated Learning will go here.
diff --git a/materials/tutorial/KDD_2022/README.md b/materials/tutorial/KDD_2022/README.md
@@ -0,0 +1 @@
+## The material of KDD 2022 tutorial will go here.
diff --git a/scripts/parse_exp_results_wandb.py b/scripts/parse_exp_results_wandb.py
@@ -95,7 +95,7 @@ def main():
                     if res['Role'] == 'Server #':
                         cur_round = res['Round']
                     res.pop('Role')
-                    if cur_round != "Final":
+                    if cur_round != "Final" and 'Results_raw' in res:
                         res.pop('Results_raw')
 
                     log_res = {}
@@ -110,6 +110,10 @@ def main():
 
                             else:
                                 exp_stop_normal = True
+                                if key == "Results_raw":
+                                    for final_type, final_type_dict in res["Results_raw"].items():
+                                        for inner_key, inner_val in final_type_dict.items():
+                                            log_res_best[f"{final_type}/{inner_key}"] = inner_val
                             #     log_res_best = {}
                             #     for best_res_type, val_dict in val.items():
                             #         for key_inner, val_inner in val_dict.items():

diff --git a/setup.py b/setup.py
@@ -9,7 +9,7 @@
 
 setuptools.setup(
     name="federatedscope",
-    version="0.0.1",
+    version="0.1.0",
     author="Alibaba Damo Academy",
     author_email="",
     description="Federated learning package",
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		@@ -0,0 +1 @@
		## The paper list of Federated Learning in NLP will go here.
Original file line number	Diff line number	Diff line change
		@@ -0,0 +1 @@
		## The paper list of Personalized Federated Learning will go here.
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		@@ -0,0 +1 @@
		## The material of KDD 2022 tutorial will go here.