Optimize GitHub Actions of CI (#508)

.github/workflows/codeql.yml

@@ -3,12 +3,14 @@ name: CodeQL (Code Scanning)
 on:
   pull_request:
     branches: [ "master" ]
+    types: [opened, synchronize, edited]
   schedule:
     - cron: '0 8 * * *'
 
 jobs:
   analyze:
     name: Analyze
+    if: false == contains(github.event.pull_request.title, 'WIP')
     runs-on: ubuntu-latest
     permissions:
       actions: read

.github/workflows/test_atc.yml

@@ -1,9 +1,13 @@
 name: UnitTests for ATC
 
-on: [push, pull_request]
+on:
+  pull_request:
+    types: [opened, synchronize, edited]
+
 
 jobs:
   run:
+    if: false == contains(github.event.pull_request.title, 'WIP')
     runs-on: ${{ matrix.os }}
     timeout-minutes: 30
     strategy:

.github/workflows/test_autotune.yml

@@ -1,9 +1,12 @@
 name: UnitTests for Autotune Module
 
-on: [push, pull_request]
+on:
+  pull_request:
+    types: [opened, synchronize, edited]
 
 jobs:
   run:
+    if: false == contains(github.event.pull_request.title, 'WIP')
     runs-on: ${{ matrix.os }}
     timeout-minutes: 20
     strategy:

.github/workflows/test_distribute.yml

@@ -1,9 +1,12 @@
 name: UnitTests for Distributed Mode
 
-on: [push, pull_request]
+on:
+  pull_request:
+    types: [opened, synchronize, edited]
 
 jobs:
   run:
+    if: false == contains(github.event.pull_request.title, 'WIP')
     runs-on: ${{ matrix.os }}
     timeout-minutes: 20
     strategy:

README.md

@@ -268,7 +268,7 @@ As a comprehensive FL platform, FederatedScope provides the fundamental implemen
 - **Differential Privacy**: Different from the encryption algorithms that require a large amount of computation resources,  differential privacy is an economical yet flexible technique to protect privacy, which has achieved great success in database and is ever-growing in federated learning.
 - ...
 
-More supports are coming soon! We have prepared a [tutorial](https://federatedscope.io/) to provide more details about how to utilize FederatedScope to enjoy your journey of Federated Learning!
+More supports are coming soon! We have prepared a [tutorial](https://federatedscope.io/) to provide more details about how to utilize FederatedScope to enjoy your journey of Federated Learning! 
 
 Materials of related topics are constantly being updated, please refer to [FL-Recommendation](https://github.com/alibaba/FederatedScope/tree/master/materials/paper_list/FL-Recommendation), [Federated-HPO](https://github.com/alibaba/FederatedScope/tree/master/materials/paper_list/Federated_HPO), [Personalized FL](https://github.com/alibaba/FederatedScope/tree/master/materials/paper_list/Personalized_FL), [Federated Graph Learning](https://github.com/alibaba/FederatedScope/tree/master/materials/paper_list/Federated_Graph_Learning), [FL-NLP](https://github.com/alibaba/FederatedScope/tree/master/materials/paper_list/FL-NLP), [FL-Attacker](https://github.com/alibaba/FederatedScope/tree/master/materials/paper_list/FL-Attacker), [FL-Incentive-Mechanism](https://github.com/alibaba/FederatedScope/tree/master/materials/paper_list/FL-Incentive), [FL-Fairness](https://github.com/alibaba/FederatedScope/tree/master/materials/paper_list/FL-Fiarness) and so on.