fix bug and add doc (#5088)

README.md

@@ -22,7 +22,8 @@ NNI automates feature engineering, neural architecture search, hyperparameter tu
 
 * **New release**: [v2.8 is available](https://github.com/microsoft/nni/releases/tag/v2.8) - _released on June-22-2022_
 * **New demo available**: [Youtube entry](https://www.youtube.com/channel/UCKcafm6861B2mnYhPbZHavw) | [Bilibili 入口](https://space.bilibili.com/1649051673) - _last updated on June-22-2022_
-* **New webinar**: [Introducing Retiarii: A deep learning exploratory-training framework on NNI](https://note.microsoft.com/MSR-Webinar-Retiarii-Registration-Live.html) - _scheduled on June-24-2021_
+* **New research paper**: [SparTA: Deep-Learning Model Sparsity via Tensor-with-Sparsity-Attribute](https://www.usenix.org/system/files/osdi22-zheng-ningxin.pdf) - _published in OSDI 2022_
+* **New research paper**: [Privacy-preserving Online AutoML for Domain-Specific Face Detection](https://openaccess.thecvf.com/content/CVPR2022/papers/Yan_Privacy-Preserving_Online_AutoML_for_Domain-Specific_Face_Detection_CVPR_2022_paper.pdf) - _published in CVPR 2022_
 * **Newly upgraded documentation**: [Doc upgraded](https://nni.readthedocs.io/en/stable)
 
 

docs/source/notes/research_publications.rst

@@ -7,6 +7,19 @@ System Research
 ---------------
 
 
+* `SparTA: Deep-Learning Model Sparsity via Tensor-with-Sparsity-Attribute <https://www.usenix.org/system/files/osdi22-zheng-ningxin.pdf>`__
+
+.. code-block:: bibtex
+
+   @inproceedings{zheng2022sparta,
+     title={$\{$SparTA$\}$:$\{$Deep-Learning$\}$ Model Sparsity via $\{$Tensor-with-Sparsity-Attribute$\}$},
+     author={Zheng, Ningxin and Lin, Bin and Zhang, Quanlu and Ma, Lingxiao and Yang, Yuqing and Yang, Fan and Wang, Yang and Yang, Mao and Zhou, Lidong},
+     booktitle={16th USENIX Symposium on Operating Systems Design and Implementation (OSDI 22)},
+     pages={213--232},
+     year={2022}
+   }
+
+
 * `Retiarii: A Deep Learning Exploratory-Training Framework <https://www.usenix.org/system/files/osdi20-zhang_quanlu.pdf>`__
 
 .. code-block:: bibtex
@@ -52,6 +65,19 @@ New Algorithms
 ^^^^^^^^^^^^^^
 
 
+* `Privacy-preserving Online AutoML for Domain-Specific Face Detection <https://openaccess.thecvf.com/content/CVPR2022/papers/Yan_Privacy-Preserving_Online_AutoML_for_Domain-Specific_Face_Detection_CVPR_2022_paper.pdf>`__
+
+.. code-block:: bibtex
+
+   @inproceedings{yan2022privacy,
+     title={Privacy-preserving Online AutoML for Domain-Specific Face Detection},
+     author={Yan, Chenqian and Zhang, Yuge and Zhang, Quanlu and Yang, Yaming and Jiang, Xinyang and Yang, Yuqing and Wang, Baoyuan},
+     booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
+     pages={4134--4144},
+     year={2022}
+   }
+
+
 * `TextNAS: A Neural Architecture Search Space Tailored for Text Representation <https://arxiv.org/pdf/1912.10729.pdf>`__
 
 .. code-block:: bibtex

nni/nas/execution/common/integration.py

@@ -237,3 +237,6 @@ class RetiariiAdvisor(MsgDispatcherBase):
     def handle_import_data(self, data):
         # FIXME: ignore imported data for now, as strategy has not supported resume
         pass
+
+    def handle_add_customized_trial(self, data):
+        pass

test/algo/nas/test_multitrial.py

@@ -98,18 +98,25 @@ def test_multitrial_experiment_resume_view(pytestconfig):
     print('python api resume...')
     exp = RetiariiExperiment.resume(exp_id)
     ensure_success(exp)
+    # sleep here because there would be several seconds for the experiment status to change
+    # to ERROR from INITIALIZED/RUNNING if the resume gets error.
+    time.sleep(6)
+    assert exp.get_status() == 'DONE', f'The experiment status should not be {exp.get_status()}'
     # TODO: currently `export_top_models` does not work as strategy's states are not resumed
     # assert isinstance(exp.export_top_models()[0], dict)
     exp.stop()
     # view the above experiment in non blocking mode then stop it
     print('python api view...')
     exp = RetiariiExperiment.view(exp_id, non_blocking=True)
+    assert exp.get_status() == 'VIEWED', f'The experiment status should not be {exp.get_status()}'
     exp.stop()
 
     # the following is nnictl resume and view
     print('nnictl resume...')
     new_env = os.environ.copy()
     new_env['PYTHONPATH'] = str(pytestconfig.rootpath)
+    # NOTE: experiment status (e.g., ERROR) is not checked, because it runs in blocking mode and
+    # the rest server exits right after the command is done
     proc = subprocess.run(f'nnictl resume {exp_id}', shell=True, env=new_env)
     assert proc.returncode == 0, 'resume nas experiment failed with code %d' % proc.returncode
     print('nnictl view...')