fix experiment import bug and add it cases: experiment import

docs/en_US/TrialExample/SklearnExamples.md

@@ -67,7 +67,7 @@ It is easy to use NNI in your scikit-learn code, there are only a few steps.
     "kernel": {"_type":"choice","_value":["linear", "rbf", "poly", "sigmoid"]},
     "degree": {"_type":"choice","_value":[1, 2, 3, 4]},
     "gamma": {"_type":"uniform","_value":[0.01, 0.1]},
-    "coef0 ": {"_type":"uniform","_value":[0.01, 0.1]}
+    "coef0": {"_type":"uniform","_value":[0.01, 0.1]}
   }
   ```
 

examples/trials/sklearn/classification/search_space.json

@@ -3,5 +3,5 @@
     "kernel": {"_type":"choice","_value":["linear", "rbf", "poly", "sigmoid"]},
     "degree": {"_type":"choice","_value":[1, 2, 3, 4]},
     "gamma": {"_type":"uniform","_value":[0.01, 0.1]},
-    "coef0 ": {"_type":"uniform","_value":[0.01, 0.1]}
+    "coef0": {"_type":"uniform","_value":[0.01, 0.1]}
 }

src/sdk/pynni/nni/msg_dispatcher.py

@@ -114,6 +114,7 @@ def handle_import_data(self, data):
         data: a list of dictionaries, each of which has at least two keys, 'parameter' and 'value'
         """
         for entry in data:
+            entry['value'] = entry['value']  if type(entry['value']) is str else json_tricks.dumps(entry['value'])
             entry['value'] = json_tricks.loads(entry['value'])
         self.tuner.import_data(data)
 

test/config/integration_tests.yml

@@ -135,6 +135,13 @@ testCases:
   validator:
     class: ExportValidator 
 
+- name: experiment-import
+  configFile: test/config/nnictl_experiment/sklearn-classification.yml
+  validator:
+    class: ImportValidator
+    kwargs:
+      import_data_file_path: config/nnictl_experiment/test_import.json
+
 - name: nnicli
   configFile: test/config/examples/sklearn-regression.yml
   config:

test/config/nnictl_experiment/sklearn-classification.yml

@@ -0,0 +1,23 @@
+authorName: nni
+experimentName: default_test
+maxExecDuration: 5m
+maxTrialNum: 4
+trialConcurrency: 2
+searchSpacePath: ../../../examples/trials/sklearn/classification/search_space.json
+
+tuner:
+  builtinTunerName: TPE
+assessor:
+  builtinAssessorName: Medianstop
+  classArgs:
+    optimize_mode: maximize
+trial:
+  codeDir: ../../../examples/trials/sklearn/classification
+  command: python3 main.py
+  gpuNum: 0
+
+useAnnotation: false
+multiPhase: false
+multiThread: false
+
+trainingServicePlatform: local

test/config/nnictl_experiment/test_import.json

@@ -0,0 +1,4 @@
+[
+    {"parameter": {"C": 0.15940134774738896, "kernel": "sigmoid", "degree": 3, "gamma": 0.07295826917955316, "coef0": 0.0978204758732429}, "value": 0.6},
+    {"parameter": {"C": 0.5556430724708544, "kernel": "linear", "degree": 3, "gamma": 0.04957496655414671, "coef0": 0.08520868779907687}, "value": 0.7}
+]

test/nni_test/nnitest/validators.py

@@ -33,6 +33,14 @@ def __call__(self, rest_endpoint, experiment_dir, nni_source_dir, **kwargs):
             print('\n\n')
         remove('report.json')
 
+class ImportValidator(ITValidator):
+    def __call__(self, rest_endpoint, experiment_dir, nni_source_dir, **kwargs):
+        exp_id = osp.split(experiment_dir)[-1]
+        import_data_file_path = kwargs.get('import_data_file_path')
+        proc = subprocess.run(['nnictl', 'experiment', 'import', exp_id, '-f', import_data_file_path])
+        assert proc.returncode == 0, \
+            '`nnictl experiment import {0} -f {1}` failed with code {2}'.format(exp_id, import_data_file_path, proc.returncode)
+
 class MetricsValidator(ITValidator):
     def __call__(self, rest_endpoint, experiment_dir, nni_source_dir, **kwargs):
         self.check_metrics(nni_source_dir, **kwargs)