fix config v2 relative path (#3439)

nni/experiment/config/base.py

@@ -47,6 +47,8 @@ class ConfigBase:
         They will be converted to snake_case automatically.
         If a field is missing and don't have default value, it will be set to `dataclasses.MISSING`.
         """
+        if 'basepath' in kwargs:
+            _base_path = kwargs.pop('basepath')
         kwargs = {util.case_insensitive(key): value for key, value in kwargs.items()}
         if _base_path is None:
             _base_path = Path()

nni/experiment/config/common.py

@@ -68,17 +68,24 @@ class ExperimentConfig(ConfigBase):
     training_service: Union[TrainingServiceConfig, List[TrainingServiceConfig]]
 
     def __init__(self, training_service_platform: Optional[Union[str, List[str]]] = None, **kwargs):
+        base_path = kwargs.pop('_base_path', None)
         kwargs = util.case_insensitive(kwargs)
         if training_service_platform is not None:
             assert 'trainingservice' not in kwargs
-            kwargs['trainingservice'] = util.training_service_config_factory(platform = training_service_platform)
+            kwargs['trainingservice'] = util.training_service_config_factory(
+                platform=training_service_platform,
+                base_path=base_path
+            )
         elif isinstance(kwargs.get('trainingservice'), (dict, list)):
             # dict means a single training service
             # list means hybrid training service
-            kwargs['trainingservice'] = util.training_service_config_factory(config = kwargs['trainingservice'])
+            kwargs['trainingservice'] = util.training_service_config_factory(
+                config=kwargs['trainingservice'],
+                base_path=base_path
+            )
         else:
             raise RuntimeError('Unsupported Training service configuration!')
-        super().__init__(**kwargs)
+        super().__init__(_base_path=base_path, **kwargs)
         for algo_type in ['tuner', 'assessor', 'advisor']:
             if isinstance(kwargs.get(algo_type), dict):
                 setattr(self, algo_type, _AlgorithmConfig(**kwargs.pop(algo_type)))

nni/experiment/config/util.py

@@ -29,7 +29,10 @@ def canonical_path(path: Optional[PathLike]) -> Optional[str]:
 def count(*values) -> int:
     return sum(value is not None and value is not False for value in values)
 
-def training_service_config_factory(platform: Union[str, List[str]] = None, config: Union[List, Dict] = None): # -> TrainingServiceConfig
+def training_service_config_factory(
+        platform: Union[str, List[str]] = None,
+        config: Union[List, Dict] = None,
+        base_path: Optional[Path] = None): # -> TrainingServiceConfig
     from .common import TrainingServiceConfig
     ts_configs = []
     if platform is not None:
@@ -47,7 +50,7 @@ def training_service_config_factory(platform: Union[str, List[str]] = None, conf
         for conf in configs:
             if conf['platform'] not in supported_platforms:
                 raise RuntimeError(f'Unrecognized platform {conf["platform"]}')
-            ts_configs.append(supported_platforms[conf['platform']](**conf))
+            ts_configs.append(supported_platforms[conf['platform']](_base_path=base_path, **conf))
     return ts_configs if len(ts_configs) > 1 else ts_configs[0]
 
 def load_config(Type, value):

nni/tools/nnictl/launcher.py

@@ -3,6 +3,7 @@
 
 import json
 import os
+from pathlib import Path
 import sys
 import string
 import random
@@ -590,7 +591,7 @@ def create_experiment(args):
     except Exception:
         print_warning('Validation with V1 schema failed. Trying to convert from V2 format...')
         try:
-            config = ExperimentConfig(**experiment_config)
+            config = ExperimentConfig(_base_path=Path(config_path).parent, **experiment_config)
             experiment_config = convert.to_v1_yaml(config)
         except Exception as e:
             print_error(f'Config in v2 format validation failed, the config error in v2 format is: {repr(e)}')