Fix smac import data (#1093)

fix smac import data

src/sdk/pynni/nni/batch_tuner/batch_tuner.py

@@ -22,11 +22,7 @@ batch_tuner.py including:
     class BatchTuner
 """
 
-import copy
-from enum import Enum, unique
-import random
-
-import numpy as np
+import logging
 
 import nni
 from nni.tuner import Tuner
@@ -35,6 +31,7 @@ TYPE = '_type'
 CHOICE = 'choice'
 VALUE = '_value'
 
+logger = logging.getLogger('batch_tuner_AutoML')
 
 class BatchTuner(Tuner):
     """
@@ -88,8 +85,8 @@ class BatchTuner(Tuner):
         ----------
         parameter_id : int
         """
-        self.count +=1
-        if self.count>len(self.values)-1:
+        self.count += 1
+        if self.count > len(self.values) - 1:
             raise nni.NoMoreTrialError('no more parameters now.')
         return self.values[self.count]
 
@@ -97,4 +94,31 @@ class BatchTuner(Tuner):
         pass
 
     def import_data(self, data):
-        pass
+        """Import additional data for tuning
+        Parameters
+        ----------
+        data:
+            a list of dictionarys, each of which has at least two keys, 'parameter' and 'value'
+        """
+        if len(self.values) == 0:
+            logger.info("Search space has not been initialized, skip this data import")
+            return
+
+        self.values = self.values[(self.count+1):]
+        self.count = -1
+
+        _completed_num = 0
+        for trial_info in data:
+            logger.info("Importing data, current processing progress %s / %s", _completed_num, len(data))
+            # simply validate data format
+            assert "parameter" in trial_info
+            _params = trial_info["parameter"]
+            assert "value" in trial_info
+            _value = trial_info['value']
+            if not _value:
+                logger.info("Useless trial data, value is %s, skip this trial data.", _value)
+                continue
+            _completed_num += 1
+            if _params in self.values:
+                self.values.remove(_params)
+        logger.info("Successfully import data to batch tuner, total data: %d, imported data: %d.", len(data), _completed_num)

src/sdk/pynni/nni/smac_tuner/smac_tuner.py

@@ -21,21 +21,21 @@
 smac_tuner.py
 """
 
-from nni.tuner import Tuner
-from nni.utils import OptimizeMode, extract_scalar_reward
-
 import sys
 import logging
 import numpy as np
-import json_tricks
-from enum import Enum, unique
-from .convert_ss_to_scenario import generate_scenario
+
+from nni.tuner import Tuner
+from nni.utils import OptimizeMode, extract_scalar_reward
 
 from smac.utils.io.cmd_reader import CMDReader
 from smac.scenario.scenario import Scenario
 from smac.facade.smac_facade import SMAC
 from smac.facade.roar_facade import ROAR
 from smac.facade.epils_facade import EPILS
+from ConfigSpaceNNI import Configuration
+
+from .convert_ss_to_scenario import generate_scenario
 
 
 class SMACTuner(Tuner):
@@ -57,6 +57,7 @@ class SMACTuner(Tuner):
         self.update_ss_done = False
         self.loguniform_key = set()
         self.categorical_dict = {}
+        self.cs = None
 
     def _main_cli(self):
         """Main function of SMAC for CLI interface
@@ -66,7 +67,7 @@ class SMACTuner(Tuner):
         instance
             optimizer
         """
-        self.logger.info("SMAC call: %s" % (" ".join(sys.argv)))
+        self.logger.info("SMAC call: %s", " ".join(sys.argv))
 
         cmd_reader = CMDReader()
         args, _ = cmd_reader.read_cmd()
@@ -95,6 +96,7 @@ class SMACTuner(Tuner):
 
         # Create scenario-object
         scen = Scenario(args.scenario_file, [])
+        self.cs = scen.cs
 
         if args.mode == "SMAC":
             optimizer = SMAC(
@@ -258,4 +260,45 @@ class SMACTuner(Tuner):
         return params
 
     def import_data(self, data):
-        pass
+        """Import additional data for tuning
+        Parameters
+        ----------
+        data:
+            a list of dictionarys, each of which has at least two keys, 'parameter' and 'value'
+        """
+        _completed_num = 0
+        for trial_info in data:
+            self.logger.info("Importing data, current processing progress %s / %s", _completed_num, len(data))
+            # simply validate data format
+            assert "parameter" in trial_info
+            _params = trial_info["parameter"]
+            assert "value" in trial_info
+            _value = trial_info['value']
+            if not _value:
+                self.logger.info("Useless trial data, value is %s, skip this trial data.", _value)
+                continue
+            # convert the keys in loguniform and categorical types
+            valid_entry = True
+            for key, value in _params.items():
+                if key in self.loguniform_key:
+                    _params[key] = np.log(value)
+                elif key in self.categorical_dict:
+                    if value in self.categorical_dict[key]:
+                        _params[key] = self.categorical_dict[key].index(value)
+                    else:
+                        self.logger.info("The value %s of key %s is not in search space.", str(value), key)
+                        valid_entry = False
+                        break
+            if not valid_entry:
+                continue
+            # start import this data entry
+            _completed_num += 1
+            config = Configuration(self.cs, values=_params)
+            if self.optimize_mode is OptimizeMode.Maximize:
+                _value = -_value
+            if self.first_one:
+                self.smbo_solver.nni_smac_receive_first_run(config, _value)
+                self.first_one = False
+            else:
+                self.smbo_solver.nni_smac_receive_runs(config, _value)
+        self.logger.info("Successfully import data to smac tuner, total data: %d, imported data: %d.", len(data), _completed_num)

tools/nni_cmd/constants.py

@@ -86,12 +86,13 @@ TUNERS_SUPPORTING_IMPORT_DATA = {
     'Anneal',
     'GridSearch',
     'MetisTuner',
-    'BOHB'
+    'BOHB',
+    'SMAC',
+    'BatchTuner'
 }
 
 TUNERS_NO_NEED_TO_IMPORT_DATA = {
     'Random',
-    'Batch_tuner',
     'Hyperband'
 }