Merge pull request #39 from microsoft/master

pull code

.gitignore

@@ -69,3 +69,6 @@ build
 *.egg-info
 
 .vscode
+
+# In case you place source code in ~/nni/
+/experiments

src/sdk/pynni/nni/__init__.py

@@ -19,16 +19,14 @@
 # ==================================================================================================
 
 
-# pylint: disable=wildcard-import
-
 from .trial import *
 from .smartparam import *
 from .nas_utils import training_update
 
 class NoMoreTrialError(Exception):
-    def __init__(self,ErrorInfo):
+    def __init__(self, ErrorInfo):
         super().__init__(self)
-        self.errorinfo=ErrorInfo
+        self.errorinfo = ErrorInfo
 
     def __str__(self):
-        return self.errorinfo
+        return self.errorinfo

src/sdk/pynni/nni/__main__.py

@@ -27,9 +27,10 @@
 import json
 import importlib
 
+from .common import enable_multi_thread, enable_multi_phase
 from .constants import ModuleName, ClassName, ClassArgs, AdvisorModuleName, AdvisorClassName
-from nni.common import enable_multi_thread, enable_multi_phase
-from nni.msg_dispatcher import MsgDispatcher
+from .msg_dispatcher import MsgDispatcher
+
 logger = logging.getLogger('nni.main')
 logger.debug('START')
 
@@ -44,7 +45,7 @@ def augment_classargs(input_class_args, classname):
                 input_class_args[key] = value
     return input_class_args
 
-def create_builtin_class_instance(classname, jsonstr_args, is_advisor = False):
+def create_builtin_class_instance(classname, jsonstr_args, is_advisor=False):
     if is_advisor:
         if classname not in AdvisorModuleName or \
             importlib.util.find_spec(AdvisorModuleName[classname]) is None:
@@ -130,55 +131,15 @@ def main():
 
     if args.advisor_class_name:
         # advisor is enabled and starts to run
-        if args.advisor_class_name in AdvisorModuleName:
-            dispatcher = create_builtin_class_instance(
-                args.advisor_class_name,
-                args.advisor_args, True)
-        else:
-            dispatcher = create_customized_class_instance(
-                args.advisor_directory,
-                args.advisor_class_filename,
-                args.advisor_class_name,
-                args.advisor_args)
-        if dispatcher is None:
-            raise AssertionError('Failed to create Advisor instance')
-        try:
-            dispatcher.run()
-        except Exception as exception:
-            logger.exception(exception)
-            raise
+        _run_advisor(args)
+
     else:
         # tuner (and assessor) is enabled and starts to run
-        tuner = None
-        assessor = None
-        if args.tuner_class_name in ModuleName:
-            tuner = create_builtin_class_instance(
-                args.tuner_class_name,
-                args.tuner_args)
-        else:
-            tuner = create_customized_class_instance(
-                args.tuner_directory,
-                args.tuner_class_filename,
-                args.tuner_class_name,
-                args.tuner_args)
-
-        if tuner is None:
-            raise AssertionError('Failed to create Tuner instance')
-
+        tuner = _create_tuner(args)
         if args.assessor_class_name:
-            if args.assessor_class_name in ModuleName:
-                assessor = create_builtin_class_instance(
-                    args.assessor_class_name,
-                    args.assessor_args)
-            else:
-                assessor = create_customized_class_instance(
-                    args.assessor_directory,
-                    args.assessor_class_filename,
-                    args.assessor_class_name,
-                    args.assessor_args)
-            if assessor is None:
-                raise AssertionError('Failed to create Assessor instance')
-
+            assessor = _create_assessor(args)
+        else:
+            assessor = None
         dispatcher = MsgDispatcher(tuner, assessor)
 
         try:
@@ -193,6 +154,59 @@ def main():
                 assessor._on_error()
             raise
 
+
+def _run_advisor(args):
+    if args.advisor_class_name in AdvisorModuleName:
+        dispatcher = create_builtin_class_instance(
+            args.advisor_class_name,
+            args.advisor_args, True)
+    else:
+        dispatcher = create_customized_class_instance(
+            args.advisor_directory,
+            args.advisor_class_filename,
+            args.advisor_class_name,
+            args.advisor_args)
+    if dispatcher is None:
+        raise AssertionError('Failed to create Advisor instance')
+    try:
+        dispatcher.run()
+    except Exception as exception:
+        logger.exception(exception)
+        raise
+
+
+def _create_tuner(args):
+    if args.tuner_class_name in ModuleName:
+        tuner = create_builtin_class_instance(
+            args.tuner_class_name,
+            args.tuner_args)
+    else:
+        tuner = create_customized_class_instance(
+            args.tuner_directory,
+            args.tuner_class_filename,
+            args.tuner_class_name,
+            args.tuner_args)
+    if tuner is None:
+        raise AssertionError('Failed to create Tuner instance')
+    return tuner
+
+
+def _create_assessor(args):
+    if args.assessor_class_name in ModuleName:
+        assessor = create_builtin_class_instance(
+            args.assessor_class_name,
+            args.assessor_args)
+    else:
+        assessor = create_customized_class_instance(
+            args.assessor_directory,
+            args.assessor_class_filename,
+            args.assessor_class_name,
+            args.assessor_args)
+    if assessor is None:
+        raise AssertionError('Failed to create Assessor instance')
+    return assessor
+
+
 if __name__ == '__main__':
     try:
         main()

src/sdk/pynni/nni/assessor.py

@@ -31,7 +31,6 @@ class AssessResult(Enum):
     Bad = False
 
 class Assessor(Recoverable):
-    # pylint: disable=no-self-use,unused-argument
 
     def assess_trial(self, trial_job_id, trial_history):
         """Determines whether a trial should be killed. Must override.
@@ -46,21 +45,20 @@ def trial_end(self, trial_job_id, success):
         trial_job_id: identifier of the trial (str).
         success: True if the trial successfully completed; False if failed or terminated.
         """
-        pass
 
     def load_checkpoint(self):
         """Load the checkpoint of assessr.
         path: checkpoint directory for assessor
         """
         checkpoin_path = self.get_checkpoint_path()
-        _logger.info('Load checkpoint ignored by assessor, checkpoint path: %s' % checkpoin_path)
+        _logger.info('Load checkpoint ignored by assessor, checkpoint path: %s', checkpoin_path)
 
     def save_checkpoint(self):
         """Save the checkpoint of assessor.
         path: checkpoint directory for assessor
         """
         checkpoin_path = self.get_checkpoint_path()
-        _logger.info('Save checkpoint ignored by assessor, checkpoint path: %s' % checkpoin_path)
+        _logger.info('Save checkpoint ignored by assessor, checkpoint path: %s', checkpoin_path)
 
     def _on_exit(self):
         pass

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

@@ -100,7 +100,7 @@ def import_data(self, data):
         data:
             a list of dictionarys, each of which has at least two keys, 'parameter' and 'value'
         """
-        if len(self.values) == 0:
+        if not self.values:
             logger.info("Search space has not been initialized, skip this data import")
             return
 

src/sdk/pynni/nni/bohb_advisor/bohb_advisor.py

@@ -51,7 +51,7 @@ def create_parameter_id():
     int
         parameter id
     """
-    global _next_parameter_id  # pylint: disable=global-statement
+    global _next_parameter_id
     _next_parameter_id += 1
     return _next_parameter_id - 1
 
@@ -80,7 +80,7 @@ def create_bracket_parameter_id(brackets_id, brackets_curr_decay, increased_id=-
     return params_id
 
 
-class Bracket(object):
+class Bracket:
     """
     A bracket in BOHB, all the information of a bracket is managed by
     an instance of this class.
@@ -98,7 +98,7 @@ class Bracket(object):
 	max_budget : float
 		The largest budget to consider. Needs to be larger than min_budget!
 		The budgets will be geometrically distributed
-        :math:`a^2 + b^2 = c^2 \sim \eta^k` for :math:`k\in [0, 1, ... , num\_subsets - 1]`.
+        :math:`a^2 + b^2 = c^2 \\sim \\eta^k` for :math:`k\\in [0, 1, ... , num\\_subsets - 1]`.
     optimize_mode: str
         optimize mode, 'maximize' or 'minimize'
     """
@@ -169,7 +169,7 @@ def inform_trial_end(self, i):
             If we have generated new trials after this trial end, we will return a new trial parameters.
             Otherwise, we will return None.
         """
-        global _KEY  # pylint: disable=global-statement
+        global _KEY
         self.num_finished_configs[i] += 1
         logger.debug('bracket id: %d, round: %d %d, finished: %d, all: %d',
                      self.s, self.i, i, self.num_finished_configs[i], self.num_configs_to_run[i])
@@ -377,8 +377,10 @@ def generate_new_bracket(self):
         if self.curr_s < 0:
             logger.info("s < 0, Finish this round of Hyperband in BOHB. Generate new round")
             self.curr_s = self.s_max
-        self.brackets[self.curr_s] = Bracket(s=self.curr_s, s_max=self.s_max, eta=self.eta,
-                                    max_budget=self.max_budget, optimize_mode=self.optimize_mode)
+        self.brackets[self.curr_s] = Bracket(
+            s=self.curr_s, s_max=self.s_max, eta=self.eta,
+            max_budget=self.max_budget, optimize_mode=self.optimize_mode
+        )
         next_n, next_r = self.brackets[self.curr_s].get_n_r()
         logger.debug(
             'new SuccessiveHalving iteration, next_n=%d, next_r=%d', next_n, next_r)
@@ -599,7 +601,7 @@ def handle_report_metric_data(self, data):
             logger.debug('bracket id = %s, metrics value = %s, type = %s', s, value, data['type'])
             s = int(s)
 
-            # add <trial_job_id, parameter_id> to self.job_id_para_id_map here, 
+            # add <trial_job_id, parameter_id> to self.job_id_para_id_map here,
             # because when the first parameter_id is created, trial_job_id is not known yet.
             if data['trial_job_id'] in self.job_id_para_id_map:
                 assert self.job_id_para_id_map[data['trial_job_id']] == data['parameter_id']
@@ -643,14 +645,14 @@ def handle_import_data(self, data):
         """
         _completed_num = 0
         for trial_info in data:
-            logger.info("Importing data, current processing progress %s / %s" %(_completed_num, len(data)))
+            logger.info("Importing data, current processing progress %s / %s", _completed_num, len(data))
             _completed_num += 1
             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)
+                logger.info("Useless trial data, value is %s, skip this trial data.", _value)
                 continue
             budget_exist_flag = False
             barely_params = dict()
@@ -662,7 +664,7 @@ def handle_import_data(self, data):
                     barely_params[keys] = _params[keys]
             if not budget_exist_flag:
                 _budget = self.max_budget
-                logger.info("Set \"TRIAL_BUDGET\" value to %s (max budget)" %self.max_budget)
+                logger.info("Set \"TRIAL_BUDGET\" value to %s (max budget)", self.max_budget)
             if self.optimize_mode is OptimizeMode.Maximize:
                 reward = -_value
             else: