Merge pull request #166 from Microsoft/master

merge master

src/sdk/pynni/nni/gridsearch_tuner/gridsearch_tuner.py

@@ -164,6 +164,11 @@ class GridSearchTuner(Tuner):
             _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)
+                continue
             _params_tuple = convert_dict2tuple(_params)
             self.supplement_data[_params_tuple] = True
         logger.info("Successfully import data to grid search tuner.")

src/sdk/pynni/nni/hyperopt_tuner/hyperopt_tuner.py

@@ -139,19 +139,50 @@ def json2vals(in_x, vals, out_y, name=ROOT):
         for i, temp in enumerate(in_x):
             json2vals(temp, vals[i], out_y, name + '[%d]' % i)
 
+def _add_index(in_x, parameter):
+    """
+    change parameters in NNI format to parameters in hyperopt format(This function also support nested dict.).
+    For example, receive parameters like:
+        {'dropout_rate': 0.8, 'conv_size': 3, 'hidden_size': 512}
+    Will change to format in hyperopt, like:
+        {'dropout_rate': 0.8, 'conv_size': {'_index': 1, '_value': 3}, 'hidden_size': {'_index': 1, '_value': 512}}
+    """
+    if TYPE not in in_x: # if at the top level
+        out_y = dict()
+        for key, value in parameter.items():
+            out_y[key] = _add_index(in_x[key], value)
+        return out_y
+    elif isinstance(in_x, dict):
+        value_type = in_x[TYPE]
+        value_format = in_x[VALUE]
+        if value_type == "choice":
+            choice_name = parameter[0] if isinstance(parameter, list) else parameter
+            for pos, item in enumerate(value_format): # here value_format is a list
+                if isinstance(item, list): # this format is ["choice_key", format_dict]
+                    choice_key = item[0]
+                    choice_value_format = item[1]
+                    if choice_key == choice_name:
+                        return {INDEX: pos, VALUE: [choice_name, _add_index(choice_value_format, parameter[1])]}
+                elif choice_name == item:
+                    return {INDEX: pos, VALUE: item}
+        else:
+            return parameter
 
 def _split_index(params):
     """
     Delete index infromation from params
     """
-    result = {}
+    if isinstance(params, list):
+        return [params[0], _split_index(params[1])]
+    elif isinstance(params, dict):
+        if INDEX in params.keys():
+            return _split_index(params[VALUE])
+        result = dict()
         for key in params:
-        if isinstance(params[key], dict):
-            value = params[key][VALUE]
-        else:
-            value = params[key]
-        result[key] = value
+            result[key] = _split_index(params[key])
         return result
+    else:
+        return params
 
 
 class HyperoptTuner(Tuner):
@@ -373,8 +404,11 @@ class HyperoptTuner(Tuner):
             _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
             self.supplement_data_num += 1
             _parameter_id = '_'.join(["ImportData", str(self.supplement_data_num)])
-            self.total_data[_parameter_id] = _params
+            self.total_data[_parameter_id] = _add_index(in_x=self.json, parameter=_params)
             self.receive_trial_result(parameter_id=_parameter_id, parameters=_params, value=_value)
         logger.info("Successfully import data to TPE/Anneal tuner.")

src/sdk/pynni/nni/metis_tuner/metis_tuner.py

@@ -65,7 +65,7 @@ class MetisTuner(Tuner):
     https://www.microsoft.com/en-us/research/publication/metis-robustly-tuning-tail-latencies-cloud-systems/
     """
 
-    def __init__(self, optimize_mode="maximize", no_resampling=True, no_candidates=True,
+    def __init__(self, optimize_mode="maximize", no_resampling=True, no_candidates=False,
                  selection_num_starting_points=600, cold_start_num=10, exploration_probability=0.9):
         """
         Parameters
@@ -417,6 +417,9 @@ class MetisTuner(Tuner):
             _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
             self.supplement_data_num += 1
             _parameter_id = '_'.join(["ImportData", str(self.supplement_data_num)])
             self.total_data.append(_params)

src/sdk/pynni/nni/msg_dispatcher_base.py

@@ -77,6 +77,8 @@ class MsgDispatcherBase(Recoverable):
                     break
             else:
                 self.enqueue_command(command, data)
+                if self.worker_exceptions:
+                    break
 
         _logger.info('Dispatcher exiting...')
         self.stopping = True

src/webui/src/components/trial-detail/DefaultMetricPoint.tsx

@@ -30,7 +30,8 @@ class DefaultPoint extends React.Component<DefaultPointProps, DefaultPointState>
         const accSource: Array<DetailAccurPoint> = [];
         Object.keys(showSource).map(item => {
             const temp = showSource[item];
-            if (temp.status === 'SUCCEEDED' && temp.acc.default !== undefined) {
+            if (temp.status === 'SUCCEEDED' && temp.acc !== undefined) {
+                if (temp.acc.default !== undefined) {
                     const searchSpace = temp.description.parameters;
                     accSource.push({
                         acc: temp.acc.default,
@@ -38,6 +39,7 @@ class DefaultPoint extends React.Component<DefaultPointProps, DefaultPointState>
                         searchSpace: JSON.stringify(searchSpace)
                     });
                 }
+            }
         });
         const resultList: Array<number | string>[] = [];
         Object.keys(accSource).map(item => {

tools/nni_cmd/common_utils.py

@@ -32,9 +32,12 @@ def get_yml_content(file_path):
     try:
         with open(file_path, 'r') as file:
             return yaml.load(file, Loader=yaml.Loader)
-    except TypeError as err:
-        print('Error: ', err)
-        return None
+    except yaml.scanner.ScannerError as err:
+        print_error('yaml file format error!')
+        exit(1)
+    except Exception as exception:
+        print_error(exception)
+        exit(1)
 
 def get_json_content(file_path):
     '''Load json file content'''
@@ -42,7 +45,7 @@ def get_json_content(file_path):
         with open(file_path, 'r') as file:
             return json.load(file)
     except TypeError as err:
-        print('Error: ', err)
+        print_error('json file format error!')
         return None
 
 def print_error(content):

tools/nni_cmd/launcher.py

@@ -114,7 +114,10 @@ def start_rest_server(port, platform, mode, config_file_name, experiment_id=None
     entry_dir = get_nni_installation_path()
     entry_file = os.path.join(entry_dir, 'main.js')
     
-    cmds = ['node', entry_file, '--port', str(port), '--mode', platform, '--start_mode', mode]
+    node_command = 'node'
+    if sys.platform == 'win32':
+        node_command = os.path.join(entry_dir[:-3], 'Scripts', 'node.exe')
+    cmds = [node_command, entry_file, '--port', str(port), '--mode', platform, '--start_mode', mode]
     if log_dir is not None:
         cmds += ['--log_dir', log_dir]
     if log_level is not None:

tools/nni_cmd/updater.py

@@ -136,7 +136,7 @@ def import_data(args):
     args.port = get_experiment_port(args)
     if args.port is not None:
         if import_data_to_restful_server(args, content):
-            print_normal('Import data success!')
+            pass
         else:
             print_error('Import data failed!')
 

tools/nni_gpu_tool/gpu_metrics_collector.py

@@ -25,9 +25,14 @@ import time
 from xml.dom import minidom
 
 def check_ready_to_run():
-    #TODO check process in windows
     if sys.platform == 'win32':
-        return True
+        pgrep_output = subprocess.check_output('wmic process where "CommandLine like \'%nni_gpu_tool.gpu_metrics_collector%\' and name like \'%python%\'" get processId')
+        pidList = pgrep_output.decode("utf-8").strip().split()
+        pidList.pop(0) # remove the key word 'ProcessId'
+        pidList = list(map(int, pidList))
+        pidList.remove(os.getpid())
+        return len(pidList) == 0
+    else:
         pgrep_output =subprocess.check_output('pgrep -fx \'python3 -m nni_gpu_tool.gpu_metrics_collector\'', shell=True)
         pidList = []
         for pid in pgrep_output.splitlines():