add batch_tuner

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

+# Copyright (c) Microsoft Corporation
+# All rights reserved.
+#
+# MIT License
+#
+# Permission is hereby granted, free of charge,
+# to any person obtaining a copy of this software and associated
+# documentation files (the "Software"), to deal in the Software without restriction,
+# including without limitation the rights to use, copy, modify, merge, publish,
+# distribute, sublicense, and/or sell copies of the Software, and
+# to permit persons to whom the Software is furnished to do so, subject to the following conditions:
+# The above copyright notice and this permission notice shall be included
+# in all copies or substantial portions of the Software.
+#
+# THE SOFTWARE IS PROVIDED *AS IS*, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING
+# BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
+# NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM,
+# DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
+'''
+batch_tuner.py including:
+    class BatchTuner
+'''
+
+import copy
+from enum import Enum, unique
+import random
+
+import numpy as np
+
+from nni.tuner import Tuner
+from . import parameter_expressions
+
+
+TYPE = '_type'
+CHOICE = 'choice'
+VALUE = '_value'
+
+
+class BatchTuner(Tuner):
+    '''
+    BatchTuner is tuner will running all the configure that user want to run batchly.
+    The search space only be accepted like:
+    {
+        'combine_params': { '_type': 'choice',
+                             '_value': '[{...}, {...}, {...}]',
+                          }
+    }
+    '''
+    
+    def __init__(self):
+        self.count = -1
+        self.values = []
+
+    def is_valid(self, search_space)
+        '''
+        Check the search space is valid: only contains 'choice' type
+        '''
+        if not len(search_space) == 1:
+            raise RuntimeException('BatchTuner only supprt one combined-paramreters key.')
+        
+        for param in search_space:
+            param_type = param[TYPE]
+            if param_type is not CHOICE:
+                raise RuntimeException('BatchTuner only supprt one combined-paramreters type is choice.')
+            else:
+                if isinstance(param[VALUE], list):
+                    return param[VALUE]
+                raise RuntimeException('The combined-paramreters value in BatchTuner is not a list.')
+        return None
+
+    def update_search_space(self, search_space):
+        self.values = is_valid(search_space)
+
+    def generate_parameters(self, parameter_id):
+        count +=1
+        if count>len(self.value)-1:
+            return None
+        return self.values[count]
+
+    def receive_trial_result(self, parameter_id, parameters, reward):
+        pass
\ No newline at end of file

src/sdk/pynni/nni/msg_dispatcher.py

@@ -89,9 +89,14 @@ class MsgDispatcher(MsgDispatcherBase):
         # data: number or trial jobs
         ids = [_create_parameter_id() for _ in range(data)]
         params_list = self.tuner.generate_multiple_parameters(ids)
-        assert len(ids) == len(params_list)
-        for i, _ in enumerate(ids):
-            send(CommandType.NewTrialJob, _pack_parameter(ids[i], params_list[i]))
+        #assert len(ids) == len(params_list)
+
+        # when parameters is None.
+        if len(params_list) == 0:
+            send(CommandType.NoMoreTrialJobs, _pack_parameter(ids[0], ''))
+        else:
+            for i, _ in enumerate(ids):
+                send(CommandType.NewTrialJob, _pack_parameter(ids[i], params_list[i]))
         return True
 
     def handle_update_search_space(self, data):

src/sdk/pynni/nni/tuner.py

@@ -42,7 +42,12 @@ class Tuner(Recoverable):
         User code must override either this function or 'generate_parameters()'.
         parameter_id_list: list of int
         """
-        return [self.generate_parameters(parameter_id) for parameter_id in parameter_id_list]
+        result = []
+        for parameter_id in parameter_id_list:
+            temp = self.generate_parameters(parameter_id)
+            if temp:
+                result.append(temp)
+        return result
 
     def receive_trial_result(self, parameter_id, parameters, reward):
         """Invoked when a trial reports its final result. Must override.

tools/nnicmd/launcher_utils.py

@@ -90,7 +90,8 @@ def parse_tuner_content(experiment_config):
     tuner_class_name_dict = {'TPE': 'HyperoptTuner',\
                             'Random': 'HyperoptTuner',\
                             'Anneal': 'HyperoptTuner',\
-                            'Evolution': 'EvolutionTuner'}
+                            'Evolution': 'EvolutionTuner',\
+                            'BatchTuning': 'BatchTuner'}
 
     tuner_algorithm_name_dict = {'TPE': 'tpe',\
                             'Random': 'random_search',\