fix bugs

examples/trials/mnist-batch-tune-keras/config.yml

@@ -2,7 +2,7 @@ authorName: default
 experimentName: example_mnist-keras
 trialConcurrency: 1
 maxExecDuration: 1h
-maxTrialNum: 10
+maxTrialNum: 6
 #choice: local, remote
 trainingServicePlatform: local
 searchSpacePath: ~/nni/examples/trials/mnist-batch-tune-keras/search_space.json
@@ -17,4 +17,4 @@ tuner:
 trial:
   command: python3 mnist-keras.py
   codeDir: ~/nni/examples/trials/mnist-batch-tune-keras
-  gpuNum: 0
\ No newline at end of file
+  gpuNum: 0

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

@@ -28,6 +28,7 @@ import random
 
 import numpy as np
 
+import nni
 from nni.tuner import Tuner
 
 TYPE = '_type'
@@ -73,7 +74,7 @@ class BatchTuner(Tuner):
     def generate_parameters(self, parameter_id):
         self.count +=1
         if self.count>len(self.values)-1:
-            return None
+            raise nni.NoMoreTrialError('no more parameters now.')
         return self.values[self.count]
 
     def receive_trial_result(self, parameter_id, parameters, reward):

src/sdk/pynni/nni/msg_dispatcher.py

@@ -89,7 +89,6 @@ 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)
 
         # when parameters is None.
         if len(params_list) == 0:

src/sdk/pynni/nni/tuner.py

@@ -21,6 +21,7 @@
 
 import logging
 
+import nni
 from .recoverable import Recoverable
 
 _logger = logging.getLogger(__name__)
@@ -44,9 +45,11 @@ class Tuner(Recoverable):
         """
         result = []
         for parameter_id in parameter_id_list:
-            temp = self.generate_parameters(parameter_id)
-            if temp:
-                result.append(temp)
+            try:
+                res = self.generate_parameters(parameter_id)
+            except nni.NoMoreTrialError:
+                return result
+            result.append(res)
         return result
 
     def receive_trial_result(self, parameter_id, parameters, reward):