Multiphase refactor and support OpenPAI training service. (#1138)

* Refactor multiphase interface

* Implement multiphase on PAI

* update multiphase doc

src/sdk/pynni/nni/networkmorphism_tuner/networkmorphism_tuner.py

@@ -123,7 +123,7 @@ class NetworkMorphismTuner(Tuner):
         """
         self.search_space = search_space
 
-    def generate_parameters(self, parameter_id):
+    def generate_parameters(self, parameter_id, **kwargs):
         """
         Returns a set of trial neural architecture, as a serializable object.
 
@@ -152,7 +152,7 @@ class NetworkMorphismTuner(Tuner):
 
         return json_out
 
-    def receive_trial_result(self, parameter_id, parameters, value):
+    def receive_trial_result(self, parameter_id, parameters, value, **kwargs):
         """ Record an observation of the objective function.
 
         Parameters

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

@@ -151,7 +151,7 @@ class SMACTuner(Tuner):
         else:
             self.logger.warning('update search space is not supported.')
 
-    def receive_trial_result(self, parameter_id, parameters, value):
+    def receive_trial_result(self, parameter_id, parameters, value, **kwargs):
         """receive_trial_result
 
         Parameters
@@ -209,7 +209,7 @@ class SMACTuner(Tuner):
                 converted_dict[key] = value
         return converted_dict
 
-    def generate_parameters(self, parameter_id):
+    def generate_parameters(self, parameter_id, **kwargs):
         """generate one instance of hyperparameters
 
         Parameters
@@ -232,7 +232,7 @@ class SMACTuner(Tuner):
                 self.total_data[parameter_id] = challenger
                 return self.convert_loguniform_categorical(challenger.get_dictionary())
 
-    def generate_multiple_parameters(self, parameter_id_list):
+    def generate_multiple_parameters(self, parameter_id_list, **kwargs):
         """generate mutiple instances of hyperparameters
 
         Parameters

src/sdk/pynni/nni/tuner.py

@@ -30,14 +30,14 @@ _logger = logging.getLogger(__name__)
 class Tuner(Recoverable):
     # pylint: disable=no-self-use,unused-argument
 
-    def generate_parameters(self, parameter_id):
+    def generate_parameters(self, parameter_id, **kwargs):
         """Returns a set of trial (hyper-)parameters, as a serializable object.
         User code must override either this function or 'generate_multiple_parameters()'.
         parameter_id: int
         """
         raise NotImplementedError('Tuner: generate_parameters not implemented')
 
-    def generate_multiple_parameters(self, parameter_id_list):
+    def generate_multiple_parameters(self, parameter_id_list, **kwargs):
         """Returns multiple sets of trial (hyper-)parameters, as iterable of serializable objects.
         Call 'generate_parameters()' by 'count' times by default.
         User code must override either this function or 'generate_parameters()'.
@@ -49,13 +49,13 @@ class Tuner(Recoverable):
         for parameter_id in parameter_id_list:
             try:
                 _logger.debug("generating param for {}".format(parameter_id))
-                res = self.generate_parameters(parameter_id)
+                res = self.generate_parameters(parameter_id, **kwargs)
             except nni.NoMoreTrialError:
                 return result
             result.append(res)
         return result
 
-    def receive_trial_result(self, parameter_id, parameters, value):
+    def receive_trial_result(self, parameter_id, parameters, value, **kwargs):
         """Invoked when a trial reports its final result. Must override.
         parameter_id: int
         parameters: object created by 'generate_parameters()'
@@ -63,7 +63,7 @@ class Tuner(Recoverable):
         """
         raise NotImplementedError('Tuner: receive_trial_result not implemented')
 
-    def receive_customized_trial_result(self, parameter_id, parameters, value):
+    def receive_customized_trial_result(self, parameter_id, parameters, value, **kwargs):
         """Invoked when a trial added by WebUI reports its final result. Do nothing by default.
         parameter_id: int
         parameters: object created by user
@@ -71,7 +71,7 @@ class Tuner(Recoverable):
         """
         _logger.info('Customized trial job %s ignored by tuner', parameter_id)
 
-    def trial_end(self, parameter_id, success):
+    def trial_end(self, parameter_id, success, **kwargs):
         """Invoked when a trial is completed or terminated. Do nothing by default.
         parameter_id: int
         success: True if the trial successfully completed; False if failed or terminated

src/sdk/pynni/tests/test_multi_phase_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.
-# ==================================================================================================
-
-
-import logging
-import random
-from io import BytesIO
-
-import nni
-import nni.protocol
-from nni.protocol import CommandType, send, receive
-from nni.multi_phase.multi_phase_tuner import MultiPhaseTuner
-from nni.multi_phase.multi_phase_dispatcher import MultiPhaseMsgDispatcher
-
-from unittest import TestCase, main
-
-class NaiveMultiPhaseTuner(MultiPhaseTuner):
-    '''
-    supports only choices
-    '''
-    def __init__(self):
-        self.search_space = None
-
-    def generate_parameters(self, parameter_id, trial_job_id=None):
-        """Returns a set of trial (hyper-)parameters, as a serializable object.
-        User code must override either this function or 'generate_multiple_parameters()'.
-        parameter_id: int
-        """
-        generated_parameters = {}
-        if self.search_space is None:
-            raise AssertionError('Search space not specified')
-        for k in self.search_space:
-            param = self.search_space[k]
-            if not param['_type'] == 'choice':
-                raise ValueError('Only choice type is supported')
-            param_values = param['_value']
-            generated_parameters[k] = param_values[random.randint(0, len(param_values)-1)]
-        logging.getLogger(__name__).debug(generated_parameters)
-        return generated_parameters
-
-
-    def receive_trial_result(self, parameter_id, parameters, value, trial_job_id):
-        logging.getLogger(__name__).debug('receive_trial_result: {},{},{},{}'.format(parameter_id, parameters, value, trial_job_id))
-
-    def receive_customized_trial_result(self, parameter_id, parameters, value, trial_job_id):
-        pass
-
-    def update_search_space(self, search_space):
-        self.search_space = search_space
-
-
-_in_buf = BytesIO()
-_out_buf = BytesIO()
-
-def _reverse_io():
-    _in_buf.seek(0)
-    _out_buf.seek(0)
-    nni.protocol._out_file = _in_buf
-    nni.protocol._in_file = _out_buf
-
-def _restore_io():
-    _in_buf.seek(0)
-    _out_buf.seek(0)
-    nni.protocol._in_file = _in_buf
-    nni.protocol._out_file = _out_buf
-
-def _test_tuner():
-    _reverse_io()  # now we are sending to Tuner's incoming stream
-    send(CommandType.UpdateSearchSpace, "{\"learning_rate\": {\"_value\": [0.0001, 0.001, 0.002, 0.005, 0.01], \"_type\": \"choice\"}, \"optimizer\": {\"_value\": [\"Adam\", \"SGD\"], \"_type\": \"choice\"}}")
-    send(CommandType.RequestTrialJobs, '2')
-    send(CommandType.ReportMetricData, '{"parameter_id":0,"type":"PERIODICAL","value":10,"trial_job_id":"abc"}')
-    send(CommandType.ReportMetricData, '{"parameter_id":1,"type":"FINAL","value":11,"trial_job_id":"abc"}')
-    send(CommandType.AddCustomizedTrialJob, '{"param":-1}')
-    send(CommandType.ReportMetricData, '{"parameter_id":2,"type":"FINAL","value":22,"trial_job_id":"abc"}')
-    send(CommandType.RequestTrialJobs, '1')
-    send(CommandType.TrialEnd, '{"trial_job_id":"abc"}')
-    _restore_io()
-
-    tuner = NaiveMultiPhaseTuner()
-    dispatcher = MultiPhaseMsgDispatcher(tuner)
-    dispatcher.run()
-
-    _reverse_io()  # now we are receiving from Tuner's outgoing stream
-
-    command, data = receive()  # this one is customized
-    print(command, data)
-
-class MultiPhaseTestCase(TestCase):
-    def test_tuner(self):
-        _test_tuner()
-
-if __name__ == '__main__':
-    main()
\ No newline at end of file

src/sdk/pynni/tests/test_tuner.py

@@ -35,7 +35,7 @@ class NaiveTuner(Tuner):
         self.trial_results = [ ]
         self.search_space = None
 
-    def generate_parameters(self, parameter_id):
+    def generate_parameters(self, parameter_id, **kwargs):
         # report Tuner's internal states to generated parameters,
         # so we don't need to pause the main loop
         self.param += 2
@@ -45,7 +45,7 @@ class NaiveTuner(Tuner):
             'search_space': self.search_space
         }
 
-    def receive_trial_result(self, parameter_id, parameters, value):
+    def receive_trial_result(self, parameter_id, parameters, value, **kwargs):
         reward = extract_scalar_reward(value)
         self.trial_results.append((parameter_id, parameters['param'], reward, False))
 
@@ -103,11 +103,9 @@ class TunerTestCase(TestCase):
         command, data = receive()  # this one is customized
         data = json.loads(data)
         self.assertIs(command, CommandType.NewTrialJob)
-        self.assertEqual(data, {
-            'parameter_id': 2,
-            'parameter_source': 'customized',
-            'parameters': { 'param': -1 }
-        })
+        self.assertEqual(data['parameter_id'], 2)
+        self.assertEqual(data['parameter_source'], 'customized')
+        self.assertEqual(data['parameters'], { 'param': -1 })
 
         self._assert_params(3, 6, [[1,4,11,False], [2,-1,22,True]], {'name':'SS0'})
 

test/async_sharing_test/simple_tuner.py

@@ -22,7 +22,7 @@ class SimpleTuner(Tuner):
         self.sig_event = Event()
         self.thread_lock = Lock()
 
-    def generate_parameters(self, parameter_id):
+    def generate_parameters(self, parameter_id, **kwargs):
         if self.f_id is None:
             self.thread_lock.acquire()
             self.f_id = parameter_id
@@ -50,7 +50,7 @@ class SimpleTuner(Tuner):
             self.thread_lock.release()
             return self.trial_meta[parameter_id]
 
-    def receive_trial_result(self, parameter_id, parameters, reward):
+    def receive_trial_result(self, parameter_id, parameters, reward, **kwargs):
         self.thread_lock.acquire()
         if parameter_id == self.f_id:
             self.trial_meta[parameter_id]['checksum'] = reward['checksum']

test/config_test/multi_phase/multi_phase.test.yml

@@ -6,9 +6,9 @@ trialConcurrency: 4
 searchSpacePath: ./search_space.json
 
 tuner:
-  codeDir: ../../../src/sdk/pynni/tests
-  classFileName: test_multi_phase_tuner.py
-  className: NaiveMultiPhaseTuner
+  builtinTunerName: TPE
+  classArgs:
+    optimize_mode: maximize
 
 trial:
   codeDir: .

test/config_test/multi_phase/multi_phase_batch.test.yml

+authorName: nni
+experimentName: default_test
+maxExecDuration: 5m
+maxTrialNum: 8
+trialConcurrency: 4
+searchSpacePath: ./search_space.json
+
+tuner:
+  builtinTunerName: BatchTuner
+
+trial:
+  codeDir: .
+  command: python3 multi_phase.py
+  gpuNum: 0
+
+useAnnotation: false
+multiPhase: true
+multiThread: false
+
+trainingServicePlatform: local

test/config_test/multi_phase/multi_phase_evolution.test.yml

+authorName: nni
+experimentName: default_test
+maxExecDuration: 5m
+maxTrialNum: 8
+trialConcurrency: 4
+searchSpacePath: ./search_space.json
+
+tuner:
+  builtinTunerName: Evolution
+  classArgs:
+    optimize_mode: maximize
+
+trial:
+  codeDir: .
+  command: python3 multi_phase.py
+  gpuNum: 0
+
+useAnnotation: false
+multiPhase: true
+multiThread: false
+
+trainingServicePlatform: local

test/config_test/multi_phase/multi_phase_grid.test.yml

+authorName: nni
+experimentName: default_test
+maxExecDuration: 5m
+maxTrialNum: 8
+trialConcurrency: 4
+searchSpacePath: ./search_space.json
+
+tuner:
+  builtinTunerName: GridSearch
+
+trial:
+  codeDir: .
+  command: python3 multi_phase.py
+  gpuNum: 0
+
+useAnnotation: false
+multiPhase: true
+multiThread: false
+
+trainingServicePlatform: local

test/config_test/multi_phase/multi_phase_metis.test.yml

+authorName: nni
+experimentName: default_test
+maxExecDuration: 5m
+maxTrialNum: 8
+trialConcurrency: 4
+searchSpacePath: ./search_space.json
+
+tuner:
+  builtinTunerName: MetisTuner
+  classArgs:
+    optimize_mode: maximize
+
+trial:
+  codeDir: .
+  command: python3 multi_phase.py
+  gpuNum: 0
+
+useAnnotation: false
+multiPhase: true
+multiThread: false
+
+trainingServicePlatform: local

test/config_test/multi_phase/multi_phase_tpe.test.yml

+authorName: nni
+experimentName: default_test
+maxExecDuration: 5m
+maxTrialNum: 8
+trialConcurrency: 4
+searchSpacePath: ./search_space.json
+
+tuner:
+  builtinTunerName: TPE
+  classArgs:
+    optimize_mode: maximize
+
+trial:
+  codeDir: .
+  command: python3 multi_phase.py
+  gpuNum: 0
+
+useAnnotation: false
+multiPhase: true
+multiThread: false
+
+trainingServicePlatform: local

test/config_test/multi_thread/multi_thread_tuner.py

@@ -6,7 +6,7 @@ class MultiThreadTuner(Tuner):
     def __init__(self):
         self.parent_done = False
 
-    def generate_parameters(self, parameter_id):
+    def generate_parameters(self, parameter_id, **kwargs):
         if parameter_id == 0:
             return {'x': 0}
         else:
@@ -14,7 +14,7 @@ class MultiThreadTuner(Tuner):
                 time.sleep(2)
             return {'x': 1}
 
-    def receive_trial_result(self, parameter_id, parameters, value):
+    def receive_trial_result(self, parameter_id, parameters, value, **kwargs):
         if parameter_id == 0:
             self.parent_done = True
 

test/naive_test/naive_tuner.py

@@ -16,12 +16,12 @@ class NaiveTuner(Tuner):
         self.cur = 0
         _logger.info('init')
 
-    def generate_parameters(self, parameter_id):
+    def generate_parameters(self, parameter_id, **kwargs):
         self.cur += 1
         _logger.info('generate parameters: %s' % self.cur)
         return { 'x': self.cur }
 
-    def receive_trial_result(self, parameter_id, parameters, value):
+    def receive_trial_result(self, parameter_id, parameters, value, **kwargs):
         reward = extract_scalar_reward(value)
         _logger.info('receive trial result: %s, %s, %s' % (parameter_id, parameters, reward))
         _result.write('%d %d\n' % (parameters['x'], reward))

tools/nni_trial_tool/constants.py

@@ -36,6 +36,8 @@ STDERR_FULL_PATH = os.path.join(LOG_DIR, 'stderr')
 
 STDOUT_API = '/stdout'
 VERSION_API = '/version'
+PARAMETER_META_API = '/parameter-file-meta'
 NNI_SYS_DIR = os.environ['NNI_SYS_DIR']
 NNI_TRIAL_JOB_ID = os.environ['NNI_TRIAL_JOB_ID']
-NNI_EXP_ID = os.environ['NNI_EXP_ID']
+NNI_EXP_ID = os.environ['NNI_EXP_ID']
\ No newline at end of file
+MULTI_PHASE = os.environ['MULTI_PHASE']

tools/nni_trial_tool/trial_keeper.py

@@ -28,30 +28,27 @@ import re
 import sys
 import select
 import json
+import threading
 from pyhdfs import HdfsClient
 import pkg_resources
-from .rest_utils import rest_post
-from .url_utils import gen_send_stdout_url, gen_send_version_url
+from .rest_utils import rest_post, rest_get
+from .url_utils import gen_send_stdout_url, gen_send_version_url, gen_parameter_meta_url
 
-from .constants import HOME_DIR, LOG_DIR, NNI_PLATFORM, STDOUT_FULL_PATH, STDERR_FULL_PATH
-from .hdfsClientUtility import copyDirectoryToHdfs, copyHdfsDirectoryToLocal
+from .constants import HOME_DIR, LOG_DIR, NNI_PLATFORM, STDOUT_FULL_PATH, STDERR_FULL_PATH, \
+    MULTI_PHASE, NNI_TRIAL_JOB_ID, NNI_SYS_DIR, NNI_EXP_ID
+from .hdfsClientUtility import copyDirectoryToHdfs, copyHdfsDirectoryToLocal, copyHdfsFileToLocal
 from .log_utils import LogType, nni_log, RemoteLogger, PipeLogReader, StdOutputType
 
 logger = logging.getLogger('trial_keeper')
 regular = re.compile('v?(?P<version>[0-9](\.[0-9]){0,1}).*')
 
-def main_loop(args):
-    '''main loop logic for trial keeper'''
+_hdfs_client = None
 
-    if not os.path.exists(LOG_DIR):
-        os.makedirs(LOG_DIR)
+def get_hdfs_client(args):
+    global _hdfs_client
 
-    stdout_file = open(STDOUT_FULL_PATH, 'a+')
-    stderr_file = open(STDERR_FULL_PATH, 'a+')
-    trial_keeper_syslogger = RemoteLogger(args.nnimanager_ip, args.nnimanager_port, 'trial_keeper', StdOutputType.Stdout, args.log_collection)
-    # redirect trial keeper's stdout and stderr to syslog
-    trial_syslogger_stdout = RemoteLogger(args.nnimanager_ip, args.nnimanager_port, 'trial', StdOutputType.Stdout, args.log_collection)
-    sys.stdout = sys.stderr = trial_keeper_syslogger
+    if _hdfs_client is not None:
+        return _hdfs_client
     # backward compatibility
     hdfs_host = None
     hdfs_output_dir = None
@@ -59,21 +56,41 @@ def main_loop(args):
         hdfs_host = args.hdfs_host
     elif args.pai_hdfs_host:
         hdfs_host = args.pai_hdfs_host
-    if args.hdfs_output_dir:
-        hdfs_output_dir = args.hdfs_output_dir
-    elif args.pai_hdfs_output_dir:
-        hdfs_output_dir = args.pai_hdfs_output_dir
+    else:
+        return None
 
     if hdfs_host is not None and args.nni_hdfs_exp_dir is not None:
         try:
             if args.webhdfs_path:
-                hdfs_client = HdfsClient(hosts='{0}:80'.format(hdfs_host), user_name=args.pai_user_name, webhdfs_path=args.webhdfs_path, timeout=5)
+                _hdfs_client = HdfsClient(hosts='{0}:80'.format(hdfs_host), user_name=args.pai_user_name, webhdfs_path=args.webhdfs_path, timeout=5)
             else:
                 # backward compatibility
-                hdfs_client = HdfsClient(hosts='{0}:{1}'.format(hdfs_host, '50070'), user_name=args.pai_user_name, timeout=5)
+                _hdfs_client = HdfsClient(hosts='{0}:{1}'.format(hdfs_host, '50070'), user_name=args.pai_user_name, timeout=5)
         except Exception as e:
             nni_log(LogType.Error, 'Create HDFS client error: ' + str(e))
             raise e
+    return _hdfs_client
+
+def main_loop(args):
+    '''main loop logic for trial keeper'''
+
+    if not os.path.exists(LOG_DIR):
+        os.makedirs(LOG_DIR)
+
+    stdout_file = open(STDOUT_FULL_PATH, 'a+')
+    stderr_file = open(STDERR_FULL_PATH, 'a+')
+    trial_keeper_syslogger = RemoteLogger(args.nnimanager_ip, args.nnimanager_port, 'trial_keeper', StdOutputType.Stdout, args.log_collection)
+    # redirect trial keeper's stdout and stderr to syslog
+    trial_syslogger_stdout = RemoteLogger(args.nnimanager_ip, args.nnimanager_port, 'trial', StdOutputType.Stdout, args.log_collection)
+    sys.stdout = sys.stderr = trial_keeper_syslogger
+    if args.hdfs_output_dir:
+        hdfs_output_dir = args.hdfs_output_dir
+    elif args.pai_hdfs_output_dir:
+        hdfs_output_dir = args.pai_hdfs_output_dir
+
+    hdfs_client = get_hdfs_client(args)
+
+    if hdfs_client is not None:
         copyHdfsDirectoryToLocal(args.nni_hdfs_exp_dir, os.getcwd(), hdfs_client)
 
     # Notice: We don't appoint env, which means subprocess wil inherit current environment and that is expected behavior
@@ -138,6 +155,52 @@ def check_version(args):
         except AttributeError as err:
             nni_log(LogType.Error, err)
 
+def is_multi_phase():
+    return MULTI_PHASE and (MULTI_PHASE in ['True', 'true'])
+
+def download_parameter(meta_list, args):
+    """
+    Download parameter file to local working directory.
+    meta_list format is defined in paiJobRestServer.ts
+    example meta_list:
+    [
+        {"experimentId":"yWFJarYa","trialId":"UpPkl","filePath":"/chec/nni/experiments/yWFJarYa/trials/UpPkl/parameter_1.cfg"},
+        {"experimentId":"yWFJarYa","trialId":"aIUMA","filePath":"/chec/nni/experiments/yWFJarYa/trials/aIUMA/parameter_1.cfg"}
+    ]
+    """
+    nni_log(LogType.Debug, str(meta_list))
+    nni_log(LogType.Debug, 'NNI_SYS_DIR: {}, trial Id: {}, experiment ID: {}'.format(NNI_SYS_DIR, NNI_TRIAL_JOB_ID, NNI_EXP_ID))
+    nni_log(LogType.Debug, 'NNI_SYS_DIR files: {}'.format(os.listdir(NNI_SYS_DIR)))
+    for meta in meta_list:
+        if meta['experimentId'] == NNI_EXP_ID and meta['trialId'] == NNI_TRIAL_JOB_ID:
+            param_fp = os.path.join(NNI_SYS_DIR, os.path.basename(meta['filePath']))
+            if not os.path.exists(param_fp):
+                hdfs_client = get_hdfs_client(args)
+                copyHdfsFileToLocal(meta['filePath'], param_fp, hdfs_client, override=False)
+
+def fetch_parameter_file(args):
+    class FetchThread(threading.Thread):
+        def __init__(self, args):
+            super(FetchThread, self).__init__()
+            self.args = args
+
+        def run(self):
+            uri = gen_parameter_meta_url(self.args.nnimanager_ip, self.args.nnimanager_port)
+            nni_log(LogType.Info, uri)
+
+            while True:
+                res = rest_get(uri, 10)
+                nni_log(LogType.Debug, 'status code: {}'.format(res.status_code))
+                if res.status_code == 200:
+                    meta_list = res.json()
+                    download_parameter(meta_list, self.args)
+                else:
+                    nni_log(LogType.Warning, 'rest response: {}'.format(str(res)))
+                time.sleep(5)
+
+    fetch_file_thread = FetchThread(args)
+    fetch_file_thread.start()
+
 if __name__ == '__main__':
     '''NNI Trial Keeper main function'''
     PARSER = argparse.ArgumentParser()
@@ -159,6 +222,8 @@ if __name__ == '__main__':
         exit(1)
     check_version(args)
     try:
+        if is_multi_phase():
+            fetch_parameter_file(args)
         main_loop(args)
     except SystemExit as se:
         nni_log(LogType.Info, 'NNI trial keeper exit with code {}'.format(se.code))

tools/nni_trial_tool/url_utils.py

@@ -18,7 +18,7 @@
 # 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.
 
-from .constants import API_ROOT_URL, BASE_URL, STDOUT_API, NNI_TRIAL_JOB_ID, NNI_EXP_ID, VERSION_API
+from .constants import API_ROOT_URL, BASE_URL, STDOUT_API, NNI_TRIAL_JOB_ID, NNI_EXP_ID, VERSION_API, PARAMETER_META_API
 
 def gen_send_stdout_url(ip, port):
     '''Generate send stdout url'''
@@ -26,4 +26,8 @@ def gen_send_stdout_url(ip, port):
 
 def gen_send_version_url(ip, port):
     '''Generate send error url'''
-    return '{0}:{1}{2}{3}/{4}/{5}'.format(BASE_URL.format(ip), port, API_ROOT_URL, VERSION_API, NNI_EXP_ID, NNI_TRIAL_JOB_ID)
+    return '{0}:{1}{2}{3}/{4}/{5}'.format(BASE_URL.format(ip), port, API_ROOT_URL, VERSION_API, NNI_EXP_ID, NNI_TRIAL_JOB_ID)
\ No newline at end of file
+
+def gen_parameter_meta_url(ip, port):
+    '''Generate send error url'''
+    return '{0}:{1}{2}{3}'.format(BASE_URL.format(ip), port, API_ROOT_URL, PARAMETER_META_API)