Merge branch 'v2.0' into master

nni/retiarii/trainer/__init__.py

-from .interface import BaseTrainer
+from .interface import BaseTrainer, BaseOneShotTrainer
 from .pytorch import PyTorchImageClassificationTrainer, PyTorchMultiModelTrainer

nni/retiarii/trainer/pytorch/base.py

@@ -43,7 +43,7 @@ def get_default_transform(dataset: str) -> Any:
     return None
 
 
-@register_trainer()
+@register_trainer
 class PyTorchImageClassificationTrainer(BaseTrainer):
     """
     Image classification trainer for PyTorch.
@@ -80,7 +80,7 @@ class PyTorchImageClassificationTrainer(BaseTrainer):
             Keyword arguments passed to trainer. Will be passed to Trainer class in future. Currently,
             only the key ``max_epochs`` is useful.
         """
-        super(PyTorchImageClassificationTrainer, self).__init__()
+        super().__init__()
         self._use_cuda = torch.cuda.is_available()
         self.model = model
         if self._use_cuda:

nni/retiarii/trainer/pytorch/darts.py

@@ -6,6 +6,7 @@ import logging
 
 import torch
 import torch.nn as nn
+import torch.nn.functional as F
 
 from ..interface import BaseOneShotTrainer
 from .utils import AverageMeterGroup, replace_layer_choice, replace_input_choice
@@ -17,13 +18,14 @@ _logger = logging.getLogger(__name__)
 class DartsLayerChoice(nn.Module):
     def __init__(self, layer_choice):
         super(DartsLayerChoice, self).__init__()
+        self.name = layer_choice.key
         self.op_choices = nn.ModuleDict(layer_choice.named_children())
         self.alpha = nn.Parameter(torch.randn(len(self.op_choices)) * 1e-3)
 
     def forward(self, *args, **kwargs):
         op_results = torch.stack([op(*args, **kwargs) for op in self.op_choices.values()])
         alpha_shape = [-1] + [1] * (len(op_results.size()) - 1)
-        return torch.sum(op_results * self.alpha.view(*alpha_shape), 0)
+        return torch.sum(op_results * F.softmax(self.alpha, -1).view(*alpha_shape), 0)
 
     def parameters(self):
         for _, p in self.named_parameters():
@@ -42,13 +44,14 @@ class DartsLayerChoice(nn.Module):
 class DartsInputChoice(nn.Module):
     def __init__(self, input_choice):
         super(DartsInputChoice, self).__init__()
+        self.name = input_choice.key
         self.alpha = nn.Parameter(torch.randn(input_choice.n_candidates) * 1e-3)
         self.n_chosen = input_choice.n_chosen or 1
 
     def forward(self, inputs):
         inputs = torch.stack(inputs)
         alpha_shape = [-1] + [1] * (len(inputs.size()) - 1)
-        return torch.sum(inputs * self.alpha.view(*alpha_shape), 0)
+        return torch.sum(inputs * F.softmax(self.alpha, -1).view(*alpha_shape), 0)
 
     def parameters(self):
         for _, p in self.named_parameters():
@@ -123,7 +126,15 @@ class DartsTrainer(BaseOneShotTrainer):
             module.to(self.device)
 
         self.model_optim = optimizer
-        self.ctrl_optim = torch.optim.Adam([m.alpha for _, m in self.nas_modules], arc_learning_rate, betas=(0.5, 0.999),
+        # use the same architecture weight for modules with duplicated names
+        ctrl_params = {}
+        for _, m in self.nas_modules:
+            if m.name in ctrl_params:
+                assert m.alpha.size() == ctrl_params[m.name].size(), 'Size of parameters with the same label should be same.'
+                m.alpha = ctrl_params[m.name]
+            else:
+                ctrl_params[m.name] = m.alpha
+        self.ctrl_optim = torch.optim.Adam(list(ctrl_params.values()), arc_learning_rate, betas=(0.5, 0.999),
                                            weight_decay=1.0E-3)
         self.unrolled = unrolled
         self.grad_clip = 5.

nni/retiarii/trainer/pytorch/proxyless.py

@@ -157,6 +157,7 @@ class ProxylessTrainer(BaseOneShotTrainer):
             module.to(self.device)
 
         self.optimizer = optimizer
+        # we do not support deduplicate control parameters with same label (like DARTS) yet.
         self.ctrl_optim = torch.optim.Adam([m.alpha for _, m in self.nas_modules], arc_learning_rate,
                                            weight_decay=0, betas=(0, 0.999), eps=1e-8)
         self._init_dataloader()

nni/retiarii/trainer/pytorch/utils.py

@@ -6,6 +6,7 @@ from collections import OrderedDict
 
 import numpy as np
 import torch
+import nni.retiarii.nn.pytorch as nn
 from nni.nas.pytorch.mutables import InputChoice, LayerChoice
 
 _logger = logging.getLogger(__name__)
@@ -157,7 +158,7 @@ def replace_layer_choice(root_module, init_fn, modules=None):
     List[Tuple[str, nn.Module]]
         A list from layer choice keys (names) and replaced modules.
     """
-    return _replace_module_with_type(root_module, init_fn, LayerChoice, modules)
+    return _replace_module_with_type(root_module, init_fn, (LayerChoice, nn.LayerChoice), modules)
 
 
 def replace_input_choice(root_module, init_fn, modules=None):
@@ -178,4 +179,4 @@ def replace_input_choice(root_module, init_fn, modules=None):
     List[Tuple[str, nn.Module]]
         A list from layer choice keys (names) and replaced modules.
     """
-    return _replace_module_with_type(root_module, init_fn, InputChoice, modules)
+    return _replace_module_with_type(root_module, init_fn, (InputChoice, nn.InputChoice), modules)

nni/retiarii/utils.py

 import inspect
+import warnings
 from collections import defaultdict
 from typing import Any
 
@@ -11,6 +12,13 @@ def import_(target: str, allow_none: bool = False) -> Any:
     return getattr(module, identifier)
 
 
+def version_larger_equal(a: str, b: str) -> bool:
+    # TODO: refactor later
+    a = a.split('+')[0]
+    b = b.split('+')[0]
+    return tuple(map(int, a.split('.'))) >= tuple(map(int, b.split('.')))
+
+
 _records = {}
 
 
@@ -19,6 +27,11 @@ def get_records():
     return _records
 
 
+def clear_records():
+    global _records
+    _records = {}
+
+
 def add_record(key, value):
     """
     """
@@ -28,69 +41,83 @@ def add_record(key, value):
         _records[key] = value
 
 
-def _register_module(original_class):
-    orig_init = original_class.__init__
-    argname_list = list(inspect.signature(original_class).parameters.keys())
-    # Make copy of original __init__, so we can call it without recursion
+def del_record(key):
+    global _records
+    if _records is not None:
+        _records.pop(key, None)
 
-    def __init__(self, *args, **kws):
-        full_args = {}
-        full_args.update(kws)
-        for i, arg in enumerate(args):
-            full_args[argname_list[i]] = arg
-        add_record(id(self), full_args)
 
-        orig_init(self, *args, **kws)  # Call the original __init__
+def _blackbox_cls(cls, module_name, register_format=None):
+    class wrapper(cls):
+        def __init__(self, *args, **kwargs):
+            argname_list = list(inspect.signature(cls).parameters.keys())
+            full_args = {}
+            full_args.update(kwargs)
 
-    original_class.__init__ = __init__  # Set the class' __init__ to the new one
-    return original_class
+            assert len(args) <= len(argname_list), f'Length of {args} is greater than length of {argname_list}.'
+            for argname, value in zip(argname_list, args):
+                full_args[argname] = value
 
+            # eject un-serializable arguments
+            for k in list(full_args.keys()):
+                # The list is not complete and does not support nested cases.
+                if not isinstance(full_args[k], (int, float, str, dict, list, tuple)):
+                    if not (register_format == 'full' and k == 'model'):
+                        # no warning if it is base model in trainer
+                        warnings.warn(f'{cls} has un-serializable arguments {k} whose value is {full_args[k]}. \
+                            This is not supported. You can ignore this warning if you are passing the model to trainer.')
+                    full_args.pop(k)
 
-def register_module():
-    """
-    Register a module.
-    """
-    # use it as a decorator: @register_module()
-    def _register(cls):
-        m = _register_module(
-            original_class=cls)
-        return m
+            if register_format == 'args':
+                add_record(id(self), full_args)
+            elif register_format == 'full':
+                full_class_name = cls.__module__ + '.' + cls.__name__
+                add_record(id(self), {'modulename': full_class_name, 'args': full_args})
+
+            super().__init__(*args, **kwargs)
 
-    return _register
+        def __del__(self):
+            del_record(id(self))
 
+    # using module_name instead of cls.__module__ because it's more natural to see where the module gets wrapped
+    # instead of simply putting torch.nn or etc.
+    wrapper.__module__ = module_name
+    wrapper.__name__ = cls.__name__
+    wrapper.__qualname__ = cls.__qualname__
+    wrapper.__init__.__doc__ = cls.__init__.__doc__
 
-def _register_trainer(original_class):
-    orig_init = original_class.__init__
-    argname_list = list(inspect.signature(original_class).parameters.keys())
-    # Make copy of original __init__, so we can call it without recursion
+    return wrapper
 
-    full_class_name = original_class.__module__ + '.' + original_class.__name__
 
-    def __init__(self, *args, **kws):
-        full_args = {}
-        full_args.update(kws)
-        for i, arg in enumerate(args):
-            # TODO: support both pytorch and tensorflow
-            from .nn.pytorch import Module
-            if isinstance(args[i], Module):
-                # ignore the base model object
-                continue
-            full_args[argname_list[i]] = arg
-        add_record(id(self), {'modulename': full_class_name, 'args': full_args})
+def blackbox(cls, *args, **kwargs):
+    """
+    To create an blackbox instance inline without decorator. For example,
 
-        orig_init(self, *args, **kws)  # Call the original __init__
+    .. code-block:: python
+        self.op = blackbox(MyCustomOp, hidden_units=128)
+    """
+    # get caller module name
+    frm = inspect.stack()[1]
+    module_name = inspect.getmodule(frm[0]).__name__
+    return _blackbox_cls(cls, module_name, 'args')(*args, **kwargs)
 
-    original_class.__init__ = __init__  # Set the class' __init__ to the new one
-    return original_class
 
+def blackbox_module(cls):
+    """
+    Register a module. Use it as a decorator.
+    """
+    frm = inspect.stack()[1]
+    module_name = inspect.getmodule(frm[0]).__name__
+    return _blackbox_cls(cls, module_name, 'args')
 
-def register_trainer():
-    def _register(cls):
-        m = _register_trainer(
-            original_class=cls)
-        return m
 
-    return _register
+def register_trainer(cls):
+    """
+    Register a trainer. Use it as a decorator.
+    """
+    frm = inspect.stack()[1]
+    module_name = inspect.getmodule(frm[0]).__name__
+    return _blackbox_cls(cls, module_name, 'full')
 
 
 _last_uid = defaultdict(int)

nni/runtime/log.py

@@ -12,6 +12,13 @@ import colorama
 from .env_vars import dispatcher_env_vars, trial_env_vars
 
 
+handlers = {}
+
+log_format = '[%(asctime)s] %(levelname)s (%(name)s/%(threadName)s) %(message)s'
+time_format = '%Y-%m-%d %H:%M:%S'
+formatter = Formatter(log_format, time_format)
+
+
 def init_logger() -> None:
     """
     This function will (and should only) get invoked on the first time of importing nni (no matter which submodule).
@@ -37,6 +44,8 @@ def init_logger() -> None:
 
     _init_logger_standalone()
 
+    logging.getLogger('filelock').setLevel(logging.WARNING)
+
 
 def init_logger_experiment() -> None:
     """
@@ -44,15 +53,19 @@ def init_logger_experiment() -> None:
 
     This function will get invoked after `init_logger()`.
     """
-    formatter.format = _colorful_format
+    colorful_formatter = Formatter(log_format, time_format)
+    colorful_formatter.format = _colorful_format
+    handlers['_default_'].setFormatter(colorful_formatter)
 
+def start_experiment_log(experiment_id: str, log_directory: Path, debug: bool) -> None:
+    log_path = _prepare_log_dir(log_directory) / 'dispatcher.log'
+    log_level = logging.DEBUG if debug else logging.INFO
+    _register_handler(FileHandler(log_path), log_level, experiment_id)
 
-time_format = '%Y-%m-%d %H:%M:%S'
+def stop_experiment_log(experiment_id: str) -> None:
+    if experiment_id in handlers:
+        logging.getLogger().removeHandler(handlers.pop(experiment_id))
 
-formatter = Formatter(
-    '[%(asctime)s] %(levelname)s (%(name)s/%(threadName)s) %(message)s',
-    time_format
-)
 
 def _init_logger_dispatcher() -> None:
     log_level_map = {
@@ -66,26 +79,20 @@ def _init_logger_dispatcher() -> None:
 
     log_path = _prepare_log_dir(dispatcher_env_vars.NNI_LOG_DIRECTORY) / 'dispatcher.log'
     log_level = log_level_map.get(dispatcher_env_vars.NNI_LOG_LEVEL, logging.INFO)
-    _setup_root_logger(FileHandler(log_path), log_level)
+    _register_handler(FileHandler(log_path), log_level)
 
 
 def _init_logger_trial() -> None:
     log_path = _prepare_log_dir(trial_env_vars.NNI_OUTPUT_DIR) / 'trial.log'
     log_file = open(log_path, 'w')
-    _setup_root_logger(StreamHandler(log_file), logging.INFO)
+    _register_handler(StreamHandler(log_file), logging.INFO)
 
     if trial_env_vars.NNI_PLATFORM == 'local':
         sys.stdout = _LogFileWrapper(log_file)
 
 
 def _init_logger_standalone() -> None:
-    _setup_nni_logger(StreamHandler(sys.stdout), logging.INFO)
-
-    # Following line does not affect NNI loggers, but without this user's logger won't
-    # print log even it's level is set to INFO, so we do it for user's convenience.
-    # If this causes any issue in future, remove it and use `logging.info()` instead of
-    # `logging.getLogger('xxx').info()` in all examples.
-    logging.basicConfig()
+    _register_handler(StreamHandler(sys.stdout), logging.INFO)
 
 
 def _prepare_log_dir(path: Optional[str]) -> Path:
@@ -95,20 +102,18 @@ def _prepare_log_dir(path: Optional[str]) -> Path:
     ret.mkdir(parents=True, exist_ok=True)
     return ret
 
-def _setup_root_logger(handler: Handler, level: int) -> None:
-    _setup_logger('', handler, level)
-
-def _setup_nni_logger(handler: Handler, level: int) -> None:
-    _setup_logger('nni', handler, level)
-
-def _setup_logger(name: str, handler: Handler, level: int) -> None:
+def _register_handler(handler: Handler, level: int, tag: str = '_default_') -> None:
+    assert tag not in handlers
+    handlers[tag] = handler
     handler.setFormatter(formatter)
-    logger = logging.getLogger(name)
+    logger = logging.getLogger()
     logger.addHandler(handler)
     logger.setLevel(level)
-    logger.propagate = False
 
 def _colorful_format(record):
+    time = formatter.formatTime(record, time_format)
+    if not record.name.startswith('nni.'):
+        return '[{}] ({}) {}'.format(time, record.name, record.msg % record.args)
     if record.levelno >= logging.ERROR:
         color = colorama.Fore.RED
     elif record.levelno >= logging.WARNING:
@@ -118,7 +123,6 @@ def _colorful_format(record):
     else:
         color = colorama.Fore.BLUE
     msg = color + (record.msg % record.args) + colorama.Style.RESET_ALL
-    time = formatter.formatTime(record, time_format)
     if record.levelno < logging.INFO:
         return '[{}] {}:{} {}'.format(time, record.threadName, record.name, msg)
     else:

nni/runtime/platform/__init__.py

@@ -9,7 +9,7 @@ if trial_env_vars.NNI_PLATFORM is None:
     from .standalone import *
 elif trial_env_vars.NNI_PLATFORM == 'unittest':
     from .test import *
-elif trial_env_vars.NNI_PLATFORM in ('local', 'remote', 'pai', 'kubeflow', 'frameworkcontroller', 'paiYarn', 'dlts', 'aml', 'adl', 'heterogeneous'):
+elif trial_env_vars.NNI_PLATFORM in ('local', 'remote', 'pai', 'kubeflow', 'frameworkcontroller', 'paiYarn', 'dlts', 'aml', 'adl', 'hybrid'):
     from .local import *
 else:
     raise RuntimeError('Unknown platform %s' % trial_env_vars.NNI_PLATFORM)

nni/tools/nnictl/config_schema.py

@@ -124,7 +124,7 @@ common_schema = {
     Optional('maxExecDuration'): And(Regex(r'^[1-9][0-9]*[s|m|h|d]$', error='ERROR: maxExecDuration format is [digit]{s,m,h,d}')),
     Optional('maxTrialNum'): setNumberRange('maxTrialNum', int, 1, 99999),
     'trainingServicePlatform': setChoice(
-        'trainingServicePlatform', 'remote', 'local', 'pai', 'kubeflow', 'frameworkcontroller', 'paiYarn', 'dlts', 'aml', 'adl', 'heterogeneous'),
+        'trainingServicePlatform', 'remote', 'local', 'pai', 'kubeflow', 'frameworkcontroller', 'paiYarn', 'dlts', 'aml', 'adl', 'hybrid'),
     Optional('searchSpacePath'): And(os.path.exists, error=SCHEMA_PATH_ERROR % 'searchSpacePath'),
     Optional('multiPhase'): setType('multiPhase', bool),
     Optional('multiThread'): setType('multiThread', bool),
@@ -262,7 +262,7 @@ aml_config_schema = {
     }
 }
 
-heterogeneous_trial_schema = {
+hybrid_trial_schema = {
     'trial': {
         'codeDir': setPathCheck('codeDir'),
         Optional('nniManagerNFSMountPath'): setPathCheck('nniManagerNFSMountPath'),
@@ -279,8 +279,8 @@ heterogeneous_trial_schema = {
     }
 }
 
-heterogeneous_config_schema = {
-    'heterogeneousConfig': {
+hybrid_config_schema = {
+    'hybridConfig': {
         'trainingServicePlatforms': ['local', 'remote', 'pai', 'aml']
     }
 }
@@ -461,7 +461,7 @@ training_service_schema_dict = {
     'frameworkcontroller': Schema({**common_schema, **frameworkcontroller_trial_schema, **frameworkcontroller_config_schema}),
     'aml': Schema({**common_schema, **aml_trial_schema, **aml_config_schema}),
     'dlts': Schema({**common_schema, **dlts_trial_schema, **dlts_config_schema}),
-    'heterogeneous': Schema({**common_schema, **heterogeneous_trial_schema, **heterogeneous_config_schema, **machine_list_schema,
+    'hybrid': Schema({**common_schema, **hybrid_trial_schema, **hybrid_config_schema, **machine_list_schema,
                              **pai_config_schema, **aml_config_schema, **remote_config_schema}),
 }
 
@@ -479,7 +479,7 @@ class NNIConfigSchema:
         self.validate_pai_trial_conifg(experiment_config)
         self.validate_kubeflow_operators(experiment_config)
         self.validate_eth0_device(experiment_config)
-        self.validate_heterogeneous_platforms(experiment_config)
+        self.validate_hybrid_platforms(experiment_config)
 
     def validate_tuner_adivosr_assessor(self, experiment_config):
         if experiment_config.get('advisor'):
@@ -590,15 +590,15 @@ class NNIConfigSchema:
                 and 'eth0' not in netifaces.interfaces():
             raise SchemaError('This machine does not contain eth0 network device, please set nniManagerIp in config file!')
     
-    def validate_heterogeneous_platforms(self, experiment_config):
+    def validate_hybrid_platforms(self, experiment_config):
         required_config_name_map = {
             'remote': 'machineList',
             'aml': 'amlConfig',
             'pai': 'paiConfig'
         }
-        if experiment_config.get('trainingServicePlatform') == 'heterogeneous':
-            for platform in experiment_config['heterogeneousConfig']['trainingServicePlatforms']:
+        if experiment_config.get('trainingServicePlatform') == 'hybrid':
+            for platform in experiment_config['hybridConfig']['trainingServicePlatforms']:
                 config_name = required_config_name_map.get(platform)
                 if config_name and not experiment_config.get(config_name):
-                    raise SchemaError('Need to set {0} for {1} in heterogeneous mode!'.format(config_name, platform))
+                    raise SchemaError('Need to set {0} for {1} in hybrid mode!'.format(config_name, platform))
                 
\ No newline at end of file

nni/tools/nnictl/launcher.py

@@ -17,7 +17,7 @@ from .launcher_utils import validate_all_content
 from .rest_utils import rest_put, rest_post, check_rest_server, check_response
 from .url_utils import cluster_metadata_url, experiment_url, get_local_urls
 from .config_utils import Config, Experiments
-from .common_utils import get_yml_content, get_json_content, print_error, print_normal, \
+from .common_utils import get_yml_content, get_json_content, print_error, print_normal, print_warning, \
                           detect_port, get_user
 
 from .constants import NNICTL_HOME_DIR, ERROR_INFO, REST_TIME_OUT, EXPERIMENT_SUCCESS_INFO, LOG_HEADER
@@ -47,10 +47,10 @@ def start_rest_server(port, platform, mode, experiment_id, foreground=False, log
         'You could use \'nnictl create --help\' to get help information' % port)
         exit(1)
 
-    if (platform != 'local') and detect_port(int(port) + 1):
-        print_error('PAI mode need an additional adjacent port %d, and the port %d is used by another process!\n' \
+    if (platform not in ['local', 'aml']) and detect_port(int(port) + 1):
+        print_error('%s mode need an additional adjacent port %d, and the port %d is used by another process!\n' \
         'You could set another port to start experiment!\n' \
-        'You could use \'nnictl create --help\' to get help information' % ((int(port) + 1), (int(port) + 1)))
+        'You could use \'nnictl create --help\' to get help information' % (platform, (int(port) + 1), (int(port) + 1)))
         exit(1)
 
     print_normal('Starting restful server...')
@@ -300,23 +300,25 @@ def set_aml_config(experiment_config, port, config_file_name):
     #set trial_config
     return set_trial_config(experiment_config, port, config_file_name), err_message
 
-def set_heterogeneous_config(experiment_config, port, config_file_name):
-    '''set heterogeneous configuration'''
-    heterogeneous_config_data = dict()
-    heterogeneous_config_data['heterogeneous_config'] = experiment_config['heterogeneousConfig']
-    platform_list = experiment_config['heterogeneousConfig']['trainingServicePlatforms']
+def set_hybrid_config(experiment_config, port, config_file_name):
+    '''set hybrid configuration'''
+    hybrid_config_data = dict()
+    hybrid_config_data['hybrid_config'] = experiment_config['hybridConfig']
+    platform_list = experiment_config['hybridConfig']['trainingServicePlatforms']
     for platform in platform_list:
         if platform == 'aml':
-            heterogeneous_config_data['aml_config'] = experiment_config['amlConfig']
+            hybrid_config_data['aml_config'] = experiment_config['amlConfig']
         elif platform ==  'remote':
             if experiment_config.get('remoteConfig'):
-                heterogeneous_config_data['remote_config'] = experiment_config['remoteConfig']
-            heterogeneous_config_data['machine_list'] = experiment_config['machineList']
+                hybrid_config_data['remote_config'] = experiment_config['remoteConfig']
+            hybrid_config_data['machine_list'] = experiment_config['machineList']
         elif platform == 'local' and experiment_config.get('localConfig'):
-            heterogeneous_config_data['local_config'] = experiment_config['localConfig']
+            hybrid_config_data['local_config'] = experiment_config['localConfig']
         elif platform == 'pai':
-            heterogeneous_config_data['pai_config'] = experiment_config['paiConfig']
-    response = rest_put(cluster_metadata_url(port), json.dumps(heterogeneous_config_data), REST_TIME_OUT)
+            hybrid_config_data['pai_config'] = experiment_config['paiConfig']
+    # It needs to connect all remote machines, set longer timeout here to wait for restful server connection response.
+    time_out = 60 if 'remote' in platform_list else REST_TIME_OUT
+    response = rest_put(cluster_metadata_url(port), json.dumps(hybrid_config_data), time_out)
     err_message = None
     if not response or not response.status_code == 200:
         if response is not None:
@@ -412,10 +414,10 @@ def set_experiment(experiment_config, mode, port, config_file_name):
             {'key': 'aml_config', 'value': experiment_config['amlConfig']})
         request_data['clusterMetaData'].append(
             {'key': 'trial_config', 'value': experiment_config['trial']})
-    elif experiment_config['trainingServicePlatform'] == 'heterogeneous':
+    elif experiment_config['trainingServicePlatform'] == 'hybrid':
         request_data['clusterMetaData'].append(
-            {'key': 'heterogeneous_config', 'value': experiment_config['heterogeneousConfig']})
-        platform_list = experiment_config['heterogeneousConfig']['trainingServicePlatforms']
+            {'key': 'hybrid_config', 'value': experiment_config['hybridConfig']})
+        platform_list = experiment_config['hybridConfig']['trainingServicePlatforms']
         request_dict = {
             'aml': {'key': 'aml_config', 'value': experiment_config.get('amlConfig')},
             'remote': {'key': 'machine_list', 'value': experiment_config.get('machineList')},
@@ -460,8 +462,8 @@ def set_platform_config(platform, experiment_config, port, config_file_name, res
         config_result, err_msg = set_dlts_config(experiment_config, port, config_file_name)
     elif platform == 'aml':
         config_result, err_msg = set_aml_config(experiment_config, port, config_file_name)
-    elif platform == 'heterogeneous':
-        config_result, err_msg = set_heterogeneous_config(experiment_config, port, config_file_name)
+    elif platform == 'hybrid':
+        config_result, err_msg = set_hybrid_config(experiment_config, port, config_file_name)
     else:
         raise Exception(ERROR_INFO % 'Unsupported platform!')
         exit(1)
@@ -509,6 +511,11 @@ def launch_experiment(args, experiment_config, mode, experiment_id):
     rest_process, start_time = start_rest_server(args.port, experiment_config['trainingServicePlatform'], \
                                                  mode, experiment_id, foreground, log_dir, log_level)
     nni_config.set_config('restServerPid', rest_process.pid)
+    # save experiment information
+    nnictl_experiment_config = Experiments()
+    nnictl_experiment_config.add_experiment(experiment_id, args.port, start_time,
+                                            experiment_config['trainingServicePlatform'],
+                                            experiment_config['experimentName'], pid=rest_process.pid, logDir=log_dir)
     # Deal with annotation
     if experiment_config.get('useAnnotation'):
         path = os.path.join(tempfile.gettempdir(), get_user(), 'nni', 'annotation')
@@ -546,11 +553,6 @@ def launch_experiment(args, experiment_config, mode, experiment_id):
 
     # start a new experiment
     print_normal('Starting experiment...')
-    # save experiment information
-    nnictl_experiment_config = Experiments()
-    nnictl_experiment_config.add_experiment(experiment_id, args.port, start_time,
-                                            experiment_config['trainingServicePlatform'],
-                                            experiment_config['experimentName'], pid=rest_process.pid, logDir=log_dir)
     # set debug configuration
     if mode != 'view' and experiment_config.get('debug') is None:
         experiment_config['debug'] = args.debug
@@ -567,7 +569,7 @@ def launch_experiment(args, experiment_config, mode, experiment_id):
             raise Exception(ERROR_INFO % 'Restful server stopped!')
         exit(1)
     if experiment_config.get('nniManagerIp'):
-        web_ui_url_list = ['{0}:{1}'.format(experiment_config['nniManagerIp'], str(args.port))]
+        web_ui_url_list = ['http://{0}:{1}'.format(experiment_config['nniManagerIp'], str(args.port))]
     else:
         web_ui_url_list = get_local_urls(args.port)
     nni_config.set_config('webuiUrl', web_ui_url_list)
@@ -592,24 +594,28 @@ def create_experiment(args):
         print_error('Please set correct config path!')
         exit(1)
     experiment_config = get_yml_content(config_path)
-    try:
-        config = ExperimentConfig(**experiment_config)
-        experiment_config = convert.to_v1_yaml(config)
-    except Exception:
-        pass
+
     try:
         validate_all_content(experiment_config, config_path)
-    except Exception as e:
-        print_error(e)
-        exit(1)
+    except Exception:
+        print_warning('Validation with V1 schema failed. Trying to convert from V2 format...')
+        try:
+            config = ExperimentConfig(**experiment_config)
+            experiment_config = convert.to_v1_yaml(config)
+        except Exception as e:
+            print_error(f'Conversion from v2 format failed: {repr(e)}')
+        try:
+            validate_all_content(experiment_config, config_path)
+        except Exception as e:
+            print_error(f'Config in v1 format validation failed. {repr(e)}')
+            exit(1)
 
     nni_config.set_config('experimentConfig', experiment_config)
     nni_config.set_config('restServerPort', args.port)
     try:
         launch_experiment(args, experiment_config, 'new', experiment_id)
     except Exception as exception:
-        nni_config = Config(experiment_id)
-        restServerPid = nni_config.get_config('restServerPid')
+        restServerPid = Experiments().get_all_experiments().get(experiment_id, {}).get('pid')
         if restServerPid:
             kill_command(restServerPid)
         print_error(exception)
@@ -641,8 +647,7 @@ def manage_stopped_experiment(args, mode):
     try:
         launch_experiment(args, experiment_config, mode, experiment_id)
     except Exception as exception:
-        nni_config = Config(experiment_id)
-        restServerPid = nni_config.get_config('restServerPid')
+        restServerPid = Experiments().get_all_experiments().get(experiment_id, {}).get('pid')
         if restServerPid:
             kill_command(restServerPid)
         print_error(exception)

nni/tools/nnictl/launcher_utils.py

@@ -105,7 +105,9 @@ def set_default_values(experiment_config):
         experiment_config['maxExecDuration'] = '999d'
     if experiment_config.get('maxTrialNum') is None:
         experiment_config['maxTrialNum'] = 99999
-    if experiment_config['trainingServicePlatform'] == 'remote':
+    if experiment_config['trainingServicePlatform'] == 'remote' or \
+       experiment_config['trainingServicePlatform'] == 'hybrid' and \
+       'remote' in experiment_config['hybridConfig']['trainingServicePlatforms']:
         for index in range(len(experiment_config['machineList'])):
             if experiment_config['machineList'][index].get('port') is None:
                 experiment_config['machineList'][index]['port'] = 22

nni/tools/nnictl/nnictl.py

@@ -2,6 +2,7 @@
 # Licensed under the MIT license.
 
 import argparse
+import logging
 import os
 import pkg_resources
 from colorama import init
@@ -32,6 +33,8 @@ def nni_info(*args):
         print('please run "nnictl {positional argument} --help" to see nnictl guidance')
 
 def parse_args():
+    logging.getLogger().setLevel(logging.ERROR)
+
     '''Definite the arguments users need to follow and input'''
     parser = argparse.ArgumentParser(prog='nnictl', description='use nnictl command to control nni experiments')
     parser.add_argument('--version', '-v', action='store_true')
@@ -243,12 +246,9 @@ def parse_args():
     def show_messsage_for_nnictl_package(args):
         print_error('nnictl package command is replaced by nnictl algo, please run nnictl algo -h to show the usage')
 
-    parser_package_subparsers = subparsers.add_parser('package', help='control nni tuner and assessor packages').add_subparsers()
-    parser_package_subparsers.add_parser('install', help='install packages').set_defaults(func=show_messsage_for_nnictl_package)
-    parser_package_subparsers.add_parser('uninstall', help='uninstall packages').set_defaults(func=show_messsage_for_nnictl_package)
-    parser_package_subparsers.add_parser('show', help='show the information of packages').set_defaults(
-        func=show_messsage_for_nnictl_package)
-    parser_package_subparsers.add_parser('list', help='list installed packages').set_defaults(func=show_messsage_for_nnictl_package)
+    parser_package_subparsers = subparsers.add_parser('package', help='this argument is replaced by algo', prefix_chars='\n')
+    parser_package_subparsers.add_argument('args', nargs=argparse.REMAINDER)
+    parser_package_subparsers.set_defaults(func=show_messsage_for_nnictl_package)
 
     #parse tensorboard command
     parser_tensorboard = subparsers.add_parser('tensorboard', help='manage tensorboard')

nni/tools/nnictl/nnictl_utils.py

@@ -50,11 +50,9 @@ def update_experiment():
     for key in experiment_dict.keys():
         if isinstance(experiment_dict[key], dict):
             if experiment_dict[key].get('status') != 'STOPPED':
-                nni_config = Config(key)
-                rest_pid = nni_config.get_config('restServerPid')
+                rest_pid = experiment_dict[key].get('pid')
                 if not detect_process(rest_pid):
                     experiment_config.update_experiment(key, 'status', 'STOPPED')
-                    experiment_config.update_experiment(key, 'port', None)
                     continue
 
 def check_experiment_id(args, update=True):
@@ -83,10 +81,10 @@ def check_experiment_id(args, update=True):
                 experiment_information += EXPERIMENT_DETAIL_FORMAT % (key,
                                                                       experiment_dict[key].get('experimentName', 'N/A'),
                                                                       experiment_dict[key]['status'],
-                                                                      experiment_dict[key]['port'],
+                                                                      experiment_dict[key].get('port', 'N/A'),
                                                                       experiment_dict[key].get('platform'),
-                                                                      experiment_dict[key]['startTime'],
-                                                                      experiment_dict[key]['endTime'])
+                                                                      time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(experiment_dict[key]['startTime'] / 1000)) if isinstance(experiment_dict[key]['startTime'], int) else experiment_dict[key]['startTime'],
+                                                                      time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(experiment_dict[key]['endTime'] / 1000)) if isinstance(experiment_dict[key]['endTime'], int) else experiment_dict[key]['endTime'])
             print(EXPERIMENT_INFORMATION_FORMAT % experiment_information)
             exit(1)
         elif not running_experiment_list:
@@ -130,7 +128,7 @@ def parse_ids(args):
         return running_experiment_list
     if args.port is not None:
         for key in running_experiment_list:
-            if experiment_dict[key]['port'] == args.port:
+            if experiment_dict[key].get('port') == args.port:
                 result_list.append(key)
         if args.id and result_list and args.id != result_list[0]:
             print_error('Experiment id and resful server port not match')
@@ -143,10 +141,10 @@ def parse_ids(args):
                 experiment_information += EXPERIMENT_DETAIL_FORMAT % (key,
                                                                       experiment_dict[key].get('experimentName', 'N/A'),
                                                                       experiment_dict[key]['status'],
-                                                                      experiment_dict[key]['port'],
+                                                                      experiment_dict[key].get('port', 'N/A'),
                                                                       experiment_dict[key].get('platform'),
-                                                                      experiment_dict[key]['startTime'],
-                                                                      experiment_dict[key]['endTime'])
+                                                                      time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(experiment_dict[key]['startTime'] / 1000)) if isinstance(experiment_dict[key]['startTime'], int) else experiment_dict[key]['startTime'],
+                                                                      time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(experiment_dict[key]['endTime'] / 1000)) if isinstance(experiment_dict[key]['endTime'], int) else experiment_dict[key]['endTime'])
             print(EXPERIMENT_INFORMATION_FORMAT % experiment_information)
             exit(1)
         else:
@@ -186,7 +184,7 @@ def get_experiment_port(args):
         exit(1)
     experiment_config = Experiments()
     experiment_dict = experiment_config.get_all_experiments()
-    return experiment_dict[experiment_id]['port']
+    return experiment_dict[experiment_id].get('port')
 
 def convert_time_stamp_to_date(content):
     '''Convert time stamp to date time format'''
@@ -202,8 +200,9 @@ def convert_time_stamp_to_date(content):
 
 def check_rest(args):
     '''check if restful server is running'''
-    nni_config = Config(get_config_filename(args))
-    rest_port = nni_config.get_config('restServerPort')
+    experiment_config = Experiments()
+    experiment_dict = experiment_config.get_all_experiments()
+    rest_port = experiment_dict.get(get_config_filename(args)).get('port')
     running, _ = check_rest_server_quick(rest_port)
     if running:
         print_normal('Restful server is running...')
@@ -220,18 +219,19 @@ def stop_experiment(args):
     if experiment_id_list:
         for experiment_id in experiment_id_list:
             print_normal('Stopping experiment %s' % experiment_id)
-            nni_config = Config(experiment_id)
-            rest_pid = nni_config.get_config('restServerPid')
+            experiment_config = Experiments()
+            experiment_dict = experiment_config.get_all_experiments()
+            rest_pid = experiment_dict.get(experiment_id).get('pid')
             if rest_pid:
                 kill_command(rest_pid)
-                tensorboard_pid_list = nni_config.get_config('tensorboardPidList')
+                tensorboard_pid_list = experiment_dict.get(experiment_id).get('tensorboardPidList')
                 if tensorboard_pid_list:
                     for tensorboard_pid in tensorboard_pid_list:
                         try:
                             kill_command(tensorboard_pid)
                         except Exception as exception:
                             print_error(exception)
-                    nni_config.set_config('tensorboardPidList', [])
+                    experiment_config.update_experiment(experiment_id, 'tensorboardPidList', [])
             print_normal('Stop experiment success.')
 
 def trial_ls(args):
@@ -250,9 +250,10 @@ def trial_ls(args):
     if args.head and args.tail:
         print_error('Head and tail cannot be set at the same time.')
         return
-    nni_config = Config(get_config_filename(args))
-    rest_port = nni_config.get_config('restServerPort')
-    rest_pid = nni_config.get_config('restServerPid')
+    experiment_config = Experiments()
+    experiment_dict = experiment_config.get_all_experiments()
+    rest_port = experiment_dict.get(get_config_filename(args)).get('port')
+    rest_pid = experiment_dict.get(get_config_filename(args)).get('pid')
     if not detect_process(rest_pid):
         print_error('Experiment is not running...')
         return
@@ -281,9 +282,10 @@ def trial_ls(args):
 
 def trial_kill(args):
     '''List trial'''
-    nni_config = Config(get_config_filename(args))
-    rest_port = nni_config.get_config('restServerPort')
-    rest_pid = nni_config.get_config('restServerPid')
+    experiment_config = Experiments()
+    experiment_dict = experiment_config.get_all_experiments()
+    rest_port = experiment_dict.get(get_config_filename(args)).get('port')
+    rest_pid = experiment_dict.get(get_config_filename(args)).get('pid')
     if not detect_process(rest_pid):
         print_error('Experiment is not running...')
         return
@@ -312,9 +314,10 @@ def trial_codegen(args):
 
 def list_experiment(args):
     '''Get experiment information'''
-    nni_config = Config(get_config_filename(args))
-    rest_port = nni_config.get_config('restServerPort')
-    rest_pid = nni_config.get_config('restServerPid')
+    experiment_config = Experiments()
+    experiment_dict = experiment_config.get_all_experiments()
+    rest_port = experiment_dict.get(get_config_filename(args)).get('port')
+    rest_pid = experiment_dict.get(get_config_filename(args)).get('pid')
     if not detect_process(rest_pid):
         print_error('Experiment is not running...')
         return
@@ -333,8 +336,9 @@ def list_experiment(args):
 
 def experiment_status(args):
     '''Show the status of experiment'''
-    nni_config = Config(get_config_filename(args))
-    rest_port = nni_config.get_config('restServerPort')
+    experiment_config = Experiments()
+    experiment_dict = experiment_config.get_all_experiments()
+    rest_port = experiment_dict.get(get_config_filename(args)).get('port')
     result, response = check_rest_server_quick(rest_port)
     if not result:
         print_normal('Restful server is not running...')
@@ -620,12 +624,12 @@ def platform_clean(args):
             break
     if platform == 'remote':
         machine_list = config_content.get('machineList')
-        remote_clean(machine_list, None)
+        remote_clean(machine_list)
     elif platform == 'pai':
         host = config_content.get('paiConfig').get('host')
         user_name = config_content.get('paiConfig').get('userName')
         output_dir = config_content.get('trial').get('outputDir')
-        hdfs_clean(host, user_name, output_dir, None)
+        hdfs_clean(host, user_name, output_dir)
     print_normal('Done.')
 
 def experiment_list(args):
@@ -651,7 +655,7 @@ def experiment_list(args):
         experiment_information += EXPERIMENT_DETAIL_FORMAT % (key,
                                                               experiment_dict[key].get('experimentName', 'N/A'),
                                                               experiment_dict[key]['status'],
-                                                              experiment_dict[key]['port'],
+                                                              experiment_dict[key].get('port', 'N/A'),
                                                               experiment_dict[key].get('platform'),
                                                               time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(experiment_dict[key]['startTime'] / 1000)) if isinstance(experiment_dict[key]['startTime'], int) else experiment_dict[key]['startTime'],
                                                               time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(experiment_dict[key]['endTime'] / 1000)) if isinstance(experiment_dict[key]['endTime'], int) else experiment_dict[key]['endTime'])
@@ -752,9 +756,10 @@ def export_trials_data(args):
             groupby.setdefault(content['trialJobId'], []).append(json.loads(content['data']))
         return groupby
 
-    nni_config = Config(get_config_filename(args))
-    rest_port = nni_config.get_config('restServerPort')
-    rest_pid = nni_config.get_config('restServerPid')
+    experiment_config = Experiments()
+    experiment_dict = experiment_config.get_all_experiments()
+    rest_port = experiment_dict.get(get_config_filename(args)).get('port')
+    rest_pid = experiment_dict.get(get_config_filename(args)).get('pid')
 
     if not detect_process(rest_pid):
         print_error('Experiment is not running...')

nni/tools/nnictl/tensorboard_utils.py

@@ -70,7 +70,7 @@ def format_tensorboard_log_path(path_list):
         new_path_list.append('name%d:%s' % (index + 1, value))
     return ','.join(new_path_list)
 
-def start_tensorboard_process(args, nni_config, path_list, temp_nni_path):
+def start_tensorboard_process(args, experiment_id, path_list, temp_nni_path):
     '''call cmds to start tensorboard process in local machine'''
     if detect_port(args.port):
         print_error('Port %s is used by another process, please reset port!' % str(args.port))
@@ -83,20 +83,19 @@ def start_tensorboard_process(args, nni_config, path_list, temp_nni_path):
     url_list = get_local_urls(args.port)
     print_green('Start tensorboard success!')
     print_normal('Tensorboard urls: ' + '     '.join(url_list))
-    tensorboard_process_pid_list = nni_config.get_config('tensorboardPidList')
+    experiment_config = Experiments()
+    tensorboard_process_pid_list = experiment_config.get_all_experiments().get(experiment_id).get('tensorboardPidList')
     if tensorboard_process_pid_list is None:
         tensorboard_process_pid_list = [tensorboard_process.pid]
     else:
         tensorboard_process_pid_list.append(tensorboard_process.pid)
-    nni_config.set_config('tensorboardPidList', tensorboard_process_pid_list)
+    experiment_config.update_experiment(experiment_id, 'tensorboardPidList', tensorboard_process_pid_list)
 
 def stop_tensorboard(args):
     '''stop tensorboard'''
     experiment_id = check_experiment_id(args)
     experiment_config = Experiments()
-    experiment_dict = experiment_config.get_all_experiments()
-    nni_config = Config(experiment_id)
-    tensorboard_pid_list = nni_config.get_config('tensorboardPidList')
+    tensorboard_pid_list = experiment_config.get_all_experiments().get(experiment_id).get('tensorboardPidList')
     if tensorboard_pid_list:
         for tensorboard_pid in tensorboard_pid_list:
             try:
@@ -104,7 +103,7 @@ def stop_tensorboard(args):
                 call(cmds)
             except Exception as exception:
                 print_error(exception)
-        nni_config.set_config('tensorboardPidList', [])
+        experiment_config.update_experiment(experiment_id, 'tensorboardPidList', [])
         print_normal('Stop tensorboard success!')
     else:
         print_error('No tensorboard configuration!')
@@ -164,4 +163,4 @@ def start_tensorboard(args):
     os.makedirs(temp_nni_path, exist_ok=True)
 
     path_list = get_path_list(args, nni_config, trial_content, temp_nni_path)
-    start_tensorboard_process(args, nni_config, path_list, temp_nni_path)
\ No newline at end of file
+    start_tensorboard_process(args, experiment_id, path_list, temp_nni_path)

nni/tools/nnictl/updater.py

@@ -5,7 +5,7 @@ import json
 import os
 from .rest_utils import rest_put, rest_post, rest_get, check_rest_server_quick, check_response
 from .url_utils import experiment_url, import_data_url
-from .config_utils import Config
+from .config_utils import Config, Experiments
 from .common_utils import get_json_content, print_normal, print_error, print_warning
 from .nnictl_utils import get_experiment_port, get_config_filename, detect_process
 from .launcher_utils import parse_time
@@ -58,8 +58,9 @@ def get_query_type(key):
 
 def update_experiment_profile(args, key, value):
     '''call restful server to update experiment profile'''
-    nni_config = Config(get_config_filename(args))
-    rest_port = nni_config.get_config('restServerPort')
+    experiment_config = Experiments()
+    experiment_dict = experiment_config.get_all_experiments()
+    rest_port = experiment_dict.get(get_config_filename(args)).get('port')
     running, _ = check_rest_server_quick(rest_port)
     if running:
         response = rest_get(experiment_url(rest_port), REST_TIME_OUT)

pipelines/fast-test.yml

@@ -4,27 +4,26 @@
 jobs:
 - job: ubuntu_latest
   pool:
-    # FIXME: In ubuntu-20.04 Python interpreter crashed during SMAC UT
-    vmImage: ubuntu-18.04
+    vmImage: ubuntu-latest
 
   # This platform tests lint and doc first.
 
   steps:
   - task: UsePythonVersion@0
     inputs:
-      versionSpec: 3.6
+      versionSpec: 3.8
     displayName: Configure Python version
 
   - script: |
       set -e
-      python3 -m pip install --upgrade pip setuptools
-      python3 -m pip install pytest coverage
-      python3 -m pip install pylint flake8
+      python -m pip install --upgrade pip setuptools
+      python -m pip install pytest coverage
+      python -m pip install pylint flake8
       echo "##vso[task.setvariable variable=PATH]${HOME}/.local/bin:${PATH}"
     displayName: Install Python tools
 
   - script: |
-      python3 setup.py develop
+      python setup.py develop
     displayName: Install NNI
 
   - script: |
@@ -35,24 +34,28 @@ jobs:
       yarn eslint
     displayName: ESLint
 
+  # FIXME: temporarily fixed to pytorch 1.6 as 1.7 won't work with compression
+
   - script: |
       set -e
       sudo apt-get install -y pandoc
-      python3 -m pip install --upgrade pygments
-      python3 -m pip install --upgrade torch>=1.7.0+cpu torchvision>=0.8.1+cpu -f https://download.pytorch.org/whl/torch_stable.html
-      python3 -m pip install --upgrade tensorflow
-      python3 -m pip install --upgrade gym onnx peewee thop graphviz
-      python3 -m pip install sphinx==1.8.3 sphinx-argparse==0.2.5 sphinx-markdown-tables==0.0.9 sphinx-rtd-theme==0.4.2 sphinxcontrib-websupport==1.1.0 recommonmark==0.5.0 nbsphinx
-      sudo apt-get install swig -y
-      python3 -m pip install -e .[SMAC,BOHB]
+      python -m pip install --upgrade pygments
+      python -m pip install "torch==1.6.0+cpu" "torchvision==0.7.0+cpu" -f https://download.pytorch.org/whl/torch_stable.html
+      python -m pip install tensorflow
+      python -m pip install gym onnx peewee thop graphviz
+      python -m pip install sphinx==3.3.1 sphinx-argparse==0.2.5 sphinx-rtd-theme==0.4.2 sphinxcontrib-websupport==1.1.0 nbsphinx
+      sudo apt-get remove swig -y
+      sudo apt-get install swig3.0 -y
+      sudo ln -s /usr/bin/swig3.0 /usr/bin/swig
+      python -m pip install -e .[SMAC,BOHB]
     displayName: Install extra dependencies
 
   - script: |
       set -e
-      python3 -m pylint --rcfile pylintrc nni
-      python3 -m flake8 nni --count --select=E9,F63,F72,F82 --show-source --statistics
+      python -m pylint --rcfile pylintrc nni
+      python -m flake8 nni --count --select=E9,F63,F72,F82 --show-source --statistics
       EXCLUDES=examples/trials/mnist-nas/*/mnist*.py,examples/trials/nas_cifar10/src/cifar10/general_child.py
-      python3 -m flake8 examples --count --exclude=$EXCLUDES --select=E9,F63,F72,F82 --show-source --statistics
+      python -m flake8 examples --count --exclude=$EXCLUDES --select=E9,F63,F72,F82 --show-source --statistics
     displayName: pylint and flake8
 
   - script: |
@@ -61,10 +64,14 @@ jobs:
     displayName: Check Sphinx documentation
 
   - script: |
+      set -e
       cd test
-      python3 -m pytest ut --ignore=ut/sdk/test_pruners.py --ignore=ut/sdk/test_compressor_tf.py
-      python3 -m pytest ut/sdk/test_pruners.py
-      python3 -m pytest ut/sdk/test_compressor_tf.py
+      python -m pytest ut --ignore=ut/sdk/test_pruners.py \
+        --ignore=ut/sdk/test_compressor_tf.py \
+        --ignore=ut/sdk/test_compressor_torch.py
+      python -m pytest ut/sdk/test_pruners.py
+      python -m pytest ut/sdk/test_compressor_tf.py
+      python -m pytest ut/sdk/test_compressor_torch.py
     displayName: Python unit test
 
   - script: |
@@ -77,7 +84,7 @@ jobs:
 
   - script: |
       cd test
-      python3 nni_test/nnitest/run_tests.py --config config/pr_tests.yml
+      python nni_test/nnitest/run_tests.py --config config/pr_tests.yml
     displayName: Simple integration test
 
 

pipelines/integration-test-adl.yml

+trigger: none
+pr: none
+schedules:
+- cron: 0 16 * * *
+  branches:
+    include: [ master ]
+
+jobs:
+- job: adl
+  pool: NNI CI KUBE CLI
+  timeoutInMinutes: 120
+
+  steps:
+  - script: |
+      export NNI_RELEASE=999.$(date -u +%Y%m%d%H%M%S)
+      echo "##vso[task.setvariable variable=PATH]${PATH}:${HOME}/.local/bin"
+      echo "##vso[task.setvariable variable=NNI_RELEASE]${NNI_RELEASE}"
+
+      echo "Working directory: ${PWD}"
+      echo "NNI version: ${NNI_RELEASE}"
+      echo "Build docker image: $(build_docker_image)"
+
+      python3 -m pip install --upgrade pip setuptools
+    displayName: Prepare
+
+  - script: |
+      set -e
+      python3 setup.py build_ts
+      python3 setup.py bdist_wheel -p manylinux1_x86_64
+      python3 -m pip install dist/nni-${NNI_RELEASE}-py3-none-manylinux1_x86_64.whl[SMAC,BOHB]
+    displayName: Build and install NNI
+
+  - script: |
+      set -e
+      cd examples/tuners/customized_tuner
+      python3 setup.py develop --user
+      nnictl algo register --meta meta_file.yml
+    displayName: Install customized tuner
+
+  - script: |
+      set -e
+      docker login -u nnidev -p $(docker_hub_password)
+      sed -i '$a RUN python3 -m pip install adaptdl tensorboard' Dockerfile
+      sed -i '$a COPY examples /examples' Dockerfile
+      sed -i '$a COPY test /test' Dockerfile
+      echo '## Build docker image ##'
+      docker build --build-arg NNI_RELEASE=${NNI_RELEASE} -t nnidev/nni-nightly .
+      echo '## Upload docker image ##'
+      docker push nnidev/nni-nightly
+    condition: eq(variables['build_docker_image'], 'true')
+    displayName: Build and upload docker image
+
+  - script: |
+      set -e
+      cd test
+      python3 nni_test/nnitest/generate_ts_config.py \
+          --ts adl \
+          --nni_docker_image nnidev/nni-nightly \
+          --checkpoint_storage_class $(checkpoint_storage_class) \
+          --checkpoint_storage_size $(checkpoint_storage_size) \
+          --nni_manager_ip $(nni_manager_ip)
+      python3 nni_test/nnitest/run_tests.py --config config/integration_tests.yml --ts adl
+    displayName: Integration test

pipelines/release.yml

 # Copyright (c) Microsoft Corporation.
 # Licensed under the MIT license.
 
+trigger: none
+pr: none
+
 jobs:
 - job: validate_version_number
   pool:
@@ -13,9 +16,11 @@ jobs:
     displayName: Configure Python version
 
   - script: |
+      echo $(build_type)
+      echo $(NNI_RELEASE)
       export BRANCH_TAG=`git describe --tags --abbrev=0`
       echo $BRANCH_TAG
-      if [[ $BRANCH_TAG = v$(NNI_RELEASE) && $(NNI_RELEASE) =~ ^v[0-9](.[0-9])+$ ]]; then
+      if [[ $BRANCH_TAG == v$(NNI_RELEASE) && $(NNI_RELEASE) =~ ^[0-9](.[0-9])+$ ]]; then
         echo 'Build version match branch tag'
       else
         echo 'Build version does not match branch tag'
@@ -25,15 +30,16 @@ jobs:
     displayName: Validate release version number and branch tag
 
   - script: |
+      echo $(build_type)
       echo $(NNI_RELEASE)
-      if [[ $(NNI_RELEASE) =~ ^[0-9](.[0-9])+a[0-9]$ ]]; then
+      if [[ $(NNI_RELEASE) =~ ^[0-9](.[0-9])+(a|b|rc)[0-9]$ ]]; then
         echo 'Valid prerelease version $(NNI_RELEASE)'
         echo `git describe --tags --abbrev=0`
       else
         echo 'Invalid build version $(NNI_RELEASE)'
         exit 1
       fi
-    condition: ne( variables['build_type'], 'rerelease' )
+    condition: ne( variables['build_type'], 'release' )
     displayName: Validate prerelease version number
 
 - job: linux
@@ -49,22 +55,22 @@ jobs:
     displayName: Configure Python version
 
   - script: |
-      python -m pip install --upgrade pip setuptools twine
+      python -m pip install --upgrade pip setuptools wheel twine
       python test/vso_tools/build_wheel.py $(NNI_RELEASE)
+    displayName: Build wheel
 
-      if [ $(build_type) = 'release' ]
-        echo 'uploading release package to pypi...'
+  - script: |
+      if [[ $(build_type) == 'release' || $(build_type) == 'rc' ]]; then
+        echo 'uploading to pypi...'
         python -m twine upload -u nni -p $(pypi_password) dist/*
-      then
       else
-        echo 'uploading prerelease package to testpypi...'
+        echo 'uploading to testpypi...'
         python -m twine upload -u nni -p $(pypi_password) --repository-url https://test.pypi.org/legacy/ dist/*
       fi
-    displayName: Build and upload wheel
+    displayName: Upload wheel
 
   - script: |
-      if [ $(build_type) = 'release' ]
-      then
+      if [[ $(build_type) == 'release' || $(build_type) == 'rc' ]]; then
         docker login -u msranni -p $(docker_hub_password)
         export IMAGE_NAME=msranni/nni
       else
@@ -74,9 +80,11 @@ jobs:
 
       echo "## Building ${IMAGE_NAME}:$(NNI_RELEASE) ##"
       docker build --build-arg NNI_RELEASE=$(NNI_RELEASE) -t ${IMAGE_NAME} .
-      docker tag ${IMAGE_NAME} ${IMAGE_NAME}:$(NNI_RELEASE)
-      docker push ${IMAGE_NAME}
-      docker push ${IMAGE_NAME}:$(NNI_RELEASE)
+      docker tag ${IMAGE_NAME} ${IMAGE_NAME}:v$(NNI_RELEASE)
+      docker push ${IMAGE_NAME}:v$(NNI_RELEASE)
+      if [[ $(build_type) != 'rc' ]]; then
+        docker push ${IMAGE_NAME}
+      fi
     displayName: Build and upload docker image
 
 - job: macos
@@ -92,18 +100,19 @@ jobs:
     displayName: Configure Python version
 
   - script: |
-      python -m pip install --upgrade pip setuptools twine
+      python -m pip install --upgrade pip setuptools wheel twine
       python test/vso_tools/build_wheel.py $(NNI_RELEASE)
+    displayName: Build wheel
 
-      if [ $(build_type) = 'release' ]
+  - script: |
+      if [[ $(build_type) == 'release' || $(build_type) == 'rc' ]]; then
         echo '## uploading to pypi ##'
         python -m twine upload -u nni -p $(pypi_password) dist/*
-      then
       else
         echo '## uploading to testpypi ##'
         python -m twine upload -u nni -p $(pypi_password) --repository-url https://test.pypi.org/legacy/ dist/*
       fi
-    displayName: Build and upload wheel
+    displayName: Upload wheel
 
 - job: windows
   dependsOn: validate_version_number
@@ -118,15 +127,16 @@ jobs:
     displayName: Configure Python version
 
   - powershell: |
-      python -m pip install --upgrade pip setuptools twine
+      python -m pip install --upgrade pip setuptools wheel twine
       python test/vso_tools/build_wheel.py $(NNI_RELEASE)
+    displayName: Build wheel
 
-      if($env:BUILD_TYPE -eq 'release'){
+  - powershell: |
+      if ($env:BUILD_TYPE -eq 'release' -Or $env:BUILD_TYPE -eq 'rc') {
         Write-Host '## uploading to pypi ##'
         python -m twine upload -u nni -p $(pypi_password) dist/*
-      }
-      else{
+      } else {
         Write-Host '## uploading to testpypi ##'
         python -m twine upload -u nni -p $(pypi_password) --repository-url https://test.pypi.org/legacy/ dist/*
       }
-    displayName: Build and upload wheel
+    displayName: Upload wheel

setup.py

@@ -69,7 +69,6 @@ dependencies = [
     'PythonWebHDFS',
     'colorama',
     'scikit-learn>=0.23.2',
-    'pkginfo',
     'websockets',
     'filelock',
     'prettytable',
@@ -112,11 +111,8 @@ def _setup():
         python_requires = '>=3.6',
         install_requires = dependencies,
         extras_require = {
-            'SMAC': [
-                'ConfigSpaceNNI @ git+https://github.com/QuanluZhang/ConfigSpace.git',
-                'smac @ git+https://github.com/QuanluZhang/SMAC3.git'
-            ],
-            'BOHB': ['ConfigSpace==0.4.7', 'statsmodels==0.10.0'],
+            'SMAC': ['ConfigSpaceNNI', 'smac4nni'],
+            'BOHB': ['ConfigSpace==0.4.7', 'statsmodels==0.12.0'],
             'PPOTuner': ['enum34', 'gym']
         },
         setup_requires = ['requests'],
@@ -189,6 +185,7 @@ class Build(build):
             sys.exit('Please set environment variable "NNI_RELEASE=<release_version>"')
         if os.path.islink('nni_node/main.js'):
             sys.exit('A development build already exists. Please uninstall NNI and run "python3 setup.py clean --all".')
+        open('nni/version.py', 'w').write(f"__version__ = '{release}'")
         super().run()
 
 class Develop(develop):
@@ -212,6 +209,7 @@ class Develop(develop):
         super().finalize_options()
 
     def run(self):
+        open('nni/version.py', 'w').write("__version__ = '999.dev0'")
         if not self.skip_ts:
             setup_ts.build(release=None)
         super().run()

setup_ts.py

@@ -196,6 +196,7 @@ def copy_nni_node(version):
         package_json['version'] = version
     json.dump(package_json, open('nni_node/package.json', 'w'), indent=2)
 
+    # reinstall without development dependencies
     _yarn('ts/nni_manager', '--prod', '--cwd', str(Path('nni_node').resolve()))
 
     shutil.copytree('ts/webui/build', 'nni_node/static')
@@ -226,9 +227,9 @@ def _symlink(target_file, link_location):
 
 def _print(*args):
     if sys.platform == 'win32':
-        print(*args)
+        print(*args, flush=True)
     else:
-        print('\033[1;36m#', *args, '\033[0m')
+        print('\033[1;36m#', *args, '\033[0m', flush=True)
 
 
 generated_files = [