Port trial examples' config file to v2 (#3721)

Co-authored-by: liuzhe <zhe.liu@microsoft.com>

examples/trials/mnist-pytorch/config_tensorboard.yml

-authorName: default
-experimentName: example_mnist_pytorch
+searchSpaceFile: search_space.json
+trialCommand: python3 mnist_tensorboard.py  # NOTE: change "python3" to "python" if you are using Windows
+trialGpuNumber: 0
 trialConcurrency: 1
-maxExecDuration: 1h
-maxTrialNum: 10
-#choice: local, remote, pai
-trainingServicePlatform: local
-searchSpacePath: search_space.json
-#choice: true, false
-useAnnotation: false
+maxTrialNumber: 10
 tuner:
-  #choice: TPE, Random, Anneal, Evolution, BatchTuner, MetisTuner, GPTuner
-  #SMAC (SMAC should be installed through nnictl)
-  builtinTunerName: TPE
+  name: TPE
   classArgs:
-    #choice: maximize, minimize
     optimize_mode: maximize
-trial:
-  command: python3 mnist_tensorboard.py
-  codeDir: .
-  gpuNum: 0
+trainingService:
+  platform: local

examples/trials/mnist-pytorch/config_v2.yml

-searchSpace:
-  momentum:
-    _type: uniform
-    _value: [0, 1]
-  hidden_size:
-    _type: choice
-    _value: [128, 256, 512, 1024]
-  batch_size:
-    _type: choice
-    _value: [16, 32, 64, 128]
-  lr:
-    _type: choice
-    _value: [0.0001, 0.001, 0.01, 0.1]
-trainingService:
-  platform: local
-trialCodeDirectory: .
-trialCommand: python3 mnist.py
-trialConcurrency: 1
-trialGpuNumber: 0
-tuner:
-  name: TPE
-  classArgs:
-    optimize_mode: maximize

examples/trials/mnist-pytorch/config_windows.yml

-authorName: default
-experimentName: example_mnist_pytorch
-trialConcurrency: 1
-maxExecDuration: 1h
-maxTrialNum: 10
-#choice: local, remote, pai
-trainingServicePlatform: local
-searchSpacePath: search_space.json
-#choice: true, false
-useAnnotation: false
-tuner:
-  #choice: TPE, Random, Anneal, Evolution, BatchTuner, MetisTuner, GPTuner
-  #SMAC (SMAC should be installed through nnictl)
-  builtinTunerName: TPE
-  classArgs:
-    #choice: maximize, minimize
-    optimize_mode: maximize
-trial:
-  command: python mnist.py
-  codeDir: .
-  gpuNum: 0

examples/trials/mnist-tfv2/config.yml

-authorName: NNI Example
-experimentName: MNIST TF v2.x
+# This is the minimal config file for an NNI experiment.
+# Use "nnictl create --config config.yml" to launch this experiment.
+# Afterwards, you can check "config_detailed.yml" for more explanation.
+
+searchSpaceFile: search_space.json
+trialCommand: python3 mnist.py  # NOTE: change "python3" to "python" if you are using Windows
+trialGpuNumber: 0
 trialConcurrency: 1
-maxExecDuration: 1h
-maxTrialNum: 10
-trainingServicePlatform: local  # choices: local, remote, pai
-searchSpacePath: search_space.json
-useAnnotation: false
 tuner:
-    builtinTunerName: TPE   # choices: TPE, Random, Anneal, Evolution, BatchTuner, MetisTuner,
-                            #          GPTuner, SMAC (SMAC should be installed through nnictl)
+  name: TPE
   classArgs:
-        optimize_mode: maximize  # choices: maximize, minimize
-trial:
-  command: python3 mnist.py
-  codeDir: .
-  gpuNum: 0
+    optimize_mode: maximize
+trainingService:
+  platform: local

examples/trials/mnist-tfv2/config_assessor.yml

-authorName: NNI Example
-experimentName: MNIST TF v2.x with assessor
-trialConcurrency: 1
-maxExecDuration: 1h
-maxTrialNum: 50
-#choice: local, remote
-trainingServicePlatform: local
-searchSpacePath: search_space.json
-#choice: true, false
-useAnnotation: false
+searchSpaceFile: search_space.json
+trialCommand: python3 mnist.py
+trialGpuNumber: 0
+trialConcurrency: 2
+maxTrialNumber: 50
 tuner:
-  #choice: TPE, Random, Anneal, Evolution, BatchTuner, MetisTuner, GPTuner
-  #SMAC (SMAC should be installed through nnictl)
-  builtinTunerName: TPE
+  name: TPE
   classArgs:
-    #choice: maximize, minimize
     optimize_mode: maximize
-assessor:
-  #choice: Medianstop, Curvefitting
-  builtinAssessorName: Curvefitting
+assessor:  # Specify early-stop algorithm
+  name: Curvefitting
   classArgs:
     epoch_num: 20
     threshold: 0.9
-trial:
-  command: python3 mnist.py
-  codeDir: .
-  gpuNum: 0
+trainingService:
+  platform: local

examples/trials/mnist-tfv2/config_detailed.yml

+# This example shows more configurable fields comparing to the minimal "config.yml"
+# You can use "nnictl create --config config_detailed.yml" to launch this experiment.
+# If you see an error message saying "port 8080 is used", use "nnictl stop --all" to stop previous experiments.
+
+name: MNIST                     # An optional name to help you distinguish experiments.
+
+# Hyper-parameter search space can either be configured here or in a seperate file.
+# "config.yml" shows how to specify a seperate search space file.
+# The common schema of search space is documented here:
+#   https://nni.readthedocs.io/en/stable/Tutorial/SearchSpaceSpec.html
+searchSpace:
+  dropout_rate:
+    _type: uniform
+    _value: [0.5, 0.9]
+  conv_size:
+    _type: choice
+    _value: [2, 3, 5, 7]
+  hidden_size:
+    _type: choice
+    _value: [128, 512, 1024]
+  batch_size:
+    _type: choice
+    _value: [16, 32]
+  learning_rate:
+    _type: choice
+    _value: [0.0001, 0.001, 0.01, 0.1]
+
+trialCommand: python3 mnist.py  # The command to launch a trial. NOTE: change "python3" to "python" if you are using Windows.
+trialCodeDirectory: .           # The path of trial code. By default it's ".", which means the same directory of this config file.
+trialGpuNumber: 1               # How many GPUs should each trial use. CUDA is required when it's greater than zero.
+
+trialConcurrency: 4             # Run 4 trials concurrently.
+maxTrialNumber: 10              # Generate at most 10 trials.
+maxExperimentDuration: 1h       # Stop generating trials after 1 hour.
+
+tuner:                          # Configure the tuning alogrithm.
+  name: TPE                     # Supported algorithms: TPE, Random, Anneal, Evolution, GridSearch, GPTuner, PBTTuner, etc.
+                                #   Full list:  https://nni.readthedocs.io/en/latest/Tuner/BuiltinTuner.html
+  classArgs:                    # Algorithm specific arguments. See the tuner's doc for details.
+    optimize_mode: maximize     #   "minimize" or "maximize"
+
+# Configure the training platform.
+# Supported platforms: local, remote, openpai, aml, kubeflow, kubernetes, adl.
+# You can find config template of some platforms in this directory, and others in mnist-pytorch example.
+trainingService:
+  platform: local
+  useActiveGpu: false           # NOTE: Use "true" if you are using an OS with graphical interface (e.g. Windows 10, Ubuntu desktop)
+                                #   Reason and details:  https://nni.readthedocs.io/en/latest/reference/experiment_config.html#useactivegpu

examples/trials/mnist-tfv2/config_hybrid.yml

+searchSpaceFile: search_space.json
+trialCommand: python3 mnist.py
+trialGpuNumber: 0
+trialConcurrency: 5
+maxTrialNumber: 20
+tuner:
+  name: TPE
+  classArgs:
+    optimize_mode: maximize
+# For local, remote, openpai, and aml, NNI can use multiple training services at one time
+trainingService:
+  - platform: local
+  - platform: remote
+    machineList:
+      - host: ${your server's IP or domain name}
+        user: ${your user name}
+        ssh_key_file: ~/.ssh/id_rsa
+  - platform: aml
+    dockerImage: msranni/nni
+    subscriptionId: ${your subscription ID}
+    resourceGroup: ${your resource group}
+    workspaceName: ${your workspace name}
+    computeTarget: ${your compute target}

examples/trials/mnist-tfv2/config_remote.yml

-authorName: default
-experimentName: example_mnist
-trialConcurrency: 1
-maxExecDuration: 1h
-maxTrialNum: 10
-#choice: local, remote, pai
-trainingServicePlatform: remote
-searchSpacePath: search_space.json
-#choice: true, false
-useAnnotation: false
+searchSpaceFile: search_space.json
+trialCommand: python3 mnist.py
+trialGpuNumber: 0
+trialConcurrency: 4
+maxTrialNumber: 20
 tuner:
-  #choice: TPE, Random, Anneal, Evolution, BatchTuner, MetisTuner
-  #SMAC (SMAC should be installed through nnictl)
-  builtinTunerName: TPE
+  name: TPE
   classArgs:
-    #choice: maximize, minimize
     optimize_mode: maximize
-trial:
-  command: python3 mnist.py
-  codeDir: .
-  gpuNum: 0
-#machineList can be empty if the platform is local
-machineList:
-  - ip: ${replace_to_your_remote_machine_ip}
-    username: ${replace_to_your_remote_machine_username}
-    sshKeyPath: ${replace_to_your_remote_machine_sshKeyPath}
-    # Below are examples of specifying python environment.
-    # pythonPath: /opt/python3.7/bin
-    # pythonPath: C:/Python37
-    # Below is an example of specifying python environment for windows anaconda user. Multiple paths separated by ';'. 
-    # pythonPath: C:/Users/yourname/.conda/envs/myenv;C:/Users/yourname/.conda/envs/myenv/Scripts;C:/Users/yourname/.conda/envs/myenv/Library/bin
-    pythonPath: ${replace_to_python_environment_path_in_your_remote_machine}
+trainingService:
+  platform: remote
+  machineList:
+    - host: ${your server's IP or domain name}
+      user: ${your user name}
+      ssh_key_file: ~/.ssh/id_rsa  # We recommend public key over password, it's more secure and convenient.
+    # You can specify more than one SSH servers:
+    - host: 123.123.123.123
+      port: 10022
+      user: nniuser
+      password: 12345
+      pythonPath: /usr/bin  # Other examples:
+                            #   /opt/python3.9/bin
+                            #   C:/Python39
+                            #   C:/Users/USERNAME/.conda/envs/ENVNAME;C:/Users/USERNAME/.conda/envs/ENVNAME/Scripts;C:/Users/USERNAME/.conda/envs/ENVNAME/Library/bin

examples/trials/mnist-tfv2/config_v2.yml

-searchSpace:
-  dropout_rate:
-    _type: uniform
-    _value: [0.5, 0.9]
-  conv_size:
-    _type: choice
-    _value: [2, 3, 5, 7]
-  hidden_size:
-    _type: choice
-    _value: [128, 512, 1024]
-  batch_size:
-    _type: choice
-    _value: [16, 32]
-  learning_rate:
-    _type: choice
-    _value: [0.0001, 0.001, 0.01, 0.1]
-trainingService:
-  platform: local
-trialCodeDirectory: .
-trialCommand: python3 mnist.py
-trialConcurrency: 1
-trialGpuNumber: 0
-tuner:
-  name: TPE
-  classArgs:
-    optimize_mode: maximize

examples/trials/mnist-tfv2/config_windows.yml

-authorName: NNI Example
-experimentName: MNIST TF v2.x
-trialConcurrency: 1
-maxExecDuration: 1h
-maxTrialNum: 10
-#choice: local, remote, pai
-trainingServicePlatform: local
-searchSpacePath: search_space.json
-#choice: true, false
-useAnnotation: false
-tuner:
-  #choice: TPE, Random, Anneal, Evolution, BatchTuner, MetisTuner, GPTuner
-  #SMAC (SMAC should be installed through nnictl)
-  builtinTunerName: TPE
-  classArgs:
-    #choice: maximize, minimize
-    optimize_mode: maximize
-trial:
-  command: python mnist.py
-  codeDir: .
-  gpuNum: 0

examples/trials/network_morphism/FashionMNIST/config.yml

-authorName: default
-experimentName: example_FashionMNIST-network-morphism
+trialCommand: python3 FashionMNIST_keras.py
+trialGpuNumber: 1
 trialConcurrency: 4
-maxExecDuration: 48h
-maxTrialNum: 200
-#choice: local, remote, pai
-trainingServicePlatform: local
-#searchSpacePath: search_space.json
-#choice: true, false
-useAnnotation: false
+maxExperimentDuration: 48h
+maxTrialNumber: 200
+searchSpace: {}  # search space of NetworkMorphism is provided via classArgs
 tuner:
-  #choice: TPE, Random, Anneal, Evolution, BatchTuner, NetworkMorphism
-  #SMAC (SMAC should be installed through nnictl)
-  builtinTunerName: NetworkMorphism
+  name: NetworkMorphism
   classArgs:
-    #choice: maximize, minimize
-    optimize_mode: maximize
-    #for now, this tuner only supports cv domain
-    task: cv
-    #input image width
-    input_width: 28
-    #input image channel
-    input_channel: 1
-    #number of classes
-    n_output_node: 10
-trial:
-  command: python3 FashionMNIST_keras.py
-  codeDir: .
-  gpuNum: 1
+    optimize_mode: maximize   # maximize or minimize
+    task: cv                  # for now, this tuner only supports cv domain
+    input_width: 28           # input image width
+    input_channel: 1          # input image channel
+    n_output_node: 10         # number of classes
+trainingService:
+  platform: local
+  useActiveGpu: false  # NOTE: Use "true" if you are using an OS with graphical interface (e.g. Windows 10, Ubuntu desktop)
+                       # Check the doc for details: https://nni.readthedocs.io/en/latest/reference/experiment_config.html#useactivegpu

examples/trials/network_morphism/FashionMNIST/config_pai.yml

-authorName: default
-experimentName: example_FashionMNIST-network-morphism
-trialConcurrency: 1
-maxExecDuration: 24h
-maxTrialNum: 10
-#choice: local, remote, pai
-trainingServicePlatform: pai
-#choice: true, false
-useAnnotation: false
-tuner:
-  #choice: TPE, Random, Anneal, Evolution, BatchTuner, NetworkMorphism
-  #SMAC (SMAC should be installed through nnictl)
-  builtinTunerName: NetworkMorphism
-  classArgs:
-    #choice: maximize, minimize
-    optimize_mode: maximize
-    # for now, this tuner only supports cv domain
-    task: cv
-    #input image width
-    input_width: 28
-    #input image channel
-    input_channel: 1
-    #number of classes
-    n_output_node: 10
-trial:
-  command: python3 FashionMNIST_keras.py
-  codeDir: .
-  gpuNum: 1
-  cpuNum: 1
-  memoryMB: 8196
-  #The docker image to run nni job on pai
-  image: msranni/nni:latest
-  nniManagerNFSMountPath: {replace_to_your_nfs_mount_path}
-  containerNFSMountPath: {replace_to_your_container_mount_path}
-  paiStorageConfigName: {replace_to_your_storage_config_name}
-paiConfig:
-  #The username to login pai
-  userName: username
-  #The token to login pai
-  token: token
-  #The host of restful server of pai
-  host: 10.10.10.10
\ No newline at end of file

examples/trials/network_morphism/cifar10/config.yml

-authorName: default
-experimentName: example_cifar10-network-morphism
+trialCommand: python3 cifar10_keras.py
+trialGpuNumber: 1
 trialConcurrency: 4
-maxExecDuration: 48h
-maxTrialNum: 200
-#choice: local, remote, pai
-trainingServicePlatform: local
-#searchSpacePath: search_space.json
-#choice: true, false
-useAnnotation: false
+maxExperimentDuration: 48h
+maxTrialNumber: 200
+searchSpace: {}  # search space of NetworkMorphism is provided via classArgs
 tuner:
-  #choice: TPE, Random, Anneal, Evolution, BatchTuner, NetworkMorphism
-  #SMAC (SMAC should be installed through nnictl)
-  builtinTunerName: NetworkMorphism
+  name: NetworkMorphism
   classArgs:
-    #choice: maximize, minimize
-    optimize_mode: maximize
-    #for now, this tuner only supports cv domain
-    task: cv
-    #input image width
-    input_width: 32
-    #input image channel
-    input_channel: 3
-    #number of classes
-    n_output_node: 10
-trial:
-  command: python3 cifar10_keras.py
-  codeDir: .
-  gpuNum: 1
+    optimize_mode: maximize   # maximize or minimize
+    task: cv                  # for now, this tuner only supports cv domain
+    input_width: 32           # input image width
+    input_channel: 3          # input image channel
+    n_output_node: 10         # number of classes
+trainingService:
+  platform: local
+  useActiveGpu: false  # NOTE: Use "true" if you are using an OS with graphical interface (e.g. Windows 10, Ubuntu desktop)
+                       # Check the doc for details: https://nni.readthedocs.io/en/latest/reference/experiment_config.html#useactivegpu

examples/trials/network_morphism/cifar10/config_pai.yml

-authorName: default
-experimentName: example_cifar10-network-morphism
-trialConcurrency: 1
-maxExecDuration: 24h
-maxTrialNum: 10
-#choice: local, remote, pai
-trainingServicePlatform: pai
-#choice: true, false
-useAnnotation: false
-tuner:
-  #choice: TPE, Random, Anneal, Evolution, BatchTuner, NetworkMorphism
-  #SMAC (SMAC should be installed through nnictl)
-  builtinTunerName: NetworkMorphism
-  classArgs:
-    #choice: maximize, minimize
-    optimize_mode: maximize
-    # for now, this tuner only supports cv domain
-    task: cv
-    #input image width
-    input_width: 32
-    #input image channel
-    input_channel: 3
-    #number of classes
-    n_output_node: 10
-trial:
-  command: python3 cifar10_keras.py
-  codeDir: .
-  gpuNum: 1
-  cpuNum: 1
-  memoryMB: 8196
-  #The docker image to run nni job on pai
-  image: msranni/nni:latest
-  nniManagerNFSMountPath: {replace_to_your_nfs_mount_path}
-  containerNFSMountPath: {replace_to_your_container_mount_path}
-  paiStorageConfigName: {replace_to_your_storage_config_name}
-paiConfig:
-  #The username to login pai
-  userName: username
-  #The token to login pai
-  token: token
-  #The host of restful server of pai
-  host: 10.10.10.10
\ No newline at end of file

examples/trials/sklearn/classification/config.yml

-authorName: default
-experimentName: example_sklearn-classification
+searchSpaceFile: search_space.json
+trialCommand: python3 main.py
 trialConcurrency: 1
-maxExecDuration: 1h
-maxTrialNum: 100
-#choice: local, remote
-trainingServicePlatform: local
-searchSpacePath: search_space.json
-#choice: true, false
-useAnnotation: false
+maxTrialNumber: 100
+maxExperimentDuration: 1h
 tuner:
-  #choice: TPE, Random, Anneal, Evolution, BatchTuner, MetisTuner
-  builtinTunerName: TPE
+  name: TPE
   classArgs:
-    #choice: maximize, minimize
     optimize_mode: maximize
-trial:
-  command: python3 main.py
-  codeDir: .
-  gpuNum: 0
+trainingService:  # For other platforms, check mnist-pytorch example
+  platform: local
\ No newline at end of file

examples/trials/sklearn/classification/config_pai.yml

-authorName: default
-experimentName: example_sklearn
-trialConcurrency: 1
-maxExecDuration: 1h
-maxTrialNum: 100
-#choice: local, remote, pai
-trainingServicePlatform: pai
-searchSpacePath: search_space.json
-#choice: true, false
-useAnnotation: false
-tuner:
-  #choice: TPE, Random, Anneal, Evolution, BatchTuner,MetisTuner
-  #SMAC (SMAC should be installed through nnictl)
-  builtinTunerName: TPE
-  classArgs:
-    #choice: maximize, minimize
-    optimize_mode: maximize
-trial:
-  command: python3 main.py
-  codeDir: .
-  gpuNum: 0
-  cpuNum: 1
-  memoryMB: 8196
-  #The docker image to run nni job on pai
-  image: msranni/nni:latest
-  nniManagerNFSMountPath: {replace_to_your_nfs_mount_path}
-  containerNFSMountPath: {replace_to_your_container_mount_path}
-  paiStorageConfigName: {replace_to_your_storage_config_name}
-paiConfig:
-  #The username to login pai
-  userName: username
-  #The token to login pai
-  token: token
-  #The host of restful server of pai
-  host: 10.10.10.10
\ No newline at end of file

examples/trials/sklearn/regression/config.yml

-authorName: default
-experimentName: example_sklearn-regression
+searchSpaceFile: search_space.json
+trialCommand: python3 main.py
 trialConcurrency: 1
-maxExecDuration: 1h
-maxTrialNum: 30
-#choice: local, remote
-trainingServicePlatform: local
-searchSpacePath: search_space.json
-#choice: true, false
-useAnnotation: false
+maxTrialNumber: 30
+maxExperimentDuration: 1h
 tuner:
-  #choice: TPE, Random, Anneal, Evolution, BatchTuner, MetisTuner
-  builtinTunerName: TPE
+  name: TPE
   classArgs:
-    #choice: maximize, minimize
     optimize_mode: maximize
-trial:
-  command: python3 main.py
-  codeDir: .
-  gpuNum: 0
+trainingService:  # For other platforms, check mnist-pytorch example
+  platform: local
\ No newline at end of file

examples/trials/sklearn/regression/config_pai.yml

-authorName: default
-experimentName: example_sklearn
-trialConcurrency: 1
-maxExecDuration: 1h
-maxTrialNum: 100
-#choice: local, remote, pai
-trainingServicePlatform: pai
-searchSpacePath: search_space.json
-#choice: true, false
-useAnnotation: false
-tuner:
-  #choice: TPE, Random, Anneal, Evolution, BatchTuner, MetisTuner
-  #SMAC (SMAC should be installed through nnictl)
-  builtinTunerName: TPE
-  classArgs:
-    #choice: maximize, minimize
-    optimize_mode: maximize
-trial:
-  command: python3 main.py
-  codeDir: .
-  gpuNum: 0
-  cpuNum: 1
-  memoryMB: 8196
-  #The docker image to run nni job on pai
-  image: msranni/nni:latest
-  nniManagerNFSMountPath: {replace_to_your_nfs_mount_path}
-  containerNFSMountPath: {replace_to_your_container_mount_path}
-  paiStorageConfigName: {replace_to_your_storage_config_name}
-paiConfig:
-  #The username to login pai
-  userName: username
-  #The token to login pai
-  token: token
-  #The host of restful server of pai
-  host: 10.10.10.10
\ No newline at end of file

nni/experiment/config/base.py

@@ -124,7 +124,7 @@ class ConfigBase:
             type_name = str(field.type).replace('typing.', '')
             optional = any([
                 type_name.startswith('Optional['),
-                type_name.startswith('Union[') and 'NoneType' in type_name,
+                type_name.startswith('Union[') and 'None' in type_name,
                 type_name == 'Any'
             ])
             if value is None: