[v2.0] Refactor code hierarchy (part 2)

.gitignore

@@ -1,6 +1,10 @@
-/nni_node/node
-/nni_node/node.exe
-/toolchain
+/nni_node/
+/toolchain/
+
+# unit test generated files
+/test/model_path/
+/test/temp.json
+/test/ut/sdk/*.pth
 
 
 # Logs

azure-pipelines.yml

@@ -14,8 +14,7 @@ jobs:
       echo "##vso[task.setvariable variable=PATH]${HOME}/.local/bin:${PATH}"
     displayName: 'Install python tools'
   - script: |
-      make
-      python3 -m pip install -U -e .
+      python3 setup.py develop
     displayName: 'Install nni toolkit via source code'
   - script: |
       set -e
@@ -46,10 +45,10 @@ jobs:
       cd test
       python3 nni_test/nnitest/run_tests.py --config config/pr_tests.yml
     displayName: 'Simple test'
-  - script: |
-      cd docs/en_US/
-      sphinx-build -M html . _build -W
-    displayName: 'Sphinx Documentation Build check'
+  #- script: |
+  #    cd docs/en_US/
+  #    sphinx-build -M html . _build -W
+  #  displayName: 'Sphinx Documentation Build check'
 
 - job: 'ubuntu_1804_python36_legacy_torch_tf'
   pool:
@@ -65,8 +64,7 @@ jobs:
       echo "##vso[task.setvariable variable=PATH]${HOME}/.local/bin:${PATH}"
     displayName: 'Install python tools'
   - script: |
-      make
-      python3 -m pip install -U -e .
+      python3 setup.py develop
     displayName: 'Install nni toolkit via source code'
   - script: |
       set -e

docs/en_US/nnicli_ref.md

@@ -3,7 +3,7 @@
 NNI client is a python API of `nnictl`, which implements the most commonly used commands. Users can use this API to control their experiments, collect experiment results and conduct advanced analyses based on experiment results in python code directly instead of using command line. Here is an example:
 
 ```
-from nni.nnicli import Experiment
+from nni.experiment import Experiment
 
 # create an experiment instance
 exp = Experiment() 
@@ -28,14 +28,14 @@ exp.stop_experiment()
 ## References
 
 ```eval_rst
-..  autoclass:: nni.nnicli.Experiment
+..  autoclass:: nni.experiment.Experiment
     :members:
-..  autoclass:: nni.nnicli.TrialJob
+..  autoclass:: nni.experiment.TrialJob
     :members:
-..  autoclass:: nni.nnicli.TrialHyperParameters
+..  autoclass:: nni.experiment.TrialHyperParameters
     :members:
-..  autoclass:: nni.nnicli.TrialMetricData
+..  autoclass:: nni.experiment.TrialMetricData
     :members:
-..  autoclass:: nni.nnicli.TrialResult
+..  autoclass:: nni.experiment.TrialResult
     :members:
 ```

nni/__init__.py

@@ -3,13 +3,13 @@
 
 __version__ = '999.0.0-developing'
 
-from .env_vars import dispatcher_env_vars
+from .runtime.env_vars import dispatcher_env_vars
 from .utils import ClassArgsValidator
 
 if dispatcher_env_vars.SDK_PROCESS != 'dispatcher':
     from .trial import *
     from .smartparam import *
-    from .nas_utils import training_update
+    from .common.nas_utils import training_update
 
 class NoMoreTrialError(Exception):
     def __init__(self, ErrorInfo):

nni/__main__.py

@@ -7,9 +7,9 @@
 import json
 import base64
 
-from .common import enable_multi_thread, enable_multi_phase
-from .msg_dispatcher import MsgDispatcher
-from .package_utils import create_builtin_class_instance, create_customized_class_instance
+from .runtime.common import enable_multi_thread, enable_multi_phase
+from .runtime.msg_dispatcher import MsgDispatcher
+from .tools.package_utils import create_builtin_class_instance, create_customized_class_instance
 
 logger = logging.getLogger('nni.main')
 logger.debug('START')

nni/compression/torch/pruning/admm_pruner.py → nni/algorithms/compression/pytorch/pruning/admm_pruner.py

@@ -5,7 +5,7 @@
 import torch
 from schema import And, Optional
 
-from ..utils.config_validation import CompressorSchema
+from nni.compression.pytorch.utils.config_validation import CompressorSchema
 from .constants import MASKER_DICT
 from .one_shot import OneshotPruner
 

nni/compression/torch/pruning/agp.py → nni/algorithms/compression/pytorch/pruning/agp.py

@@ -13,8 +13,8 @@
 import torch
 from schema import And, Optional
 from .constants import MASKER_DICT
-from ..utils.config_validation import CompressorSchema
-from ..compressor import Pruner
+from nni.compression.pytorch.utils.config_validation import CompressorSchema
+from nni.compression.pytorch.compressor import Pruner
 
 __all__ = ['AGPPruner']
 

nni/compression/torch/pruning/amc/amc_pruner.py → nni/algorithms/compression/pytorch/pruning/amc/amc_pruner.py

@@ -9,7 +9,7 @@
 import torch
 from torch.utils.tensorboard import SummaryWriter
 
-from nni.compression.torch.compressor import Pruner
+from nni.compression.pytorch.compressor import Pruner
 from .channel_pruning_env import ChannelPruningEnv
 from .lib.agent import DDPG
 from .lib.utils import get_output_folder

nni/compression/torch/pruning/amc/channel_pruning_env.py → nni/algorithms/compression/pytorch/pruning/amc/channel_pruning_env.py

@@ -10,7 +10,7 @@
 import torch
 import torch.nn as nn
 
-from nni.compression.torch.compressor import PrunerModuleWrapper
+from nni.compression.pytorch.compressor import PrunerModuleWrapper
 from .. import AMCWeightMasker
 
 _logger = logging.getLogger(__name__)

nni/compression/torch/pruning/auto_compress_pruner.py → nni/algorithms/compression/pytorch/pruning/auto_compress_pruner.py

@@ -8,10 +8,10 @@
 from schema import And, Optional
 
 from nni.utils import OptimizeMode
-from nni.compression.torch import ModelSpeedup
+from nni.compression.pytorch import ModelSpeedup
 
-from ..compressor import Pruner
-from ..utils.config_validation import CompressorSchema
+from nni.compression.pytorch.compressor import Pruner
+from nni.compression.pytorch.utils.config_validation import CompressorSchema
 from .simulated_annealing_pruner import SimulatedAnnealingPruner
 from .admm_pruner import ADMMPruner
 

nni/compression/torch/pruning/constants.py → nni/algorithms/compression/pytorch/pruning/constants.py

@@ -2,7 +2,7 @@
 # Licensed under the MIT license.
 
 
-from ..pruning import LevelPrunerMasker, SlimPrunerMasker, L1FilterPrunerMasker, \
+from . import LevelPrunerMasker, SlimPrunerMasker, L1FilterPrunerMasker, \
     L2FilterPrunerMasker, FPGMPrunerMasker, TaylorFOWeightFilterPrunerMasker, \
     ActivationAPoZRankFilterPrunerMasker, ActivationMeanRankFilterPrunerMasker
 

nni/compression/torch/pruning/lottery_ticket.py → nni/algorithms/compression/pytorch/pruning/lottery_ticket.py

@@ -5,8 +5,8 @@
 import logging
 import torch
 from schema import And, Optional
-from ..utils.config_validation import CompressorSchema
-from ..compressor import Pruner
+from nni.compression.pytorch.utils.config_validation import CompressorSchema
+from nni.compression.pytorch.compressor import Pruner
 from .finegrained_pruning import LevelPrunerMasker
 
 logger = logging.getLogger('torch pruner')

nni/compression/torch/pruning/net_adapt_pruner.py → nni/algorithms/compression/pytorch/pruning/net_adapt_pruner.py

@@ -10,9 +10,9 @@
 
 from nni.utils import OptimizeMode
 
-from ..compressor import Pruner
-from ..utils.config_validation import CompressorSchema
-from ..utils.num_param_counter import get_total_num_weights
+from nni.compression.pytorch.compressor import Pruner
+from nni.compression.pytorch.utils.config_validation import CompressorSchema
+from nni.compression.pytorch.utils.num_param_counter import get_total_num_weights
 from .constants_pruner import PRUNER_DICT
 
 

nni/compression/torch/pruning/one_shot.py → nni/algorithms/compression/pytorch/pruning/one_shot.py

@@ -3,11 +3,11 @@
 
 import logging
 from schema import And, Optional, SchemaError
-from nni._graph_utils import TorchModuleGraph
-from nni.compression.torch.utils.shape_dependency import ChannelDependency, GroupDependency
+from nni.common.graph_utils import TorchModuleGraph
+from nni.compression.pytorch.utils.shape_dependency import ChannelDependency, GroupDependency
 from .constants import MASKER_DICT
-from ..utils.config_validation import CompressorSchema
-from ..compressor import Pruner
+from nni.compression.pytorch.utils.config_validation import CompressorSchema
+from nni.compression.pytorch.compressor import Pruner
 
 
 __all__ = ['LevelPruner', 'SlimPruner', 'L1FilterPruner', 'L2FilterPruner', 'FPGMPruner',

nni/compression/torch/pruning/sensitivity_pruner.py → nni/algorithms/compression/pytorch/pruning/sensitivity_pruner.py

@@ -8,10 +8,10 @@
 import torch
 
 from schema import And, Optional
-from ..compressor import Pruner
-from ..utils.config_validation import CompressorSchema
+from nni.compression.pytorch.compressor import Pruner
+from nni.compression.pytorch.utils.config_validation import CompressorSchema
 from .constants_pruner import PRUNER_DICT
-from ..utils.sensitivity_analysis import SensitivityAnalysis
+from nni.compression.pytorch.utils.sensitivity_analysis import SensitivityAnalysis
 
 
 MAX_PRUNE_RATIO_PER_ITER = 0.95

nni/compression/torch/pruning/simulated_annealing_pruner.py → nni/algorithms/compression/pytorch/pruning/simulated_annealing_pruner.py

@@ -12,8 +12,8 @@
 
 from nni.utils import OptimizeMode
 
-from ..compressor import Pruner
-from ..utils.config_validation import CompressorSchema
+from nni.compression.pytorch.compressor import Pruner
+from nni.compression.pytorch.utils.config_validation import CompressorSchema
 from .constants_pruner import PRUNER_DICT
 
 

nni/compression/torch/quantization/quantizers.py → nni/algorithms/compression/pytorch/quantization/quantizers.py

@@ -5,8 +5,8 @@
 import copy
 import torch
 from schema import Schema, And, Or, Optional
-from ..utils.config_validation import CompressorSchema
-from ..compressor import Quantizer, QuantGrad, QuantType
+from nni.compression.pytorch.utils.config_validation import CompressorSchema
+from nni.compression.pytorch.compressor import Quantizer, QuantGrad, QuantType
 
 __all__ = ['NaiveQuantizer', 'QAT_Quantizer', 'DoReFaQuantizer', 'BNNQuantizer']
 

nni/compression/tensorflow/pruning/one_shot.py → nni/algorithms/compression/tensorflow/pruning/one_shot.py

@@ -1,6 +1,6 @@
 import tensorflow as tf
 
-from ..compressor import Pruner
+from nni.compression.tensorflow import Pruner
 
 __all__ = [
     'OneshotPruner',

nni/bohb_advisor/bohb_advisor.py → nni/algorithms/hpo/bohb_advisor/bohb_advisor.py

@@ -14,10 +14,10 @@
 import ConfigSpace.hyperparameters as CSH
 
 from nni import ClassArgsValidator
-from nni.protocol import CommandType, send
-from nni.msg_dispatcher_base import MsgDispatcherBase
+from nni.runtime.protocol import CommandType, send
+from nni.runtime.msg_dispatcher_base import MsgDispatcherBase
 from nni.utils import OptimizeMode, MetricType, extract_scalar_reward
-from nni.common import multi_phase_enabled
+from nni.runtime.common import multi_phase_enabled
 
 from .config_generator import CG_BOHB
 

nni/hyperband_advisor/hyperband_advisor.py → nni/algorithms/hpo/hyperband_advisor/hyperband_advisor.py

@@ -15,9 +15,9 @@
 from schema import Schema, Optional
 
 from nni import ClassArgsValidator
-from nni.common import multi_phase_enabled
-from nni.msg_dispatcher_base import MsgDispatcherBase
-from nni.protocol import CommandType, send
+from nni.runtime.common import multi_phase_enabled
+from nni.runtime.msg_dispatcher_base import MsgDispatcherBase
+from nni.runtime.protocol import CommandType, send
 from nni.utils import NodeType, OptimizeMode, MetricType, extract_scalar_reward
 from nni import parameter_expressions
 

nni/metis_tuner/Regression_GMM/Selection.py → nni/algorithms/hpo/metis_tuner/Regression_GMM/Selection.py

@@ -5,8 +5,8 @@
 import random
 import sys
 
-import nni.metis_tuner.lib_acquisition_function as lib_acquisition_function
-import nni.metis_tuner.lib_constraint_summation as lib_constraint_summation
+from .. import lib_acquisition_function
+from .. import lib_constraint_summation
 
 sys.path.insert(1, os.path.join(sys.path[0], '..'))
 

nni/metis_tuner/Regression_GP/OutlierDetection.py → nni/algorithms/hpo/metis_tuner/Regression_GP/OutlierDetection.py

@@ -9,8 +9,8 @@
 import sys
 from multiprocessing.dummy import Pool as ThreadPool
 
-import nni.metis_tuner.Regression_GP.CreateModel as gp_create_model
-import nni.metis_tuner.Regression_GP.Prediction as gp_prediction
+from . import CreateModel as gp_create_model
+from . import Prediction as gp_prediction
 
 sys.path.insert(1, os.path.join(sys.path[0], '..'))
 

nni/metis_tuner/Regression_GP/Selection.py → nni/algorithms/hpo/metis_tuner/Regression_GP/Selection.py

@@ -5,10 +5,10 @@
 import random
 import sys
 
-import nni.metis_tuner.lib_acquisition_function as lib_acquisition_function
-import nni.metis_tuner.lib_constraint_summation as lib_constraint_summation
-import nni.metis_tuner.lib_data as lib_data
-import nni.metis_tuner.Regression_GP.Prediction as gp_prediction
+from .. import lib_acquisition_function
+from .. import lib_constraint_summation
+from .. import lib_data
+from . import Prediction as gp_prediction
 
 sys.path.insert(1, os.path.join(sys.path[0], '..'))
 

nni/metis_tuner/lib_acquisition_function.py → nni/algorithms/hpo/metis_tuner/lib_acquisition_function.py

@@ -11,7 +11,7 @@
 from scipy.stats import norm
 from scipy.optimize import minimize
 
-import nni.metis_tuner.lib_data as lib_data
+from . import lib_data
 
 
 def next_hyperparameter_expected_improvement(fun_prediction,