[v2.0] Refactor code hierarchy (part 2) (#2987)

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

@@ -5,8 +5,8 @@ import copy
 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 schema import And, Optional
 
 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 logging
 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 schema import And, Optional
 
 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 logging
 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

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