Refactor model compression directory structure (#2501)

docs/en_US/Compressor/ModelSpeedup.md

@@ -21,7 +21,7 @@ For each module, we should prepare four functions, three for shape inference and
 ## Usage
 
 ```python
-from nni.compression.speedup.torch import ModelSpeedup
+from nni.compression.torch import ModelSpeedup
 # model: the model you want to speed up
 # dummy_input: dummy input of the model, given to `jit.trace`
 # masks_file: the mask file created by pruning algorithms

examples/model_compress/model_speedup.py

@@ -6,8 +6,7 @@ import torch.nn as nn
 import torch.nn.functional as F
 from torchvision import datasets, transforms
 from models.cifar10.vgg import VGG
-from nni.compression.speedup.torch import ModelSpeedup
-from nni.compression.torch import apply_compression_results
+from nni.compression.torch import apply_compression_results, ModelSpeedup
 
 torch.manual_seed(0)
 use_mask = True

src/sdk/pynni/nni/compression/torch/__init__.py

 # Copyright (c) Microsoft Corporation.
 # Licensed under the MIT license.
 
+from .pruning import *
+from .quantization import *
 from .compressor import Compressor, Pruner, Quantizer
-from .pruners import *
-from .weight_rank_filter_pruners import *
-from .activation_rank_filter_pruners import *
-from .quantizers import *
-from .apply_compression import apply_compression_results
-from .gradient_rank_filter_pruners import *
+from .speedup import ModelSpeedup

src/sdk/pynni/nni/compression/torch/pruning/__init__.py

+# Copyright (c) Microsoft Corporation.
+# Licensed under the MIT license.
+
+from .pruners import *
+from .weight_rank_filter_pruners import *
+from .activation_rank_filter_pruners import *
+from .apply_compression import apply_compression_results
+from .gradient_rank_filter_pruners import *

src/sdk/pynni/nni/compression/torch/activation_rank_filter_pruners.py → src/sdk/pynni/nni/compression/torch/pruning/activation_rank_filter_pruners.py

@@ -4,8 +4,8 @@
 import logging
 import torch
 from schema import And, Optional
-from .utils import CompressorSchema
-from .compressor import Pruner
+from ..utils.config_validation import CompressorSchema
+from ..compressor import Pruner
 
 __all__ = ['ActivationAPoZRankFilterPruner', 'ActivationMeanRankFilterPruner']
 

src/sdk/pynni/nni/compression/torch/gradient_rank_filter_pruners.py → src/sdk/pynni/nni/compression/torch/pruning/gradient_rank_filter_pruners.py

@@ -3,7 +3,7 @@
 
 import logging
 import torch
-from .compressor import Pruner
+from ..compressor import Pruner
 
 __all__ = ['TaylorFOWeightFilterPruner']
 

src/sdk/pynni/nni/compression/torch/pruners.py → src/sdk/pynni/nni/compression/torch/pruning/pruners.py

@@ -5,8 +5,8 @@ import copy
 import logging
 import torch
 from schema import And, Optional
-from .compressor import Pruner
-from .utils import CompressorSchema
+from ..utils.config_validation import CompressorSchema
+from ..compressor import Pruner
 
 __all__ = ['LevelPruner', 'AGP_Pruner', 'SlimPruner', 'LotteryTicketPruner']
 

src/sdk/pynni/nni/compression/torch/weight_rank_filter_pruners.py → src/sdk/pynni/nni/compression/torch/pruning/weight_rank_filter_pruners.py

@@ -4,8 +4,8 @@
 import logging
 import torch
 from schema import And, Optional
-from .utils import CompressorSchema
-from .compressor import Pruner
+from ..utils.config_validation import CompressorSchema
+from ..compressor import Pruner
 
 __all__ = ['L1FilterPruner', 'L2FilterPruner', 'FPGMPruner']
 

src/sdk/pynni/nni/compression/torch/quantization/__init__.py

+# Copyright (c) Microsoft Corporation.
+# Licensed under the MIT license.
+
+from .quantizers import *

src/sdk/pynni/nni/compression/torch/quantizers.py → src/sdk/pynni/nni/compression/torch/quantization/quantizers.py

@@ -4,8 +4,8 @@
 import logging
 import torch
 from schema import Schema, And, Or, Optional
-from .utils import CompressorSchema
-from .compressor import Quantizer, QuantGrad, QuantType
+from ..utils.config_validation import CompressorSchema
+from ..compressor import Quantizer, QuantGrad, QuantType
 
 __all__ = ['NaiveQuantizer', 'QAT_Quantizer', 'DoReFaQuantizer', 'BNNQuantizer']
 

src/sdk/pynni/tests/test_model_speedup.py

@@ -10,8 +10,7 @@ from torchvision.models.vgg import vgg16
 from torchvision.models.resnet import resnet18
 from unittest import TestCase, main
 
-from nni.compression.torch import L1FilterPruner, apply_compression_results
-from nni.compression.speedup.torch import ModelSpeedup
+from nni.compression.torch import L1FilterPruner, apply_compression_results, ModelSpeedup
 
 torch.manual_seed(0)