Integration test (#3088)

deployment/docker/Dockerfile → Dockerfile

@@ -3,12 +3,15 @@
 
 FROM nvidia/cuda:9.2-cudnn7-runtime-ubuntu18.04
 
+ARG NNI_RELEASE
+
 LABEL maintainer='Microsoft NNI Team<nni@microsoft.com>'
 
 ENV DEBIAN_FRONTEND=noninteractive 
 
-RUN apt-get -y update && \
-    apt-get -y install sudo \
+RUN apt-get -y update
+RUN apt-get -y install \
+    sudo \
     apt-utils \
     git \
     curl \
@@ -26,28 +29,27 @@ RUN apt-get -y update && \
     python3-dev \
     python3-pip \
     python3-tk \
-    libcupti-dev && \
-    apt-get clean && \
-    rm -rf /var/lib/apt/lists/*
+    libcupti-dev
+RUN apt-get clean
+RUN rm -rf /var/lib/apt/lists/*
 
 #
 # generate python script
 #
-RUN cp /usr/bin/python3 /usr/bin/python
+RUN ln -s python3 /usr/bin/python
 
 #
 # update pip
 #
-RUN python3 -m pip install --upgrade pip==20.0.2 setuptools==41.0.0
+RUN python3 -m pip install --upgrade pip==20.2.4 setuptools==50.3.2
 
 # numpy 1.14.3  scipy 1.1.0
-RUN python3 -m pip --no-cache-dir install \
-    numpy==1.14.3 scipy==1.1.0
+RUN python3 -m pip --no-cache-dir install numpy==1.14.3 scipy==1.1.0
 
 #
-# Tensorflow 1.15
+# TensorFlow
 #
-RUN python3 -m pip --no-cache-dir install tensorflow-gpu==1.15.0
+RUN python3 -m pip --no-cache-dir install tensorflow==2.3.1
 
 #
 # Keras 2.1.6
@@ -73,7 +75,8 @@ RUN python3 -m pip --no-cache-dir install pandas==0.23.4 lightgbm==2.2.2
 #
 # Install NNI
 #
-RUN python3 -m pip --no-cache-dir install nni
+COPY dist/nni-${NNI_RELEASE}-py3-none-manylinux1_x86_64.whl .
+RUN python3 -m pip install nni-${NNI_RELEASE}-py3-none-manylinux1_x86_64.whl
 
 #
 # install aml package
@@ -81,7 +84,6 @@ RUN python3 -m pip --no-cache-dir install nni
 RUN python3 -m pip --no-cache-dir install azureml
 RUN python3 -m pip --no-cache-dir install azureml-sdk
 
-
 ENV PATH=/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/root/.local/bin:/usr/bin:/bin:/sbin
 
 WORKDIR /root

examples/model_compress/BNN_quantizer_cifar10.py

@@ -5,7 +5,7 @@ import torch
 import torch.nn as nn
 import torch.nn.functional as F
 from torchvision import datasets, transforms
-from nni.compression.torch import BNNQuantizer
+from nni.algorithms.compression.pytorch.quantization import BNNQuantizer
 
 
 class VGG_Cifar10(nn.Module):

examples/model_compress/DoReFaQuantizer_torch_mnist.py

 import torch
 import torch.nn.functional as F
 from torchvision import datasets, transforms
-from nni.compression.torch import DoReFaQuantizer
+from nni.algorithms.compression.pytorch.quantization import DoReFaQuantizer
 
 
 class Mnist(torch.nn.Module):
@@ -86,4 +86,4 @@ def main():
 
 
 if __name__ == '__main__':
-    main()
\ No newline at end of file
+    main()

examples/model_compress/L1_torch_cifar10.py

@@ -3,7 +3,7 @@ import torch
 import torch.nn as nn
 import torch.nn.functional as F
 from torchvision import datasets, transforms
-from nni.compression.torch import L1FilterPruner
+from nni.algorithms.compression.pytorch.pruning import L1FilterPruner
 from models.cifar10.vgg import VGG
 
 

examples/model_compress/QAT_torch_quantizer.py

 import torch
 import torch.nn.functional as F
 from torchvision import datasets, transforms
-from nni.compression.torch import QAT_Quantizer
+from nni.algorithms.compression.pytorch.quantization import QAT_Quantizer
 
 
 class Mnist(torch.nn.Module):

examples/model_compress/amc/amc_search.py

@@ -8,7 +8,7 @@ import time
 import torch
 import torch.nn as nn
 from torchvision.models import resnet
-from nni.compression.torch import AMCPruner
+from nni.algorithms.compression.pytorch.pruning import AMCPruner
 from data import get_split_dataset
 from utils import AverageMeter, accuracy
 

examples/model_compress/amc/amc_train.py

@@ -15,9 +15,9 @@ import torch.optim as optim
 from tensorboardX import SummaryWriter
 from torchvision.models import resnet
 
-from nni.compression.torch.pruning.amc.lib.net_measure import measure_model
-from nni.compression.torch.pruning.amc.lib.utils import get_output_folder
-from nni.compression.torch import ModelSpeedup
+from nni.algorithms.compression.pytorch.pruning.amc.lib.net_measure import measure_model
+from nni.algorithms.compression.pytorch.pruning.amc.lib.utils import get_output_folder
+from nni.compression.pytorch import ModelSpeedup
 
 from data import get_dataset
 from utils import AverageMeter, accuracy, progress_bar

examples/model_compress/auto_pruners_torch.py

@@ -14,10 +14,10 @@ from torchvision import datasets, transforms
 from models.mnist.lenet import LeNet
 from models.cifar10.vgg import VGG
 from models.cifar10.resnet import ResNet18, ResNet50
-from nni.compression.torch import L1FilterPruner, L2FilterPruner, FPGMPruner
-from nni.compression.torch import SimulatedAnnealingPruner, ADMMPruner, NetAdaptPruner, AutoCompressPruner
-from nni.compression.torch import ModelSpeedup
-from nni.compression.torch.utils.counter import count_flops_params
+from nni.algorithms.compression.pytorch.pruning import L1FilterPruner, L2FilterPruner, FPGMPruner
+from nni.algorithms.compression.pytorch.pruning import SimulatedAnnealingPruner, ADMMPruner, NetAdaptPruner, AutoCompressPruner
+from nni.compression.pytorch import ModelSpeedup
+from nni.compression.pytorch.utils.counter import count_flops_params
 
 
 def get_data(dataset, data_dir, batch_size, test_batch_size):

examples/model_compress/lottery_torch_mnist_fc.py

@@ -6,7 +6,7 @@ import torch.nn.functional as F
 import torch.utils.data
 import torchvision.datasets as datasets
 import torchvision.transforms as transforms
-from nni.compression.torch import LotteryTicketPruner
+from nni.algorithms.compression.pytorch.pruning import LotteryTicketPruner
 
 class fc1(nn.Module):
 

examples/model_compress/model_prune_torch.py

@@ -9,8 +9,16 @@ from torchvision import datasets, transforms
 
 from models.cifar10.vgg import VGG
 import nni
-from nni.compression.torch import LevelPruner, SlimPruner, FPGMPruner, L1FilterPruner, \
-    L2FilterPruner, AGPPruner, ActivationMeanRankFilterPruner, ActivationAPoZRankFilterPruner
+from nni.algorithms.compression.pytorch.pruning import (
+    LevelPruner,
+    SlimPruner,
+    FPGMPruner,
+    L1FilterPruner,
+    L2FilterPruner,
+    AGPPruner,
+    ActivationMeanRankFilterPruner,
+    ActivationAPoZRankFilterPruner
+)
 
 prune_config = {
     'level': {