Fix integration test on speedup examples (#3945)

docs/en_US/Compression/ModelSpeedup.rst

@@ -37,7 +37,7 @@ Usage
    out = model(dummy_input)
    print('elapsed time: ', time.time() - start)
 
-For complete examples please refer to :githublink:`the code <examples/model_compress/pruning/model_speedup.py>`
+For complete examples please refer to :githublink:`the code <examples/model_compress/pruning/speedup/model_speedup.py>`
 
 NOTE: The current implementation supports PyTorch 1.3.1 or newer.
 
@@ -51,7 +51,7 @@ For PyTorch we can only replace modules, if functions in ``forward`` should be r
 Speedup Results of Examples
 ---------------------------
 
-The code of these experiments can be found :githublink:`here <examples/model_compress/pruning/model_speedup.py>`.
+The code of these experiments can be found :githublink:`here <examples/model_compress/pruning/speedup/model_speedup.py>`.
 
 slim pruner example
 ^^^^^^^^^^^^^^^^^^^

examples/model_compress/pruning/speedup/model_speedup.py

@@ -7,7 +7,7 @@ import torch.nn.functional as F
 from torchvision import datasets, transforms
 
 import sys
-sys.path.append('../../models')
+sys.path.append('../models')
 from cifar10.vgg import VGG
 from mnist.lenet import LeNet
 
@@ -45,7 +45,7 @@ def model_inference(config):
     masks_file = config['masks_file']
     device = torch.device(
         'cuda') if torch.cuda.is_available() else torch.device('cpu')
-        
+
     # device = torch.device(config['device'])
     if config['model_name'] == 'vgg16':
         model = VGG(depth=16)

test/scripts/model_compression.sh

@@ -8,19 +8,19 @@ cd ${CWD}/../examples/model_compress/pruning
 
 echo "testing fpgm pruning and speedup..."
 python3 basic_pruners_torch.py --pruner fpgm --pretrain-epochs 1 --fine-tune-epochs 1 --model vgg16 --dataset cifar10
-python3 model_speedup.py --example_name fpgm
+python3 speedup/model_speedup.py --example_name fpgm
 
 echo "testing slim pruning and speedup..."
 python3 basic_pruners_torch.py --pruner slim --pretrain-epochs 1 --fine-tune-epochs 1 --model vgg19 --dataset cifar10 --sparsity 0.7
-python3 model_speedup.py --example_name slim
+python3 speedup/model_speedup.py --example_name slim
 
 echo "testing l1filter pruning and speedup..."
 python3 basic_pruners_torch.py --pruner l1filter --pretrain-epochs 1 --fine-tune-epochs 1 --model vgg16 --dataset cifar10 --pretrained-model-dir experiment_data/pretrain_cifar10_vgg16.pth
-python3 model_speedup.py --example_name l1filter
+python3 speedup/model_speedup.py --example_name l1filter
 
 echo "testing apoz pruning and speedup..."
 python3 basic_pruners_torch.py --pruner apoz --pretrain-epochs 1 --fine-tune-epochs 1 --model vgg16 --dataset cifar10 --pretrained-model-dir experiment_data/pretrain_cifar10_vgg16.pth
-python3 model_speedup.py --example_name apoz
+python3 speedup/model_speedup.py --example_name apoz
 
 echo 'testing level pruner pruning'
 python3 basic_pruners_torch.py --pruner level --pretrain-epochs 1 --fine-tune-epochs 1 --model lenet --dataset mnist