forked from goodfeli/cleverhans
-
Notifications
You must be signed in to change notification settings - Fork 0
/
.travis.yml
92 lines (86 loc) · 4.08 KB
/
.travis.yml
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
# adapted from https://github.com/fchollet/keras/blob/master/.travis.yml
sudo: required
dist: trusty
language: python
python:
- 2.7
- 3.5
env:
- KERAS_BACKEND=tensorflow TENSORFLOW_V=1.8.0 PYTORCH=False
- KERAS_BACKEND=tensorflow TENSORFLOW_V=1.9.0 PYTORCH=False
- KERAS_BACKEND=tensorflow TENSORFLOW_V=1.9.0 PYTORCH=True
install:
# code below is taken from http://conda.pydata.org/docs/travis.html
# We do this conditionally because it saves us some downloading if the
# version is the same.
- if [[ "$TRAVIS_PYTHON_VERSION" == "2.7" ]]; then
wget https://repo.continuum.io/miniconda/Miniconda-latest-Linux-x86_64.sh -O miniconda.sh;
else
wget https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh -O miniconda.sh;
fi
- bash miniconda.sh -b -p $HOME/miniconda
- export PATH="$HOME/miniconda/bin:$PATH"
- hash -r
- conda config --set always_yes yes --set changeps1 no
- conda update -q conda
# Useful for debugging any issues with conda
- conda info -a
- conda create -q -n test-environment python=$TRAVIS_PYTHON_VERSION numpy scipy pyqt=4.11 matplotlib pandas h5py six mkl-service
- source activate test-environment
# install TensorFlow
- if [[ "$TRAVIS_PYTHON_VERSION" == "2.7" && "$TENSORFLOW_V" == "1.8.0" ]]; then
pip install https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.8.0-cp27-none-linux_x86_64.whl;
elif [[ "$TRAVIS_PYTHON_VERSION" == "2.7" && "$TENSORFLOW_V" == "1.9.0" ]]; then
pip install https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.9.0-cp27-none-linux_x86_64.whl;
elif [[ "$TRAVIS_PYTHON_VERSION" == "3.5" && "$TENSORFLOW_V" == "1.8.0" ]]; then
pip install https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.8.0-cp35-cp35m-linux_x86_64.whl;
elif [[ "$TRAVIS_PYTHON_VERSION" == "3.5" && "$TENSORFLOW_V" == "1.9.0" ]]; then
pip install https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.9.0-cp35-cp35m-linux_x86_64.whl;
fi
- time pip install -q -e ".[test]"
- if [[ "$PYTORCH" == True ]]; then
pip install torch==0.4.0 torchvision==0.2.1 -q;
fi
# workaround for version incompatibility between the scipy version in conda
# and the system-provided /usr/lib/x86_64-linux-gnu/libstdc++.so.6
# by installing a conda-provided libgcc and adding it to the load path
- conda install libgcc
- export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/home/travis/miniconda/envs/test-environment/lib
# install serialization dependencies
- pip install joblib
# install dependencies for adversarial competition eval infra tests
- pip install google-cloud==0.33.1
- pip install Pillow
# Style checks
- pip install pylint
# To be able to exclude subdirectories in nose tests
- pip install nose-exclude
# command to run tests
script:
# exit on first error
- set -e
# run keras backend init to initialize backend config
- python -c "import keras.backend"
# create dataset directory to avoid concurrent directory creation at runtime
- mkdir ~/.keras/datasets
# set up keras backend
- sed -i -e 's/"backend":[[:space:]]*"[^"]*/"backend":\ "'$KERAS_BACKEND'/g' ~/.keras/keras.json;
- echo -e "Running tests with the following config:\n$(cat ~/.keras/keras.json)"
# test for evaluation infrastructure are very fast, so running them first
- nosetests -v --nologcapture -w examples/nips17_adversarial_competition/eval_infra/code/ eval_lib/tests/
#
# --nologcapture: avoids a large amount of unnecessary tensorflow output
# --stop: stop on first error. Gives feedback from travis faster
#
# Tests for certification code require Tensorflow 1.9 or higher,
# thus skipping these tests for lower version of Tensorflow.
- if [[ "$PYTORCH" == True ]]; then
nosetests --nologcapture -v --stop tests_pytorch;
elif [[ "$PYTORCH" == False ]]; then
if [[ "$TENSORFLOW_V" == "1.8.0" ]]; then
nosetests -v --nologcapture --stop --exclude-dir=cleverhans/experimental/certification cleverhans;
else
nosetests -v --nologcapture --stop cleverhans;
fi;
nosetests --nologcapture -v --stop tests_tf;
fi