forked from horovod/horovod
-
Notifications
You must be signed in to change notification settings - Fork 2
/
Dockerfile.test.cpu
270 lines (231 loc) · 13.4 KB
/
Dockerfile.test.cpu
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
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
ARG UBUNTU_VERSION=20.04
FROM ubuntu:${UBUNTU_VERSION}
# Arguments for the build. UBUNTU_VERSION needs to be repeated because
# the first usage only applies to the FROM tag.
ARG UBUNTU_VERSION=20.04
ARG MPI_KIND=OpenMPI
ARG PYTHON_VERSION=3.6
ARG GPP_VERSION=7
# NOTE: keep versions in sync with setup.py extras_require{'dev'}:
ARG TENSORFLOW_PACKAGE=tensorflow-cpu==1.15.0
ARG KERAS_PACKAGE=keras==2.2.4
ARG PYTORCH_PACKAGE=torch==1.2.0+cpu
ARG PYTORCH_LIGHTNING_PACKAGE=pytorch_lightning==0.7.6
ARG TORCHVISION_PACKAGE=torchvision==0.4.0+cpu
ARG MXNET_PACKAGE=mxnet==1.5.0
ARG PYSPARK_PACKAGE=pyspark==2.4.7
# if SPARK_PACKAGE is set, installs Spark into /spark from the tgz archive
# if SPARK_PACKAGE is a preview version, installs PySpark from the tgz archive
# see https://archive.apache.org/dist/spark/ for available packages, version must match PYSPARK_PACKAGE
ARG SPARK_PACKAGE=spark-2.4.7/spark-2.4.7-bin-hadoop2.7.tgz
ARG CCL_PACKAGE=master
ARG HOROVOD_BUILD_FLAGS=""
# to avoid interaction with apt-get
ENV DEBIAN_FRONTEND=noninteractive
# Set default shell to /bin/bash
SHELL ["/bin/bash", "-euo", "pipefail", "-c"]
# Prepare to install specific g++ versions
RUN apt-get update -qq && apt-get install -y --no-install-recommends software-properties-common
RUN add-apt-repository ppa:ubuntu-toolchain-r/test
# Install essential packages.
RUN apt-get update -qq && apt-get install -y --no-install-recommends \
wget \
ca-certificates \
cmake \
openssh-client \
openssh-server \
git \
build-essential \
g++-${GPP_VERSION} \
moreutils
# setup ssh service
RUN ssh-keygen -f /root/.ssh/id_rsa -q -N ''
RUN cp -v /root/.ssh/id_rsa.pub /root/.ssh/authorized_keys
# Install Python.
RUN apt-get update -qq && apt-get install -y python${PYTHON_VERSION} python${PYTHON_VERSION}-dev python${PYTHON_VERSION}-distutils
RUN ln -s -f /usr/bin/python${PYTHON_VERSION} /usr/bin/python
RUN ln -s -f /usr/bin/python${PYTHON_VERSION} /usr/bin/python${PYTHON_VERSION/%.*/}
RUN wget --progress=dot:mega https://bootstrap.pypa.io/get-pip.py && python get-pip.py && rm get-pip.py
# pinning pip to 21.0.0 as 22.0.0 cannot fetch pytorch packages from html linl
# https://github.com/pytorch/pytorch/issues/72045
RUN pip install --no-cache-dir -U --force pip~=21.0.0 setuptools requests pytest mock pytest-forked parameterized
# Add launch helper scripts
RUN echo "env SPARK_HOME=/spark SPARK_DRIVER_MEM=512m PYSPARK_PYTHON=/usr/bin/python${PYTHON_VERSION} PYSPARK_DRIVER_PYTHON=/usr/bin/python${PYTHON_VERSION} \"\$@\"" > /spark_env.sh
RUN echo /spark_env.sh pytest -v --capture=no --continue-on-collection-errors --junit-xml=/artifacts/junit.\$1.\${HOROVOD_RANK:-\${OMPI_COMM_WORLD_RANK:-\${PMI_RANK}}}.\$2.xml \${@:2} > /pytest.sh
RUN echo /spark_env.sh pytest -v --capture=no --continue-on-collection-errors --junit-xml=/artifacts/junit.\$1.standalone.\$2.xml --forked \${@:2} > /pytest_standalone.sh
RUN chmod a+x /spark_env.sh
RUN chmod a+x /pytest.sh
RUN chmod a+x /pytest_standalone.sh
# Install Spark stand-alone cluster.
RUN if [[ -n ${SPARK_PACKAGE} ]]; then \
wget --progress=dot:giga "https://www.apache.org/dyn/closer.lua/spark/${SPARK_PACKAGE}?action=download" -O - | tar -xzC /tmp; \
archive=$(basename "${SPARK_PACKAGE}") bash -c "mv -v /tmp/\${archive/%.tgz/} /spark"; \
fi
# Install PySpark.
RUN apt-get update -qq && apt install -y openjdk-8-jdk-headless
RUN if [[ ${SPARK_PACKAGE} != *"-preview"* ]]; then \
pip install --no-cache-dir ${PYSPARK_PACKAGE}; \
else \
apt-get update -qq && apt-get install pandoc; \
pip install --no-cache-dir pypandoc; \
(cd /spark/python && python setup.py sdist && pip install --no-cache-dir dist/pyspark-*.tar.gz && rm dist/pyspark-*); \
fi
# Pin cloudpickle to 1.3.0
# Dill breaks clouldpickle > 1.3.0 when using Spark2
# https://github.com/cloudpipe/cloudpickle/issues/393
RUN if [[ ${PYSPARK_PACKAGE} == "pyspark==2."* ]]; then \
pip install --no-cache-dir cloudpickle==1.3.0; \
fi
# Install Ray.
# Updating to 1.7.0 to pass ray tests
RUN pip install --no-cache-dir ray==1.7.0
# Install MPI.
RUN if [[ ${MPI_KIND} == "OpenMPI" ]]; then \
wget --progress=dot:mega -O /tmp/openmpi-3.0.0-bin.tar.gz https://github.com/horovod/horovod/files/1596799/openmpi-3.0.0-bin.tar.gz && \
cd /usr/local && tar -zxf /tmp/openmpi-3.0.0-bin.tar.gz && ldconfig && \
echo "mpirun -allow-run-as-root -np 2 -H localhost:2 -bind-to none -map-by slot -mca mpi_abort_print_stack 1" > /mpirun_command; \
elif [[ ${MPI_KIND} == "ONECCL" ]]; then \
wget --progress=dot:mega -O /tmp/oneccl.tar.gz https://github.com/oneapi-src/oneCCL/archive/${CCL_PACKAGE}.tar.gz && \
cd /tmp && tar -zxf oneccl.tar.gz && \
mkdir oneCCL-${CCL_PACKAGE}/build && cd oneCCL-${CCL_PACKAGE}/build && cmake .. -DCMAKE_INSTALL_PREFIX=/usr/local/oneccl -DCMAKE_BUILD_TYPE=Release && make -j install && \
rm /tmp/oneccl.tar.gz && rm -Rf /tmp/oneCCL-${CCL_PACKAGE} && \
sed -i 's/if \[ -z \"\${I_MPI_ROOT}\" \]/if [ -z \"${I_MPI_ROOT:-}\" ]/g' /usr/local/oneccl/env/setvars.sh && \
sed -i 's/ \$1/ \${1:-}/g' /usr/local/oneccl/env/setvars.sh && \
echo ". /usr/local/oneccl/env/setvars.sh" > /oneccl_env && \
chmod +x /oneccl_env && \
echo "export CCL_ATL_TRANSPORT=ofi; \
export HOROVOD_CCL_CACHE=1; \
echo \"\$(env)\"; \
echo \"mpirun is \$(which mpirun)\"; \
echo \"LD_LIBRARY_PATH is \$(echo \$LD_LIBRARY_PATH)\"; \
echo \"oneCCL links with \$(ldd /usr/local/oneccl/lib/libccl.so)\"; \
mpirun -np 2 -hosts localhost \$@" > /mpirun_command_ofi && \
chmod +x /mpirun_command_ofi && \
cp /mpirun_command_ofi /mpirun_command_mpi && \
sed -i 's/export CCL_ATL_TRANSPORT=ofi;/export CCL_ATL_TRANSPORT=mpi;/g' /mpirun_command_mpi && \
sed -i 's/export HOROVOD_CCL_CACHE=1;/export HOROVOD_CCL_CACHE=0;/g' /mpirun_command_mpi && \
echo "/mpirun_command_mpi" > /mpirun_command && \
echo "-L/usr/local/oneccl/lib -lmpi -I/usr/local/oneccl/include" > /mpicc_oneccl && \
chmod +x /mpicc_oneccl; \
elif [[ ${MPI_KIND} == "MPICH" ]]; then \
apt-get update -qq && apt-get install -y mpich && \
echo "mpirun -np 2" > /mpirun_command; \
fi
# Install mpi4py.
# This requires SETUPTOOLS_USE_DISTUTILS=stdlib as with setuptools>=60.1.0 installing mpi4py broke
# https://github.com/mpi4py/mpi4py/issues/157#issuecomment-1001022274
RUN if [[ ${MPI_KIND} != "None" ]]; then \
if [[ ${MPI_KIND} == "ONECCL" ]]; then \
export I_MPI_ROOT=/usr/local/oneccl; \
export MPICC=/usr/local/oneccl/bin/mpicc; \
fi; \
SETUPTOOLS_USE_DISTUTILS=stdlib pip install --no-cache-dir mpi4py; \
fi
# Install TensorFlow and Keras (releases).
# Pin scipy!=1.4.0: https://github.com/scipy/scipy/issues/11237
RUN if [[ ${TENSORFLOW_PACKAGE} != "tf-nightly" ]]; then \
pip install --no-cache-dir ${TENSORFLOW_PACKAGE}; \
if [[ ${KERAS_PACKAGE} != "None" ]]; then \
pip uninstall -y keras-nightly; \
pip install --no-cache-dir ${KERAS_PACKAGE} "scipy!=1.4.0" "pandas<1.1.0"; \
fi; \
mkdir -p ~/.keras; \
python -c "import tensorflow as tf; tf.keras.datasets.mnist.load_data()"; \
fi
# Pin h5py < 3 for tensorflow: https://github.com/tensorflow/tensorflow/issues/44467
RUN pip install 'h5py<3.0' --force-reinstall
# Install PyTorch (releases).
# Pin Pillow<7.0 for torchvision < 0.5.0: https://github.com/pytorch/vision/issues/1718
# Pin Pillow!=8.3.0 for torchvision: https://github.com/pytorch/vision/issues/4146
RUN if [[ ${PYTORCH_PACKAGE} != "torch-nightly" ]]; then \
pip install --no-cache-dir ${PYTORCH_PACKAGE} ${TORCHVISION_PACKAGE} -f https://download.pytorch.org/whl/torch_stable.html; \
if [[ "${TORCHVISION_PACKAGE/%+*/}" == torchvision==0.[1234].* ]]; then \
pip install --no-cache-dir "Pillow<7.0" --no-deps; \
else \
pip install --no-cache-dir "Pillow!=8.3.0" --no-deps; \
fi; \
fi
RUN pip install ${PYTORCH_LIGHTNING_PACKAGE}
# Install MXNet (releases).
RUN if [[ ${MXNET_PACKAGE} != "mxnet-nightly" ]]; then \
pip install --no-cache-dir ${MXNET_PACKAGE} ; \
fi
# Prefetch Spark MNIST dataset.
RUN mkdir -p /work
RUN mkdir -p /data && wget --progress=dot:mega https://horovod-datasets.s3.amazonaws.com/mnist.bz2 -O /data/mnist.bz2
# Prefetch Spark Rossmann dataset.
RUN mkdir -p /work
RUN mkdir -p /data && wget --progress=dot:mega https://horovod-datasets.s3.amazonaws.com/rossmann.tgz -O - | tar -xzC /data
# Prefetch PyTorch datasets.
RUN wget --progress=dot:mega https://horovod-datasets.s3.amazonaws.com/pytorch_datasets.tgz -O - | tar -xzC /data
### END OF CACHE ###
COPY . /horovod
# Install nightly packages here so they do not get cached
# Install TensorFlow and Keras (nightly).
# Pin scipy!=1.4.0: https://github.com/scipy/scipy/issues/11237
RUN if [[ ${TENSORFLOW_PACKAGE} == "tf-nightly" ]]; then \
pip install --no-cache-dir ${TENSORFLOW_PACKAGE}; \
if [[ ${KERAS_PACKAGE} != "None" ]]; then \
pip uninstall -y keras-nightly; \
pip install --no-cache-dir ${KERAS_PACKAGE} "scipy!=1.4.0" "pandas<1.1.0"; \
fi; \
mkdir -p ~/.keras; \
python -c "import tensorflow as tf; tf.keras.datasets.mnist.load_data()"; \
fi
# Install PyTorch (nightly).
# Pin Pillow!=8.3.0 for torchvision: https://github.com/pytorch/vision/issues/4146
RUN if [[ ${PYTORCH_PACKAGE} == "torch-nightly" ]]; then \
pip install --no-cache-dir --pre torch ${TORCHVISION_PACKAGE} -f https://download.pytorch.org/whl/nightly/cpu/torch_nightly.html; \
pip install --no-cache-dir "Pillow!=8.3.0" --no-deps; \
fi
# Install MXNet (nightly).
RUN if [[ ${MXNET_PACKAGE} == "mxnet-nightly" ]]; then \
pip install --no-cache-dir --pre mxnet -f https://dist.mxnet.io/python/all; \
fi
# Install Horovod.
RUN if [[ ${MPI_KIND} == "ONECCL" ]]; then \
if [ -z "${LD_LIBRARY_PATH:-}" ]; then \
export LD_LIBRARY_PATH=""; \
fi; \
if [ -z "${PYTHONPATH:-}" ]; then \
export PYTHONPATH=""; \
fi; \
. /usr/local/oneccl/env/setvars.sh; \
export I_MPI_ROOT=/usr/local/oneccl; \
echo "horovod python setup.py sdist, mpicxx is $(which mpicxx)"; \
fi; \
cd /horovod && \
python setup.py sdist && \
bash -c "${HOROVOD_BUILD_FLAGS} HOROVOD_WITH_TENSORFLOW=1 HOROVOD_WITH_PYTORCH=1 HOROVOD_WITH_MXNET=1 pip install --no-cache-dir -v $(ls /horovod/dist/horovod-*.tar.gz)[spark,ray]"
# Show the effective python package version to easily spot version differences
RUN pip freeze | sort
# Hack for compatibility of MNIST example with TensorFlow 1.1.0.
RUN if [[ ${TENSORFLOW_PACKAGE} == "tensorflow==1.1.0" ]]; then \
sed -i "s/from tensorflow import keras/from tensorflow.contrib import keras/" /horovod/examples/tensorflow/tensorflow_mnist.py; \
fi
# Hack TensorFlow MNIST example to be smaller.
RUN sed -i "s/last_step=20000/last_step=100/" /horovod/examples/tensorflow/tensorflow_mnist.py
# Hack TensorFlow Eager MNIST example to be smaller.
RUN sed -i "s/dataset.take(20000/dataset.take(100/" /horovod/examples/tensorflow/tensorflow_mnist_eager.py
# Hack TensorFlow 2.0 example to be smaller.
RUN sed -i "s/dataset.take(10000/dataset.take(100/" /horovod/examples/tensorflow2/tensorflow2_mnist.py
# Hack Keras MNIST advanced example to be smaller.
RUN sed -i "s/'--epochs', type=int, default=24,/'--epochs', type=int, default=9,/" /horovod/examples/keras/keras_mnist_advanced.py
RUN sed -i "s/model.add(Conv2D(32, kernel_size=(3, 3),/model.add(Conv2D(1, kernel_size=(3, 3),/" /horovod/examples/keras/keras_mnist_advanced.py
RUN sed -i "s/model.add(Conv2D(64, (3, 3), activation='relu'))//" /horovod/examples/keras/keras_mnist_advanced.py
# Hack TensorFlow 2.0 Keras MNIST advanced example to be smaller.
RUN sed -i "s/epochs=24/epochs=9/" /horovod/examples/tensorflow2/tensorflow2_keras_mnist.py
RUN sed -i "s/tf.keras.layers.Conv2D(32, \\[3, 3\\],/tf.keras.layers.Conv2D(1, [3, 3],/" /horovod/examples/tensorflow2/tensorflow2_keras_mnist.py
RUN sed -i -E "s/\s+tf.keras.layers.Conv2D\(64, \\[3, 3\\], activation='relu'\),//" /horovod/examples/tensorflow2/tensorflow2_keras_mnist.py
# Hack PyTorch MNIST example to be smaller.
RUN sed -i "s/'--epochs', type=int, default=10,/'--epochs', type=int, default=2,/" /horovod/examples/pytorch/pytorch_mnist.py
RUN sed -i "s/self.fc1 = nn.Linear(320, 50)/self.fc1 = nn.Linear(784, 50)/" /horovod/examples/pytorch/pytorch_mnist.py
RUN sed -i "s/x = F.relu(F.max_pool2d(self.conv1(x), 2))//" /horovod/examples/pytorch/pytorch_mnist.py
RUN sed -i "s/x = F.relu(F.max_pool2d(self.conv2_drop(self.conv2(x)), 2))//" /horovod/examples/pytorch/pytorch_mnist.py
RUN sed -i "s/x = x.view(-1, 320)/x = x.view(-1, 784)/" /horovod/examples/pytorch/pytorch_mnist.py
# Hack Keras Spark Rossmann Run example to be smaller.
RUN sed -i "s/x = Dense(1000,/x = Dense(100,/g" /horovod/examples/spark/keras/keras_spark_rossmann_run.py
RUN sed -i "s/x = Dense(500,/x = Dense(50,/g" /horovod/examples/spark/keras/keras_spark_rossmann_run.py
# Hack Keras Spark Rossmann Estimator example to be smaller.
RUN sed -i "s/x = Dense(1000,/x = Dense(100,/g" /horovod/examples/spark/keras/keras_spark_rossmann_estimator.py
RUN sed -i "s/x = Dense(500,/x = Dense(50,/g" /horovod/examples/spark/keras/keras_spark_rossmann_estimator.py