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docker-compose.test.yml
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version: '2.3'
services:
test-cpu-base:
build:
context: .
dockerfile: Dockerfile.test.cpu
privileged: true
test-cpu-openmpi-py2_7-tf1_1_0-keras2_0_0-torch0_4_0-mxnet1_4_1-pyspark2_1_2:
extends: test-cpu-base
build:
args:
MPI_KIND: OpenMPI
PYTHON_VERSION: 2.7
TENSORFLOW_PACKAGE: tensorflow==1.1.0
KERAS_PACKAGE: keras==2.0.0
PYTORCH_PACKAGE: torch==0.4.0
PYSPARK_PACKAGE: pyspark==2.1.2
test-cpu-openmpi-py3_5-tf1_1_0-keras2_0_0-torch0_4_0-mxnet1_4_1-pyspark2_1_2:
extends: test-cpu-base
build:
args:
MPI_KIND: OpenMPI
PYTHON_VERSION: 3.5
TENSORFLOW_PACKAGE: tensorflow==1.1.0
KERAS_PACKAGE: keras==2.0.0
PYTORCH_PACKAGE: torch==0.4.0
PYSPARK_PACKAGE: pyspark==2.1.2
test-cpu-openmpi-py3_6-tf1_1_0-keras2_0_0-torch0_4_0-mxnet1_4_1-pyspark2_1_2:
extends: test-cpu-base
build:
args:
MPI_KIND: OpenMPI
PYTHON_VERSION: 3.6
TENSORFLOW_PACKAGE: tensorflow==1.1.0
KERAS_PACKAGE: keras==2.0.0
PYTORCH_PACKAGE: torch==0.4.0
PYSPARK_PACKAGE: pyspark==2.1.2
test-cpu-openmpi-py2_7-tf1_6_0-keras2_1_2-torch0_4_1-mxnet1_4_1-pyspark2_3_2:
extends: test-cpu-base
build:
args:
MPI_KIND: OpenMPI
PYTHON_VERSION: 2.7
TENSORFLOW_PACKAGE: tensorflow==1.6.0
KERAS_PACKAGE: keras==2.1.2
PYTORCH_PACKAGE: torch==0.4.1
PYSPARK_PACKAGE: pyspark==2.3.2
test-cpu-openmpi-py3_5-tf1_6_0-keras2_1_2-torch0_4_1-mxnet1_4_1-pyspark2_3_2:
extends: test-cpu-base
build:
args:
MPI_KIND: OpenMPI
PYTHON_VERSION: 3.5
TENSORFLOW_PACKAGE: tensorflow==1.6.0
KERAS_PACKAGE: keras==2.1.2
PYTORCH_PACKAGE: torch==0.4.1
PYSPARK_PACKAGE: pyspark==2.3.2
test-cpu-openmpi-py3_6-tf1_6_0-keras2_1_2-torch0_4_1-mxnet1_4_1-pyspark2_3_2:
extends: test-cpu-base
build:
args:
MPI_KIND: OpenMPI
PYTHON_VERSION: 3.6
TENSORFLOW_PACKAGE: tensorflow==1.6.0
KERAS_PACKAGE: keras==2.1.2
PYTORCH_PACKAGE: torch==0.4.1
PYSPARK_PACKAGE: pyspark==2.3.2
test-cpu-openmpi-py2_7-tf1_12_0-keras2_2_2-torch1_0_0-mxnet1_4_1-pyspark2_4_0:
extends: test-cpu-base
build:
args:
MPI_KIND: OpenMPI
PYTHON_VERSION: 2.7
TENSORFLOW_PACKAGE: tensorflow==1.12.0
KERAS_PACKAGE: keras==2.2.2
PYTORCH_PACKAGE: torch==1.0.0
PYSPARK_PACKAGE: pyspark==2.4.0
test-cpu-openmpi-py3_5-tf1_12_0-keras2_2_2-torch1_0_0-mxnet1_4_1-pyspark2_4_0:
extends: test-cpu-base
build:
args:
MPI_KIND: OpenMPI
PYTHON_VERSION: 3.5
TENSORFLOW_PACKAGE: tensorflow==1.12.0
KERAS_PACKAGE: keras==2.2.2
PYTORCH_PACKAGE: torch==1.0.0
PYSPARK_PACKAGE: pyspark==2.4.0
test-cpu-openmpi-py3_6-tf1_12_0-keras2_2_2-torch1_0_0-mxnet1_4_1-pyspark2_4_0:
extends: test-cpu-base
build:
args:
MPI_KIND: OpenMPI
PYTHON_VERSION: 3.6
TENSORFLOW_PACKAGE: tensorflow==1.12.0
KERAS_PACKAGE: keras==2.2.2
PYTORCH_PACKAGE: torch==1.0.0
PYSPARK_PACKAGE: pyspark==2.4.0
test-cpu-openmpi-py2_7-tfhead-kerashead-torchhead-mxnethead-pyspark2_4_0:
extends: test-cpu-base
build:
args:
MPI_KIND: OpenMPI
PYTHON_VERSION: 2.7
TENSORFLOW_PACKAGE: tf-nightly
KERAS_PACKAGE: git+https://github.com/keras-team/keras.git
PYTORCH_PACKAGE: torch-nightly
TORCHVISION_PACKAGE: torchvision_nightly
PYSPARK_PACKAGE: pyspark==2.4.0
MXNET_PACKAGE: mxnet --pre
test-cpu-openmpi-py3_6-tfhead-kerashead-torchhead-mxnethead-pyspark2_4_0:
extends: test-cpu-base
build:
args:
MPI_KIND: OpenMPI
PYTHON_VERSION: 3.6
TENSORFLOW_PACKAGE: tf-nightly
KERAS_PACKAGE: git+https://github.com/keras-team/keras.git
PYTORCH_PACKAGE: torch-nightly
TORCHVISION_PACKAGE: torchvision_nightly
PYSPARK_PACKAGE: pyspark==2.4.0
MXNET_PACKAGE: mxnet --pre
test-cpu-mpich-py2_7-tf1_12_0-keras2_2_2-torch1_0_0-mxnet1_4_1-pyspark2_4_0:
extends: test-cpu-base
build:
args:
MPI_KIND: MPICH
PYTHON_VERSION: 2.7
TENSORFLOW_PACKAGE: tensorflow==1.12.0
KERAS_PACKAGE: keras==2.2.2
PYTORCH_PACKAGE: torch==1.0.0
PYSPARK_PACKAGE: pyspark==2.4.0
test-cpu-mlsl-py3_6-tf1_12_0-keras2_2_2-torch1_0_0-mxnet1_4_0-pyspark2_4_0:
extends: test-cpu-base
build:
args:
MPI_KIND: MLSL
PYTHON_VERSION: 3.6
TENSORFLOW_PACKAGE: tensorflow==1.12.0
KERAS_PACKAGE: keras==2.2.2
PYTORCH_PACKAGE: torch==1.0.0
PYSPARK_PACKAGE: pyspark==2.4.0
test-gpu-base:
build:
context: .
dockerfile: Dockerfile.test.gpu
runtime: nvidia
# We plumb CUDA_VISIBLE_DEVICES instead of NVIDIA_VISIBLE_DEVICES because
# the latter does not work in privileged mode that we use in the containers.
environment:
- CUDA_VISIBLE_DEVICES
privileged: true
test-gpu-openmpi-py2_7-tf1_6_0-keras2_1_2-torch0_4_1-mxnet1_4_1-pyspark2_3_2:
extends: test-gpu-base
build:
args:
CUDNN_VERSION: 7.0.5.15-1+cuda9.0
MPI_KIND: OpenMPI
PYTHON_VERSION: 2.7
TENSORFLOW_PACKAGE: tensorflow-gpu==1.6.0
KERAS_PACKAGE: keras==2.1.2
PYTORCH_PACKAGE: torch==0.4.1
PYSPARK_PACKAGE: pyspark==2.3.2
test-gpu-openmpi-py3_5-tf1_6_0-keras2_1_2-torch0_4_1-mxnet1_4_1-pyspark2_3_2:
extends: test-gpu-base
build:
args:
CUDNN_VERSION: 7.0.5.15-1+cuda9.0
MPI_KIND: OpenMPI
PYTHON_VERSION: 3.5
TENSORFLOW_PACKAGE: tensorflow-gpu==1.6.0
KERAS_PACKAGE: keras==2.1.2
PYTORCH_PACKAGE: torch==0.4.1
PYSPARK_PACKAGE: pyspark==2.3.2
test-gpu-openmpi-py2_7-tf1_12_0-keras2_2_2-torch1_0_0-mxnet1_4_1-pyspark2_4_0:
extends: test-gpu-base
build:
args:
MPI_KIND: OpenMPI
PYTHON_VERSION: 2.7
TENSORFLOW_PACKAGE: tensorflow-gpu==1.12.0
KERAS_PACKAGE: keras==2.2.2
PYTORCH_PACKAGE: torch==1.0.0
PYSPARK_PACKAGE: pyspark==2.4.0
test-gpu-openmpi-py3_5-tf1_12_0-keras2_2_2-torch1_0_0-mxnet1_4_1-pyspark2_4_0:
extends: test-gpu-base
build:
args:
MPI_KIND: OpenMPI
PYTHON_VERSION: 3.5
TENSORFLOW_PACKAGE: tensorflow-gpu==1.12.0
KERAS_PACKAGE: keras==2.2.2
PYTORCH_PACKAGE: torch==1.0.0
PYSPARK_PACKAGE: pyspark==2.4.0
test-gpu-openmpi-py2_7-tfhead-kerashead-torchhead-mxnethead-pyspark2_4_0:
extends: test-gpu-base
build:
args:
CUDA_DOCKER_VERSION: 10.0-devel-ubuntu16.04
CUDNN_VERSION: 7.4.1.5-1+cuda10.0
NCCL_VERSION_OVERRIDE: 2.3.7-1+cuda10.0
MPI_KIND: OpenMPI
PYTHON_VERSION: 2.7
TENSORFLOW_PACKAGE: tf-nightly-gpu
KERAS_PACKAGE: git+https://github.com/keras-team/keras.git
PYTORCH_PACKAGE: torch-nightly
TORCHVISION_PACKAGE: torchvision_nightly
MXNET_PACKAGE: mxnet-cu100 --pre
PYSPARK_PACKAGE: pyspark==2.4.0
test-gpu-openmpi-py3_6-tfhead-kerashead-torchhead-mxnethead-pyspark2_4_0:
extends: test-gpu-base
build:
args:
CUDA_DOCKER_VERSION: 10.0-devel-ubuntu16.04
CUDNN_VERSION: 7.4.1.5-1+cuda10.0
NCCL_VERSION_OVERRIDE: 2.3.7-1+cuda10.0
MPI_KIND: OpenMPI
PYTHON_VERSION: 3.6
TENSORFLOW_PACKAGE: tf-nightly-gpu
KERAS_PACKAGE: git+https://github.com/keras-team/keras.git
PYTORCH_PACKAGE: torch-nightly
TORCHVISION_PACKAGE: torchvision_nightly
MXNET_PACKAGE: mxnet-cu100 --pre
PYSPARK_PACKAGE: pyspark==2.4.0
test-gpu-mpich-py2_7-tf1_12_0-keras2_2_2-torch1_0_0-mxnet1_4_1-pyspark2_4_0:
extends: test-gpu-base
build:
args:
MPI_KIND: MPICH
PYTHON_VERSION: 2.7
TENSORFLOW_PACKAGE: tensorflow-gpu==1.12.0
KERAS_PACKAGE: keras==2.2.2
PYTORCH_PACKAGE: torch==1.0.0
PYSPARK_PACKAGE: pyspark==2.4.0
test-mixed-openmpi-py2_7-tf1_12_0-keras2_2_2-torch1_0_0-mxnet1_4_1-pyspark2_4_0:
extends: test-gpu-base
build:
args:
MPI_KIND: OpenMPI
PYTHON_VERSION: 2.7
TENSORFLOW_PACKAGE: tensorflow-gpu==1.12.0
KERAS_PACKAGE: keras==2.2.2
PYTORCH_PACKAGE: torch==1.0.0
PYSPARK_PACKAGE: pyspark==2.4.0
HOROVOD_BUILD_FLAGS: ""
HOROVOD_MIXED_INSTALL: 1