Slide from Google : http://files.informatandm.com/uploads/2019/5/Apr_18_Dan_Lorenc_The_Future_of_Cloud_Native_CI_CD.pdf Blog IBM : https://developer.ibm.com/tutorials/knative-build-app-development-with-tekton/
https://openshift.github.io/pipelines-docs/docs/docs/index.html
OpenShift Pipelines are cloud-native, continuous integration and delivery solutions based on Kubernetes resources. It uses Tekton Pipelines.
https://github.com/openshift/pipelines-tutorial
Install via OperatorHub
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Starting local Bazel server and connecting to it... | |
{ "source_HEAD": "1c83755e5a1269b528042e6d318d66e363ffc349", "source_remote_origin": "https://github.com/tensorflow/tensorflow.git", "OS_VER": "CentOS release 6.10 (Final)", "GLIBC_VER": "ldd (GNU libc) 2.12", "PIP_VER": "pip 19.2.3 from /opt/rh/rh-python36/root/usr/lib/python3.6/site-packages/pip (python 3.6)", "PROTOC_VER": "libprotoc 2.3.0", "LOGICAL_CPUS": "64", "CORES_PER_PCPU": " 16", "PHYSICAL_CPUS": "2", "GCC_VER": "gcc (GCC) 8.2.1 20180905 (Red Hat 8.2.1-3)", "OS": "Linux", "kernel": "3.10.0-1058.el7.x86_64", "architecture": "broadwell", "processor": "Intel(R) Xeon(R) CPU E5-2697A v4 @ 2.60GHz", "Bazel_version": "Build label: 0.24.1- (@non-git)", "Java_version": "1.8.0_222", "Python_version": "3.6.3", "gpp_version": "g++ (GCC) 8.2.1 20180905 (Red Hat 8.2.1-3)", "swig_version": "", "NVIDIA_driver_version": "", "CUDA_device_count": "", "CUDA_device_names": "", "CUDA_toolkit_version": "V10.0.130", "GCC_FLAGS": "-march=broadwell -mmmx -msse -msse2 -mss |
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{ "source_HEAD": "1c83755e5a1269b528042e6d318d66e363ffc349", "source_remote_origin": "https://github.com/tensorflow/tensorflow.git", "OS_VER": "CentOS release 6.10 (Final)", "GLIBC_VER": "ldd (GNU libc) 2.12", "PIP_VER": "pip 19.2.3 from /opt/rh/rh-python36/root/usr/lib/python3.6/site-packages/pip (python 3.6)", "PROTOC_VER": "libprotoc 2.3.0", "LOGICAL_CPUS": "64", "CORES_PER_PCPU": " 16", "PHYSICAL_CPUS": "2", "GCC_VER": "gcc (GCC) 8.2.1 20180905 (Red Hat 8.2.1-3)", "OS": "Linux", "kernel": "3.10.0-1058.el7.x86_64", "architecture": "broadwell", "processor": "Intel(R) Xeon(R) CPU E5-2697A v4 @ 2.60GHz", "Bazel_version": "Build label: 0.24.1- (@non-git)", "Java_version": "1.8.0_222", "Python_version": "3.6.3", "gpp_version": "g++ (GCC) 8.2.1 20180905 (Red Hat 8.2.1-3)", "swig_version": "", "NVIDIA_driver_version": "", "CUDA_device_count": "", "CUDA_device_names": "", "CUDA_toolkit_version": "V10.0.130", "GCC_FLAGS": "-march=broadwell -mmmx -msse -msse2 -msse3 -mssse3 -mcx16 -msahf -mmovbe -maes -mpclmul -mpop |
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rm -fr /usr/bin/python | |
ln -s /usr/bin/python2.6 /usr/bin/python | |
export PYTHON_LIB_PATH=/usr/lib64/python2.6/site-packages | |
python -V | |
yum install devtoolset-8 prelink mlocate -y | |
export DEV_TOOLSET_VERSION=8 | |
export JAVA_HOME=/usr/lib/jvm/java-1.8.0-openjdk-1.8.0.222.b10-0.el6_10.x86_64 | |
export CUSTOM_BUILD='bazel build -c opt --config=cuda --cxxopt="-D_GLIBCXX_USE_CXX11_ABI=0" --verbose_failures //tensorflow/tools/pip_package:build_pip_package' |
Following steps work for F29 for F31 look here
cat /etc/redhat-release
Fedora release 29 (Twenty Nine)
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docker run -it aicoe/tf-in-container:1.13.1-centos7 /bin/bash | |
[root@11174edc6cf7 /]# | |
[root@11174edc6cf7 /]# pip install ^C | |
[root@11174edc6cf7 /]# python -V | |
Python 2.7.5 | |
[root@11174edc6cf7 /]# scl enable rh-python36 | |
Need at least 3 arguments. | |
Run scl --help to get help. | |
[root@11174edc6cf7 /]# scl enable rh-python36 bash | |
[root@11174edc6cf7 /]# python -V |
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git checkout remotes/origin/v0.5-branch | |
cd components/tensorflow-notebook-image | |
./build_image.sh ./Dockerfile submod/tensorflow-1.13.1-notebook-cpu v0.5.0 ./versions/1.13.1/version-config.json | |
./build_image.sh ./Dockerfile submod/tensorflow-1.13.1-notebook-cpu v0.5.0 ./versions/1.13.1/version-config.json | |
+ DOCKERFILE=./Dockerfile | |
++ dirname ./Dockerfile | |
+ CONTEXT_DIR=. | |
+ IMAGE=submod/tensorflow-1.13.1-notebook-cpu | |
+ TAG=v0.5.0 | |
+ CONFIG_FILE=./versions/1.13.1/version-config.json |
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tensorflow/core/kernels/unary_ops_composition.cc:432:1: required from here | |
tensorflow/core/kernels/unary_ops_composition.cc:140:20: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits<float>::type {aka __vector(4) float}' [-Wignored-attributes] | |
INFO: From Compiling tensorflow/core/distributed_runtime/worker_session.cc [for host]: | |
In file included from ./tensorflow/core/platform/default/logging.h:24:0, | |
from ./tensorflow/core/platform/logging.h:25, | |
from ./tensorflow/core/framework/allocator.h:28, | |
from ./tensorflow/core/common_runtime/device.h:35, | |
from ./tensorflow/core/common_runtime/device_mgr.h:25, | |
from ./tensorflow/core/distributed_runtime/worker_session.h:21, | |
from tensorflow/core/distributed_runtime/worker_session.cc:15: |
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gcc version 7.3.1 20180303 (Red Hat 7.3.1-5) (GCC) | |
https://bugzilla.redhat.com/show_bug.cgi?id=1570308 | |
external/eigen_archive/unsupported/Eigen/CXX11/src/Tensor/TensorDevice.h:35:62: required from 'Eigen::TensorDevice<ExpressionType, DeviceType>& Eigen::TensorDevice<ExpressionType, DeviceType>::operator=(const OtherDerived&) [with OtherDerived = Eigen::TensorMirrorPadOp<Eigen::array<Eigen::IndexPair<int>, 4>, const Eigen::TensorMap<Eigen::Tensor<const double, 4, 1, int>, 16, Eigen::MakePointer> >; ExpressionType = Eigen::TensorMap<Eigen::Tensor<double, 4, 1, int>, 16, Eigen::MakePointer>; DeviceType = Eigen::ThreadPoolDevice]' | |
./tensorflow/core/kernels/mirror_pad_op.h:351:27: required from 'void tensorflow::functor::MirrorPad<Device, T, Tpaddings, Dims>::operator()(const Device&, typename tensorflow::TTypes<T, Dims, int>::Tensor, typename tensorflow::TTypes<T, Dims, int>::ConstTensor, typename tensorflow::TTypes<Tpaddings>::ConstMatrix, int) [with Device = Eigen::ThreadPoolDevice; T = double; Tpaddin |