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settings.sh
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settings.sh
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#!/usr/bin/env bash
# Copyright 2017 Google Inc.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions
# are met:
#
# 1. Redistributions of source code must retain the above copyright notice,
# this list of conditions and the following disclaimer.
#
# 2. Redistributions in binary form must reproduce the above copyright
# notice, this list of conditions and the following disclaimer in the
# documentation and/or other materials provided with the distribution.
#
# 3. Neither the name of the copyright holder nor the names of its
# contributors may be used to endorse or promote products derived from this
# software without specific prior written permission.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
# ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE
# LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
# CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
# SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
# INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
# CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
# ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
# POSSIBILITY OF SUCH DAMAGE.
# Source this file---these options are needed for TF config and for
# successive bazel runs.
# Set this to 1 if the system image already has TensorFlow preinstalled. This
# will skip the installation of TensorFlow.
export DV_USE_PREINSTALLED_TF="${DV_USE_PREINSTALLED_TF:-0}"
export TF_CUDA_CLANG=0
export TF_ENABLE_XLA=0
export TF_NEED_CUDA=0
export TF_NEED_GCP=1
export TF_NEED_GDR=0
export TF_NEED_HDFS=0
export TF_NEED_JEMALLOC=0
export TF_NEED_MKL=0
export TF_NEED_MPI=0
export TF_NEED_OPENCL=0
export TF_NEED_OPENCL_SYCL=0
export TF_NEED_S3=0
export TF_NEED_VERBS=0
# Used if TF_NEED_CUDA=1
export TF_CUDA_VERSION="8.0"
export CUDA_TOOLKIT_PATH="/usr/local/cuda"
export TF_CUDNN_VERSION="6"
export CUDNN_INSTALL_PATH="/usr/lib/x86_64-linux-gnu"
# The version of bazel we want to build DeepVariant.
DV_BAZEL_VERSION="0.15.0"
# Path to the public bucket containing DeepVariant-related artifacts.
export DEEPVARIANT_BUCKET="gs://deepvariant"
export DV_PACKAGE_BUCKET_PATH="${DEEPVARIANT_BUCKET}/packages"
export DV_PACKAGE_CURL_PATH="https://storage.googleapis.com/deepvariant/packages"
# Set this to 1 to use the nightly (latest) build of TensorFlow instead of a
# named release version. Set it to an already existing value in the environment
# (allowing command line control of the build), defaulting to 0 (release build).
# Note that setting this to 1 implies that the C++ code in DeepVariant will be
# build using the master branch and not the pinned version to avoid
# incompatibilities between TensorFlow C++ used to build DeepVariant and the
# tf-nightly wheel.
export DV_TF_NIGHTLY_BUILD="${DV_TF_NIGHTLY_BUILD:-0}"
# The branch/tag we checkout to build our C++ dependencies against. This is not
# the same as the python version of TensorFlow we use, but should be similar or
# we risk having version incompatibilities between our C++ code and the Python
# code we use at runtime.
if [[ "${DV_TF_NIGHTLY_BUILD}" = "1" ]]; then
export DV_CPP_TENSORFLOW_TAG="master"
else
export DV_CPP_TENSORFLOW_TAG="r1.9"
fi
export DV_GCP_OPTIMIZED_TF_WHL_VERSION="1.9.0"
export DV_TENSORFLOW_STANDARD_GPU_WHL_VERSION="1.9.0"
export DV_TENSORFLOW_STANDARD_CPU_WHL_VERSION="1.9.0"
# Set this to 1 to use DeepVariant with GPUs. Set it to an already existing
# value in the environment (allowing command line control of the build),
# defaulting to 0 (CPU only build).
export DV_GPU_BUILD="${DV_GPU_BUILD:-0}"
# If this variable is set to 1, DeepVariant will use a TensorFlow wheel file
# compiled with MKL support for corei7 or better chipsets, which
# significantly speeds up execution when running on modern CPUs. The default
# TensorFlow wheel files don't contain these instructions (and thereby run on a
# broader set of CPUs). Using this optimized wheel reduces the runtime of
# DeepVariant's call_variants step by >3x. This is called the GCP (Google Cloud
# Platform) optimized wheel because all GCP instances have at least Sandy Bridge
# or better chipsets, so this wheel should run anywhere on GCP.
export DV_USE_GCP_OPTIMIZED_TF_WHL="${DV_USE_GCP_OPTIMIZED_TF_WHL:-1}"
export GCP_OPTIMIZED_TF_WHL_FILENAME="tensorflow-${DV_GCP_OPTIMIZED_TF_WHL_VERSION}.deepvariant_gcp-cp27-none-linux_x86_64.whl"
export GCP_OPTIMIZED_TF_WHL_PATH="${DV_PACKAGE_BUCKET_PATH}/tensorflow"
export GCP_OPTIMIZED_TF_WHL_CURL_PATH="${DV_PACKAGE_CURL_PATH}/tensorflow"
# Set this to 1 to make our prereq scripts install the CUDA libraries.
# If you already have CUDA installed, such as on a properly provisioned
# Docker image, it shouldn't be necessary.
export DV_INSTALL_GPU_DRIVERS="${DV_INSTALL_GPU_DRIVERS:-0}"
export PYTHON_BIN_PATH=$(which python)
export USE_DEFAULT_PYTHON_LIB_PATH=1
export DV_COPT_FLAGS="--copt=-march=corei7 --copt=-Wno-sign-compare --copt=-Wno-write-strings"
function note_build_stage {
echo "========== [$(date)] Stage '${1}' starting"
}