configure

#!/usr/bin/env bash

set -e
set -o pipefail

# Find out the absolute path to where ./configure resides
pushd `dirname $0` > /dev/null
SOURCE_BASE_DIR=`pwd -P`
popd > /dev/null

PLATFORM="$(uname -s | tr 'A-Z' 'a-z')"
function is_windows() {
  # On windows, the shell script is actually running in msys
  if [[ "${PLATFORM}" =~ msys_nt* ]]; then
    true
  else
    false
  fi
}

function bazel_clean_and_fetch() {
  # bazel clean --expunge currently doesn't work on Windows
  # TODO(pcloudy): Re-enable it after bazel clean --expunge is fixed.
  if ! is_windows; then
    bazel clean --expunge
    # TODO(https://github.com/bazelbuild/bazel/issues/2220) Remove the nested `bazel query`.
    bazel fetch $(bazel query "//tensorflow/... -//tensorflow/examples/android/...")
  else
    # TODO(pcloudy): Also filter out //tensorflow/examples/android/... on Windows after
    # https://github.com/bazelbuild/bazel/issues/2248 is fixed.
    bazel fetch //tensorflow/...
  fi
}

## Set up python-related environment settings
while true; do
  fromuser=""
  if [ -z "$PYTHON_BIN_PATH" ]; then
    default_python_bin_path=$(which python || which python3  || true)
    read -p "Please specify the location of python. [Default is $default_python_bin_path]: " PYTHON_BIN_PATH
    fromuser="1"
    if [ -z "$PYTHON_BIN_PATH" ]; then
      PYTHON_BIN_PATH=$default_python_bin_path
    fi
  fi
  if [ -e "$PYTHON_BIN_PATH" ]; then
    break
  fi
  echo "Invalid python path. ${PYTHON_BIN_PATH} cannot be found" 1>&2
  if [ -z "$fromuser" ]; then
    exit 1
  fi
  PYTHON_BIN_PATH=""
  # Retry
done

## Set up architecture-dependent optimization flags.
if [ -z "$CC_OPT_FLAGS" ]; then
  default_cc_opt_flags="-march=native"
  read -p "Please specify optimization flags to use during compilation [Default is $default_cc_opt_flags]: " CC_OPT_FLAGS
  if [ -z "$CC_OPT_FLAGS" ]; then
    CC_OPT_FLAGS=$default_cc_opt_flags
  fi
fi

if is_windows; then
  TF_NEED_GCP=0
  TF_NEED_HDFS=0
  TF_NEED_JEMALLOC=0
  TF_NEED_OPENCL=0
fi

while [ "$TF_NEED_JEMALLOC" == "" ]; do
  read -p "Do you wish to use jemalloc as the malloc implementation? "\
"(Linux only) [Y/n] " INPUT
  case $INPUT in
    [Yy]* ) echo "jemalloc enabled on Linux"; TF_NEED_JEMALLOC=1;;
    [Nn]* ) echo "jemalloc disabled on Linux"; TF_NEED_JEMALLOC=0;;
    "" ) echo "jemalloc enabled on Linux"; TF_NEED_JEMALLOC=1;;
    * ) echo "Invalid selection: " $INPUT;;
  esac
done

if [ "$TF_NEED_JEMALLOC" == "1" ]; then
  sed -i -e "s/WITH_JEMALLOC = False/WITH_JEMALLOC = True/" tensorflow/core/platform/default/build_config.bzl
else
  sed -i -e "s/WITH_JEMALLOC = True/WITH_JEMALLOC = False/" tensorflow/core/platform/default/build_config.bzl
fi

while [ "$TF_NEED_GCP" == "" ]; do
  read -p "Do you wish to build TensorFlow with "\
"Google Cloud Platform support? [y/N] " INPUT
  case $INPUT in
    [Yy]* ) echo "Google Cloud Platform support will be enabled for "\
"TensorFlow"; TF_NEED_GCP=1;;
    [Nn]* ) echo "No Google Cloud Platform support will be enabled for "\
"TensorFlow"; TF_NEED_GCP=0;;
    "" ) echo "No Google Cloud Platform support will be enabled for "\
"TensorFlow"; TF_NEED_GCP=0;;
    * ) echo "Invalid selection: " $INPUT;;
  esac
done

if [ "$TF_NEED_GCP" == "1" ]; then
  ## Verify that libcurl header files are available.
  # Only check Linux, since on MacOS the header files are installed with XCode.
  if [[ $(uname -a) =~ Linux ]] && [[ ! -f "/usr/include/curl/curl.h" ]]; then
    echo "ERROR: It appears that the development version of libcurl is not "\
"available. Please install the libcurl3-dev package."
    exit 1
  fi

  # Update Bazel build configuration.
  sed -i -e "s/WITH_GCP_SUPPORT = False/WITH_GCP_SUPPORT = True/" tensorflow/core/platform/default/build_config.bzl
else
  # Update Bazel build configuration.
  sed -i -e "s/WITH_GCP_SUPPORT = True/WITH_GCP_SUPPORT = False/" tensorflow/core/platform/default/build_config.bzl
fi

while [ "$TF_NEED_HDFS" == "" ]; do
  read -p "Do you wish to build TensorFlow with "\
"Hadoop File System support? [y/N] " INPUT
  case $INPUT in
    [Yy]* ) echo "Hadoop File System support will be enabled for "\
"TensorFlow"; TF_NEED_HDFS=1;;
    [Nn]* ) echo "No Hadoop File System support will be enabled for "\
"TensorFlow"; TF_NEED_HDFS=0;;
    "" ) echo "No Hadoop File System support will be enabled for "\
"TensorFlow"; TF_NEED_HDFS=0;;
    * ) echo "Invalid selection: " $INPUT;;
  esac
done

if [ "$TF_NEED_HDFS" == "1" ]; then
  # Update Bazel build configuration.
  sed -i -e "s/WITH_HDFS_SUPPORT = False/WITH_HDFS_SUPPORT = True/" tensorflow/core/platform/default/build_config.bzl
else
  # Update Bazel build configuration.
  sed -i -e "s/WITH_HDFS_SUPPORT = True/WITH_HDFS_SUPPORT = False/" tensorflow/core/platform/default/build_config.bzl
fi

## Enable XLA.
while [ "$TF_ENABLE_XLA" == "" ]; do
  read -p "Do you wish to build TensorFlow with the XLA just-in-time compiler (experimental)? [y/N] " INPUT
  case $INPUT in
    [Yy]* ) echo "XLA JIT support will be enabled for TensorFlow"; TF_ENABLE_XLA=1;;
    [Nn]* ) echo "No XLA JIT support will be enabled for TensorFlow"; TF_ENABLE_XLA=0;;
    "" ) echo "No XLA support will be enabled for TensorFlow"; TF_ENABLE_XLA=0;;
    * ) echo "Invalid selection: " $INPUT;;
  esac
done

if [ "$TF_ENABLE_XLA" == "1" ]; then
  # Update Bazel build configuration.
  perl -pi -e "s,WITH_XLA_SUPPORT = (False|True),WITH_XLA_SUPPORT = True,s" tensorflow/core/platform/default/build_config.bzl
else
  # Update Bazel build configuration.
  perl -pi -e "s,WITH_XLA_SUPPORT = (False|True),WITH_XLA_SUPPORT = False,s" tensorflow/core/platform/default/build_config.bzl
fi


# Invoke python_config and set up symlinks to python includes
./util/python/python_config.sh --setup "$PYTHON_BIN_PATH"

# Append CC optimization flags to bazel.rc
echo >> tools/bazel.rc
for opt in $CC_OPT_FLAGS; do
  echo "build --cxxopt=$opt --copt=$opt" >> tools/bazel.rc
done

# Run the gen_git_source to create links where bazel can track dependencies for
# git hash propagation
GEN_GIT_SOURCE=tensorflow/tools/git/gen_git_source.py
chmod a+x ${GEN_GIT_SOURCE}
"${PYTHON_BIN_PATH}" ${GEN_GIT_SOURCE} --configure "${SOURCE_BASE_DIR}"

## Set up SYCL-related environment settings
while [ "$TF_NEED_OPENCL" == "" ]; do
  read -p "Do you wish to build TensorFlow with OpenCL support? [y/N] " INPUT
  case $INPUT in
    [Yy]* ) echo "OpenCL support will be enabled for TensorFlow"; TF_NEED_OPENCL=1;;
    [Nn]* ) echo "No OpenCL support will be enabled for TensorFlow"; TF_NEED_OPENCL=0;;
    "" ) echo "No OpenCL support will be enabled for TensorFlow"; TF_NEED_OPENCL=0;;
    * ) echo "Invalid selection: " $INPUT;;
  esac
done

## Set up Cuda-related environment settings

while [ "$TF_NEED_CUDA" == "" ]; do
  read -p "Do you wish to build TensorFlow with CUDA support? [y/N] " INPUT
  case $INPUT in
    [Yy]* ) echo "CUDA support will be enabled for TensorFlow"; TF_NEED_CUDA=1;;
    [Nn]* ) echo "No CUDA support will be enabled for TensorFlow"; TF_NEED_CUDA=0;;
    "" ) echo "No CUDA support will be enabled for TensorFlow"; TF_NEED_CUDA=0;;
    * ) echo "Invalid selection: " $INPUT;;
  esac
done

export TF_NEED_CUDA
export TF_NEED_OPENCL
if [[ "$TF_NEED_CUDA" == "0" ]] && [[ "$TF_NEED_OPENCL" == "0" ]]; then
  echo "Configuration finished"
  bazel_clean_and_fetch
  exit
fi

if [ "$TF_NEED_CUDA" == "1" ]; then
# Set up which gcc nvcc should use as the host compiler
# No need to set this on Windows
while ! is_windows && true; do
  fromuser=""
  if [ -z "$GCC_HOST_COMPILER_PATH" ]; then
    default_gcc_host_compiler_path=$(which gcc || true)
    read -p "Please specify which gcc should be used by nvcc as the host compiler. [Default is $default_gcc_host_compiler_path]: " GCC_HOST_COMPILER_PATH
    fromuser="1"
    if [ -z "$GCC_HOST_COMPILER_PATH" ]; then
      GCC_HOST_COMPILER_PATH="$default_gcc_host_compiler_path"
    fi
  fi
  if [ -e "$GCC_HOST_COMPILER_PATH" ]; then
    export GCC_HOST_COMPILER_PATH
    break
  fi
  echo "Invalid gcc path. ${GCC_HOST_COMPILER_PATH} cannot be found" 1>&2
  if [ -z "$fromuser" ]; then
    exit 1
  fi
  GCC_HOST_COMPILER_PATH=""
  # Retry
done

# Find out where the CUDA toolkit is installed
OSNAME=`uname -s`

while true; do
  # Configure the Cuda SDK version to use.
  if [ -z "$TF_CUDA_VERSION" ]; then
    read -p "Please specify the CUDA SDK version you want to use, e.g. 7.0. [Leave empty to use system default]: " TF_CUDA_VERSION
  fi

  fromuser=""
  if [ -z "$CUDA_TOOLKIT_PATH" ]; then
    default_cuda_path=/usr/local/cuda
    if is_windows; then
      if [ -z "$CUDA_PATH" ]; then
        default_cuda_path="C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v8.0"
      else
        default_cuda_path="$(cygpath -m "$CUDA_PATH")"
      fi
    fi
    read -p "Please specify the location where CUDA $TF_CUDA_VERSION toolkit is installed. Refer to README.md for more details. [Default is $default_cuda_path]: " CUDA_TOOLKIT_PATH
    fromuser="1"
    if [ -z "$CUDA_TOOLKIT_PATH" ]; then
      CUDA_TOOLKIT_PATH="$default_cuda_path"
    fi
  fi

  if [[ -z "$TF_CUDA_VERSION" ]]; then
    TF_CUDA_EXT=""
  else
    TF_CUDA_EXT=".$TF_CUDA_VERSION"
  fi

  if is_windows; then
    CUDA_RT_LIB_PATH="lib/x64/cudart.lib"
  elif [ "$OSNAME" == "Linux" ]; then
    CUDA_RT_LIB_PATH="lib64/libcudart.so${TF_CUDA_EXT}"
  elif [ "$OSNAME" == "Darwin" ]; then
    CUDA_RT_LIB_PATH="lib/libcudart${TF_CUDA_EXT}.dylib"
  fi

  if [ -e "${CUDA_TOOLKIT_PATH}/${CUDA_RT_LIB_PATH}" ]; then
    export CUDA_TOOLKIT_PATH
    export TF_CUDA_VERSION
    break
  fi
  echo "Invalid path to CUDA $TF_CUDA_VERSION toolkit. ${CUDA_TOOLKIT_PATH}/${CUDA_RT_LIB_PATH} cannot be found"

  if [ -z "$fromuser" ]; then
    exit 1
  fi
  # Retry
  TF_CUDA_VERSION=""
  CUDA_TOOLKIT_PATH=""
done

# Find out where the cuDNN library is installed
while true; do
  # Configure the Cudnn version to use.
  if [ -z "$TF_CUDNN_VERSION" ]; then
    read -p "Please specify the Cudnn version you want to use. [Leave empty to use system default]: " TF_CUDNN_VERSION
  fi

  fromuser=""
  if [ -z "$CUDNN_INSTALL_PATH" ]; then
    default_cudnn_path=${CUDA_TOOLKIT_PATH}
    read -p "Please specify the location where cuDNN $TF_CUDNN_VERSION library is installed. Refer to README.md for more details. [Default is $default_cudnn_path]: " CUDNN_INSTALL_PATH
    fromuser="1"
    if [ -z "$CUDNN_INSTALL_PATH" ]; then
      CUDNN_INSTALL_PATH=$default_cudnn_path
    fi
    # Result returned from "read" will be used unexpanded. That make "~" unuseable.
    # Going through one more level of expansion to handle that.
    CUDNN_INSTALL_PATH=`"${PYTHON_BIN_PATH}" -c "import os; print(os.path.realpath(os.path.expanduser('${CUDNN_INSTALL_PATH}')))"`
  fi

  if [[ -z "$TF_CUDNN_VERSION" ]]; then
    TF_CUDNN_EXT=""
    cudnn_lib_path=""
    cudnn_alt_lib_path=""
    if is_windows; then
      cudnn_lib_path="${CUDNN_INSTALL_PATH}/lib/x64/cudnn.lib"
      cudnn_alt_lib_path="${CUDNN_INSTALL_PATH}/lib/x64/cudnn.lib"
    elif [ "$OSNAME" == "Linux" ]; then
      cudnn_lib_path="${CUDNN_INSTALL_PATH}/lib64/libcudnn.so"
      cudnn_alt_lib_path="${CUDNN_INSTALL_PATH}/libcudnn.so"
    elif [ "$OSNAME" == "Darwin" ]; then
      cudnn_lib_path="${CUDNN_INSTALL_PATH}/lib/libcudnn.dylib"
      cudnn_alt_lib_path="${CUDNN_INSTALL_PATH}/libcudnn.dylib"
    fi
    # Resolve to the SONAME of the symlink.  Use readlink without -f
    # to resolve exactly once to the SONAME.  E.g, libcudnn.so ->
    # libcudnn.so.4.
    # If the path is not a symlink, readlink will exit with an error code, so
    # in that case, we return the path itself.
    if [ -f "$cudnn_lib_path" ]; then
      REALVAL=`readlink "${cudnn_lib_path}" || echo "${cudnn_lib_path}"`
    else
      REALVAL=`readlink "${cudnn_alt_lib_path}" || echo "${cudnn_alt_lib_path}"`
    fi

    # Extract the version of the SONAME, if it was indeed symlinked to
    # the SONAME version of the file.
    if [[ "$REALVAL" =~ .so[.]+([0-9]*) ]]; then
      TF_CUDNN_EXT="."${BASH_REMATCH[1]}
      TF_CUDNN_VERSION=${BASH_REMATCH[1]}
      echo "libcudnn.so resolves to libcudnn${TF_CUDNN_EXT}"
    elif [[ "$REALVAL" =~ ([0-9]*).dylib ]]; then
      TF_CUDNN_EXT=${BASH_REMATCH[1]}".dylib"
      TF_CUDNN_VERSION=${BASH_REMATCH[1]}
      echo "libcudnn.dylib resolves to libcudnn${TF_CUDNN_EXT}"
    fi
  else
    if [ "$OSNAME" == "Darwin" ]; then
      TF_CUDNN_EXT=".${TF_CUDNN_VERSION}.dylib"
    else
      TF_CUDNN_EXT=".$TF_CUDNN_VERSION"
    fi
  fi

  if is_windows; then
    CUDA_DNN_LIB_PATH="lib/x64/cudnn.lib"
    CUDA_DNN_LIB_ALT_PATH="lib/x64/cudnn.lib"
  elif [ "$OSNAME" == "Linux" ]; then
    CUDA_DNN_LIB_PATH="lib64/libcudnn.so${TF_CUDNN_EXT}"
    CUDA_DNN_LIB_ALT_PATH="libcudnn.so${TF_CUDNN_EXT}"
  elif [ "$OSNAME" == "Darwin" ]; then
    CUDA_DNN_LIB_PATH="lib/libcudnn${TF_CUDNN_EXT}"
    CUDA_DNN_LIB_ALT_PATH="libcudnn${TF_CUDNN_EXT}"
  fi

  if [ -e "$CUDNN_INSTALL_PATH/${CUDA_DNN_LIB_ALT_PATH}" -o -e "$CUDNN_INSTALL_PATH/${CUDA_DNN_LIB_PATH}" ]; then
    export TF_CUDNN_VERSION
    export CUDNN_INSTALL_PATH
    break
  fi

  if [ "$OSNAME" == "Linux" ]; then
    CUDNN_PATH_FROM_LDCONFIG="$(ldconfig -p | sed -n 's/.*libcudnn.so .* => \(.*\)/\1/p')"
    if [ -e "${CUDNN_PATH_FROM_LDCONFIG}${TF_CUDNN_EXT}" ]; then
      export TF_CUDNN_VERSION
      export CUDNN_INSTALL_PATH="$(dirname ${CUDNN_PATH_FROM_LDCONFIG})"
      break
    fi
  fi
  echo "Invalid path to cuDNN ${CUDNN_VERSION} toolkit. Neither of the following two files can be found:"
  echo "${CUDNN_INSTALL_PATH}/${CUDA_DNN_LIB_PATH}"
  echo "${CUDNN_INSTALL_PATH}/${CUDA_DNN_LIB_ALT_PATH}"
  if [ "$OSNAME" == "Linux" ]; then
    echo "${CUDNN_PATH_FROM_LDCONFIG}${TF_CUDNN_EXT}"
  fi

  if [ -z "$fromuser" ]; then
    exit 1
  fi
  # Retry
  TF_CUDNN_VERSION=""
  CUDNN_INSTALL_PATH=""
done

# Configure the compute capabilities that TensorFlow builds for.
# Since Cuda toolkit is not backward-compatible, this is not guaranteed to work.
while true; do
  fromuser=""
  default_cuda_compute_capabilities="3.5,5.2"
  if [ -z "$TF_CUDA_COMPUTE_CAPABILITIES" ]; then
cat << EOF
Please specify a list of comma-separated Cuda compute capabilities you want to build with.
You can find the compute capability of your device at: https://developer.nvidia.com/cuda-gpus.
Please note that each additional compute capability significantly increases your build time and binary size.
EOF
    read -p "[Default is: \"3.5,5.2\"]: " TF_CUDA_COMPUTE_CAPABILITIES
    fromuser=1
  fi
  if [ -z "$TF_CUDA_COMPUTE_CAPABILITIES" ]; then
    TF_CUDA_COMPUTE_CAPABILITIES=$default_cuda_compute_capabilities
  fi
  # Check whether all capabilities from the input is valid
  COMPUTE_CAPABILITIES=${TF_CUDA_COMPUTE_CAPABILITIES//,/ }
  ALL_VALID=1
  for CAPABILITY in $COMPUTE_CAPABILITIES; do
    if [[ ! "$CAPABILITY" =~ [0-9]+.[0-9]+ ]]; then
      echo "Invalid compute capability: " $CAPABILITY
      ALL_VALID=0
      break
    fi
  done
  if [ "$ALL_VALID" == "0" ]; then
    if [ -z "$fromuser" ]; then
      exit 1
    fi
  else
    export TF_CUDA_COMPUTE_CAPABILITIES
    break
  fi
  TF_CUDA_COMPUTE_CAPABILITIES=""
done

if is_windows; then
  # The following three variables are needed for MSVC toolchain configuration in Bazel
  export CUDA_PATH="$CUDA_TOOLKIT_PATH"
  export CUDA_COMPUTE_CAPABILITIES="$TF_CUDA_COMPUTE_CAPABILITIES"
  export NO_WHOLE_ARCHIVE_OPTION=1

  # Set GCC_HOST_COMPILER_PATH to keep cuda_configure.bzl happy
  export GCC_HOST_COMPILER_PATH="/usr/bin/dummy_compiler"
fi

# end of if "$TF_NEED_CUDA" == "1"
fi

# OpenCL configuration

if [ "$TF_NEED_OPENCL" == "1" ]; then

# Determine which C++ compiler should be used as the host compiler
while true; do
  fromuser=""
  if [ -z "$HOST_CXX_COMPILER" ]; then
    default_cxx_host_compiler=$(which clang++-3.6 || true)
    read -p "Please specify which C++ compiler should be used as the host C++ compiler. [Default is $default_cxx_host_compiler]: " HOST_CXX_COMPILER
    fromuser="1"
    if [ -z "$HOST_CXX_COMPILER" ]; then
      HOST_CXX_COMPILER=$default_cxx_host_compiler
    fi
  fi
  if [ -e "$HOST_CXX_COMPILER" ]; then
    export HOST_CXX_COMPILER
    break
  fi
  echo "Invalid C++ compiler path. ${HOST_CXX_COMPILER} cannot be found" 1>&2
  if [ -z "$fromuser" ]; then
    exit 1
  fi
  HOST_CXX_COMPILER=""
  # Retry
done

# Determine which C compiler should be used as the host compiler
while true; do
  fromuser=""
  if [ -z "$HOST_C_COMPILER" ]; then
    default_c_host_compiler=$(which clang-3.6 || true)
    read -p "Please specify which C compiler should be used as the host C compiler. [Default is $default_c_host_compiler]: " HOST_C_COMPILER
    fromuser="1"
    if [ -z "$HOST_C_COMPILER" ]; then
      HOST_C_COMPILER=$default_c_host_compiler
    fi
  fi
  if [ -e "$HOST_C_COMPILER" ]; then
    export HOST_C_COMPILER
    break
  fi
  echo "Invalid C compiler path. ${HOST_C_COMPILER} cannot be found" 1>&2
  if [ -z "$fromuser" ]; then
    exit 1
  fi
  HOST_C_COMPILER=""
  # Retry
done

while true; do
  # Configure the OPENCL version to use.
  TF_OPENCL_VERSION="1.2"

  # Point to ComputeCpp root
  if [ -z "$COMPUTECPP_TOOLKIT_PATH" ]; then
    default_computecpp_toolkit_path=/usr/local/computecpp
    read -p "Please specify the location where ComputeCpp for SYCL $TF_OPENCL_VERSION is installed. [Default is $default_computecpp_toolkit_path]: " COMPUTECPP_TOOLKIT_PATH
    fromuser="1"
    if [ -z "$COMPUTECPP_TOOLKIT_PATH" ]; then
      COMPUTECPP_TOOLKIT_PATH=$default_computecpp_toolkit_path
    fi
  fi

  if [ "$OSNAME" == "Linux" ]; then
    SYCL_RT_LIB_PATH="lib/libComputeCpp.so"
  fi

  if [ -e "${COMPUTECPP_TOOLKIT_PATH}/${SYCL_RT_LIB_PATH}" ]; then
    export COMPUTECPP_TOOLKIT_PATH
    break
  fi
  echo "Invalid SYCL $TF_OPENCL_VERSION library path. ${COMPUTECPP_TOOLKIT_PATH}/${SYCL_RT_LIB_PATH} cannot be found"

  if [ -z "$fromuser" ]; then
    exit 1
  fi
  # Retry
  TF_OPENCL_VERSION=""
  COMPUTECPP_TOOLKIT_PATH=""
done

# end of if "$TF_NEED_OPENCL" == "1"
fi

bazel_clean_and_fetch

echo "Configuration finished"