configure.py

# Copyright 2017 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
"""configure script to get build parameters from user."""

from __future__ import absolute_import
from __future__ import division
from __future__ import print_function

import argparse
import errno
import os
import platform
import re
import subprocess
import sys

# pylint: disable=g-import-not-at-top
try:
  from shutil import which
except ImportError:
  from distutils.spawn import find_executable as which
# pylint: enable=g-import-not-at-top

_DEFAULT_CUDA_VERSION = '9.0'
_DEFAULT_CUDNN_VERSION = '7'
_DEFAULT_NCCL_VERSION = '2.2'
_DEFAULT_CUDA_COMPUTE_CAPABILITIES = '3.5,7.0'
_DEFAULT_CUDA_PATH = '/usr/local/cuda'
_DEFAULT_CUDA_PATH_LINUX = '/opt/cuda'
_DEFAULT_CUDA_PATH_WIN = ('C:/Program Files/NVIDIA GPU Computing '
                          'Toolkit/CUDA/v%s' % _DEFAULT_CUDA_VERSION)
_TF_OPENCL_VERSION = '1.2'
_DEFAULT_COMPUTECPP_TOOLKIT_PATH = '/usr/local/computecpp'
_DEFAULT_TRISYCL_INCLUDE_DIR = '/usr/local/triSYCL/include'
_SUPPORTED_ANDROID_NDK_VERSIONS = [10, 11, 12, 13, 14, 15, 16]

_DEFAULT_PROMPT_ASK_ATTEMPTS = 10

_TF_WORKSPACE_ROOT = os.path.abspath(os.path.dirname(__file__))
_TF_BAZELRC_FILENAME = '.tf_configure.bazelrc'
_TF_BAZELRC = os.path.join(_TF_WORKSPACE_ROOT, _TF_BAZELRC_FILENAME)
_TF_WORKSPACE = os.path.join(_TF_WORKSPACE_ROOT, 'WORKSPACE')

if platform.machine() == 'ppc64le':
  _DEFAULT_TENSORRT_PATH_LINUX = '/usr/lib/powerpc64le-linux-gnu/'
else:
  _DEFAULT_TENSORRT_PATH_LINUX = '/usr/lib/%s-linux-gnu' % platform.machine()


class UserInputError(Exception):
  pass


def is_windows():
  return platform.system() == 'Windows'


def is_linux():
  return platform.system() == 'Linux'


def is_macos():
  return platform.system() == 'Darwin'


def is_ppc64le():
  return platform.machine() == 'ppc64le'


def is_cygwin():
  return platform.system().startswith('CYGWIN_NT')


def get_input(question):
  try:
    try:
      answer = raw_input(question)
    except NameError:
      answer = input(question)  # pylint: disable=bad-builtin
  except EOFError:
    answer = ''
  return answer


def symlink_force(target, link_name):
  """Force symlink, equivalent of 'ln -sf'.

  Args:
    target: items to link to.
    link_name: name of the link.
  """
  try:
    os.symlink(target, link_name)
  except OSError as e:
    if e.errno == errno.EEXIST:
      os.remove(link_name)
      os.symlink(target, link_name)
    else:
      raise e


def sed_in_place(filename, old, new):
  """Replace old string with new string in file.

  Args:
    filename: string for filename.
    old: string to replace.
    new: new string to replace to.
  """
  with open(filename, 'r') as f:
    filedata = f.read()
  newdata = filedata.replace(old, new)
  with open(filename, 'w') as f:
    f.write(newdata)


def write_to_bazelrc(line):
  with open(_TF_BAZELRC, 'a') as f:
    f.write(line + '\n')


def write_action_env_to_bazelrc(var_name, var):
  write_to_bazelrc('build --action_env %s="%s"' % (var_name, str(var)))


def run_shell(cmd, allow_non_zero=False):
  if allow_non_zero:
    try:
      output = subprocess.check_output(cmd)
    except subprocess.CalledProcessError as e:
      output = e.output
  else:
    output = subprocess.check_output(cmd)
  return output.decode('UTF-8').strip()


def cygpath(path):
  """Convert path from posix to windows."""
  return os.path.abspath(path).replace('\\', '/')


def get_python_path(environ_cp, python_bin_path):
  """Get the python site package paths."""
  python_paths = []
  if environ_cp.get('PYTHONPATH'):
    python_paths = environ_cp.get('PYTHONPATH').split(':')
  try:
    library_paths = run_shell([
        python_bin_path, '-c',
        'import site; print("\\n".join(site.getsitepackages()))'
    ]).split('\n')
  except subprocess.CalledProcessError:
    library_paths = [
        run_shell([
            python_bin_path, '-c',
            'from distutils.sysconfig import get_python_lib;'
            'print(get_python_lib())'
        ])
    ]

  all_paths = set(python_paths + library_paths)

  paths = []
  for path in all_paths:
    if os.path.isdir(path):
      paths.append(path)
  return paths


def get_python_major_version(python_bin_path):
  """Get the python major version."""
  return run_shell([python_bin_path, '-c', 'import sys; print(sys.version[0])'])


def setup_python(environ_cp):
  """Setup python related env variables."""
  # Get PYTHON_BIN_PATH, default is the current running python.
  default_python_bin_path = sys.executable
  ask_python_bin_path = ('Please specify the location of python. [Default is '
                         '%s]: ') % default_python_bin_path
  while True:
    python_bin_path = get_from_env_or_user_or_default(
        environ_cp, 'PYTHON_BIN_PATH', ask_python_bin_path,
        default_python_bin_path)
    # Check if the path is valid
    if os.path.isfile(python_bin_path) and os.access(python_bin_path, os.X_OK):
      break
    elif not os.path.exists(python_bin_path):
      print('Invalid python path: %s cannot be found.' % python_bin_path)
    else:
      print('%s is not executable.  Is it the python binary?' % python_bin_path)
    environ_cp['PYTHON_BIN_PATH'] = ''

  # Convert python path to Windows style before checking lib and version
  if is_windows() or is_cygwin():
    python_bin_path = cygpath(python_bin_path)

  # Get PYTHON_LIB_PATH
  python_lib_path = environ_cp.get('PYTHON_LIB_PATH')
  if not python_lib_path:
    python_lib_paths = get_python_path(environ_cp, python_bin_path)
    if environ_cp.get('USE_DEFAULT_PYTHON_LIB_PATH') == '1':
      python_lib_path = python_lib_paths[0]
    else:
      print('Found possible Python library paths:\n  %s' %
            '\n  '.join(python_lib_paths))
      default_python_lib_path = python_lib_paths[0]
      python_lib_path = get_input(
          'Please input the desired Python library path to use.  '
          'Default is [%s]\n' % python_lib_paths[0])
      if not python_lib_path:
        python_lib_path = default_python_lib_path
    environ_cp['PYTHON_LIB_PATH'] = python_lib_path

  python_major_version = get_python_major_version(python_bin_path)

  # Convert python path to Windows style before writing into bazel.rc
  if is_windows() or is_cygwin():
    python_lib_path = cygpath(python_lib_path)

  # Set-up env variables used by python_configure.bzl
  write_action_env_to_bazelrc('PYTHON_BIN_PATH', python_bin_path)
  write_action_env_to_bazelrc('PYTHON_LIB_PATH', python_lib_path)
  write_to_bazelrc('build --python_path=\"%s"' % python_bin_path)
  environ_cp['PYTHON_BIN_PATH'] = python_bin_path

  # Write tools/python_bin_path.sh
  with open(
      os.path.join(_TF_WORKSPACE_ROOT, 'tools', 'python_bin_path.sh'),
      'w') as f:
    f.write('export PYTHON_BIN_PATH="%s"' % python_bin_path)


def reset_tf_configure_bazelrc(workspace_path):
  """Reset file that contains customized config settings."""
  open(_TF_BAZELRC, 'w').close()
  bazelrc_path = os.path.join(workspace_path, '.bazelrc')

  data = []
  if os.path.exists(bazelrc_path):
    with open(bazelrc_path, 'r') as f:
      data = f.read().splitlines()
  with open(bazelrc_path, 'w') as f:
    for l in data:
      if _TF_BAZELRC_FILENAME in l:
        continue
      f.write('%s\n' % l)
    f.write('import %%workspace%%/%s\n' % _TF_BAZELRC_FILENAME)


def cleanup_makefile():
  """Delete any leftover BUILD files from the Makefile build.

  These files could interfere with Bazel parsing.
  """
  makefile_download_dir = os.path.join(_TF_WORKSPACE_ROOT, 'tensorflow',
                                       'contrib', 'makefile', 'downloads')
  if os.path.isdir(makefile_download_dir):
    for root, _, filenames in os.walk(makefile_download_dir):
      for f in filenames:
        if f.endswith('BUILD'):
          os.remove(os.path.join(root, f))


def get_var(environ_cp,
            var_name,
            query_item,
            enabled_by_default,
            question=None,
            yes_reply=None,
            no_reply=None):
  """Get boolean input from user.

  If var_name is not set in env, ask user to enable query_item or not. If the
  response is empty, use the default.

  Args:
    environ_cp: copy of the os.environ.
    var_name: string for name of environment variable, e.g. "TF_NEED_HDFS".
    query_item: string for feature related to the variable, e.g. "Hadoop File
      System".
    enabled_by_default: boolean for default behavior.
    question: optional string for how to ask for user input.
    yes_reply: optional string for reply when feature is enabled.
    no_reply: optional string for reply when feature is disabled.

  Returns:
    boolean value of the variable.

  Raises:
    UserInputError: if an environment variable is set, but it cannot be
      interpreted as a boolean indicator, assume that the user has made a
      scripting error, and will continue to provide invalid input.
      Raise the error to avoid infinitely looping.
  """
  if not question:
    question = 'Do you wish to build TensorFlow with %s support?' % query_item
  if not yes_reply:
    yes_reply = '%s support will be enabled for TensorFlow.' % query_item
  if not no_reply:
    no_reply = 'No %s' % yes_reply

  yes_reply += '\n'
  no_reply += '\n'

  if enabled_by_default:
    question += ' [Y/n]: '
  else:
    question += ' [y/N]: '

  var = environ_cp.get(var_name)
  if var is not None:
    var_content = var.strip().lower()
    true_strings = ('1', 't', 'true', 'y', 'yes')
    false_strings = ('0', 'f', 'false', 'n', 'no')
    if var_content in true_strings:
      var = True
    elif var_content in false_strings:
      var = False
    else:
      raise UserInputError(
          'Environment variable %s must be set as a boolean indicator.\n'
          'The following are accepted as TRUE : %s.\n'
          'The following are accepted as FALSE: %s.\n'
          'Current value is %s.' % (var_name, ', '.join(true_strings),
                                    ', '.join(false_strings), var))

  while var is None:
    user_input_origin = get_input(question)
    user_input = user_input_origin.strip().lower()
    if user_input == 'y':
      print(yes_reply)
      var = True
    elif user_input == 'n':
      print(no_reply)
      var = False
    elif not user_input:
      if enabled_by_default:
        print(yes_reply)
        var = True
      else:
        print(no_reply)
        var = False
    else:
      print('Invalid selection: %s' % user_input_origin)
  return var


def set_build_var(environ_cp,
                  var_name,
                  query_item,
                  option_name,
                  enabled_by_default,
                  bazel_config_name=None):
  """Set if query_item will be enabled for the build.

  Ask user if query_item will be enabled. Default is used if no input is given.
  Set subprocess environment variable and write to .bazelrc if enabled.

  Args:
    environ_cp: copy of the os.environ.
    var_name: string for name of environment variable, e.g. "TF_NEED_HDFS".
    query_item: string for feature related to the variable, e.g. "Hadoop File
      System".
    option_name: string for option to define in .bazelrc.
    enabled_by_default: boolean for default behavior.
    bazel_config_name: Name for Bazel --config argument to enable build feature.
  """

  var = str(int(get_var(environ_cp, var_name, query_item, enabled_by_default)))
  environ_cp[var_name] = var
  if var == '1':
    write_to_bazelrc('build --define %s=true' % option_name)
  elif bazel_config_name is not None:
    # TODO(mikecase): Migrate all users of configure.py to use --config Bazel
    # options and not to set build configs through environment variables.
    write_to_bazelrc(
        'build:%s --define %s=true' % (bazel_config_name, option_name))


def set_action_env_var(environ_cp,
                       var_name,
                       query_item,
                       enabled_by_default,
                       question=None,
                       yes_reply=None,
                       no_reply=None):
  """Set boolean action_env variable.

  Ask user if query_item will be enabled. Default is used if no input is given.
  Set environment variable and write to .bazelrc.

  Args:
    environ_cp: copy of the os.environ.
    var_name: string for name of environment variable, e.g. "TF_NEED_HDFS".
    query_item: string for feature related to the variable, e.g. "Hadoop File
      System".
    enabled_by_default: boolean for default behavior.
    question: optional string for how to ask for user input.
    yes_reply: optional string for reply when feature is enabled.
    no_reply: optional string for reply when feature is disabled.
  """
  var = int(
      get_var(environ_cp, var_name, query_item, enabled_by_default, question,
              yes_reply, no_reply))

  write_action_env_to_bazelrc(var_name, var)
  environ_cp[var_name] = str(var)


def convert_version_to_int(version):
  """Convert a version number to a integer that can be used to compare.

  Version strings of the form X.YZ and X.Y.Z-xxxxx are supported. The
  'xxxxx' part, for instance 'homebrew' on OS/X, is ignored.

  Args:
    version: a version to be converted

  Returns:
    An integer if converted successfully, otherwise return None.
  """
  version = version.split('-')[0]
  version_segments = version.split('.')
  for seg in version_segments:
    if not seg.isdigit():
      return None

  version_str = ''.join(['%03d' % int(seg) for seg in version_segments])
  return int(version_str)


def check_bazel_version(min_version):
  """Check installed bazel version is at least min_version.

  Args:
    min_version: string for minimum bazel version.

  Returns:
    The bazel version detected.
  """
  if which('bazel') is None:
    print('Cannot find bazel. Please install bazel.')
    sys.exit(0)
  curr_version = run_shell(
      ['bazel', '--batch', '--bazelrc=/dev/null', 'version'])

  for line in curr_version.split('\n'):
    if 'Build label: ' in line:
      curr_version = line.split('Build label: ')[1]
      break

  min_version_int = convert_version_to_int(min_version)
  curr_version_int = convert_version_to_int(curr_version)

  # Check if current bazel version can be detected properly.
  if not curr_version_int:
    print('WARNING: current bazel installation is not a release version.')
    print('Make sure you are running at least bazel %s' % min_version)
    return curr_version

  print('You have bazel %s installed.' % curr_version)

  if curr_version_int < min_version_int:
    print('Please upgrade your bazel installation to version %s or higher to '
          'build TensorFlow!' % min_version)
    sys.exit(0)
  return curr_version


def set_cc_opt_flags(environ_cp):
  """Set up architecture-dependent optimization flags.

  Also append CC optimization flags to bazel.rc..

  Args:
    environ_cp: copy of the os.environ.
  """
  if is_ppc64le():
    # gcc on ppc64le does not support -march, use mcpu instead
    default_cc_opt_flags = '-mcpu=native'
  elif is_windows():
    default_cc_opt_flags = '/arch:AVX'
  else:
    default_cc_opt_flags = '-march=native'
  question = ('Please specify optimization flags to use during compilation when'
              ' bazel option "--config=opt" is specified [Default is %s]: '
             ) % default_cc_opt_flags
  cc_opt_flags = get_from_env_or_user_or_default(environ_cp, 'CC_OPT_FLAGS',
                                                 question, default_cc_opt_flags)
  for opt in cc_opt_flags.split():
    write_to_bazelrc('build:opt --copt=%s' % opt)
  # It should be safe on the same build host.
  if not is_ppc64le() and not is_windows():
    write_to_bazelrc('build:opt --host_copt=-march=native')
  write_to_bazelrc('build:opt --define with_default_optimizations=true')


def set_tf_cuda_clang(environ_cp):
  """set TF_CUDA_CLANG action_env.

  Args:
    environ_cp: copy of the os.environ.
  """
  question = 'Do you want to use clang as CUDA compiler?'
  yes_reply = 'Clang will be used as CUDA compiler.'
  no_reply = 'nvcc will be used as CUDA compiler.'
  set_action_env_var(
      environ_cp,
      'TF_CUDA_CLANG',
      None,
      False,
      question=question,
      yes_reply=yes_reply,
      no_reply=no_reply)


def set_tf_download_clang(environ_cp):
  """Set TF_DOWNLOAD_CLANG action_env."""
  question = 'Do you wish to download a fresh release of clang? (Experimental)'
  yes_reply = 'Clang will be downloaded and used to compile tensorflow.'
  no_reply = 'Clang will not be downloaded.'
  set_action_env_var(
      environ_cp,
      'TF_DOWNLOAD_CLANG',
      None,
      False,
      question=question,
      yes_reply=yes_reply,
      no_reply=no_reply)


def get_from_env_or_user_or_default(environ_cp, var_name, ask_for_var,
                                    var_default):
  """Get var_name either from env, or user or default.

  If var_name has been set as environment variable, use the preset value, else
  ask for user input. If no input is provided, the default is used.

  Args:
    environ_cp: copy of the os.environ.
    var_name: string for name of environment variable, e.g. "TF_NEED_HDFS".
    ask_for_var: string for how to ask for user input.
    var_default: default value string.

  Returns:
    string value for var_name
  """
  var = environ_cp.get(var_name)
  if not var:
    var = get_input(ask_for_var)
    print('\n')
  if not var:
    var = var_default
  return var


def set_clang_cuda_compiler_path(environ_cp):
  """Set CLANG_CUDA_COMPILER_PATH."""
  default_clang_path = which('clang') or ''
  ask_clang_path = ('Please specify which clang should be used as device and '
                    'host compiler. [Default is %s]: ') % default_clang_path

  while True:
    clang_cuda_compiler_path = get_from_env_or_user_or_default(
        environ_cp, 'CLANG_CUDA_COMPILER_PATH', ask_clang_path,
        default_clang_path)
    if os.path.exists(clang_cuda_compiler_path):
      break

    # Reset and retry
    print('Invalid clang path: %s cannot be found.' % clang_cuda_compiler_path)
    environ_cp['CLANG_CUDA_COMPILER_PATH'] = ''

  # Set CLANG_CUDA_COMPILER_PATH
  environ_cp['CLANG_CUDA_COMPILER_PATH'] = clang_cuda_compiler_path
  write_action_env_to_bazelrc('CLANG_CUDA_COMPILER_PATH',
                              clang_cuda_compiler_path)


def prompt_loop_or_load_from_env(environ_cp,
                                 var_name,
                                 var_default,
                                 ask_for_var,
                                 check_success,
                                 error_msg,
                                 suppress_default_error=False,
                                 n_ask_attempts=_DEFAULT_PROMPT_ASK_ATTEMPTS):
  """Loop over user prompts for an ENV param until receiving a valid response.

  For the env param var_name, read from the environment or verify user input
  until receiving valid input. When done, set var_name in the environ_cp to its
  new value.

  Args:
    environ_cp: (Dict) copy of the os.environ.
    var_name: (String) string for name of environment variable, e.g. "TF_MYVAR".
    var_default: (String) default value string.
    ask_for_var: (String) string for how to ask for user input.
    check_success: (Function) function that takes one argument and returns a
      boolean. Should return True if the value provided is considered valid. May
      contain a complex error message if error_msg does not provide enough
      information. In that case, set suppress_default_error to True.
    error_msg: (String) String with one and only one '%s'. Formatted with each
      invalid response upon check_success(input) failure.
    suppress_default_error: (Bool) Suppress the above error message in favor of
      one from the check_success function.
    n_ask_attempts: (Integer) Number of times to query for valid input before
      raising an error and quitting.

  Returns:
    [String] The value of var_name after querying for input.

  Raises:
    UserInputError: if a query has been attempted n_ask_attempts times without
      success, assume that the user has made a scripting error, and will
      continue to provide invalid input. Raise the error to avoid infinitely
      looping.
  """
  default = environ_cp.get(var_name) or var_default
  full_query = '%s [Default is %s]: ' % (
      ask_for_var,
      default,
  )

  for _ in range(n_ask_attempts):
    val = get_from_env_or_user_or_default(environ_cp, var_name, full_query,
                                          default)
    if check_success(val):
      break
    if not suppress_default_error:
      print(error_msg % val)
    environ_cp[var_name] = ''
  else:
    raise UserInputError(
        'Invalid %s setting was provided %d times in a row. '
        'Assuming to be a scripting mistake.' % (var_name, n_ask_attempts))

  environ_cp[var_name] = val
  return val


def create_android_ndk_rule(environ_cp):
  """Set ANDROID_NDK_HOME and write Android NDK WORKSPACE rule."""
  if is_windows() or is_cygwin():
    default_ndk_path = cygpath(
        '%s/Android/Sdk/ndk-bundle' % environ_cp['APPDATA'])
  elif is_macos():
    default_ndk_path = '%s/library/Android/Sdk/ndk-bundle' % environ_cp['HOME']
  else:
    default_ndk_path = '%s/Android/Sdk/ndk-bundle' % environ_cp['HOME']

  def valid_ndk_path(path):
    return (os.path.exists(path) and
            os.path.exists(os.path.join(path, 'source.properties')))

  android_ndk_home_path = prompt_loop_or_load_from_env(
      environ_cp,
      var_name='ANDROID_NDK_HOME',
      var_default=default_ndk_path,
      ask_for_var='Please specify the home path of the Android NDK to use.',
      check_success=valid_ndk_path,
      error_msg=('The path %s or its child file "source.properties" '
                 'does not exist.'))
  write_action_env_to_bazelrc('ANDROID_NDK_HOME', android_ndk_home_path)
  write_action_env_to_bazelrc('ANDROID_NDK_API_LEVEL',
                              check_ndk_level(android_ndk_home_path))


def create_android_sdk_rule(environ_cp):
  """Set Android variables and write Android SDK WORKSPACE rule."""
  if is_windows() or is_cygwin():
    default_sdk_path = cygpath('%s/Android/Sdk' % environ_cp['APPDATA'])
  elif is_macos():
    default_sdk_path = '%s/library/Android/Sdk' % environ_cp['HOME']
  else:
    default_sdk_path = '%s/Android/Sdk' % environ_cp['HOME']

  def valid_sdk_path(path):
    return (os.path.exists(path) and
            os.path.exists(os.path.join(path, 'platforms')) and
            os.path.exists(os.path.join(path, 'build-tools')))

  android_sdk_home_path = prompt_loop_or_load_from_env(
      environ_cp,
      var_name='ANDROID_SDK_HOME',
      var_default=default_sdk_path,
      ask_for_var='Please specify the home path of the Android SDK to use.',
      check_success=valid_sdk_path,
      error_msg=('Either %s does not exist, or it does not contain the '
                 'subdirectories "platforms" and "build-tools".'))

  platforms = os.path.join(android_sdk_home_path, 'platforms')
  api_levels = sorted(os.listdir(platforms))
  api_levels = [x.replace('android-', '') for x in api_levels]

  def valid_api_level(api_level):
    return os.path.exists(
        os.path.join(android_sdk_home_path, 'platforms',
                     'android-' + api_level))

  android_api_level = prompt_loop_or_load_from_env(
      environ_cp,
      var_name='ANDROID_API_LEVEL',
      var_default=api_levels[-1],
      ask_for_var=('Please specify the Android SDK API level to use. '
                   '[Available levels: %s]') % api_levels,
      check_success=valid_api_level,
      error_msg='Android-%s is not present in the SDK path.')

  build_tools = os.path.join(android_sdk_home_path, 'build-tools')
  versions = sorted(os.listdir(build_tools))

  def valid_build_tools(version):
    return os.path.exists(
        os.path.join(android_sdk_home_path, 'build-tools', version))

  android_build_tools_version = prompt_loop_or_load_from_env(
      environ_cp,
      var_name='ANDROID_BUILD_TOOLS_VERSION',
      var_default=versions[-1],
      ask_for_var=('Please specify an Android build tools version to use. '
                   '[Available versions: %s]') % versions,
      check_success=valid_build_tools,
      error_msg=('The selected SDK does not have build-tools version %s '
                 'available.'))

  write_action_env_to_bazelrc('ANDROID_BUILD_TOOLS_VERSION',
                              android_build_tools_version)
  write_action_env_to_bazelrc('ANDROID_SDK_API_LEVEL', android_api_level)
  write_action_env_to_bazelrc('ANDROID_SDK_HOME', android_sdk_home_path)


def check_ndk_level(android_ndk_home_path):
  """Check the revision number of an Android NDK path."""
  properties_path = '%s/source.properties' % android_ndk_home_path
  if is_windows() or is_cygwin():
    properties_path = cygpath(properties_path)
  with open(properties_path, 'r') as f:
    filedata = f.read()

  revision = re.search(r'Pkg.Revision = (\d+)', filedata)
  if revision:
    ndk_api_level = revision.group(1)
  else:
    raise Exception('Unable to parse NDK revision.')
  if int(ndk_api_level) not in _SUPPORTED_ANDROID_NDK_VERSIONS:
    print('WARNING: The API level of the NDK in %s is %s, which is not '
          'supported by Bazel (officially supported versions: %s). Please use '
          'another version. Compiling Android targets may result in confusing '
          'errors.\n' % (android_ndk_home_path, ndk_api_level,
                         _SUPPORTED_ANDROID_NDK_VERSIONS))
  return ndk_api_level


def set_gcc_host_compiler_path(environ_cp):
  """Set GCC_HOST_COMPILER_PATH."""
  default_gcc_host_compiler_path = which('gcc') or ''
  cuda_bin_symlink = '%s/bin/gcc' % environ_cp.get('CUDA_TOOLKIT_PATH')

  if os.path.islink(cuda_bin_symlink):
    # os.readlink is only available in linux
    default_gcc_host_compiler_path = os.path.realpath(cuda_bin_symlink)

  gcc_host_compiler_path = prompt_loop_or_load_from_env(
      environ_cp,
      var_name='GCC_HOST_COMPILER_PATH',
      var_default=default_gcc_host_compiler_path,
      ask_for_var=
      'Please specify which gcc should be used by nvcc as the host compiler.',
      check_success=os.path.exists,
      error_msg='Invalid gcc path. %s cannot be found.',
  )

  write_action_env_to_bazelrc('GCC_HOST_COMPILER_PATH', gcc_host_compiler_path)


def reformat_version_sequence(version_str, sequence_count):
  """Reformat the version string to have the given number of sequences.

  For example:
  Given (7, 2) -> 7.0
        (7.0.1, 2) -> 7.0
        (5, 1) -> 5
        (5.0.3.2, 1) -> 5

  Args:
      version_str: String, the version string.
      sequence_count: int, an integer.

  Returns:
      string, reformatted version string.
  """
  v = version_str.split('.')
  if len(v) < sequence_count:
    v = v + (['0'] * (sequence_count - len(v)))

  return '.'.join(v[:sequence_count])


def set_tf_cuda_version(environ_cp):
  """Set CUDA_TOOLKIT_PATH and TF_CUDA_VERSION."""
  ask_cuda_version = (
      'Please specify the CUDA SDK version you want to use. '
      '[Leave empty to default to CUDA %s]: ') % _DEFAULT_CUDA_VERSION

  for _ in range(_DEFAULT_PROMPT_ASK_ATTEMPTS):
    # Configure the Cuda SDK version to use.
    tf_cuda_version = get_from_env_or_user_or_default(
        environ_cp, 'TF_CUDA_VERSION', ask_cuda_version, _DEFAULT_CUDA_VERSION)
    tf_cuda_version = reformat_version_sequence(str(tf_cuda_version), 2)

    # Find out where the CUDA toolkit is installed
    default_cuda_path = _DEFAULT_CUDA_PATH
    if is_windows() or is_cygwin():
      default_cuda_path = cygpath(
          environ_cp.get('CUDA_PATH', _DEFAULT_CUDA_PATH_WIN))
    elif is_linux():
      # If the default doesn't exist, try an alternative default.
      if (not os.path.exists(default_cuda_path)
         ) and os.path.exists(_DEFAULT_CUDA_PATH_LINUX):
        default_cuda_path = _DEFAULT_CUDA_PATH_LINUX
    ask_cuda_path = ('Please specify the location where CUDA %s toolkit is'
                     ' installed. Refer to README.md for more details. '
                     '[Default is %s]: ') % (tf_cuda_version, default_cuda_path)
    cuda_toolkit_path = get_from_env_or_user_or_default(
        environ_cp, 'CUDA_TOOLKIT_PATH', ask_cuda_path, default_cuda_path)
    if is_windows() or is_cygwin():
      cuda_toolkit_path = cygpath(cuda_toolkit_path)

    if is_windows():
      cuda_rt_lib_paths = ['lib/x64/cudart.lib']
    elif is_linux():
      cuda_rt_lib_paths = [
          '%s/libcudart.so.%s' % (x, tf_cuda_version) for x in [
              'lib64',
              'lib/powerpc64le-linux-gnu',
              'lib/x86_64-linux-gnu',
          ]
      ]
    elif is_macos():
      cuda_rt_lib_paths = ['lib/libcudart.%s.dylib' % tf_cuda_version]

    cuda_toolkit_paths_full = [
        os.path.join(cuda_toolkit_path, x) for x in cuda_rt_lib_paths
    ]
    if any([os.path.exists(x) for x in cuda_toolkit_paths_full]):
      break

    # Reset and retry
    print('Invalid path to CUDA %s toolkit. %s cannot be found' %
          (tf_cuda_version, cuda_toolkit_paths_full))
    environ_cp['TF_CUDA_VERSION'] = ''
    environ_cp['CUDA_TOOLKIT_PATH'] = ''

  else:
    raise UserInputError('Invalid TF_CUDA_SETTING setting was provided %d '
                         'times in a row. Assuming to be a scripting mistake.' %
                         _DEFAULT_PROMPT_ASK_ATTEMPTS)

  # Set CUDA_TOOLKIT_PATH and TF_CUDA_VERSION
  environ_cp['CUDA_TOOLKIT_PATH'] = cuda_toolkit_path
  write_action_env_to_bazelrc('CUDA_TOOLKIT_PATH', cuda_toolkit_path)
  environ_cp['TF_CUDA_VERSION'] = tf_cuda_version
  write_action_env_to_bazelrc('TF_CUDA_VERSION', tf_cuda_version)


def set_tf_cudnn_version(environ_cp):
  """Set CUDNN_INSTALL_PATH and TF_CUDNN_VERSION."""
  ask_cudnn_version = (
      'Please specify the cuDNN version you want to use. '
      '[Leave empty to default to cuDNN %s.0]: ') % _DEFAULT_CUDNN_VERSION

  for _ in range(_DEFAULT_PROMPT_ASK_ATTEMPTS):
    tf_cudnn_version = get_from_env_or_user_or_default(
        environ_cp, 'TF_CUDNN_VERSION', ask_cudnn_version,
        _DEFAULT_CUDNN_VERSION)
    tf_cudnn_version = reformat_version_sequence(str(tf_cudnn_version), 1)

    default_cudnn_path = environ_cp.get('CUDA_TOOLKIT_PATH')
    ask_cudnn_path = (r'Please specify the location where cuDNN %s library is '
                      'installed. Refer to README.md for more details. [Default'
                      ' is %s]: ') % (tf_cudnn_version, default_cudnn_path)
    cudnn_install_path = get_from_env_or_user_or_default(
        environ_cp, 'CUDNN_INSTALL_PATH', ask_cudnn_path, default_cudnn_path)

    # Result returned from "read" will be used unexpanded. That make "~"
    # unusable. Going through one more level of expansion to handle that.
    cudnn_install_path = os.path.realpath(
        os.path.expanduser(cudnn_install_path))
    if is_windows() or is_cygwin():
      cudnn_install_path = cygpath(cudnn_install_path)

    if is_windows():
      cuda_dnn_lib_path = 'lib/x64/cudnn.lib'
      cuda_dnn_lib_alt_path = 'lib/x64/cudnn.lib'
    elif is_linux():
      cuda_dnn_lib_path = 'lib64/libcudnn.so.%s' % tf_cudnn_version
      cuda_dnn_lib_alt_path = 'libcudnn.so.%s' % tf_cudnn_version
    elif is_macos():
      cuda_dnn_lib_path = 'lib/libcudnn.%s.dylib' % tf_cudnn_version
      cuda_dnn_lib_alt_path = 'libcudnn.%s.dylib' % tf_cudnn_version

    cuda_dnn_lib_path_full = os.path.join(cudnn_install_path, cuda_dnn_lib_path)
    cuda_dnn_lib_alt_path_full = os.path.join(cudnn_install_path,
                                              cuda_dnn_lib_alt_path)
    if os.path.exists(cuda_dnn_lib_path_full) or os.path.exists(
        cuda_dnn_lib_alt_path_full):
      break

    # Try another alternative for Linux
    if is_linux():
      ldconfig_bin = which('ldconfig') or '/sbin/ldconfig'
      cudnn_path_from_ldconfig = run_shell([ldconfig_bin, '-p'])
      cudnn_path_from_ldconfig = re.search('.*libcudnn.so .* => (.*)',
                                           cudnn_path_from_ldconfig)
      if cudnn_path_from_ldconfig:
        cudnn_path_from_ldconfig = cudnn_path_from_ldconfig.group(1)
        if os.path.exists(
            '%s.%s' % (cudnn_path_from_ldconfig, tf_cudnn_version)):
          cudnn_install_path = os.path.dirname(cudnn_path_from_ldconfig)
          break

    # Reset and Retry
    print(
        'Invalid path to cuDNN %s toolkit. None of the following files can be '
        'found:' % tf_cudnn_version)
    print(cuda_dnn_lib_path_full)
    print(cuda_dnn_lib_alt_path_full)
    if is_linux():
      print('%s.%s' % (cudnn_path_from_ldconfig, tf_cudnn_version))

    environ_cp['TF_CUDNN_VERSION'] = ''
  else:
    raise UserInputError('Invalid TF_CUDNN setting was provided %d '
                         'times in a row. Assuming to be a scripting mistake.' %
                         _DEFAULT_PROMPT_ASK_ATTEMPTS)

  # Set CUDNN_INSTALL_PATH and TF_CUDNN_VERSION
  environ_cp['CUDNN_INSTALL_PATH'] = cudnn_install_path
  write_action_env_to_bazelrc('CUDNN_INSTALL_PATH', cudnn_install_path)
  environ_cp['TF_CUDNN_VERSION'] = tf_cudnn_version
  write_action_env_to_bazelrc('TF_CUDNN_VERSION', tf_cudnn_version)


def is_cuda_compatible(lib, cuda_ver, cudnn_ver):
  """Check compatibility between given library and cudnn/cudart libraries."""
  ldd_bin = which('ldd') or '/usr/bin/ldd'
  ldd_out = run_shell([ldd_bin, lib], True)
  ldd_out = ldd_out.split(os.linesep)
  cudnn_pattern = re.compile('.*libcudnn.so\\.?(.*) =>.*$')
  cuda_pattern = re.compile('.*libcudart.so\\.?(.*) =>.*$')
  cudnn = None
  cudart = None
  cudnn_ok = True  # assume no cudnn dependency by default
  cuda_ok = True  # assume no cuda dependency by default
  for line in ldd_out:
    if 'libcudnn.so' in line:
      cudnn = cudnn_pattern.search(line)
      cudnn_ok = False
    elif 'libcudart.so' in line:
      cudart = cuda_pattern.search(line)
      cuda_ok = False
  if cudnn and len(cudnn.group(1)):
    cudnn = convert_version_to_int(cudnn.group(1))
  if cudart and len(cudart.group(1)):
    cudart = convert_version_to_int(cudart.group(1))
  if cudnn is not None:
    cudnn_ok = (cudnn == cudnn_ver)
  if cudart is not None:
    cuda_ok = (cudart == cuda_ver)
  return cudnn_ok and cuda_ok


def set_tf_tensorrt_install_path(environ_cp):
  """Set TENSORRT_INSTALL_PATH and TF_TENSORRT_VERSION.

  Adapted from code contributed by Sami Kama (https://github.com/samikama).

  Args:
    environ_cp: copy of the os.environ.

  Raises:
    ValueError: if this method was called under non-Linux platform.
    UserInputError: if user has provided invalid input multiple times.
  """
  if not is_linux():
    raise ValueError('Currently TensorRT is only supported on Linux platform.')

  # Ask user whether to add TensorRT support.
  if str(int(get_var(environ_cp, 'TF_NEED_TENSORRT', 'TensorRT',
                     False))) != '1':
    return

  for _ in range(_DEFAULT_PROMPT_ASK_ATTEMPTS):
    ask_tensorrt_path = (r'Please specify the location where TensorRT is '
                         'installed. [Default is %s]:') % (
                             _DEFAULT_TENSORRT_PATH_LINUX)
    trt_install_path = get_from_env_or_user_or_default(
        environ_cp, 'TENSORRT_INSTALL_PATH', ask_tensorrt_path,
        _DEFAULT_TENSORRT_PATH_LINUX)

    # Result returned from "read" will be used unexpanded. That make "~"
    # unusable. Going through one more level of expansion to handle that.
    trt_install_path = os.path.realpath(os.path.expanduser(trt_install_path))

    def find_libs(search_path):
      """Search for libnvinfer.so in "search_path"."""
      fl = set()
      if os.path.exists(search_path) and os.path.isdir(search_path):
        fl.update([
            os.path.realpath(os.path.join(search_path, x))
            for x in os.listdir(search_path)
            if 'libnvinfer.so' in x
        ])
      return fl

    possible_files = find_libs(trt_install_path)
    possible_files.update(find_libs(os.path.join(trt_install_path, 'lib')))
    possible_files.update(find_libs(os.path.join(trt_install_path, 'lib64')))
    cuda_ver = convert_version_to_int(environ_cp['TF_CUDA_VERSION'])
    cudnn_ver = convert_version_to_int(environ_cp['TF_CUDNN_VERSION'])
    nvinfer_pattern = re.compile('.*libnvinfer.so.?(.*)$')
    highest_ver = [0, None, None]

    for lib_file in possible_files:
      if is_cuda_compatible(lib_file, cuda_ver, cudnn_ver):
        matches = nvinfer_pattern.search(lib_file)
        if len(matches.groups()) == 0:
          continue
        ver_str = matches.group(1)
        ver = convert_version_to_int(ver_str) if len(ver_str) else 0
        if ver > highest_ver[0]:
          highest_ver = [ver, ver_str, lib_file]
    if highest_ver[1] is not None:
      trt_install_path = os.path.dirname(highest_ver[2])
      tf_tensorrt_version = highest_ver[1]
      break

    # Try another alternative from ldconfig.
    ldconfig_bin = which('ldconfig') or '/sbin/ldconfig'
    ldconfig_output = run_shell([ldconfig_bin, '-p'])
    search_result = re.search('.*libnvinfer.so\\.?([0-9.]*).* => (.*)',
                              ldconfig_output)
    if search_result:
      libnvinfer_path_from_ldconfig = search_result.group(2)
      if os.path.exists(libnvinfer_path_from_ldconfig):
        if is_cuda_compatible(libnvinfer_path_from_ldconfig, cuda_ver,
                              cudnn_ver):
          trt_install_path = os.path.dirname(libnvinfer_path_from_ldconfig)
          tf_tensorrt_version = search_result.group(1)
          break

    # Reset and Retry
    if possible_files:
      print('TensorRT libraries found in one the following directories',
            'are not compatible with selected cuda and cudnn installations')
      print(trt_install_path)
      print(os.path.join(trt_install_path, 'lib'))
      print(os.path.join(trt_install_path, 'lib64'))
      if search_result:
        print(libnvinfer_path_from_ldconfig)
    else:
      print(
          'Invalid path to TensorRT. None of the following files can be found:')
      print(trt_install_path)
      print(os.path.join(trt_install_path, 'lib'))
      print(os.path.join(trt_install_path, 'lib64'))
      if search_result:
        print(libnvinfer_path_from_ldconfig)

  else:
    raise UserInputError('Invalid TF_TENSORRT setting was provided %d '
                         'times in a row. Assuming to be a scripting mistake.' %
                         _DEFAULT_PROMPT_ASK_ATTEMPTS)

  # Set TENSORRT_INSTALL_PATH and TF_TENSORRT_VERSION
  environ_cp['TENSORRT_INSTALL_PATH'] = trt_install_path
  write_action_env_to_bazelrc('TENSORRT_INSTALL_PATH', trt_install_path)
  environ_cp['TF_TENSORRT_VERSION'] = tf_tensorrt_version
  write_action_env_to_bazelrc('TF_TENSORRT_VERSION', tf_tensorrt_version)


def set_tf_nccl_install_path(environ_cp):
  """Set NCCL_INSTALL_PATH and TF_NCCL_VERSION.

  Args:
    environ_cp: copy of the os.environ.

  Raises:
    ValueError: if this method was called under non-Linux platform.
    UserInputError: if user has provided invalid input multiple times.
  """
  if not is_linux():
    raise ValueError('Currently NCCL is only supported on Linux platforms.')

  ask_nccl_version = (
      'Please specify the NCCL version you want to use. If NCCL %s is not '
      'installed, then you can use version 1.3 that can be fetched '
      'automatically but it may have worse performance with multiple GPUs. '
      '[Default is %s]: ') % (_DEFAULT_NCCL_VERSION, _DEFAULT_NCCL_VERSION)

  for _ in range(_DEFAULT_PROMPT_ASK_ATTEMPTS):
    tf_nccl_version = get_from_env_or_user_or_default(
        environ_cp, 'TF_NCCL_VERSION', ask_nccl_version, _DEFAULT_NCCL_VERSION)
    tf_nccl_version = reformat_version_sequence(str(tf_nccl_version), 1)

    if tf_nccl_version == '1':
      break  # No need to get install path, NCCL 1 is a GitHub repo.

    # TODO(csigg): Look with ldconfig first if we can find the library in paths
    # like /usr/lib/x86_64-linux-gnu and the header file in the corresponding
    # include directory. This is where the NCCL .deb packages install them.
    # Then ask the user if we should use that. Instead of a single
    # NCCL_INSTALL_PATH, pass separate NCCL_LIB_PATH and NCCL_HDR_PATH to
    # nccl_configure.bzl
    default_nccl_path = environ_cp.get('CUDA_TOOLKIT_PATH')
    ask_nccl_path = (r'Please specify the location where NCCL %s library is '
                     'installed. Refer to README.md for more details. [Default '
                     'is %s]:') % (tf_nccl_version, default_nccl_path)
    nccl_install_path = get_from_env_or_user_or_default(
        environ_cp, 'NCCL_INSTALL_PATH', ask_nccl_path, default_nccl_path)

    # Result returned from "read" will be used unexpanded. That make "~"
    # unusable. Going through one more level of expansion to handle that.
    nccl_install_path = os.path.realpath(os.path.expanduser(nccl_install_path))
    if is_windows() or is_cygwin():
      nccl_install_path = cygpath(nccl_install_path)

    if is_windows():
      nccl_lib_path = 'lib/x64/nccl.lib'
    elif is_linux():
      nccl_lib_path = 'lib/libnccl.so.%s' % tf_nccl_version
    elif is_macos():
      nccl_lib_path = 'lib/libnccl.%s.dylib' % tf_nccl_version

    nccl_lib_path = os.path.join(nccl_install_path, nccl_lib_path)
    nccl_hdr_path = os.path.join(nccl_install_path, 'include/nccl.h')
    if os.path.exists(nccl_lib_path) and os.path.exists(nccl_hdr_path):
      # Set NCCL_INSTALL_PATH
      environ_cp['NCCL_INSTALL_PATH'] = nccl_install_path
      write_action_env_to_bazelrc('NCCL_INSTALL_PATH', nccl_install_path)
      break

    # Reset and Retry
    print('Invalid path to NCCL %s toolkit, %s or %s not found. Please use the '
          'O/S agnostic package of NCCL 2' % (tf_nccl_version, nccl_lib_path,
                                              nccl_hdr_path))

    environ_cp['TF_NCCL_VERSION'] = ''
  else:
    raise UserInputError('Invalid TF_NCCL setting was provided %d '
                         'times in a row. Assuming to be a scripting mistake.' %
                         _DEFAULT_PROMPT_ASK_ATTEMPTS)

  # Set TF_NCCL_VERSION
  environ_cp['TF_NCCL_VERSION'] = tf_nccl_version
  write_action_env_to_bazelrc('TF_NCCL_VERSION', tf_nccl_version)


def get_native_cuda_compute_capabilities(environ_cp):
  """Get native cuda compute capabilities.

  Args:
    environ_cp: copy of the os.environ.

  Returns:
    string of native cuda compute capabilities, separated by comma.
  """
  device_query_bin = os.path.join(
      environ_cp.get('CUDA_TOOLKIT_PATH'), 'extras/demo_suite/deviceQuery')
  if os.path.isfile(device_query_bin) and os.access(device_query_bin, os.X_OK):
    try:
      output = run_shell(device_query_bin).split('\n')
      pattern = re.compile('[0-9]*\\.[0-9]*')
      output = [pattern.search(x) for x in output if 'Capability' in x]
      output = ','.join(x.group() for x in output if x is not None)
    except subprocess.CalledProcessError:
      output = ''
  else:
    output = ''
  return output


def set_tf_cuda_compute_capabilities(environ_cp):
  """Set TF_CUDA_COMPUTE_CAPABILITIES."""
  while True:
    native_cuda_compute_capabilities = get_native_cuda_compute_capabilities(
        environ_cp)
    if not native_cuda_compute_capabilities:
      default_cuda_compute_capabilities = _DEFAULT_CUDA_COMPUTE_CAPABILITIES
    else:
      default_cuda_compute_capabilities = native_cuda_compute_capabilities

    ask_cuda_compute_capabilities = (
        'Please specify a list of comma-separated '
        'Cuda compute capabilities you want to '
        'build with.\nYou can find the compute '
        'capability of your device at: '
        'https://developer.nvidia.com/cuda-gpus.\nPlease'
        ' note that each additional compute '
        'capability significantly increases your '
        'build time and binary size. [Default is: %s]: ' %
        default_cuda_compute_capabilities)
    tf_cuda_compute_capabilities = get_from_env_or_user_or_default(
        environ_cp, 'TF_CUDA_COMPUTE_CAPABILITIES',
        ask_cuda_compute_capabilities, default_cuda_compute_capabilities)
    # Check whether all capabilities from the input is valid
    all_valid = True
    # Remove all whitespace characters before splitting the string
    # that users may insert by accident, as this will result in error
    tf_cuda_compute_capabilities = ''.join(tf_cuda_compute_capabilities.split())
    for compute_capability in tf_cuda_compute_capabilities.split(','):
      m = re.match('[0-9]+.[0-9]+', compute_capability)
      if not m:
        print('Invalid compute capability: ' % compute_capability)
        all_valid = False
      else:
        ver = int(m.group(0).split('.')[0])
        if ver < 3:
          print('Only compute capabilities 3.0 or higher are supported.')
          all_valid = False

    if all_valid:
      break

    # Reset and Retry
    environ_cp['TF_CUDA_COMPUTE_CAPABILITIES'] = ''

  # Set TF_CUDA_COMPUTE_CAPABILITIES
  environ_cp['TF_CUDA_COMPUTE_CAPABILITIES'] = tf_cuda_compute_capabilities
  write_action_env_to_bazelrc('TF_CUDA_COMPUTE_CAPABILITIES',
                              tf_cuda_compute_capabilities)


def set_other_cuda_vars(environ_cp):
  """Set other CUDA related variables."""
  # If CUDA is enabled, always use GPU during build and test.
  if environ_cp.get('TF_CUDA_CLANG') == '1':
    write_to_bazelrc('build --config=cuda_clang')
    write_to_bazelrc('test --config=cuda_clang')
  else:
    write_to_bazelrc('build --config=cuda')
    write_to_bazelrc('test --config=cuda')


def set_host_cxx_compiler(environ_cp):
  """Set HOST_CXX_COMPILER."""
  default_cxx_host_compiler = which('g++') or ''

  host_cxx_compiler = prompt_loop_or_load_from_env(
      environ_cp,
      var_name='HOST_CXX_COMPILER',
      var_default=default_cxx_host_compiler,
      ask_for_var=('Please specify which C++ compiler should be used as the '
                   'host C++ compiler.'),
      check_success=os.path.exists,
      error_msg='Invalid C++ compiler path. %s cannot be found.',
  )

  write_action_env_to_bazelrc('HOST_CXX_COMPILER', host_cxx_compiler)


def set_host_c_compiler(environ_cp):
  """Set HOST_C_COMPILER."""
  default_c_host_compiler = which('gcc') or ''

  host_c_compiler = prompt_loop_or_load_from_env(
      environ_cp,
      var_name='HOST_C_COMPILER',
      var_default=default_c_host_compiler,
      ask_for_var=('Please specify which C compiler should be used as the host '
                   'C compiler.'),
      check_success=os.path.exists,
      error_msg='Invalid C compiler path. %s cannot be found.',
  )

  write_action_env_to_bazelrc('HOST_C_COMPILER', host_c_compiler)


def set_computecpp_toolkit_path(environ_cp):
  """Set COMPUTECPP_TOOLKIT_PATH."""

  def toolkit_exists(toolkit_path):
    """Check if a computecpp toolkit path is valid."""
    if is_linux():
      sycl_rt_lib_path = 'lib/libComputeCpp.so'
    else:
      sycl_rt_lib_path = ''

    sycl_rt_lib_path_full = os.path.join(toolkit_path, sycl_rt_lib_path)
    exists = os.path.exists(sycl_rt_lib_path_full)
    if not exists:
      print('Invalid SYCL %s library path. %s cannot be found' %
            (_TF_OPENCL_VERSION, sycl_rt_lib_path_full))
    return exists

  computecpp_toolkit_path = prompt_loop_or_load_from_env(
      environ_cp,
      var_name='COMPUTECPP_TOOLKIT_PATH',
      var_default=_DEFAULT_COMPUTECPP_TOOLKIT_PATH,
      ask_for_var=(
          'Please specify the location where ComputeCpp for SYCL %s is '
          'installed.' % _TF_OPENCL_VERSION),
      check_success=toolkit_exists,
      error_msg='Invalid SYCL compiler path. %s cannot be found.',
      suppress_default_error=True)

  write_action_env_to_bazelrc('COMPUTECPP_TOOLKIT_PATH',
                              computecpp_toolkit_path)


def set_trisycl_include_dir(environ_cp):
  """Set TRISYCL_INCLUDE_DIR."""

  ask_trisycl_include_dir = ('Please specify the location of the triSYCL '
                             'include directory. (Use --config=sycl_trisycl '
                             'when building with Bazel) '
                             '[Default is %s]: ') % (
                                 _DEFAULT_TRISYCL_INCLUDE_DIR)

  while True:
    trisycl_include_dir = get_from_env_or_user_or_default(
        environ_cp, 'TRISYCL_INCLUDE_DIR', ask_trisycl_include_dir,
        _DEFAULT_TRISYCL_INCLUDE_DIR)
    if os.path.exists(trisycl_include_dir):
      break

    print('Invalid triSYCL include directory, %s cannot be found' %
          (trisycl_include_dir))

  # Set TRISYCL_INCLUDE_DIR
  environ_cp['TRISYCL_INCLUDE_DIR'] = trisycl_include_dir
  write_action_env_to_bazelrc('TRISYCL_INCLUDE_DIR', trisycl_include_dir)


def set_mpi_home(environ_cp):
  """Set MPI_HOME."""

  default_mpi_home = which('mpirun') or which('mpiexec') or ''
  default_mpi_home = os.path.dirname(os.path.dirname(default_mpi_home))

  def valid_mpi_path(mpi_home):
    exists = (
        os.path.exists(os.path.join(mpi_home, 'include')) and
        os.path.exists(os.path.join(mpi_home, 'lib')))
    if not exists:
      print('Invalid path to the MPI Toolkit. %s or %s cannot be found' %
            (os.path.join(mpi_home, 'include'),
             os.path.exists(os.path.join(mpi_home, 'lib'))))
    return exists

  _ = prompt_loop_or_load_from_env(
      environ_cp,
      var_name='MPI_HOME',
      var_default=default_mpi_home,
      ask_for_var='Please specify the MPI toolkit folder.',
      check_success=valid_mpi_path,
      error_msg='',
      suppress_default_error=True)


def set_other_mpi_vars(environ_cp):
  """Set other MPI related variables."""
  # Link the MPI header files
  mpi_home = environ_cp.get('MPI_HOME')
  symlink_force('%s/include/mpi.h' % mpi_home, 'third_party/mpi/mpi.h')

  # Determine if we use OpenMPI or MVAPICH, these require different header files
  # to be included here to make bazel dependency checker happy
  if os.path.exists(os.path.join(mpi_home, 'include/mpi_portable_platform.h')):
    symlink_force(
        os.path.join(mpi_home, 'include/mpi_portable_platform.h'),
        'third_party/mpi/mpi_portable_platform.h')
    # TODO(gunan): avoid editing files in configure
    sed_in_place('third_party/mpi/mpi.bzl', 'MPI_LIB_IS_OPENMPI=False',
                 'MPI_LIB_IS_OPENMPI=True')
  else:
    # MVAPICH / MPICH
    symlink_force(
        os.path.join(mpi_home, 'include/mpio.h'), 'third_party/mpi/mpio.h')
    symlink_force(
        os.path.join(mpi_home, 'include/mpicxx.h'), 'third_party/mpi/mpicxx.h')
    # TODO(gunan): avoid editing files in configure
    sed_in_place('third_party/mpi/mpi.bzl', 'MPI_LIB_IS_OPENMPI=True',
                 'MPI_LIB_IS_OPENMPI=False')

  if os.path.exists(os.path.join(mpi_home, 'lib/libmpi.so')):
    symlink_force(
        os.path.join(mpi_home, 'lib/libmpi.so'), 'third_party/mpi/libmpi.so')
  else:
    raise ValueError('Cannot find the MPI library file in %s/lib' % mpi_home)


def set_system_libs_flag(environ_cp):
  syslibs = environ_cp.get('TF_SYSTEM_LIBS', '')
  if syslibs and syslibs != '':
    if ',' in syslibs:
      syslibs = ','.join(sorted(syslibs.split(',')))
    else:
      syslibs = ','.join(sorted(syslibs.split()))
    write_action_env_to_bazelrc('TF_SYSTEM_LIBS', syslibs)

  if 'PREFIX' in environ_cp:
    write_to_bazelrc('build --define=PREFIX=%s' % environ_cp['PREFIX'])
  if 'LIBDIR' in environ_cp:
    write_to_bazelrc('build --define=LIBDIR=%s' % environ_cp['LIBDIR'])
  if 'INCLUDEDIR' in environ_cp:
    write_to_bazelrc('build --define=INCLUDEDIR=%s' % environ_cp['INCLUDEDIR'])


def set_windows_build_flags(environ_cp):
  """Set Windows specific build options."""
  # The non-monolithic build is not supported yet
  write_to_bazelrc('build --config monolithic')
  # Suppress warning messages
  write_to_bazelrc('build --copt=-w --host_copt=-w')
  # Output more verbose information when something goes wrong
  write_to_bazelrc('build --verbose_failures')
  # The host and target platforms are the same in Windows build. So we don't
  # have to distinct them. This avoids building the same targets twice.
  write_to_bazelrc('build --distinct_host_configuration=false')
  # Enable short object file path to avoid long path issue on Windows.
  # TODO(pcloudy): Remove this flag when upgrading Bazel to 0.16.0
  # Short object file path will be enabled by default.
  write_to_bazelrc('build --experimental_shortened_obj_file_path=true')
  # When building zip file for some py_binary and py_test targets, don't
  # include its dependencies. This is for:
  #   1. Running python tests against the system installed TF pip package.
  #   2. Avoiding redundant files in
  #      //tensorflow/tools/pip_package:simple_console_windows,
  #      which is a py_binary used during creating TF pip package.
  #      See https://github.com/tensorflow/tensorflow/issues/22390
  write_to_bazelrc('build --define=no_tensorflow_py_deps=true')

  if get_var(
      environ_cp, 'TF_OVERRIDE_EIGEN_STRONG_INLINE', 'Eigen strong inline',
      True, ('Would you like to override eigen strong inline for some C++ '
             'compilation to reduce the compilation time?'),
      'Eigen strong inline overridden.', 'Not overriding eigen strong inline, '
      'some compilations could take more than 20 mins.'):
    # Due to a known MSVC compiler issue
    # https://github.com/tensorflow/tensorflow/issues/10521
    # Overriding eigen strong inline speeds up the compiling of
    # conv_grad_ops_3d.cc and conv_ops_3d.cc by 20 minutes,
    # but this also hurts the performance. Let users decide what they want.
    write_to_bazelrc('build --define=override_eigen_strong_inline=true')


def config_info_line(name, help_text):
  """Helper function to print formatted help text for Bazel config options."""
  print('\t--config=%-12s\t# %s' % (name, help_text))


def main():
  parser = argparse.ArgumentParser()
  parser.add_argument(
      '--workspace',
      type=str,
      default=_TF_WORKSPACE_ROOT,
      help='The absolute path to your active Bazel workspace.')
  args = parser.parse_args()

  # Make a copy of os.environ to be clear when functions and getting and setting
  # environment variables.
  environ_cp = dict(os.environ)

  check_bazel_version('0.15.0')

  reset_tf_configure_bazelrc(args.workspace)
  cleanup_makefile()
  setup_python(environ_cp)

  if is_windows():
    environ_cp['TF_NEED_JEMALLOC'] = '0'
    environ_cp['TF_NEED_OPENCL_SYCL'] = '0'
    environ_cp['TF_NEED_COMPUTECPP'] = '0'
    environ_cp['TF_NEED_OPENCL'] = '0'
    environ_cp['TF_CUDA_CLANG'] = '0'
    environ_cp['TF_NEED_TENSORRT'] = '0'
    # TODO(ibiryukov): Investigate using clang as a cpu or cuda compiler on
    # Windows.
    environ_cp['TF_DOWNLOAD_CLANG'] = '0'
    environ_cp['TF_ENABLE_XLA'] = '0'
    environ_cp['TF_NEED_MPI'] = '0'
    environ_cp['TF_SET_ANDROID_WORKSPACE'] = '0'

  if is_macos():
    environ_cp['TF_NEED_JEMALLOC'] = '0'
    environ_cp['TF_NEED_TENSORRT'] = '0'

  # The numpy package on ppc64le uses OpenBLAS which has multi-threading
  # issues that lead to incorrect answers.  Set OMP_NUM_THREADS=1 at
  # runtime to allow the Tensorflow testcases which compare numpy
  # results to Tensorflow results to succeed.
  if is_ppc64le():
    write_action_env_to_bazelrc('OMP_NUM_THREADS', 1)

  set_build_var(environ_cp, 'TF_NEED_JEMALLOC', 'jemalloc as malloc',
                'with_jemalloc', True)
  set_build_var(environ_cp, 'TF_ENABLE_XLA', 'XLA JIT', 'with_xla_support',
                False, 'xla')


  set_action_env_var(environ_cp, 'TF_NEED_OPENCL_SYCL', 'OpenCL SYCL', False)
  if environ_cp.get('TF_NEED_OPENCL_SYCL') == '1':
    set_host_cxx_compiler(environ_cp)
    set_host_c_compiler(environ_cp)
    set_action_env_var(environ_cp, 'TF_NEED_COMPUTECPP', 'ComputeCPP', True)
    if environ_cp.get('TF_NEED_COMPUTECPP') == '1':
      set_computecpp_toolkit_path(environ_cp)
    else:
      set_trisycl_include_dir(environ_cp)

  set_action_env_var(environ_cp, 'TF_NEED_ROCM', 'ROCm', False)
  if (environ_cp.get('TF_NEED_ROCM') == '1' and
      'LD_LIBRARY_PATH' in environ_cp and
      environ_cp.get('LD_LIBRARY_PATH') != '1'):
    write_action_env_to_bazelrc('LD_LIBRARY_PATH',
                                environ_cp.get('LD_LIBRARY_PATH'))

  set_action_env_var(environ_cp, 'TF_NEED_CUDA', 'CUDA', False)
  if (environ_cp.get('TF_NEED_CUDA') == '1' and
      'TF_CUDA_CONFIG_REPO' not in environ_cp):
    set_tf_cuda_version(environ_cp)
    set_tf_cudnn_version(environ_cp)
    if is_linux():
      set_tf_tensorrt_install_path(environ_cp)
      set_tf_nccl_install_path(environ_cp)

    set_tf_cuda_compute_capabilities(environ_cp)
    if 'LD_LIBRARY_PATH' in environ_cp and environ_cp.get(
        'LD_LIBRARY_PATH') != '1':
      write_action_env_to_bazelrc('LD_LIBRARY_PATH',
                                  environ_cp.get('LD_LIBRARY_PATH'))

    set_tf_cuda_clang(environ_cp)
    if environ_cp.get('TF_CUDA_CLANG') == '1':
      # Ask whether we should download the clang toolchain.
      set_tf_download_clang(environ_cp)
      if environ_cp.get('TF_DOWNLOAD_CLANG') != '1':
        # Set up which clang we should use as the cuda / host compiler.
        set_clang_cuda_compiler_path(environ_cp)
      else:
        # Use downloaded LLD for linking.
        write_to_bazelrc('build:cuda_clang --config=download_clang_use_lld')
        write_to_bazelrc('test:cuda_clang --config=download_clang_use_lld')
    else:
      # Set up which gcc nvcc should use as the host compiler
      # No need to set this on Windows
      if not is_windows():
        set_gcc_host_compiler_path(environ_cp)
    set_other_cuda_vars(environ_cp)
  else:
    # CUDA not required. Ask whether we should download the clang toolchain and
    # use it for the CPU build.
    set_tf_download_clang(environ_cp)
    if environ_cp.get('TF_DOWNLOAD_CLANG') == '1':
      write_to_bazelrc('build --config=download_clang')
      write_to_bazelrc('test --config=download_clang')

  # SYCL / ROCm / CUDA are mutually exclusive.
  # At most 1 GPU platform can be configured.
  gpu_platform_count = 0
  if environ_cp.get('TF_NEED_OPENCL_SYCL') == '1':
    gpu_platform_count += 1
  if environ_cp.get('TF_NEED_ROCM') == '1':
    gpu_platform_count += 1
  if environ_cp.get('TF_NEED_CUDA') == '1':
    gpu_platform_count += 1
  if gpu_platform_count >= 2:
    raise UserInputError('SYCL / CUDA / ROCm are mututally exclusive. '
                         'At most 1 GPU platform can be configured.')

  set_build_var(environ_cp, 'TF_NEED_MPI', 'MPI', 'with_mpi_support', False)
  if environ_cp.get('TF_NEED_MPI') == '1':
    set_mpi_home(environ_cp)
    set_other_mpi_vars(environ_cp)

  set_cc_opt_flags(environ_cp)
  set_system_libs_flag(environ_cp)
  if is_windows():
    set_windows_build_flags(environ_cp)

  # Add a config option to build TensorFlow 2.0 API.
  write_to_bazelrc('build:v2 --define=tf_api_version=2')

  if get_var(environ_cp, 'TF_SET_ANDROID_WORKSPACE', 'android workspace', False,
             ('Would you like to interactively configure ./WORKSPACE for '
              'Android builds?'), 'Searching for NDK and SDK installations.',
             'Not configuring the WORKSPACE for Android builds.'):
    create_android_ndk_rule(environ_cp)
    create_android_sdk_rule(environ_cp)

  # On Windows, we don't have MKL support and the build is always monolithic.
  # So no need to print the following message.
  # TODO(pcloudy): remove the following if check when they make sense on Windows
  if not is_windows():
    print('Preconfigured Bazel build configs. You can use any of the below by '
          'adding "--config=<>" to your build command. See tools/bazel.rc for '
          'more details.')
    config_info_line('mkl', 'Build with MKL support.')
    config_info_line('monolithic', 'Config for mostly static monolithic build.')
    config_info_line('gdr', 'Build with GDR support.')
    config_info_line('verbs', 'Build with libverbs support.')
    config_info_line('ngraph', 'Build with Intel nGraph support.')


if __name__ == '__main__':
  main()