# 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 = '10.0'
_DEFAULT_CUDNN_VERSION = '7'
_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, 17, 18]

_DEFAULT_PROMPT_ASK_ATTEMPTS = 10

_TF_BAZELRC_FILENAME = '.tf_configure.bazelrc'
_TF_WORKSPACE_ROOT = ''
_TF_BAZELRC = ''
_TF_CURRENT_BAZEL_VERSION = None

NCCL_LIB_PATHS = [
    'lib64/', 'lib/powerpc64le-linux-gnu/', 'lib/x86_64-linux-gnu/', ''
]

# List of files to be configured for using Bazel on Apple platforms.
APPLE_BAZEL_FILES = [
    'tensorflow/lite/experimental/objc/BUILD',
    'tensorflow/lite/experimental/swift/BUILD'
]

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

  _ = 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

  # If choosen python_lib_path is from a path specified in the PYTHONPATH
  # variable, need to tell bazel to include PYTHONPATH
  if environ_cp.get('PYTHONPATH'):
    python_paths = environ_cp.get('PYTHONPATH').split(':')
    if python_lib_path in python_paths:
      write_action_env_to_bazelrc('PYTHONPATH', environ_cp.get('PYTHONPATH'))

  # 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():
  """Reset file that contains customized config settings."""
  open(_TF_BAZELRC, 'w').close()


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:%s --define %s=true' % (bazel_config_name, option_name))
    write_to_bazelrc('build --config=%s' % bazel_config_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, max_version):
  """Check installed bazel version is between min_version and max_version.

  Args:
    min_version: string for minimum bazel version.
    max_version: string for maximum 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)
  max_version_int = convert_version_to_int(max_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(1)
  if (curr_version_int > max_version_int and
      'TF_IGNORE_MAX_BAZEL_VERSION' not in os.environ):
    print('Please downgrade your bazel installation to version %s or lower to '
          'build TensorFlow! To downgrade: download the installer for the old '
          'version (from https://github.com/bazelbuild/bazel/releases) then '
          'run the installer.' % max_version)
    sys.exit(1)
  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 -Wno-sign-compare'
  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]: ') % _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 not matches.groups():
          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, NCCL_HDR_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 locally installed NCCL version you want to use. '
      '[Default is to use https://github.com/nvidia/nccl]: ')

  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, '')

    if not tf_nccl_version:
      break  # No need to get install path, building the open source code.

    tf_nccl_version = reformat_version_sequence(str(tf_nccl_version), 1)

    # 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.

    # First check to see if NCCL is in the ldconfig.
    # If its found, use that location.
    if is_linux():
      ldconfig_bin = which('ldconfig') or '/sbin/ldconfig'
      nccl2_path_from_ldconfig = run_shell([ldconfig_bin, '-p'])
      nccl2_path_from_ldconfig = re.search('.*libnccl.so .* => (.*)',
                                           nccl2_path_from_ldconfig)
    if nccl2_path_from_ldconfig:
      nccl2_path_from_ldconfig = nccl2_path_from_ldconfig.group(1)
      if os.path.exists('%s.%s' % (nccl2_path_from_ldconfig, tf_nccl_version)):
        nccl_install_path = os.path.dirname(nccl2_path_from_ldconfig)
        print('NCCL libraries found in ' + nccl2_path_from_ldconfig)

        # Check if this is the main system lib location
        if re.search('.*linux-gnu', nccl_install_path):
          trunc_nccl_install_path = '/usr'
          print('This looks like a system path.')
        else:
          trunc_nccl_install_path = nccl_install_path + '/..'

        # Look for header
        nccl_hdr_path = trunc_nccl_install_path + '/include'
        print('Assuming NCCL header path is ' + nccl_hdr_path)
        if os.path.exists(nccl_hdr_path + '/nccl.h'):
          # Set NCCL_INSTALL_PATH
          environ_cp['NCCL_INSTALL_PATH'] = nccl_install_path
          write_action_env_to_bazelrc('NCCL_INSTALL_PATH', nccl_install_path)

          # Set NCCL_HDR_PATH
          environ_cp['NCCL_HDR_PATH'] = nccl_hdr_path
          write_action_env_to_bazelrc('NCCL_HDR_PATH', nccl_hdr_path)
          break
        else:
          print(
              'The header for NCCL2 cannot be found. Please install the libnccl-dev package.'
          )
      else:
        print('NCCL2 is listed by ldconfig but the library is not found. '
              'Your ldconfig is out of date. Please run sudo ldconfig.')
    else:
      # NCCL is not found in ldconfig. Ask the user for the location.
      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)

      nccl_lib_path = ''
      if is_windows():
        nccl_lib_path = 'lib/x64/nccl.lib'
      elif is_linux():
        nccl_lib_filename = 'libnccl.so.%s' % tf_nccl_version
        nccl_lpath = '%s/lib/%s' % (nccl_install_path, nccl_lib_filename)
        if not os.path.exists(nccl_lpath):
          for relative_path in NCCL_LIB_PATHS:
            path = '%s/%s%s' % (nccl_install_path, relative_path,
                                nccl_lib_filename)
            if os.path.exists(path):
              print('NCCL found at ' + path)
              nccl_lib_path = path
              break
        else:
          nccl_lib_path = nccl_lpath
      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(
          os.path.dirname(nccl_lib_path), '../include/nccl.h')
      print('Assuming NCCL header path is ' + nccl_hdr_path)
      if os.path.exists(nccl_lib_path) and os.path.exists(nccl_hdr_path):
        # Set NCCL_INSTALL_PATH
        environ_cp['NCCL_INSTALL_PATH'] = os.path.dirname(nccl_lib_path)
        write_action_env_to_bazelrc('NCCL_INSTALL_PATH',
                                    os.path.dirname(nccl_lib_path))

        # Set NCCL_HDR_PATH
        environ_cp['NCCL_HDR_PATH'] = os.path.dirname(nccl_hdr_path)
        write_action_env_to_bazelrc('NCCL_HDR_PATH',
                                    os.path.dirname(nccl_hdr_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, and that '
        'TensorFlow only supports compute '
        'capabilities >= 3.5 [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: %s' % compute_capability)
        all_valid = False
      else:
        ver = float(m.group(0))
        if ver < 3.0:
          print('ERROR: TensorFlow only supports CUDA compute capabilities 3.0 '
                'and higher. Please re-specify the list of compute '
                'capabilities excluding version %s.' % ver)
          all_valid = False
        if ver < 3.5:
          print('WARNING: XLA does not support CUDA compute capabilities '
                'lower than 3.5. Disable XLA when running on older GPUs.')

    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')) or
         os.path.exists(os.path.join(mpi_home, 'lib64')) or
         os.path.exists(os.path.join(mpi_home, 'lib32'))))
    if not exists:
      print(
          'Invalid path to the MPI Toolkit. %s or %s or %s or %s cannot be found'
          % (os.path.join(mpi_home, 'include'),
             os.path.exists(os.path.join(mpi_home, 'lib')),
             os.path.exists(os.path.join(mpi_home, 'lib64')),
             os.path.exists(os.path.join(mpi_home, 'lib32'))))
    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')
  elif os.path.exists(os.path.join(mpi_home, 'lib64/libmpi.so')):
    symlink_force(
        os.path.join(mpi_home, 'lib64/libmpi.so'), 'third_party/mpi/libmpi.so')
  elif os.path.exists(os.path.join(mpi_home, 'lib32/libmpi.so')):
    symlink_force(
        os.path.join(mpi_home, 'lib32/libmpi.so'), 'third_party/mpi/libmpi.so')

  else:
    raise ValueError(
        'Cannot find the MPI library file in %s/lib or %s/lib64 or %s/lib32' %
        (mpi_home, mpi_home, mpi_home))


def system_specific_test_config(env):
  """Add default test flags required for TF tests to bazelrc."""
  write_to_bazelrc('test --flaky_test_attempts=3')
  write_to_bazelrc('test --test_size_filters=small,medium')
  write_to_bazelrc(
      'test --test_tag_filters=-benchmark-test,-no_oss,-oss_serial')
  write_to_bazelrc('test --build_tag_filters=-benchmark-test,-no_oss')
  if is_windows():
    if env.get('TF_NEED_CUDA', None) == '1':
      write_to_bazelrc(
          'test --test_tag_filters=-no_windows,-no_windows_gpu,-no_gpu')
      write_to_bazelrc(
          'test --build_tag_filters=-no_windows,-no_windows_gpu,-no_gpu')
    else:
      write_to_bazelrc('test --test_tag_filters=-no_windows,-gpu')
      write_to_bazelrc('test --build_tag_filters=-no_windows,-gpu')
  elif is_macos():
    write_to_bazelrc('test --test_tag_filters=-gpu,-nomac,-no_mac')
    write_to_bazelrc('test --build_tag_filters=-gpu,-nomac,-no_mac')
  elif is_linux():
    if env.get('TF_NEED_CUDA', None) == '1':
      write_to_bazelrc('test --test_tag_filters=-no_gpu')
      write_to_bazelrc('test --build_tag_filters=-no_gpu')
      write_to_bazelrc('test --test_env=LD_LIBRARY_PATH')
    else:
      write_to_bazelrc('test --test_tag_filters=-gpu')
      write_to_bazelrc('test --build_tag_filters=-gpu')


def set_system_libs_flag(environ_cp):
  syslibs = environ_cp.get('TF_SYSTEM_LIBS', '')
  if 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')
  # Fix winsock2.h conflicts
  write_to_bazelrc(
      'build --copt=-DWIN32_LEAN_AND_MEAN --host_copt=-DWIN32_LEAN_AND_MEAN')
  # 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')

  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 configure_apple_bazel_rules():
  """Configures Bazel rules for building on Apple platforms.

  Enables analyzing and building Apple Bazel rules on Apple platforms. This
  function will only be executed if `is_macos()` is true.
  """
  if not is_macos():
    return
  for filepath in APPLE_BAZEL_FILES:
    print(
        'Configuring %s file to analyze and build Bazel rules on Apple platforms.'
        % filepath)
    existing_filepath = os.path.join(_TF_WORKSPACE_ROOT, filepath + '.apple')
    renamed_filepath = os.path.join(_TF_WORKSPACE_ROOT, filepath)
    os.rename(existing_filepath, renamed_filepath)
  if _TF_CURRENT_BAZEL_VERSION is None or _TF_CURRENT_BAZEL_VERSION < 23000:
    print(
        'Building Bazel rules on Apple platforms requires Bazel 0.23 or later.')


def main():
  global _TF_WORKSPACE_ROOT
  global _TF_BAZELRC
  global _TF_CURRENT_BAZEL_VERSION

  parser = argparse.ArgumentParser()
  parser.add_argument(
      '--workspace',
      type=str,
      default=os.path.abspath(os.path.dirname(__file__)),
      help='The absolute path to your active Bazel workspace.')
  args = parser.parse_args()

  _TF_WORKSPACE_ROOT = args.workspace
  _TF_BAZELRC = os.path.join(_TF_WORKSPACE_ROOT, _TF_BAZELRC_FILENAME)

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

  current_bazel_version = check_bazel_version('0.19.0', '0.23.2')
  _TF_CURRENT_BAZEL_VERSION = convert_version_to_int(current_bazel_version)

  reset_tf_configure_bazelrc()

  cleanup_makefile()
  setup_python(environ_cp)

  if is_windows():
    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_NEED_MPI'] = '0'
    environ_cp['TF_SET_ANDROID_WORKSPACE'] = '0'

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

  xla_enabled_by_default = is_linux()
  set_build_var(environ_cp, 'TF_ENABLE_XLA', 'XLA JIT', 'with_xla_support',
                xla_enabled_by_default, '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)

  system_specific_test_config(os.environ)

  if get_var(
      environ_cp, 'TF_CONFIGURE_APPLE_BAZEL_RULES',
      'Configure Bazel rules for Apple platforms', False,
      ('Would you like to configure Bazel rules for building on Apple platforms?'
      ), 'Configuring Bazel rules for Apple platforms.',
      'Not configuring Bazel rules for Apple platforms.'):
    configure_apple_bazel_rules()

  print('Preconfigured Bazel build configs. You can use any of the below by '
        'adding "--config=<>" to your build command. See .bazelrc 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.')
  config_info_line('numa', 'Build with NUMA support.')
  config_info_line(
      'dynamic_kernels',
      '(Experimental) Build kernels into separate shared objects.')

  print('Preconfigured Bazel build configs to DISABLE default on features:')
  config_info_line('noaws', 'Disable AWS S3 filesystem support.')
  config_info_line('nogcp', 'Disable GCP support.')
  config_info_line('nohdfs', 'Disable HDFS support.')
  config_info_line('noignite', 'Disable Apache Ignite support.')
  config_info_line('nokafka', 'Disable Apache Kafka support.')
  config_info_line('nonccl', 'Disable NVIDIA NCCL support.')


if __name__ == '__main__':
  main()