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-rw-r--r--configure.py118
1 files changed, 72 insertions, 46 deletions
diff --git a/configure.py b/configure.py
index 31a83b4a15..f97bf8a668 100644
--- a/configure.py
+++ b/configure.py
@@ -35,8 +35,8 @@ except ImportError:
_DEFAULT_CUDA_VERSION = '9.0'
_DEFAULT_CUDNN_VERSION = '7'
-_DEFAULT_NCCL_VERSION = '1.3'
-_DEFAULT_CUDA_COMPUTE_CAPABILITIES = '3.5,5.2'
+_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 '
@@ -680,7 +680,7 @@ def create_android_sdk_rule(environ_cp):
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/ndk-bundle' % environ_cp['HOME']
+ default_sdk_path = '%s/library/Android/Sdk' % environ_cp['HOME']
else:
default_sdk_path = '%s/Android/Sdk' % environ_cp['HOME']
@@ -835,6 +835,8 @@ def set_tf_cuda_version(environ_cp):
'[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_path = 'lib/x64/cudart.lib'
@@ -880,7 +882,7 @@ def set_tf_cudnn_version(environ_cp):
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)
+ ' 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)
@@ -1095,8 +1097,10 @@ def set_tf_nccl_install_path(environ_cp):
raise ValueError('Currently NCCL is only supported on Linux platforms.')
ask_nccl_version = (
- 'Please specify the NCCL version you want to use. '
- '[Leave empty to default to NCCL %s]: ') % _DEFAULT_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(
@@ -1134,9 +1138,7 @@ def set_tf_nccl_install_path(environ_cp):
nccl_lib_path = os.path.join(nccl_install_path, nccl_lib_path)
nccl_hdr_path = os.path.join(nccl_install_path, 'include/nccl.h')
- nccl_license_path = os.path.join(nccl_install_path, 'NCCL-SLA.txt')
- if os.path.exists(nccl_lib_path) and os.path.exists(
- nccl_hdr_path) and os.path.exists(nccl_license_path):
+ 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)
@@ -1199,7 +1201,7 @@ def set_tf_cuda_compute_capabilities(environ_cp):
'https://developer.nvidia.com/cuda-gpus.\nPlease'
' note that each additional compute '
'capability significantly increases your '
- 'build time and binary size. [Default is: %s]' %
+ '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',
@@ -1234,28 +1236,13 @@ def set_tf_cuda_compute_capabilities(environ_cp):
def set_other_cuda_vars(environ_cp):
"""Set other CUDA related variables."""
- if is_windows():
- # The following three variables are needed for MSVC toolchain configuration
- # in Bazel
- environ_cp['CUDA_PATH'] = environ_cp.get('CUDA_TOOLKIT_PATH')
- environ_cp['CUDA_COMPUTE_CAPABILITIES'] = environ_cp.get(
- 'TF_CUDA_COMPUTE_CAPABILITIES')
- environ_cp['NO_WHOLE_ARCHIVE_OPTION'] = 1
- write_action_env_to_bazelrc('CUDA_PATH', environ_cp.get('CUDA_PATH'))
- write_action_env_to_bazelrc('CUDA_COMPUTE_CAPABILITIE',
- environ_cp.get('CUDA_COMPUTE_CAPABILITIE'))
- write_action_env_to_bazelrc('NO_WHOLE_ARCHIVE_OPTION',
- environ_cp.get('NO_WHOLE_ARCHIVE_OPTION'))
- write_to_bazelrc('build --config=win-cuda')
- write_to_bazelrc('test --config=win-cuda')
+ # 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:
- # 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')
+ write_to_bazelrc('build --config=cuda')
+ write_to_bazelrc('test --config=cuda')
def set_host_cxx_compiler(environ_cp):
@@ -1415,14 +1402,36 @@ def set_build_strip_flag():
write_to_bazelrc('build --strip=always')
-def set_windows_build_flags():
- if is_windows():
- # 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')
+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')
+
+ 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):
@@ -1442,7 +1451,7 @@ def main():
# environment variables.
environ_cp = dict(os.environ)
- check_bazel_version('0.10.0')
+ check_bazel_version('0.15.0')
reset_tf_configure_bazelrc(args.workspace)
cleanup_makefile()
@@ -1462,11 +1471,23 @@ def main():
# 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_GDR'] = '0'
+ environ_cp['TF_NEED_VERBS'] = '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_NEED_GCP', 'Google Cloud Platform',
@@ -1538,7 +1559,8 @@ def main():
set_grpc_build_flags()
set_cc_opt_flags(environ_cp)
set_build_strip_flag()
- set_windows_build_flags()
+ if is_windows():
+ set_windows_build_flags(environ_cp)
if get_var(
environ_cp, 'TF_SET_ANDROID_WORKSPACE', 'android workspace',
@@ -1550,11 +1572,15 @@ def main():
create_android_ndk_rule(environ_cp)
create_android_sdk_rule(environ_cp)
- 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.')
+ # 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.')
if __name__ == '__main__':
main()