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nGraph integration with TensorFlow

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* Added nGraph bridge as a third_party to be built with TensorFlow based on user selection.
* Added a limited set of C++ unit tests to verify the correctness of the computation
This commit is contained in:
Avijit 2018-07-24 23:35:27 -07:00 committed by GitHub
parent 80fb8679ab
commit 121e0161c5
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16 changed files with 1728 additions and 1045 deletions
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1
WORKSPACE
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@ -79,3 +79,4 @@ new_http_archive(
"http://download.tensorflow.org/models/speech_commands_v0.01.zip", "http://download.tensorflow.org/models/speech_commands_v0.01.zip",
], ],
) )

269
configure.py
View File

@ -153,14 +153,18 @@ def get_python_path(environ_cp, python_bin_path):
if environ_cp.get('PYTHONPATH'): if environ_cp.get('PYTHONPATH'):
python_paths = environ_cp.get('PYTHONPATH').split(':') python_paths = environ_cp.get('PYTHONPATH').split(':')
try: try:
library_paths = run_shell( library_paths = run_shell([
[python_bin_path, '-c', python_bin_path, '-c',
'import site; print("\\n".join(site.getsitepackages()))']).split('\n') 'import site; print("\\n".join(site.getsitepackages()))'
]).split('\n')
except subprocess.CalledProcessError: except subprocess.CalledProcessError:
library_paths = [run_shell( library_paths = [
[python_bin_path, '-c', run_shell([
python_bin_path, '-c',
'from distutils.sysconfig import get_python_lib;' 'from distutils.sysconfig import get_python_lib;'
'print(get_python_lib())'])] 'print(get_python_lib())'
])
]
all_paths = set(python_paths + library_paths) all_paths = set(python_paths + library_paths)
@ -173,14 +177,16 @@ def get_python_path(environ_cp, python_bin_path):
def get_python_major_version(python_bin_path): def get_python_major_version(python_bin_path):
"""Get the python major version.""" """Get the python major version."""
return run_shell([python_bin_path, '-c', 'import sys; print(sys.version[0])']) return run_shell(
[python_bin_path, '-c', 'import sys; print(sys.version[0])'])
def setup_python(environ_cp): def setup_python(environ_cp):
"""Setup python related env variables.""" """Setup python related env variables."""
# Get PYTHON_BIN_PATH, default is the current running python. # Get PYTHON_BIN_PATH, default is the current running python.
default_python_bin_path = sys.executable default_python_bin_path = sys.executable
ask_python_bin_path = ('Please specify the location of python. [Default is ' ask_python_bin_path = (
'Please specify the location of python. [Default is '
'%s]: ') % default_python_bin_path '%s]: ') % default_python_bin_path
while True: while True:
python_bin_path = get_from_env_or_user_or_default( python_bin_path = get_from_env_or_user_or_default(
@ -193,7 +199,8 @@ def setup_python(environ_cp):
elif not os.path.exists(python_bin_path): elif not os.path.exists(python_bin_path):
print('Invalid python path: %s cannot be found.' % python_bin_path) print('Invalid python path: %s cannot be found.' % python_bin_path)
else: else:
print('%s is not executable. Is it the python binary?' % python_bin_path) print('%s is not executable. Is it the python binary?' %
python_bin_path)
environ_cp['PYTHON_BIN_PATH'] = '' environ_cp['PYTHON_BIN_PATH'] = ''
# Convert python path to Windows style before checking lib and version # Convert python path to Windows style before checking lib and version
@ -230,8 +237,9 @@ def setup_python(environ_cp):
environ_cp['PYTHON_BIN_PATH'] = python_bin_path environ_cp['PYTHON_BIN_PATH'] = python_bin_path
# Write tools/python_bin_path.sh # Write tools/python_bin_path.sh
with open(os.path.join( with open(
_TF_WORKSPACE_ROOT, 'tools', 'python_bin_path.sh'), 'w') as f: os.path.join(_TF_WORKSPACE_ROOT, 'tools', 'python_bin_path.sh'),
'w') as f:
f.write('export PYTHON_BIN_PATH="%s"' % python_bin_path) f.write('export PYTHON_BIN_PATH="%s"' % python_bin_path)
@ -261,8 +269,8 @@ def cleanup_makefile():
These files could interfere with Bazel parsing. These files could interfere with Bazel parsing.
""" """
makefile_download_dir = os.path.join( makefile_download_dir = os.path.join(_TF_WORKSPACE_ROOT, 'tensorflow',
_TF_WORKSPACE_ROOT, 'tensorflow', 'contrib', 'makefile', 'downloads') 'contrib', 'makefile', 'downloads')
if os.path.isdir(makefile_download_dir): if os.path.isdir(makefile_download_dir):
for root, _, filenames in os.walk(makefile_download_dir): for root, _, filenames in os.walk(makefile_download_dir):
for f in filenames: for f in filenames:
@ -330,9 +338,8 @@ def get_var(environ_cp,
'Environment variable %s must be set as a boolean indicator.\n' 'Environment variable %s must be set as a boolean indicator.\n'
'The following are accepted as TRUE : %s.\n' 'The following are accepted as TRUE : %s.\n'
'The following are accepted as FALSE: %s.\n' 'The following are accepted as FALSE: %s.\n'
'Current value is %s.' % ( 'Current value is %s.' % (var_name, ', '.join(true_strings),
var_name, ', '.join(true_strings), ', '.join(false_strings), ', '.join(false_strings), var))
var))
while var is None: while var is None:
user_input_origin = get_input(question) user_input_origin = get_input(question)
@ -355,8 +362,12 @@ def get_var(environ_cp,
return var return var
def set_build_var(environ_cp, var_name, query_item, option_name, def set_build_var(environ_cp,
enabled_by_default, bazel_config_name=None): var_name,
query_item,
option_name,
enabled_by_default,
bazel_config_name=None):
"""Set if query_item will be enabled for the build. """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. Ask user if query_item will be enabled. Default is used if no input is given.
@ -372,15 +383,16 @@ def set_build_var(environ_cp, var_name, query_item, option_name,
bazel_config_name: Name for Bazel --config argument to enable build feature. 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))) var = str(
int(get_var(environ_cp, var_name, query_item, enabled_by_default)))
environ_cp[var_name] = var environ_cp[var_name] = var
if var == '1': if var == '1':
write_to_bazelrc('build --define %s=true' % option_name) write_to_bazelrc('build --define %s=true' % option_name)
elif bazel_config_name is not None: elif bazel_config_name is not None:
# TODO(mikecase): Migrate all users of configure.py to use --config Bazel # TODO(mikecase): Migrate all users of configure.py to use --config Bazel
# options and not to set build configs through environment variables. # options and not to set build configs through environment variables.
write_to_bazelrc('build:%s --define %s=true' write_to_bazelrc(
% (bazel_config_name, option_name)) 'build:%s --define %s=true' % (bazel_config_name, option_name))
def set_action_env_var(environ_cp, def set_action_env_var(environ_cp,
@ -447,7 +459,8 @@ def check_bazel_version(min_version):
if which('bazel') is None: if which('bazel') is None:
print('Cannot find bazel. Please install bazel.') print('Cannot find bazel. Please install bazel.')
sys.exit(0) sys.exit(0)
curr_version = run_shell(['bazel', '--batch', '--bazelrc=/dev/null', 'version']) curr_version = run_shell(
['bazel', '--batch', '--bazelrc=/dev/null', 'version'])
for line in curr_version.split('\n'): for line in curr_version.split('\n'):
if 'Build label: ' in line: if 'Build label: ' in line:
@ -466,7 +479,8 @@ def check_bazel_version(min_version):
print('You have bazel %s installed.' % curr_version) print('You have bazel %s installed.' % curr_version)
if curr_version_int < min_version_int: if curr_version_int < min_version_int:
print('Please upgrade your bazel installation to version %s or higher to ' print(
'Please upgrade your bazel installation to version %s or higher to '
'build TensorFlow!' % min_version) 'build TensorFlow!' % min_version)
sys.exit(0) sys.exit(0)
return curr_version return curr_version
@ -487,11 +501,12 @@ def set_cc_opt_flags(environ_cp):
default_cc_opt_flags = '/arch:AVX' default_cc_opt_flags = '/arch:AVX'
else: else:
default_cc_opt_flags = '-march=native' default_cc_opt_flags = '-march=native'
question = ('Please specify optimization flags to use during compilation when' question = (
'Please specify optimization flags to use during compilation when'
' bazel option "--config=opt" is specified [Default is %s]: ' ' bazel option "--config=opt" is specified [Default is %s]: '
) % default_cc_opt_flags ) % default_cc_opt_flags
cc_opt_flags = get_from_env_or_user_or_default(environ_cp, 'CC_OPT_FLAGS', cc_opt_flags = get_from_env_or_user_or_default(
question, default_cc_opt_flags) environ_cp, 'CC_OPT_FLAGS', question, default_cc_opt_flags)
for opt in cc_opt_flags.split(): for opt in cc_opt_flags.split():
write_to_bazelrc('build:opt --copt=%s' % opt) write_to_bazelrc('build:opt --copt=%s' % opt)
# It should be safe on the same build host. # It should be safe on the same build host.
@ -499,6 +514,7 @@ def set_cc_opt_flags(environ_cp):
write_to_bazelrc('build:opt --host_copt=-march=native') write_to_bazelrc('build:opt --host_copt=-march=native')
write_to_bazelrc('build:opt --define with_default_optimizations=true') write_to_bazelrc('build:opt --define with_default_optimizations=true')
def set_tf_cuda_clang(environ_cp): def set_tf_cuda_clang(environ_cp):
"""set TF_CUDA_CLANG action_env. """set TF_CUDA_CLANG action_env.
@ -561,7 +577,8 @@ def get_from_env_or_user_or_default(environ_cp, var_name, ask_for_var,
def set_clang_cuda_compiler_path(environ_cp): def set_clang_cuda_compiler_path(environ_cp):
"""Set CLANG_CUDA_COMPILER_PATH.""" """Set CLANG_CUDA_COMPILER_PATH."""
default_clang_path = which('clang') or '' default_clang_path = which('clang') or ''
ask_clang_path = ('Please specify which clang should be used as device and ' ask_clang_path = (
'Please specify which clang should be used as device and '
'host compiler. [Default is %s]: ') % default_clang_path 'host compiler. [Default is %s]: ') % default_clang_path
while True: while True:
@ -572,7 +589,8 @@ def set_clang_cuda_compiler_path(environ_cp):
break break
# Reset and retry # Reset and retry
print('Invalid clang path: %s cannot be found.' % clang_cuda_compiler_path) print('Invalid clang path: %s cannot be found.' %
clang_cuda_compiler_path)
environ_cp['CLANG_CUDA_COMPILER_PATH'] = '' environ_cp['CLANG_CUDA_COMPILER_PATH'] = ''
# Set CLANG_CUDA_COMPILER_PATH # Set CLANG_CUDA_COMPILER_PATH
@ -581,16 +599,14 @@ def set_clang_cuda_compiler_path(environ_cp):
clang_cuda_compiler_path) clang_cuda_compiler_path)
def prompt_loop_or_load_from_env( def prompt_loop_or_load_from_env(environ_cp,
environ_cp,
var_name, var_name,
var_default, var_default,
ask_for_var, ask_for_var,
check_success, check_success,
error_msg, error_msg,
suppress_default_error=False, suppress_default_error=False,
n_ask_attempts=_DEFAULT_PROMPT_ASK_ATTEMPTS n_ask_attempts=_DEFAULT_PROMPT_ASK_ATTEMPTS):
):
"""Loop over user prompts for an ENV param until receiving a valid response. """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 For the env param var_name, read from the environment or verify user input
@ -629,9 +645,7 @@ def prompt_loop_or_load_from_env(
) )
for _ in range(n_ask_attempts): for _ in range(n_ask_attempts):
val = get_from_env_or_user_or_default(environ_cp, val = get_from_env_or_user_or_default(environ_cp, var_name, full_query,
var_name,
full_query,
default) default)
if check_success(val): if check_success(val):
break break
@ -639,9 +653,9 @@ def prompt_loop_or_load_from_env(
print(error_msg % val) print(error_msg % val)
environ_cp[var_name] = '' environ_cp[var_name] = ''
else: else:
raise UserInputError('Invalid %s setting was provided %d times in a row. ' raise UserInputError(
'Assuming to be a scripting mistake.' % 'Invalid %s setting was provided %d times in a row. '
(var_name, n_ask_attempts)) 'Assuming to be a scripting mistake.' % (var_name, n_ask_attempts))
environ_cp[var_name] = val environ_cp[var_name] = val
return val return val
@ -650,16 +664,16 @@ def prompt_loop_or_load_from_env(
def create_android_ndk_rule(environ_cp): def create_android_ndk_rule(environ_cp):
"""Set ANDROID_NDK_HOME and write Android NDK WORKSPACE rule.""" """Set ANDROID_NDK_HOME and write Android NDK WORKSPACE rule."""
if is_windows() or is_cygwin(): if is_windows() or is_cygwin():
default_ndk_path = cygpath('%s/Android/Sdk/ndk-bundle' % default_ndk_path = cygpath(
environ_cp['APPDATA']) '%s/Android/Sdk/ndk-bundle' % environ_cp['APPDATA'])
elif is_macos(): elif is_macos():
default_ndk_path = '%s/library/Android/Sdk/ndk-bundle' % environ_cp['HOME'] default_ndk_path = '%s/library/Android/Sdk/ndk-bundle' % environ_cp['HOME']
else: else:
default_ndk_path = '%s/Android/Sdk/ndk-bundle' % environ_cp['HOME'] default_ndk_path = '%s/Android/Sdk/ndk-bundle' % environ_cp['HOME']
def valid_ndk_path(path): def valid_ndk_path(path):
return (os.path.exists(path) and return (os.path.exists(path)
os.path.exists(os.path.join(path, 'source.properties'))) and os.path.exists(os.path.join(path, 'source.properties')))
android_ndk_home_path = prompt_loop_or_load_from_env( android_ndk_home_path = prompt_loop_or_load_from_env(
environ_cp, environ_cp,
@ -668,8 +682,7 @@ def create_android_ndk_rule(environ_cp):
ask_for_var='Please specify the home path of the Android NDK to use.', ask_for_var='Please specify the home path of the Android NDK to use.',
check_success=valid_ndk_path, check_success=valid_ndk_path,
error_msg=('The path %s or its child file "source.properties" ' error_msg=('The path %s or its child file "source.properties" '
'does not exist.') 'does not exist.'))
)
write_action_env_to_bazelrc('ANDROID_NDK_HOME', android_ndk_home_path) write_action_env_to_bazelrc('ANDROID_NDK_HOME', android_ndk_home_path)
write_action_env_to_bazelrc('ANDROID_NDK_API_LEVEL', write_action_env_to_bazelrc('ANDROID_NDK_API_LEVEL',
check_ndk_level(android_ndk_home_path)) check_ndk_level(android_ndk_home_path))
@ -685,9 +698,9 @@ def create_android_sdk_rule(environ_cp):
default_sdk_path = '%s/Android/Sdk' % environ_cp['HOME'] default_sdk_path = '%s/Android/Sdk' % environ_cp['HOME']
def valid_sdk_path(path): def valid_sdk_path(path):
return (os.path.exists(path) and return (os.path.exists(path)
os.path.exists(os.path.join(path, 'platforms')) and and os.path.exists(os.path.join(path, 'platforms'))
os.path.exists(os.path.join(path, 'build-tools'))) and os.path.exists(os.path.join(path, 'build-tools')))
android_sdk_home_path = prompt_loop_or_load_from_env( android_sdk_home_path = prompt_loop_or_load_from_env(
environ_cp, environ_cp,
@ -703,8 +716,8 @@ def create_android_sdk_rule(environ_cp):
api_levels = [x.replace('android-', '') for x in api_levels] api_levels = [x.replace('android-', '') for x in api_levels]
def valid_api_level(api_level): def valid_api_level(api_level):
return os.path.exists(os.path.join(android_sdk_home_path, return os.path.exists(
'platforms', os.path.join(android_sdk_home_path, 'platforms',
'android-' + api_level)) 'android-' + api_level))
android_api_level = prompt_loop_or_load_from_env( android_api_level = prompt_loop_or_load_from_env(
@ -720,9 +733,8 @@ def create_android_sdk_rule(environ_cp):
versions = sorted(os.listdir(build_tools)) versions = sorted(os.listdir(build_tools))
def valid_build_tools(version): def valid_build_tools(version):
return os.path.exists(os.path.join(android_sdk_home_path, return os.path.exists(
'build-tools', os.path.join(android_sdk_home_path, 'build-tools', version))
version))
android_build_tools_version = prompt_loop_or_load_from_env( android_build_tools_version = prompt_loop_or_load_from_env(
environ_cp, environ_cp,
@ -736,10 +748,8 @@ def create_android_sdk_rule(environ_cp):
write_action_env_to_bazelrc('ANDROID_BUILD_TOOLS_VERSION', write_action_env_to_bazelrc('ANDROID_BUILD_TOOLS_VERSION',
android_build_tools_version) android_build_tools_version)
write_action_env_to_bazelrc('ANDROID_SDK_API_LEVEL', write_action_env_to_bazelrc('ANDROID_SDK_API_LEVEL', android_api_level)
android_api_level) write_action_env_to_bazelrc('ANDROID_SDK_HOME', android_sdk_home_path)
write_action_env_to_bazelrc('ANDROID_SDK_HOME',
android_sdk_home_path)
def check_ndk_level(android_ndk_home_path): def check_ndk_level(android_ndk_home_path):
@ -756,7 +766,8 @@ def check_ndk_level(android_ndk_home_path):
else: else:
raise Exception('Unable to parse NDK revision.') raise Exception('Unable to parse NDK revision.')
if int(ndk_api_level) not in _SUPPORTED_ANDROID_NDK_VERSIONS: 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 ' print(
'WARNING: The API level of the NDK in %s is %s, which is not '
'supported by Bazel (officially supported versions: %s). Please use ' 'supported by Bazel (officially supported versions: %s). Please use '
'another version. Compiling Android targets may result in confusing ' 'another version. Compiling Android targets may result in confusing '
'errors.\n' % (android_ndk_home_path, ndk_api_level, 'errors.\n' % (android_ndk_home_path, ndk_api_level,
@ -783,7 +794,8 @@ def set_gcc_host_compiler_path(environ_cp):
error_msg='Invalid gcc path. %s cannot be found.', error_msg='Invalid gcc path. %s cannot be found.',
) )
write_action_env_to_bazelrc('GCC_HOST_COMPILER_PATH', gcc_host_compiler_path) write_action_env_to_bazelrc('GCC_HOST_COMPILER_PATH',
gcc_host_compiler_path)
def reformat_version_sequence(version_str, sequence_count): def reformat_version_sequence(version_str, sequence_count):
@ -817,7 +829,8 @@ def set_tf_cuda_version(environ_cp):
for _ in range(_DEFAULT_PROMPT_ASK_ATTEMPTS): for _ in range(_DEFAULT_PROMPT_ASK_ATTEMPTS):
# Configure the Cuda SDK version to use. # Configure the Cuda SDK version to use.
tf_cuda_version = get_from_env_or_user_or_default( tf_cuda_version = get_from_env_or_user_or_default(
environ_cp, 'TF_CUDA_VERSION', ask_cuda_version, _DEFAULT_CUDA_VERSION) environ_cp, 'TF_CUDA_VERSION', ask_cuda_version,
_DEFAULT_CUDA_VERSION)
tf_cuda_version = reformat_version_sequence(str(tf_cuda_version), 2) tf_cuda_version = reformat_version_sequence(str(tf_cuda_version), 2)
# Find out where the CUDA toolkit is installed # Find out where the CUDA toolkit is installed
@ -832,7 +845,8 @@ def set_tf_cuda_version(environ_cp):
default_cuda_path = _DEFAULT_CUDA_PATH_LINUX default_cuda_path = _DEFAULT_CUDA_PATH_LINUX
ask_cuda_path = ('Please specify the location where CUDA %s toolkit is' ask_cuda_path = ('Please specify the location where CUDA %s toolkit is'
' installed. Refer to README.md for more details. ' ' installed. Refer to README.md for more details. '
'[Default is %s]: ') % (tf_cuda_version, default_cuda_path) '[Default is %s]: ') % (tf_cuda_version,
default_cuda_path)
cuda_toolkit_path = get_from_env_or_user_or_default( cuda_toolkit_path = get_from_env_or_user_or_default(
environ_cp, 'CUDA_TOOLKIT_PATH', ask_cuda_path, default_cuda_path) environ_cp, 'CUDA_TOOLKIT_PATH', ask_cuda_path, default_cuda_path)
if is_windows() or is_cygwin(): if is_windows() or is_cygwin():
@ -845,7 +859,8 @@ def set_tf_cuda_version(environ_cp):
elif is_macos(): elif is_macos():
cuda_rt_lib_path = 'lib/libcudart.%s.dylib' % tf_cuda_version cuda_rt_lib_path = 'lib/libcudart.%s.dylib' % tf_cuda_version
cuda_toolkit_path_full = os.path.join(cuda_toolkit_path, cuda_rt_lib_path) cuda_toolkit_path_full = os.path.join(cuda_toolkit_path,
cuda_rt_lib_path)
if os.path.exists(cuda_toolkit_path_full): if os.path.exists(cuda_toolkit_path_full):
break break
@ -856,7 +871,8 @@ def set_tf_cuda_version(environ_cp):
environ_cp['CUDA_TOOLKIT_PATH'] = '' environ_cp['CUDA_TOOLKIT_PATH'] = ''
else: else:
raise UserInputError('Invalid TF_CUDA_SETTING setting was provided %d ' raise UserInputError(
'Invalid TF_CUDA_SETTING setting was provided %d '
'times in a row. Assuming to be a scripting mistake.' % 'times in a row. Assuming to be a scripting mistake.' %
_DEFAULT_PROMPT_ASK_ATTEMPTS) _DEFAULT_PROMPT_ASK_ATTEMPTS)
@ -880,11 +896,13 @@ def set_tf_cudnn_version(environ_cp):
tf_cudnn_version = reformat_version_sequence(str(tf_cudnn_version), 1) tf_cudnn_version = reformat_version_sequence(str(tf_cudnn_version), 1)
default_cudnn_path = environ_cp.get('CUDA_TOOLKIT_PATH') default_cudnn_path = environ_cp.get('CUDA_TOOLKIT_PATH')
ask_cudnn_path = (r'Please specify the location where cuDNN %s library is ' ask_cudnn_path = (
r'Please specify the location where cuDNN %s library is '
'installed. Refer to README.md for more details. [Default' '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( cudnn_install_path = get_from_env_or_user_or_default(
environ_cp, 'CUDNN_INSTALL_PATH', ask_cudnn_path, default_cudnn_path) environ_cp, 'CUDNN_INSTALL_PATH', ask_cudnn_path,
default_cudnn_path)
# Result returned from "read" will be used unexpanded. That make "~" # Result returned from "read" will be used unexpanded. That make "~"
# unusable. Going through one more level of expansion to handle that. # unusable. Going through one more level of expansion to handle that.
@ -903,7 +921,8 @@ def set_tf_cudnn_version(environ_cp):
cuda_dnn_lib_path = 'lib/libcudnn.%s.dylib' % tf_cudnn_version 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_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_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_full = os.path.join(cudnn_install_path,
cuda_dnn_lib_alt_path) cuda_dnn_lib_alt_path)
if os.path.exists(cuda_dnn_lib_path_full) or os.path.exists( if os.path.exists(cuda_dnn_lib_path_full) or os.path.exists(
@ -920,7 +939,8 @@ def set_tf_cudnn_version(environ_cp):
cudnn_path_from_ldconfig = cudnn_path_from_ldconfig.group(1) cudnn_path_from_ldconfig = cudnn_path_from_ldconfig.group(1)
if os.path.exists('%s.%s' % (cudnn_path_from_ldconfig, if os.path.exists('%s.%s' % (cudnn_path_from_ldconfig,
tf_cudnn_version)): tf_cudnn_version)):
cudnn_install_path = os.path.dirname(cudnn_path_from_ldconfig) cudnn_install_path = os.path.dirname(
cudnn_path_from_ldconfig)
break break
# Reset and Retry # Reset and Retry
@ -934,7 +954,8 @@ def set_tf_cudnn_version(environ_cp):
environ_cp['TF_CUDNN_VERSION'] = '' environ_cp['TF_CUDNN_VERSION'] = ''
else: else:
raise UserInputError('Invalid TF_CUDNN setting was provided %d ' raise UserInputError(
'Invalid TF_CUDNN setting was provided %d '
'times in a row. Assuming to be a scripting mistake.' % 'times in a row. Assuming to be a scripting mistake.' %
_DEFAULT_PROMPT_ASK_ATTEMPTS) _DEFAULT_PROMPT_ASK_ATTEMPTS)
@ -987,7 +1008,8 @@ def set_tf_tensorrt_install_path(environ_cp):
UserInputError: if user has provided invalid input multiple times. UserInputError: if user has provided invalid input multiple times.
""" """
if not is_linux(): if not is_linux():
raise ValueError('Currently TensorRT is only supported on Linux platform.') raise ValueError(
'Currently TensorRT is only supported on Linux platform.')
# Ask user whether to add TensorRT support. # Ask user whether to add TensorRT support.
if str(int(get_var(environ_cp, 'TF_NEED_TENSORRT', 'TensorRT', if str(int(get_var(environ_cp, 'TF_NEED_TENSORRT', 'TensorRT',
@ -1004,7 +1026,8 @@ def set_tf_tensorrt_install_path(environ_cp):
# Result returned from "read" will be used unexpanded. That make "~" # Result returned from "read" will be used unexpanded. That make "~"
# unusable. Going through one more level of expansion to handle that. # unusable. Going through one more level of expansion to handle that.
trt_install_path = os.path.realpath(os.path.expanduser(trt_install_path)) trt_install_path = os.path.realpath(
os.path.expanduser(trt_install_path))
def find_libs(search_path): def find_libs(search_path):
"""Search for libnvinfer.so in "search_path".""" """Search for libnvinfer.so in "search_path"."""
@ -1012,14 +1035,14 @@ def set_tf_tensorrt_install_path(environ_cp):
if os.path.exists(search_path) and os.path.isdir(search_path): if os.path.exists(search_path) and os.path.isdir(search_path):
fl.update([ fl.update([
os.path.realpath(os.path.join(search_path, x)) os.path.realpath(os.path.join(search_path, x))
for x in os.listdir(search_path) for x in os.listdir(search_path) if 'libnvinfer.so' in x
if 'libnvinfer.so' in x
]) ])
return fl return fl
possible_files = find_libs(trt_install_path) 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, 'lib')))
possible_files.update(find_libs(os.path.join(trt_install_path, 'lib64'))) possible_files.update(
find_libs(os.path.join(trt_install_path, 'lib64')))
cuda_ver = convert_version_to_int(environ_cp['TF_CUDA_VERSION']) cuda_ver = convert_version_to_int(environ_cp['TF_CUDA_VERSION'])
cudnn_ver = convert_version_to_int(environ_cp['TF_CUDNN_VERSION']) cudnn_ver = convert_version_to_int(environ_cp['TF_CUDNN_VERSION'])
nvinfer_pattern = re.compile('.*libnvinfer.so.?(.*)$') nvinfer_pattern = re.compile('.*libnvinfer.so.?(.*)$')
@ -1049,14 +1072,17 @@ def set_tf_tensorrt_install_path(environ_cp):
if os.path.exists(libnvinfer_path_from_ldconfig): if os.path.exists(libnvinfer_path_from_ldconfig):
if is_cuda_compatible(libnvinfer_path_from_ldconfig, cuda_ver, if is_cuda_compatible(libnvinfer_path_from_ldconfig, cuda_ver,
cudnn_ver): cudnn_ver):
trt_install_path = os.path.dirname(libnvinfer_path_from_ldconfig) trt_install_path = os.path.dirname(
libnvinfer_path_from_ldconfig)
tf_tensorrt_version = search_result.group(1) tf_tensorrt_version = search_result.group(1)
break break
# Reset and Retry # Reset and Retry
if possible_files: if possible_files:
print('TensorRT libraries found in one the following directories', print(
'are not compatible with selected cuda and cudnn installations') 'TensorRT libraries found in one the following directories',
'are not compatible with selected cuda and cudnn installations'
)
print(trt_install_path) print(trt_install_path)
print(os.path.join(trt_install_path, 'lib')) print(os.path.join(trt_install_path, 'lib'))
print(os.path.join(trt_install_path, 'lib64')) print(os.path.join(trt_install_path, 'lib64'))
@ -1064,7 +1090,8 @@ def set_tf_tensorrt_install_path(environ_cp):
print(libnvinfer_path_from_ldconfig) print(libnvinfer_path_from_ldconfig)
else: else:
print( print(
'Invalid path to TensorRT. None of the following files can be found:') 'Invalid path to TensorRT. None of the following files can be found:'
)
print(trt_install_path) print(trt_install_path)
print(os.path.join(trt_install_path, 'lib')) print(os.path.join(trt_install_path, 'lib'))
print(os.path.join(trt_install_path, 'lib64')) print(os.path.join(trt_install_path, 'lib64'))
@ -1072,7 +1099,8 @@ def set_tf_tensorrt_install_path(environ_cp):
print(libnvinfer_path_from_ldconfig) print(libnvinfer_path_from_ldconfig)
else: else:
raise UserInputError('Invalid TF_TENSORRT setting was provided %d ' raise UserInputError(
'Invalid TF_TENSORRT setting was provided %d '
'times in a row. Assuming to be a scripting mistake.' % 'times in a row. Assuming to be a scripting mistake.' %
_DEFAULT_PROMPT_ASK_ATTEMPTS) _DEFAULT_PROMPT_ASK_ATTEMPTS)
@ -1094,7 +1122,8 @@ def set_tf_nccl_install_path(environ_cp):
UserInputError: if user has provided invalid input multiple times. UserInputError: if user has provided invalid input multiple times.
""" """
if not is_linux(): if not is_linux():
raise ValueError('Currently NCCL is only supported on Linux platforms.') raise ValueError(
'Currently NCCL is only supported on Linux platforms.')
ask_nccl_version = ( ask_nccl_version = (
'Please specify the NCCL version you want to use. ' 'Please specify the NCCL version you want to use. '
@ -1102,7 +1131,8 @@ def set_tf_nccl_install_path(environ_cp):
for _ in range(_DEFAULT_PROMPT_ASK_ATTEMPTS): for _ in range(_DEFAULT_PROMPT_ASK_ATTEMPTS):
tf_nccl_version = get_from_env_or_user_or_default( tf_nccl_version = get_from_env_or_user_or_default(
environ_cp, 'TF_NCCL_VERSION', ask_nccl_version, _DEFAULT_NCCL_VERSION) environ_cp, 'TF_NCCL_VERSION', ask_nccl_version,
_DEFAULT_NCCL_VERSION)
tf_nccl_version = reformat_version_sequence(str(tf_nccl_version), 1) tf_nccl_version = reformat_version_sequence(str(tf_nccl_version), 1)
if tf_nccl_version == '1': if tf_nccl_version == '1':
@ -1115,7 +1145,8 @@ def set_tf_nccl_install_path(environ_cp):
# NCCL_INSTALL_PATH, pass separate NCCL_LIB_PATH and NCCL_HDR_PATH to # NCCL_INSTALL_PATH, pass separate NCCL_LIB_PATH and NCCL_HDR_PATH to
# nccl_configure.bzl # nccl_configure.bzl
default_nccl_path = environ_cp.get('CUDA_TOOLKIT_PATH') default_nccl_path = environ_cp.get('CUDA_TOOLKIT_PATH')
ask_nccl_path = (r'Please specify the location where NCCL %s library is ' ask_nccl_path = (
r'Please specify the location where NCCL %s library is '
'installed. Refer to README.md for more details. [Default ' 'installed. Refer to README.md for more details. [Default '
'is %s]:') % (tf_nccl_version, default_nccl_path) 'is %s]:') % (tf_nccl_version, default_nccl_path)
nccl_install_path = get_from_env_or_user_or_default( nccl_install_path = get_from_env_or_user_or_default(
@ -1123,7 +1154,8 @@ def set_tf_nccl_install_path(environ_cp):
# Result returned from "read" will be used unexpanded. That make "~" # Result returned from "read" will be used unexpanded. That make "~"
# unusable. Going through one more level of expansion to handle that. # unusable. Going through one more level of expansion to handle that.
nccl_install_path = os.path.realpath(os.path.expanduser(nccl_install_path)) nccl_install_path = os.path.realpath(
os.path.expanduser(nccl_install_path))
if is_windows() or is_cygwin(): if is_windows() or is_cygwin():
nccl_install_path = cygpath(nccl_install_path) nccl_install_path = cygpath(nccl_install_path)
@ -1145,13 +1177,15 @@ def set_tf_nccl_install_path(environ_cp):
break break
# Reset and Retry # Reset and Retry
print('Invalid path to NCCL %s toolkit, %s or %s not found. Please use the ' 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, 'O/S agnostic package of NCCL 2' % (tf_nccl_version, nccl_lib_path,
nccl_hdr_path)) nccl_hdr_path))
environ_cp['TF_NCCL_VERSION'] = '' environ_cp['TF_NCCL_VERSION'] = ''
else: else:
raise UserInputError('Invalid TF_NCCL setting was provided %d ' raise UserInputError(
'Invalid TF_NCCL setting was provided %d '
'times in a row. Assuming to be a scripting mistake.' % 'times in a row. Assuming to be a scripting mistake.' %
_DEFAULT_PROMPT_ASK_ATTEMPTS) _DEFAULT_PROMPT_ASK_ATTEMPTS)
@ -1170,7 +1204,8 @@ def get_native_cuda_compute_capabilities(environ_cp):
""" """
device_query_bin = os.path.join( device_query_bin = os.path.join(
environ_cp.get('CUDA_TOOLKIT_PATH'), 'extras/demo_suite/deviceQuery') 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): if os.path.isfile(device_query_bin) and os.access(device_query_bin,
os.X_OK):
try: try:
output = run_shell(device_query_bin).split('\n') output = run_shell(device_query_bin).split('\n')
pattern = re.compile('[0-9]*\\.[0-9]*') pattern = re.compile('[0-9]*\\.[0-9]*')
@ -1210,7 +1245,8 @@ def set_tf_cuda_compute_capabilities(environ_cp):
all_valid = True all_valid = True
# Remove all whitespace characters before splitting the string # Remove all whitespace characters before splitting the string
# that users may insert by accident, as this will result in error # that users may insert by accident, as this will result in error
tf_cuda_compute_capabilities = ''.join(tf_cuda_compute_capabilities.split()) tf_cuda_compute_capabilities = ''.join(
tf_cuda_compute_capabilities.split())
for compute_capability in tf_cuda_compute_capabilities.split(','): for compute_capability in tf_cuda_compute_capabilities.split(','):
m = re.match('[0-9]+.[0-9]+', compute_capability) m = re.match('[0-9]+.[0-9]+', compute_capability)
if not m: if not m:
@ -1219,7 +1255,9 @@ def set_tf_cuda_compute_capabilities(environ_cp):
else: else:
ver = int(m.group(0).split('.')[0]) ver = int(m.group(0).split('.')[0])
if ver < 3: if ver < 3:
print('Only compute capabilities 3.0 or higher are supported.') print(
'Only compute capabilities 3.0 or higher are supported.'
)
all_valid = False all_valid = False
if all_valid: if all_valid:
@ -1270,7 +1308,8 @@ def set_host_c_compiler(environ_cp):
environ_cp, environ_cp,
var_name='HOST_C_COMPILER', var_name='HOST_C_COMPILER',
var_default=default_c_host_compiler, var_default=default_c_host_compiler,
ask_for_var=('Please specify which C compiler should be used as the host ' ask_for_var=(
'Please specify which C compiler should be used as the host '
'C compiler.'), 'C compiler.'),
check_success=os.path.exists, check_success=os.path.exists,
error_msg='Invalid C compiler path. %s cannot be found.', error_msg='Invalid C compiler path. %s cannot be found.',
@ -1289,8 +1328,7 @@ def set_computecpp_toolkit_path(environ_cp):
else: else:
sycl_rt_lib_path = '' sycl_rt_lib_path = ''
sycl_rt_lib_path_full = os.path.join(toolkit_path, sycl_rt_lib_path_full = os.path.join(toolkit_path, sycl_rt_lib_path)
sycl_rt_lib_path)
exists = os.path.exists(sycl_rt_lib_path_full) exists = os.path.exists(sycl_rt_lib_path_full)
if not exists: if not exists:
print('Invalid SYCL %s library path. %s cannot be found' % print('Invalid SYCL %s library path. %s cannot be found' %
@ -1318,8 +1356,8 @@ def set_trisycl_include_dir(environ_cp):
ask_trisycl_include_dir = ('Please specify the location of the triSYCL ' ask_trisycl_include_dir = ('Please specify the location of the triSYCL '
'include directory. (Use --config=sycl_trisycl ' 'include directory. (Use --config=sycl_trisycl '
'when building with Bazel) ' 'when building with Bazel) '
'[Default is %s]: ' '[Default is %s]: ') % (
) % (_DEFAULT_TRISYCL_INCLUDE_DIR) _DEFAULT_TRISYCL_INCLUDE_DIR)
while True: while True:
trisycl_include_dir = get_from_env_or_user_or_default( trisycl_include_dir = get_from_env_or_user_or_default(
@ -1328,13 +1366,12 @@ def set_trisycl_include_dir(environ_cp):
if os.path.exists(trisycl_include_dir): if os.path.exists(trisycl_include_dir):
break break
print('Invalid triSYCL include directory, %s cannot be found' print('Invalid triSYCL include directory, %s cannot be found' %
% (trisycl_include_dir)) (trisycl_include_dir))
# Set TRISYCL_INCLUDE_DIR # Set TRISYCL_INCLUDE_DIR
environ_cp['TRISYCL_INCLUDE_DIR'] = trisycl_include_dir environ_cp['TRISYCL_INCLUDE_DIR'] = trisycl_include_dir
write_action_env_to_bazelrc('TRISYCL_INCLUDE_DIR', write_action_env_to_bazelrc('TRISYCL_INCLUDE_DIR', trisycl_include_dir)
trisycl_include_dir)
def set_mpi_home(environ_cp): def set_mpi_home(environ_cp):
@ -1344,8 +1381,8 @@ def set_mpi_home(environ_cp):
default_mpi_home = os.path.dirname(os.path.dirname(default_mpi_home)) default_mpi_home = os.path.dirname(os.path.dirname(default_mpi_home))
def valid_mpi_path(mpi_home): def valid_mpi_path(mpi_home):
exists = (os.path.exists(os.path.join(mpi_home, 'include')) and exists = (os.path.exists(os.path.join(mpi_home, 'include'))
os.path.exists(os.path.join(mpi_home, 'lib'))) and os.path.exists(os.path.join(mpi_home, 'lib')))
if not exists: if not exists:
print('Invalid path to the MPI Toolkit. %s or %s cannot be found' % print('Invalid path to the MPI Toolkit. %s or %s cannot be found' %
(os.path.join(mpi_home, 'include'), (os.path.join(mpi_home, 'include'),
@ -1370,7 +1407,8 @@ def set_other_mpi_vars(environ_cp):
# Determine if we use OpenMPI or MVAPICH, these require different header files # Determine if we use OpenMPI or MVAPICH, these require different header files
# to be included here to make bazel dependency checker happy # to be included here to make bazel dependency checker happy
if os.path.exists(os.path.join(mpi_home, 'include/mpi_portable_platform.h')): if os.path.exists(
os.path.join(mpi_home, 'include/mpi_portable_platform.h')):
symlink_force( symlink_force(
os.path.join(mpi_home, 'include/mpi_portable_platform.h'), os.path.join(mpi_home, 'include/mpi_portable_platform.h'),
'third_party/mpi/mpi_portable_platform.h') 'third_party/mpi/mpi_portable_platform.h')
@ -1382,16 +1420,19 @@ def set_other_mpi_vars(environ_cp):
symlink_force( symlink_force(
os.path.join(mpi_home, 'include/mpio.h'), 'third_party/mpi/mpio.h') os.path.join(mpi_home, 'include/mpio.h'), 'third_party/mpi/mpio.h')
symlink_force( symlink_force(
os.path.join(mpi_home, 'include/mpicxx.h'), 'third_party/mpi/mpicxx.h') os.path.join(mpi_home, 'include/mpicxx.h'),
'third_party/mpi/mpicxx.h')
# TODO(gunan): avoid editing files in configure # TODO(gunan): avoid editing files in configure
sed_in_place('third_party/mpi/mpi.bzl', 'MPI_LIB_IS_OPENMPI=True', sed_in_place('third_party/mpi/mpi.bzl', 'MPI_LIB_IS_OPENMPI=True',
'MPI_LIB_IS_OPENMPI=False') 'MPI_LIB_IS_OPENMPI=False')
if os.path.exists(os.path.join(mpi_home, 'lib/libmpi.so')): if os.path.exists(os.path.join(mpi_home, 'lib/libmpi.so')):
symlink_force( symlink_force(
os.path.join(mpi_home, 'lib/libmpi.so'), 'third_party/mpi/libmpi.so') os.path.join(mpi_home, 'lib/libmpi.so'),
'third_party/mpi/libmpi.so')
else: else:
raise ValueError('Cannot find the MPI library file in %s/lib' % mpi_home) raise ValueError(
'Cannot find the MPI library file in %s/lib' % mpi_home)
def set_grpc_build_flags(): def set_grpc_build_flags():
@ -1419,7 +1460,8 @@ def config_info_line(name, help_text):
def main(): def main():
parser = argparse.ArgumentParser() parser = argparse.ArgumentParser()
parser.add_argument("--workspace", parser.add_argument(
"--workspace",
type=str, type=str,
default=_TF_WORKSPACE_ROOT, default=_TF_WORKSPACE_ROOT,
help="The absolute path to your active Bazel workspace.") help="The absolute path to your active Bazel workspace.")
@ -1466,24 +1508,27 @@ def main():
'with_kafka_support', True, 'kafka') 'with_kafka_support', True, 'kafka')
set_build_var(environ_cp, 'TF_ENABLE_XLA', 'XLA JIT', 'with_xla_support', set_build_var(environ_cp, 'TF_ENABLE_XLA', 'XLA JIT', 'with_xla_support',
False, 'xla') False, 'xla')
set_build_var(environ_cp, 'TF_NEED_GDR', 'GDR', 'with_gdr_support', set_build_var(environ_cp, 'TF_NEED_GDR', 'GDR', 'with_gdr_support', False,
False, 'gdr') 'gdr')
set_build_var(environ_cp, 'TF_NEED_VERBS', 'VERBS', 'with_verbs_support', set_build_var(environ_cp, 'TF_NEED_VERBS', 'VERBS', 'with_verbs_support',
False, 'verbs') False, 'verbs')
set_build_var(environ_cp, 'TF_NEED_NGRAPH', 'nGraph',
'with_ngraph_support', False, 'ngraph')
set_action_env_var(environ_cp, 'TF_NEED_OPENCL_SYCL', 'OpenCL SYCL', False) set_action_env_var(environ_cp, 'TF_NEED_OPENCL_SYCL', 'OpenCL SYCL', False)
if environ_cp.get('TF_NEED_OPENCL_SYCL') == '1': if environ_cp.get('TF_NEED_OPENCL_SYCL') == '1':
set_host_cxx_compiler(environ_cp) set_host_cxx_compiler(environ_cp)
set_host_c_compiler(environ_cp) set_host_c_compiler(environ_cp)
set_action_env_var(environ_cp, 'TF_NEED_COMPUTECPP', 'ComputeCPP', True) set_action_env_var(environ_cp, 'TF_NEED_COMPUTECPP', 'ComputeCPP',
True)
if environ_cp.get('TF_NEED_COMPUTECPP') == '1': if environ_cp.get('TF_NEED_COMPUTECPP') == '1':
set_computecpp_toolkit_path(environ_cp) set_computecpp_toolkit_path(environ_cp)
else: else:
set_trisycl_include_dir(environ_cp) set_trisycl_include_dir(environ_cp)
set_action_env_var(environ_cp, 'TF_NEED_CUDA', 'CUDA', False) set_action_env_var(environ_cp, 'TF_NEED_CUDA', 'CUDA', False)
if (environ_cp.get('TF_NEED_CUDA') == '1' and if (environ_cp.get('TF_NEED_CUDA') == '1'
'TF_CUDA_CONFIG_REPO' not in environ_cp): and 'TF_CUDA_CONFIG_REPO' not in environ_cp):
set_tf_cuda_version(environ_cp) set_tf_cuda_version(environ_cp)
set_tf_cudnn_version(environ_cp) set_tf_cudnn_version(environ_cp)
if is_linux(): if is_linux():
@ -1527,12 +1572,10 @@ def main():
set_build_strip_flag() set_build_strip_flag()
set_windows_build_flags() set_windows_build_flags()
if get_var( if get_var(environ_cp, 'TF_SET_ANDROID_WORKSPACE', 'android workspace',
environ_cp, 'TF_SET_ANDROID_WORKSPACE', 'android workspace',
False, False,
('Would you like to interactively configure ./WORKSPACE for ' ('Would you like to interactively configure ./WORKSPACE for '
'Android builds?'), 'Android builds?'), 'Searching for NDK and SDK installations.',
'Searching for NDK and SDK installations.',
'Not configuring the WORKSPACE for Android builds.'): 'Not configuring the WORKSPACE for Android builds.'):
create_android_ndk_rule(environ_cp) create_android_ndk_rule(environ_cp)
create_android_sdk_rule(environ_cp) create_android_sdk_rule(environ_cp)
@ -1541,7 +1584,9 @@ def main():
'adding "--config=<>" to your build command. See tools/bazel.rc for ' 'adding "--config=<>" to your build command. See tools/bazel.rc for '
'more details.') 'more details.')
config_info_line('mkl', 'Build with MKL support.') config_info_line('mkl', 'Build with MKL support.')
config_info_line('monolithic', 'Config for mostly static monolithic build.') config_info_line('monolithic',
'Config for mostly static monolithic build.')
if __name__ == '__main__': if __name__ == '__main__':
main() main()

14
tensorflow/BUILD
View File

@ -24,6 +24,8 @@ load(
"gen_api_init_files", # @unused "gen_api_init_files", # @unused
) )
load("//third_party/ngraph:build_defs.bzl", "if_ngraph")
# Config setting for determining if we are building for Android. # Config setting for determining if we are building for Android.
config_setting( config_setting(
name = "android", name = "android",
@ -408,6 +410,14 @@ config_setting(
visibility = ["//visibility:public"], visibility = ["//visibility:public"],
) )
# This flag is set from the configure step when the user selects with nGraph option.
# By default it should be false
config_setting(
name = "with_ngraph_support",
values = {"define": "with_ngraph_support=true"},
visibility = ["//visibility:public"],
)
package_group( package_group(
name = "internal", name = "internal",
packages = [ packages = [
@ -540,7 +550,7 @@ tf_cc_shared_object(
"//tensorflow/c:version_script.lds", "//tensorflow/c:version_script.lds",
"//tensorflow/c/eager:c_api", "//tensorflow/c/eager:c_api",
"//tensorflow/core:tensorflow", "//tensorflow/core:tensorflow",
], ]
) )
tf_cc_shared_object( tf_cc_shared_object(
@ -568,7 +578,7 @@ tf_cc_shared_object(
"//tensorflow/cc:scope", "//tensorflow/cc:scope",
"//tensorflow/cc/profiler", "//tensorflow/cc/profiler",
"//tensorflow/core:tensorflow", "//tensorflow/core:tensorflow",
], ] + if_ngraph(["@ngraph_tf//:ngraph_tf"])
) )
exports_files( exports_files(

3
tensorflow/core/BUILD
View File

@ -2325,6 +2325,7 @@ tf_generate_proto_text_sources(
":lib_internal", ":lib_internal",
":protos_all_proto_cc", ":protos_all_proto_cc",
], ],
visibility = ["//visibility:public"],
) )
cc_library( cc_library(
@ -2435,6 +2436,7 @@ cc_header_only_library(
deps = [ deps = [
":core_cpu_lib", ":core_cpu_lib",
], ],
visibility = ["//visibility:public"],
) )
tf_cuda_library( tf_cuda_library(
@ -2560,6 +2562,7 @@ tf_cuda_library(
cc_library( cc_library(
name = "protos_cc", name = "protos_cc",
deps = ["//tensorflow/core/platform/default/build_config:protos_cc"], deps = ["//tensorflow/core/platform/default/build_config:protos_cc"],
visibility = ["//visibility:public"],
) )
# Library containing all of the graph construction code that is # Library containing all of the graph construction code that is

1
tensorflow/core/common_runtime/threadpool_device_factory.cc
View File

@ -19,6 +19,7 @@ limitations under the License.
#include <vector> #include <vector>
#include "tensorflow/core/common_runtime/device_factory.h" #include "tensorflow/core/common_runtime/device_factory.h"
#include "tensorflow/core/framework/allocator.h" #include "tensorflow/core/framework/allocator.h"
#include "tensorflow/core/lib/io/path.h"
#include "tensorflow/core/public/session_options.h" #include "tensorflow/core/public/session_options.h"
namespace tensorflow { namespace tensorflow {

4
tensorflow/python/BUILD
View File

@ -44,6 +44,7 @@ load("//tensorflow/core:platform/default/build_config_root.bzl", "tf_additional_
load("//tensorflow/core:platform/default/build_config_root.bzl", "tf_additional_mpi_deps") load("//tensorflow/core:platform/default/build_config_root.bzl", "tf_additional_mpi_deps")
load("//tensorflow/core:platform/default/build_config_root.bzl", "tf_additional_gdr_deps") load("//tensorflow/core:platform/default/build_config_root.bzl", "tf_additional_gdr_deps")
load("//tensorflow/core:platform/default/build_config_root.bzl", "if_static") load("//tensorflow/core:platform/default/build_config_root.bzl", "if_static")
load("//third_party/ngraph:build_defs.bzl","if_ngraph")
py_library( py_library(
name = "python", name = "python",
@ -3669,7 +3670,8 @@ tf_py_wrap_cc(
tf_additional_plugin_deps() + tf_additional_plugin_deps() +
tf_additional_verbs_deps() + tf_additional_verbs_deps() +
tf_additional_mpi_deps() + tf_additional_mpi_deps() +
tf_additional_gdr_deps()), tf_additional_gdr_deps())+
if_ngraph(["@ngraph_tf//:ngraph_tf"])
) )
# ** Targets for Windows build (start) ** # ** Targets for Windows build (start) **

5
tensorflow/tensorflow.bzl
View File

@ -24,6 +24,10 @@ load(
"if_mkl", "if_mkl",
"if_mkl_lnx_x64" "if_mkl_lnx_x64"
) )
load(
"//third_party/ngraph:build_defs.bzl",
"if_ngraph",
)
def register_extension_info(**kwargs): def register_extension_info(**kwargs):
pass pass
@ -214,6 +218,7 @@ def tf_copts(android_optimization_level_override="-O2", is_external=False):
+ if_cuda(["-DGOOGLE_CUDA=1"]) + if_cuda(["-DGOOGLE_CUDA=1"])
+ if_tensorrt(["-DGOOGLE_TENSORRT=1"]) + if_tensorrt(["-DGOOGLE_TENSORRT=1"])
+ if_mkl(["-DINTEL_MKL=1", "-DEIGEN_USE_VML"]) + if_mkl(["-DINTEL_MKL=1", "-DEIGEN_USE_VML"])
+ if_ngraph(["-DINTEL_NGRAPH=1"])
+ if_mkl_lnx_x64(["-fopenmp"]) + if_mkl_lnx_x64(["-fopenmp"])
+ if_android_arm(["-mfpu=neon"]) + if_android_arm(["-mfpu=neon"])
+ if_linux_x86_64(["-msse3"]) + if_linux_x86_64(["-msse3"])

33
tensorflow/workspace.bzl
View File

@ -803,6 +803,39 @@ def tf_workspace(path_prefix="", tf_repo_name=""):
strip_prefix = "rules_android-0.1.1", strip_prefix = "rules_android-0.1.1",
) )
tf_http_archive(
name = "ngraph",
urls = [
"https://mirror.bazel.build/github.com/NervanaSystems/ngraph/archive/v0.5.0.tar.gz",
"https://github.com/NervanaSystems/ngraph/archive/v0.5.0.tar.gz",
],
sha256 = "cb35d3d98836f615408afd18371fb13e3400711247e0d822ba7f306c45e9bb2c",
strip_prefix = "ngraph-0.5.0",
build_file = clean_dep("//third_party/ngraph:ngraph.BUILD"),
)
tf_http_archive(
name = "nlohmann_json_lib",
urls = [
"https://mirror.bazel.build/github.com/nlohmann/json/archive/v3.1.1.tar.gz",
"https://github.com/nlohmann/json/archive/v3.1.1.tar.gz",
],
sha256 = "9f3549824af3ca7e9707a2503959886362801fb4926b869789d6929098a79e47",
strip_prefix = "json-3.1.1",
build_file = clean_dep("//third_party/ngraph:nlohmann_json.BUILD"),
)
tf_http_archive(
name = "ngraph_tf",
urls = [
"https://mirror.bazel.build/github.com/NervanaSystems/ngraph-tf/archive/v0.3.0-rc0.tar.gz",
"https://github.com/NervanaSystems/ngraph-tf/archive/v0.3.0-rc0.tar.gz"
],
sha256 = "c09a35d0a605afeeaf5aad81181a6abc7e9b9e39312e8fdfbae20cbd8eb58523",
strip_prefix = "ngraph-tf-0.3.0-rc0",
build_file = clean_dep("//third_party/ngraph:ngraph_tf.BUILD"),
)
############################################################################## ##############################################################################
# BIND DEFINITIONS # BIND DEFINITIONS
# #

1
third_party/ngraph/BUILD vendored Normal file
View File

@ -0,0 +1 @@
licenses(["notice"]) # 3-Clause BSD

201
third_party/ngraph/LICENSE vendored Normal file
View File

@ -0,0 +1,201 @@
Apache License
Version 2.0, January 2004
http://www.apache.org/licenses/
TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
1. Definitions.
"License" shall mean the terms and conditions for use, reproduction,
and distribution as defined by Sections 1 through 9 of this document.
"Licensor" shall mean the copyright owner or entity authorized by
the copyright owner that is granting the License.
"Legal Entity" shall mean the union of the acting entity and all
other entities that control, are controlled by, or are under common
control with that entity. For the purposes of this definition,
"control" means (i) the power, direct or indirect, to cause the
direction or management of such entity, whether by contract or
otherwise, or (ii) ownership of fifty percent (50%) or more of the
outstanding shares, or (iii) beneficial ownership of such entity.
"You" (or "Your") shall mean an individual or Legal Entity
exercising permissions granted by this License.
"Source" form shall mean the preferred form for making modifications,
including but not limited to software source code, documentation
source, and configuration files.
"Object" form shall mean any form resulting from mechanical
transformation or translation of a Source form, including but
not limited to compiled object code, generated documentation,
and conversions to other media types.
"Work" shall mean the work of authorship, whether in Source or
Object form, made available under the License, as indicated by a
copyright notice that is included in or attached to the work
(an example is provided in the Appendix below).
"Derivative Works" shall mean any work, whether in Source or Object
form, that is based on (or derived from) the Work and for which the
editorial revisions, annotations, elaborations, or other modifications
represent, as a whole, an original work of authorship. For the purposes
of this License, Derivative Works shall not include works that remain
separable from, or merely link (or bind by name) to the interfaces of,
the Work and Derivative Works thereof.
"Contribution" shall mean any work of authorship, including
the original version of the Work and any modifications or additions
to that Work or Derivative Works thereof, that is intentionally
submitted to Licensor for inclusion in the Work by the copyright owner
or by an individual or Legal Entity authorized to submit on behalf of
the copyright owner. For the purposes of this definition, "submitted"
means any form of electronic, verbal, or written communication sent
to the Licensor or its representatives, including but not limited to
communication on electronic mailing lists, source code control systems,
and issue tracking systems that are managed by, or on behalf of, the
Licensor for the purpose of discussing and improving the Work, but
excluding communication that is conspicuously marked or otherwise
designated in writing by the copyright owner as "Not a Contribution."
"Contributor" shall mean Licensor and any individual or Legal Entity
on behalf of whom a Contribution has been received by Licensor and
subsequently incorporated within the Work.
2. Grant of Copyright License. Subject to the terms and conditions of
this License, each Contributor hereby grants to You a perpetual,
worldwide, non-exclusive, no-charge, royalty-free, irrevocable
copyright license to reproduce, prepare Derivative Works of,
publicly display, publicly perform, sublicense, and distribute the
Work and such Derivative Works in Source or Object form.
3. Grant of Patent License. Subject to the terms and conditions of
this License, each Contributor hereby grants to You a perpetual,
worldwide, non-exclusive, no-charge, royalty-free, irrevocable
(except as stated in this section) patent license to make, have made,
use, offer to sell, sell, import, and otherwise transfer the Work,
where such license applies only to those patent claims licensable
by such Contributor that are necessarily infringed by their
Contribution(s) alone or by combination of their Contribution(s)
with the Work to which such Contribution(s) was submitted. If You
institute patent litigation against any entity (including a
cross-claim or counterclaim in a lawsuit) alleging that the Work
or a Contribution incorporated within the Work constitutes direct
or contributory patent infringement, then any patent licenses
granted to You under this License for that Work shall terminate
as of the date such litigation is filed.
4. Redistribution. You may reproduce and distribute copies of the
Work or Derivative Works thereof in any medium, with or without
modifications, and in Source or Object form, provided that You
meet the following conditions:
(a) You must give any other recipients of the Work or
Derivative Works a copy of this License; and
(b) You must cause any modified files to carry prominent notices
stating that You changed the files; and
(c) You must retain, in the Source form of any Derivative Works
that You distribute, all copyright, patent, trademark, and
attribution notices from the Source form of the Work,
excluding those notices that do not pertain to any part of
the Derivative Works; and
(d) If the Work includes a "NOTICE" text file as part of its
distribution, then any Derivative Works that You distribute must
include a readable copy of the attribution notices contained
within such NOTICE file, excluding those notices that do not
pertain to any part of the Derivative Works, in at least one
of the following places: within a NOTICE text file distributed
as part of the Derivative Works; within the Source form or
documentation, if provided along with the Derivative Works; or,
within a display generated by the Derivative Works, if and
wherever such third-party notices normally appear. The contents
of the NOTICE file are for informational purposes only and
do not modify the License. You may add Your own attribution
notices within Derivative Works that You distribute, alongside
or as an addendum to the NOTICE text from the Work, provided
that such additional attribution notices cannot be construed
as modifying the License.
You may add Your own copyright statement to Your modifications and
may provide additional or different license terms and conditions
for use, reproduction, or distribution of Your modifications, or
for any such Derivative Works as a whole, provided Your use,
reproduction, and distribution of the Work otherwise complies with
the conditions stated in this License.
5. Submission of Contributions. Unless You explicitly state otherwise,
any Contribution intentionally submitted for inclusion in the Work
by You to the Licensor shall be under the terms and conditions of
this License, without any additional terms or conditions.
Notwithstanding the above, nothing herein shall supersede or modify
the terms of any separate license agreement you may have executed
with Licensor regarding such Contributions.
6. Trademarks. This License does not grant permission to use the trade
names, trademarks, service marks, or product names of the Licensor,
except as required for reasonable and customary use in describing the
origin of the Work and reproducing the content of the NOTICE file.
7. Disclaimer of Warranty. Unless required by applicable law or
agreed to in writing, Licensor provides the Work (and each
Contributor provides its Contributions) on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or
implied, including, without limitation, any warranties or conditions
of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A
PARTICULAR PURPOSE. You are solely responsible for determining the
appropriateness of using or redistributing the Work and assume any
risks associated with Your exercise of permissions under this License.
8. Limitation of Liability. In no event and under no legal theory,
whether in tort (including negligence), contract, or otherwise,
unless required by applicable law (such as deliberate and grossly
negligent acts) or agreed to in writing, shall any Contributor be
liable to You for damages, including any direct, indirect, special,
incidental, or consequential damages of any character arising as a
result of this License or out of the use or inability to use the
Work (including but not limited to damages for loss of goodwill,
work stoppage, computer failure or malfunction, or any and all
other commercial damages or losses), even if such Contributor
has been advised of the possibility of such damages.
9. Accepting Warranty or Additional Liability. While redistributing
the Work or Derivative Works thereof, You may choose to offer,
and charge a fee for, acceptance of support, warranty, indemnity,
or other liability obligations and/or rights consistent with this
License. However, in accepting such obligations, You may act only
on Your own behalf and on Your sole responsibility, not on behalf
of any other Contributor, and only if You agree to indemnify,
defend, and hold each Contributor harmless for any liability
incurred by, or claims asserted against, such Contributor by reason
of your accepting any such warranty or additional liability.
END OF TERMS AND CONDITIONS
APPENDIX: How to apply the Apache License to your work.
To apply the Apache License to your work, attach the following
boilerplate notice, with the fields enclosed by brackets "{}"
replaced with your own identifying information. (Don't include
the brackets!) The text should be enclosed in the appropriate
comment syntax for the file format. We also recommend that a
file or class name and description of purpose be included on the
same "printed page" as the copyright notice for easier
identification within third-party archives.
Copyright {yyyy} {name of copyright owner}
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.

201
third_party/ngraph/NGRAPH_LICENSE vendored Normal file
View File

@ -0,0 +1,201 @@
Apache License
Version 2.0, January 2004
http://www.apache.org/licenses/
TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
1. Definitions.
"License" shall mean the terms and conditions for use, reproduction,
and distribution as defined by Sections 1 through 9 of this document.
"Licensor" shall mean the copyright owner or entity authorized by
the copyright owner that is granting the License.
"Legal Entity" shall mean the union of the acting entity and all
other entities that control, are controlled by, or are under common
control with that entity. For the purposes of this definition,
"control" means (i) the power, direct or indirect, to cause the
direction or management of such entity, whether by contract or
otherwise, or (ii) ownership of fifty percent (50%) or more of the
outstanding shares, or (iii) beneficial ownership of such entity.
"You" (or "Your") shall mean an individual or Legal Entity
exercising permissions granted by this License.
"Source" form shall mean the preferred form for making modifications,
including but not limited to software source code, documentation
source, and configuration files.
"Object" form shall mean any form resulting from mechanical
transformation or translation of a Source form, including but
not limited to compiled object code, generated documentation,
and conversions to other media types.
"Work" shall mean the work of authorship, whether in Source or
Object form, made available under the License, as indicated by a
copyright notice that is included in or attached to the work
(an example is provided in the Appendix below).
"Derivative Works" shall mean any work, whether in Source or Object
form, that is based on (or derived from) the Work and for which the
editorial revisions, annotations, elaborations, or other modifications
represent, as a whole, an original work of authorship. For the purposes
of this License, Derivative Works shall not include works that remain
separable from, or merely link (or bind by name) to the interfaces of,
the Work and Derivative Works thereof.
"Contribution" shall mean any work of authorship, including
the original version of the Work and any modifications or additions
to that Work or Derivative Works thereof, that is intentionally
submitted to Licensor for inclusion in the Work by the copyright owner
or by an individual or Legal Entity authorized to submit on behalf of
the copyright owner. For the purposes of this definition, "submitted"
means any form of electronic, verbal, or written communication sent
to the Licensor or its representatives, including but not limited to
communication on electronic mailing lists, source code control systems,
and issue tracking systems that are managed by, or on behalf of, the
Licensor for the purpose of discussing and improving the Work, but
excluding communication that is conspicuously marked or otherwise
designated in writing by the copyright owner as "Not a Contribution."
"Contributor" shall mean Licensor and any individual or Legal Entity
on behalf of whom a Contribution has been received by Licensor and
subsequently incorporated within the Work.
2. Grant of Copyright License. Subject to the terms and conditions of
this License, each Contributor hereby grants to You a perpetual,
worldwide, non-exclusive, no-charge, royalty-free, irrevocable
copyright license to reproduce, prepare Derivative Works of,
publicly display, publicly perform, sublicense, and distribute the
Work and such Derivative Works in Source or Object form.
3. Grant of Patent License. Subject to the terms and conditions of
this License, each Contributor hereby grants to You a perpetual,
worldwide, non-exclusive, no-charge, royalty-free, irrevocable
(except as stated in this section) patent license to make, have made,
use, offer to sell, sell, import, and otherwise transfer the Work,
where such license applies only to those patent claims licensable
by such Contributor that are necessarily infringed by their
Contribution(s) alone or by combination of their Contribution(s)
with the Work to which such Contribution(s) was submitted. If You
institute patent litigation against any entity (including a
cross-claim or counterclaim in a lawsuit) alleging that the Work
or a Contribution incorporated within the Work constitutes direct
or contributory patent infringement, then any patent licenses
granted to You under this License for that Work shall terminate
as of the date such litigation is filed.
4. Redistribution. You may reproduce and distribute copies of the
Work or Derivative Works thereof in any medium, with or without
modifications, and in Source or Object form, provided that You
meet the following conditions:
(a) You must give any other recipients of the Work or
Derivative Works a copy of this License; and
(b) You must cause any modified files to carry prominent notices
stating that You changed the files; and
(c) You must retain, in the Source form of any Derivative Works
that You distribute, all copyright, patent, trademark, and
attribution notices from the Source form of the Work,
excluding those notices that do not pertain to any part of
the Derivative Works; and
(d) If the Work includes a "NOTICE" text file as part of its
distribution, then any Derivative Works that You distribute must
include a readable copy of the attribution notices contained
within such NOTICE file, excluding those notices that do not
pertain to any part of the Derivative Works, in at least one
of the following places: within a NOTICE text file distributed
as part of the Derivative Works; within the Source form or
documentation, if provided along with the Derivative Works; or,
within a display generated by the Derivative Works, if and
wherever such third-party notices normally appear. The contents
of the NOTICE file are for informational purposes only and
do not modify the License. You may add Your own attribution
notices within Derivative Works that You distribute, alongside
or as an addendum to the NOTICE text from the Work, provided
that such additional attribution notices cannot be construed
as modifying the License.
You may add Your own copyright statement to Your modifications and
may provide additional or different license terms and conditions
for use, reproduction, or distribution of Your modifications, or
for any such Derivative Works as a whole, provided Your use,
reproduction, and distribution of the Work otherwise complies with
the conditions stated in this License.
5. Submission of Contributions. Unless You explicitly state otherwise,
any Contribution intentionally submitted for inclusion in the Work
by You to the Licensor shall be under the terms and conditions of
this License, without any additional terms or conditions.
Notwithstanding the above, nothing herein shall supersede or modify
the terms of any separate license agreement you may have executed
with Licensor regarding such Contributions.
6. Trademarks. This License does not grant permission to use the trade
names, trademarks, service marks, or product names of the Licensor,
except as required for reasonable and customary use in describing the
origin of the Work and reproducing the content of the NOTICE file.
7. Disclaimer of Warranty. Unless required by applicable law or
agreed to in writing, Licensor provides the Work (and each
Contributor provides its Contributions) on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or
implied, including, without limitation, any warranties or conditions
of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A
PARTICULAR PURPOSE. You are solely responsible for determining the
appropriateness of using or redistributing the Work and assume any
risks associated with Your exercise of permissions under this License.
8. Limitation of Liability. In no event and under no legal theory,
whether in tort (including negligence), contract, or otherwise,
unless required by applicable law (such as deliberate and grossly
negligent acts) or agreed to in writing, shall any Contributor be
liable to You for damages, including any direct, indirect, special,
incidental, or consequential damages of any character arising as a
result of this License or out of the use or inability to use the
Work (including but not limited to damages for loss of goodwill,
work stoppage, computer failure or malfunction, or any and all
other commercial damages or losses), even if such Contributor
has been advised of the possibility of such damages.
9. Accepting Warranty or Additional Liability. While redistributing
the Work or Derivative Works thereof, You may choose to offer,
and charge a fee for, acceptance of support, warranty, indemnity,
or other liability obligations and/or rights consistent with this
License. However, in accepting such obligations, You may act only
on Your own behalf and on Your sole responsibility, not on behalf
of any other Contributor, and only if You agree to indemnify,
defend, and hold each Contributor harmless for any liability
incurred by, or claims asserted against, such Contributor by reason
of your accepting any such warranty or additional liability.
END OF TERMS AND CONDITIONS
APPENDIX: How to apply the Apache License to your work.
To apply the Apache License to your work, attach the following
boilerplate notice, with the fields enclosed by brackets "{}"
replaced with your own identifying information. (Don't include
the brackets!) The text should be enclosed in the appropriate
comment syntax for the file format. We also recommend that a
file or class name and description of purpose be included on the
same "printed page" as the copyright notice for easier
identification within third-party archives.
Copyright {yyyy} {name of copyright owner}
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.

16
third_party/ngraph/build_defs.bzl vendored Normal file
View File

@ -0,0 +1,16 @@
def clean_dep(dep):
return str(Label(dep))
def if_ngraph(a):
"""Shorthand for select()'ing on whether we're building with nGraph support.
Returns a select statement which evaluates to if_true if we're building
with nGraph. Otherwise, the select statement evaluates to default.
"""
ret_val = select({
clean_dep("//tensorflow:with_ngraph_support"): a,
"//conditions:default": []
})
return ret_val

45
third_party/ngraph/ngraph.BUILD vendored Normal file
View File

@ -0,0 +1,45 @@
licenses(["notice"]) # 3-Clause BSD
exports_files(["license.txt"])
filegroup(
name = "LICENSE",
srcs = [
"license.txt",
],
visibility = ["//visibility:public"],
)
cc_library(
name = "ngraph_core",
srcs = glob([
"src/ngraph/*.cpp",
"src/ngraph/autodiff/*.cpp",
"src/ngraph/builder/*.cpp",
"src/ngraph/descriptor/*.cpp",
"src/ngraph/descriptor/layout/*.cpp",
"src/ngraph/op/*.cpp",
"src/ngraph/op/util/*.cpp",
"src/ngraph/pattern/*.cpp",
"src/ngraph/pattern/*.hpp",
"src/ngraph/pass/*.cpp",
"src/ngraph/pass/*.hpp",
"src/ngraph/runtime/*.cpp",
"src/ngraph/type/*.cpp",
"src/ngraph/runtime/interpreter/*.cpp",
"src/ngraph/runtime/interpreter/*.hpp",
]),
hdrs = glob(["src/ngraph/**/*.hpp"]),
deps = [
"@eigen_archive//:eigen",
"@nlohmann_json_lib",
],
copts = [
"-I external/ngraph/src",
"-I external/nlohmann_json_lib/include/",
'-D SHARED_LIB_EXT=\\".so\\"',
'-D NGRAPH_VERSION=\\"0.5.0\\"',
],
visibility = ["//visibility:public"],
alwayslink=1
)

96
third_party/ngraph/ngraph_tf.BUILD vendored Normal file
View File

@ -0,0 +1,96 @@
licenses(["notice"]) # 3-Clause BSD
exports_files(["license.txt"])
filegroup(
name = "LICENSE",
srcs = [
"license.txt",
],
visibility = ["//visibility:public"],
)
load(
"@org_tensorflow//tensorflow:tensorflow.bzl",
"tf_cc_test"
)
cc_library(
name = "ngraph_libs_linux",
srcs = [
"lib/libiomp5.so",
"lib/libmklml_intel.so",
],
visibility = ["//visibility:public"],
)
cc_library(
name = "ngraph_tf",
srcs =
[
"src/ngraph_builder.h",
"src/ngraph_builder.cc",
"src/ngraph_cluster.h",
"src/ngraph_cluster.cc",
"src/ngraph_cluster_manager.h",
"src/ngraph_cluster_manager.cc",
"src/ngraph_confirm_pass.cc",
"src/ngraph_device.cc",
"src/ngraph_encapsulate_op.cc",
"src/ngraph_encapsulate_pass.cc",
"src/ngraph_freshness_tracker.h",
"src/ngraph_freshness_tracker.cc",
"src/ngraph_graph_rewrite_passes.cc",
"src/ngraph_liberate_pass.cc",
"src/ngraph_op_kernels.cc",
"src/ngraph_stub_ops.cc",
"src/ngraph_utils.h",
"src/ngraph_utils.cc",
"src/ngraph_send_recv_ops.cc",
"src/ngraph_variable_ops.cc",
"src/tf_graphcycles.cc",
"logging/ngraph_log.h",
"logging/ngraph_log.cc",
"logging/tf_graph_writer.h",
"logging/tf_graph_writer.cc",
],
hdrs = [
"src/tf_graphcycles.h"
],
deps = [
"@org_tensorflow//tensorflow/core:protos_all_proto_text",
"@org_tensorflow//tensorflow/core:framework_headers_lib",
"@org_tensorflow//tensorflow/core:core_cpu_headers_lib",
"@ngraph//:ngraph_core"
],
copts = [
"-I external/ngraph_tf/src",
"-I external/ngraph_tf/logging",
"-I external/ngraph/src",
"-D NGRAPH_EMBEDDED_IN_TENSORFLOW=1",
],
visibility = ["//visibility:public"],
)
tf_cc_test(
name = "ngraph_tf_tests",
size = "small",
srcs = [
"test/tf_exec.cpp",
"test/main.cpp",
],
deps = [
":ngraph_tf",
"@com_google_googletest//:gtest",
"@org_tensorflow//tensorflow/cc:cc_ops",
"@org_tensorflow//tensorflow/cc:client_session",
"@org_tensorflow//tensorflow/core:tensorflow",
],
extra_copts = [
"-fexceptions ",
"-D NGRAPH_EMBEDDED_IN_TENSORFLOW=1",
"-I external/ngraph_tf/src",
"-I external/ngraph_tf/logging",
"-I external/ngraph/src",
],
)

23
third_party/ngraph/nlohmann_json.BUILD vendored Normal file
View File

@ -0,0 +1,23 @@
licenses(["notice"]) # 3-Clause BSD
exports_files(["license.txt"])
filegroup(
name = "LICENSE",
srcs = [
"license.txt",
],
visibility = ["//visibility:public"],
)
cc_library(
name = "nlohmann_json_lib",
hdrs = glob([
"include/nlohmann/**/*.hpp",
]),
copts = [
"-I external/nlohmann_json_lib",
],
visibility = ["//visibility:public"],
alwayslink=1
)