Stylegan error

error: #error “C++ versions less than C++11 are not supported.”
#error “C++ versions less than C++11 are not supported.”

NVCC returned an error.

ftlib custom_ops

Copyright © 2019, NVIDIA Corporation. All rights reserved.

This work is made available under the Nvidia Source Code License-NC.

To view a copy of this license, visit

https://nvlabs.github.io/stylegan2/license.html

“”“TensorFlow custom ops builder.
“””

import os
import re
import uuid
import hashlib
import tempfile
import shutil
import tensorflow as tf
from tensorflow.python.client import device_lib # pylint: disable=no-name-in-module

#----------------------------------------------------------------------------

Global options.

cuda_cache_path = os.path.join(os.path.dirname(file), ‘_cudacache’)
cuda_cache_version_tag = ‘v1’
do_not_hash_included_headers = False # Speed up compilation by assuming that headers included by the CUDA code never change. Unsafe!
verbose = True # Print status messages to stdout.

compiler_bindir_search_path = [
‘C:/Program Files (x86)/Microsoft Visual Studio/2017/Community/VC/Tools/MSVC/14.14.26428/bin/Hostx64/x64’,
‘C:/Program Files (x86)/Microsoft Visual Studio/2019/Community/VC/Tools/MSVC/14.23.28105/bin/Hostx64/x64’,
‘C:/Program Files (x86)/Microsoft Visual Studio 14.0/vc/bin’,
]

#----------------------------------------------------------------------------

Internal helper funcs.

def _find_compiler_bindir():
for compiler_path in compiler_bindir_search_path:
if os.path.isdir(compiler_path):
return compiler_path
return None

def _get_compute_cap(device):
caps_str = device.physical_device_desc
m = re.search(‘compute capability: (\d+).(\d+)’, caps_str)
major = m.group(1)
minor = m.group(2)
return (major, minor)

def _get_cuda_gpu_arch_string():
gpus = [x for x in device_lib.list_local_devices() if x.device_type == ‘GPU’]
if len(gpus) == 0:
raise RuntimeError(‘No GPU devices found’)
(major, minor) = get_compute_cap(gpus[0])
return 'sm%s%s’ % (major, minor)

def _run_cmd(cmd):
with os.popen(cmd) as pipe:
output = pipe.read()
status = pipe.close()
if status is not None:
raise RuntimeError(‘NVCC returned an error. See below for full command line and output log:\n\n%s\n\n%s’ % (cmd, output))

def _prepare_nvcc_cli(opts):

cmd = 'nvcc ’ + opts.strip()

####################################################################
cmd = ‘nvcc --std=c++11 -DNDEBUG ’ + opts.strip()
################################################################333
cmd += ’ --disable-warnings’
cmd += ’ --include-path “%s”’ % tf.sysconfig.get_include()
cmd += ’ --include-path “%s”’ % os.path.join(tf.sysconfig.get_include(), ‘external’, ‘protobuf_archive’, ‘src’)
cmd += ’ --include-path “%s”’ % os.path.join(tf.sysconfig.get_include(), ‘external’, ‘com_google_absl’)
cmd += ’ --include-path “%s”’ % os.path.join(tf.sysconfig.get_include(), ‘external’, ‘eigen_archive’)

compiler_bindir = _find_compiler_bindir()
if compiler_bindir is None:
    # Require that _find_compiler_bindir succeeds on Windows.  Allow
    # nvcc to use whatever is the default on Linux.
    if os.name == 'nt':
        raise RuntimeError('Could not find MSVC/GCC/CLANG installation on this computer. Check compiler_bindir_search_path list in "%s".' % __file__)
else:
    cmd += ' --compiler-bindir "%s"' % compiler_bindir
cmd += ' 2>&1'
return cmd

#----------------------------------------------------------------------------

Main entry point.

_plugin_cache = dict()

def get_plugin(cuda_file):
cuda_file_base = os.path.basename(cuda_file)
cuda_file_name, cuda_file_ext = os.path.splitext(cuda_file_base)

# Already in cache?
if cuda_file in _plugin_cache:
    return _plugin_cache[cuda_file]

# Setup plugin.
if verbose:
    print('Setting up TensorFlow plugin "%s": ' % cuda_file_base, end='', flush=True)
try:
    # Hash CUDA source.
    md5 = hashlib.md5()
    with open(cuda_file, 'rb') as f:
        md5.update(f.read())
    md5.update(b'\n')

    # Hash headers included by the CUDA code by running it through the preprocessor.
    if not do_not_hash_included_headers:
        if verbose:
            print('Preprocessing... ', end='', flush=True)
        with tempfile.TemporaryDirectory() as tmp_dir:
            tmp_file = os.path.join(tmp_dir, cuda_file_name + '_tmp' + cuda_file_ext)
            _run_cmd(_prepare_nvcc_cli('"%s" --preprocess -o "%s" --keep --keep-dir "%s"' % (cuda_file, tmp_file, tmp_dir)))
            with open(tmp_file, 'rb') as f:
                bad_file_str = ('"' + cuda_file.replace('\\', '/') + '"').encode('utf-8') # __FILE__ in error check macros
                good_file_str = ('"' + cuda_file_base + '"').encode('utf-8')
                for ln in f:
                    if not ln.startswith(b'# ') and not ln.startswith(b'#line '): # ignore line number pragmas
                        ln = ln.replace(bad_file_str, good_file_str)
                        md5.update(ln)
                md5.update(b'\n')

    # Select compiler options.
    compile_opts = ''
    if os.name == 'nt':
        compile_opts += '"%s"' % os.path.join(tf.sysconfig.get_lib(), 'python', '_pywrap_tensorflow_internal.lib')
    elif os.name == 'posix':
        compile_opts += '"%s"' % os.path.join(tf.sysconfig.get_lib(), 'python', '_pywrap_tensorflow_internal.so')
        #########################################################################################
        compile_opts += ' --compiler-options \'-fPIC -D_GLIBCXX_USE_CXX11_ABI=1\''
        #########################################################################################33
    else:
        assert False # not Windows or Linux, w00t?
    compile_opts += ' --gpu-architecture=%s' % _get_cuda_gpu_arch_string()
    compile_opts += ' --use_fast_math'
    nvcc_cmd = _prepare_nvcc_cli(compile_opts)

    # Hash build configuration.
    md5.update(('nvcc_cmd: ' + nvcc_cmd).encode('utf-8') + b'\n')
    md5.update(('tf.VERSION: ' + tf.VERSION).encode('utf-8') + b'\n')
    md5.update(('cuda_cache_version_tag: ' + cuda_cache_version_tag).encode('utf-8') + b'\n')

    # Compile if not already compiled.
    bin_file_ext = '.dll' if os.name == 'nt' else '.so'
    bin_file = os.path.join(cuda_cache_path, cuda_file_name + '_' + md5.hexdigest() + bin_file_ext)
    if not os.path.isfile(bin_file):
        if verbose:
            print('Compiling... ', end='', flush=True)
        with tempfile.TemporaryDirectory() as tmp_dir:
            tmp_file = os.path.join(tmp_dir, cuda_file_name + '_tmp' + bin_file_ext)
            _run_cmd(nvcc_cmd + ' "%s" --shared -o "%s" --keep --keep-dir "%s"' % (cuda_file, tmp_file, tmp_dir))
            os.makedirs(cuda_cache_path, exist_ok=True)
            intermediate_file = os.path.join(cuda_cache_path, cuda_file_name + '_' + uuid.uuid4().hex + '_tmp' + bin_file_ext)
            shutil.copyfile(tmp_file, intermediate_file)
            os.rename(intermediate_file, bin_file) # atomic

    # Load.
    if verbose:
        print('Loading... ', end='', flush=True)
    plugin = tf.load_op_library(bin_file)

    # Add to cache.
    _plugin_cache[cuda_file] = plugin
    if verbose:
        print('Done.', flush=True)
    return plugin

except:
    if verbose:
        print('Failed!', flush=True)
    raise