PTI/models/StyleCLIP/global_directions/dnnlib/tflib/custom_ops.py

# Copyright (c) 2020, NVIDIA CORPORATION.  All rights reserved.
#
# NVIDIA CORPORATION and its licensors retain all intellectual property
# and proprietary rights in and to this software, related documentation
# and any modifications thereto.  Any use, reproduction, disclosure or
# distribution of this software and related documentation without an express
# license agreement from NVIDIA CORPORATION is strictly prohibited.

"""TensorFlow custom ops builder.
"""

import glob
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

from .. import util

#----------------------------------------------------------------------------
# Global configs.

cuda_cache_path = None
cuda_cache_version_tag = 'v1'
do_not_hash_included_headers = True # Speed up compilation by assuming that headers included by the CUDA code never change.
verbose = True # Print status messages to stdout.

#----------------------------------------------------------------------------
# Internal helper funcs.

def _find_compiler_bindir():
    hostx64_paths = sorted(glob.glob('C:/Program Files (x86)/Microsoft Visual Studio/*/Professional/VC/Tools/MSVC/*/bin/Hostx64/x64'), reverse=True)
    if hostx64_paths != []:
        return hostx64_paths[0]
    hostx64_paths = sorted(glob.glob('C:/Program Files (x86)/Microsoft Visual Studio/*/BuildTools/VC/Tools/MSVC/*/bin/Hostx64/x64'), reverse=True)
    if hostx64_paths != []:
        return hostx64_paths[0]
    hostx64_paths = sorted(glob.glob('C:/Program Files (x86)/Microsoft Visual Studio/*/Community/VC/Tools/MSVC/*/bin/Hostx64/x64'), reverse=True)
    if hostx64_paths != []:
        return hostx64_paths[0]
    vc_bin_dir = 'C:/Program Files (x86)/Microsoft Visual Studio 14.0/vc/bin'
    if os.path.isdir(vc_bin_dir):
        return vc_bin_dir
    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 += ' --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, extra_nvcc_options=[]):
    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 configs.
        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 += f' --compiler-options \'-fPIC\''
            compile_opts += f' --compiler-options \'{" ".join(tf.sysconfig.get_compile_flags())}\''
            compile_opts += f' --linker-options \'{" ".join(tf.sysconfig.get_link_flags())}\''
        else:
            assert False # not Windows or Linux, w00t?
        compile_opts += f' --gpu-architecture={_get_cuda_gpu_arch_string()}'
        compile_opts += ' --use_fast_math'
        for opt in extra_nvcc_options:
            compile_opts += ' ' + opt
        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.
        cache_dir = util.make_cache_dir_path('tflib-cudacache') if cuda_cache_path is None else cuda_cache_path
        bin_file_ext = '.dll' if os.name == 'nt' else '.so'
        bin_file = os.path.join(cache_dir, 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(cache_dir, exist_ok=True)
                intermediate_file = os.path.join(cache_dir, 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

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