File size: 6,646 Bytes
a0bcaae
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
# Copyright (c) 2021, NVIDIA CORPORATION & AFFILIATES.  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.

import glob
import hashlib
import importlib
import os
import re
import shutil
import uuid

import torch
import torch.utils.cpp_extension
from torch.utils.file_baton import FileBaton

#----------------------------------------------------------------------------
# Global options.

verbosity = 'brief' # Verbosity level: 'none', 'brief', 'full'

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

def _find_compiler_bindir():
    patterns = [
        'C:/Program Files*/Microsoft Visual Studio/*/Professional/VC/Tools/MSVC/*/bin/Hostx64/x64',
        'C:/Program Files*/Microsoft Visual Studio/*/BuildTools/VC/Tools/MSVC/*/bin/Hostx64/x64',
        'C:/Program Files*/Microsoft Visual Studio/*/Community/VC/Tools/MSVC/*/bin/Hostx64/x64',
        'C:/Program Files*/Microsoft Visual Studio */vc/bin',
    ]
    for pattern in patterns:
        matches = sorted(glob.glob(pattern))
        if len(matches):
            return matches[-1]
    return None

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

def _get_mangled_gpu_name():
    name = torch.cuda.get_device_name().lower()
    out = []
    for c in name:
        if re.match('[a-z0-9_-]+', c):
            out.append(c)
        else:
            out.append('-')
    return ''.join(out)

#----------------------------------------------------------------------------
# Main entry point for compiling and loading C++/CUDA plugins.

_cached_plugins = dict()

def get_plugin(module_name, sources, headers=None, source_dir=None, **build_kwargs):
    assert verbosity in ['none', 'brief', 'full']
    if headers is None:
        headers = []
    if source_dir is not None:
        sources = [os.path.join(source_dir, fname) for fname in sources]
        headers = [os.path.join(source_dir, fname) for fname in headers]

    # Already cached?
    if module_name in _cached_plugins:
        return _cached_plugins[module_name]

    # Print status.
    if verbosity == 'full':
        print(f'Setting up PyTorch plugin "{module_name}"...')
    elif verbosity == 'brief':
        print(f'Setting up PyTorch plugin "{module_name}"... ', end='', flush=True)
    verbose_build = (verbosity == 'full')

    # Compile and load.
    try: # pylint: disable=too-many-nested-blocks
        # Make sure we can find the necessary compiler binaries.
        if os.name == 'nt' and os.system("where cl.exe >nul 2>nul") != 0:
            compiler_bindir = _find_compiler_bindir()
            if compiler_bindir is None:
                raise RuntimeError(f'Could not find MSVC/GCC/CLANG installation on this computer. Check _find_compiler_bindir() in "{__file__}".')
            os.environ['PATH'] += ';' + compiler_bindir

        # Some containers set TORCH_CUDA_ARCH_LIST to a list that can either
        # break the build or unnecessarily restrict what's available to nvcc.
        # Unset it to let nvcc decide based on what's available on the
        # machine.
        os.environ['TORCH_CUDA_ARCH_LIST'] = ''

        # Incremental build md5sum trickery.  Copies all the input source files
        # into a cached build directory under a combined md5 digest of the input
        # source files.  Copying is done only if the combined digest has changed.
        # This keeps input file timestamps and filenames the same as in previous
        # extension builds, allowing for fast incremental rebuilds.
        #
        # This optimization is done only in case all the source files reside in
        # a single directory (just for simplicity) and if the TORCH_EXTENSIONS_DIR
        # environment variable is set (we take this as a signal that the user
        # actually cares about this.)
        #
        # EDIT: We now do it regardless of TORCH_EXTENSIOS_DIR, in order to work
        # around the *.cu dependency bug in ninja config.
        #
        all_source_files = sorted(sources + headers)
        all_source_dirs = set(os.path.dirname(fname) for fname in all_source_files)
        if len(all_source_dirs) == 1: # and ('TORCH_EXTENSIONS_DIR' in os.environ):

            # Compute combined hash digest for all source files.
            hash_md5 = hashlib.md5()
            for src in all_source_files:
                with open(src, 'rb') as f:
                    hash_md5.update(f.read())

            # Select cached build directory name.
            source_digest = hash_md5.hexdigest()
            build_top_dir = torch.utils.cpp_extension._get_build_directory(module_name, verbose=verbose_build) # pylint: disable=protected-access
            cached_build_dir = os.path.join(build_top_dir, f'{source_digest}-{_get_mangled_gpu_name()}')

            if not os.path.isdir(cached_build_dir):
                tmpdir = f'{build_top_dir}/srctmp-{uuid.uuid4().hex}'
                os.makedirs(tmpdir)
                for src in all_source_files:
                    shutil.copyfile(src, os.path.join(tmpdir, os.path.basename(src)))
                try:
                    os.replace(tmpdir, cached_build_dir) # atomic
                except OSError:
                    # source directory already exists, delete tmpdir and its contents.
                    shutil.rmtree(tmpdir)
                    if not os.path.isdir(cached_build_dir): raise

            # Compile.
            cached_sources = [os.path.join(cached_build_dir, os.path.basename(fname)) for fname in sources]
            torch.utils.cpp_extension.load(name=module_name, build_directory=cached_build_dir,
                verbose=verbose_build, sources=cached_sources, **build_kwargs)
        else:
            torch.utils.cpp_extension.load(name=module_name, verbose=verbose_build, sources=sources, **build_kwargs)

        # Load.
        module = importlib.import_module(module_name)

    except:
        if verbosity == 'brief':
            print('Failed!')
        raise

    # Print status and add to cache dict.
    if verbosity == 'full':
        print(f'Done setting up PyTorch plugin "{module_name}".')
    elif verbosity == 'brief':
        print('Done.')
    _cached_plugins[module_name] = module
    return module

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