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
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
|
# -*- Python -*-
"""Repository rule for TensorRT configuration.
`tensorrt_configure` depends on the following environment variables:
* `TF_TENSORRT_VERSION`: The TensorRT libnvinfer version.
* `TENSORRT_INSTALL_PATH`: The installation path of the TensorRT library.
"""
load(
"//third_party/gpus:cuda_configure.bzl",
"auto_configure_fail",
"get_cpu_value",
"find_cuda_define",
"matches_version",
"symlink_genrule_for_dir",
)
_TENSORRT_INSTALL_PATH = "TENSORRT_INSTALL_PATH"
_TF_TENSORRT_VERSION = "TF_TENSORRT_VERSION"
_TF_TENSORRT_LIBS = ["nvinfer"]
_TF_TENSORRT_HEADERS = ["NvInfer.h", "NvUtils.h"]
_DEFINE_TENSORRT_SONAME_MAJOR = "#define NV_TENSORRT_SONAME_MAJOR"
_DEFINE_TENSORRT_SONAME_MINOR = "#define NV_TENSORRT_SONAME_MINOR"
_DEFINE_TENSORRT_SONAME_PATCH = "#define NV_TENSORRT_SONAME_PATCH"
def _headers_exist(repository_ctx, path):
"""Returns whether all TensorRT header files could be found in 'path'.
Args:
repository_ctx: The repository context.
path: The TensorRT include path to check.
Returns:
True if all TensorRT header files can be found in the path.
"""
for h in _TF_TENSORRT_HEADERS:
if not repository_ctx.path("%s/%s" % (path, h)).exists:
return False
return True
def _find_trt_header_dir(repository_ctx, trt_install_path):
"""Returns the path to the directory containing headers of TensorRT.
Args:
repository_ctx: The repository context.
trt_install_path: The TensorRT library install directory.
Returns:
The path of the directory containing the TensorRT header.
"""
if trt_install_path == "/usr/lib/x86_64-linux-gnu":
path = "/usr/include/x86_64-linux-gnu"
if _headers_exist(repository_ctx, path):
return path
if trt_install_path == "/usr/lib/aarch64-linux-gnu":
path = "/usr/include/aarch64-linux-gnu"
if _headers_exist(repository_ctx, path):
return path
path = str(repository_ctx.path("%s/../include" % trt_install_path).realpath)
if _headers_exist(repository_ctx, path):
return path
auto_configure_fail(
"Cannot find NvInfer.h with TensorRT install path %s" % trt_install_path)
def _trt_lib_version(repository_ctx, trt_install_path):
"""Detects the library (e.g. libnvinfer) version of TensorRT.
Args:
repository_ctx: The repository context.
trt_install_path: The TensorRT library install directory.
Returns:
A string containing the library version of TensorRT.
"""
trt_header_dir = _find_trt_header_dir(repository_ctx, trt_install_path)
major_version = find_cuda_define(repository_ctx, trt_header_dir, "NvInfer.h",
_DEFINE_TENSORRT_SONAME_MAJOR)
minor_version = find_cuda_define(repository_ctx, trt_header_dir, "NvInfer.h",
_DEFINE_TENSORRT_SONAME_MINOR)
patch_version = find_cuda_define(repository_ctx, trt_header_dir, "NvInfer.h",
_DEFINE_TENSORRT_SONAME_PATCH)
full_version = "%s.%s.%s" % (major_version, minor_version, patch_version)
environ_version = repository_ctx.os.environ[_TF_TENSORRT_VERSION].strip()
if not matches_version(environ_version, full_version):
auto_configure_fail(
("TensorRT library version detected from %s/%s (%s) does not match " +
"TF_TENSORRT_VERSION (%s). To fix this rerun configure again.") %
(trt_header_dir, "NvInfer.h", full_version, environ_version))
return environ_version
def _find_trt_libs(repository_ctx, trt_install_path, trt_lib_version):
"""Finds the given TensorRT library on the system.
Adapted from code contributed by Sami Kama (https://github.com/samikama).
Args:
repository_ctx: The repository context.
trt_install_path: The TensorRT library installation directory.
trt_lib_version: The version of TensorRT library files as returned
by _trt_lib_version.
Returns:
Map of library names to structs with the following fields:
src_file_path: The full path to the library found on the system.
dst_file_name: The basename of the target library.
"""
objdump = repository_ctx.which("objdump")
result = {}
for lib in _TF_TENSORRT_LIBS:
dst_file_name = "lib%s.so.%s" % (lib, trt_lib_version)
src_file_path = repository_ctx.path("%s/%s" % (trt_install_path,
dst_file_name))
if not src_file_path.exists:
auto_configure_fail(
"Cannot find TensorRT library %s" % str(src_file_path))
if objdump != None:
objdump_out = repository_ctx.execute([objdump, "-p", str(src_file_path)])
for line in objdump_out.stdout.splitlines():
if "SONAME" in line:
dst_file_name = line.strip().split(" ")[-1]
result.update({
lib:
struct(
dst_file_name=dst_file_name,
src_file_path=str(src_file_path.realpath))
})
return result
def _tpl(repository_ctx, tpl, substitutions):
repository_ctx.template(tpl, Label("//third_party/tensorrt:%s.tpl" % tpl),
substitutions)
def _create_dummy_repository(repository_ctx):
"""Create a dummy TensorRT repository."""
_tpl(repository_ctx, "build_defs.bzl", {"%{tensorrt_is_configured}": "False"})
substitutions = {
"%{tensorrt_genrules}": "",
"%{tensorrt_headers}": "",
}
for lib in _TF_TENSORRT_LIBS:
k = "%%{%s}" % lib.replace("nv", "nv_")
substitutions.update({k: ""})
_tpl(repository_ctx, "BUILD", substitutions)
def _tensorrt_configure_impl(repository_ctx):
"""Implementation of the tensorrt_configure repository rule."""
if _TENSORRT_INSTALL_PATH not in repository_ctx.os.environ:
_create_dummy_repository(repository_ctx)
return
if (get_cpu_value(repository_ctx) != "Linux"):
auto_configure_fail("TensorRT is supported only on Linux.")
if _TF_TENSORRT_VERSION not in repository_ctx.os.environ:
auto_configure_fail("TensorRT library (libnvinfer) version is not set.")
trt_install_path = repository_ctx.os.environ[_TENSORRT_INSTALL_PATH].strip()
if not repository_ctx.path(trt_install_path).exists:
auto_configure_fail(
"Cannot find TensorRT install path %s." % trt_install_path)
# Set up the symbolic links for the library files.
trt_lib_version = _trt_lib_version(repository_ctx, trt_install_path)
trt_libs = _find_trt_libs(repository_ctx, trt_install_path, trt_lib_version)
trt_lib_src = []
trt_lib_dest = []
for lib in trt_libs.values():
trt_lib_src.append(lib.src_file_path)
trt_lib_dest.append(lib.dst_file_name)
genrules = [
symlink_genrule_for_dir(repository_ctx, None, "tensorrt/lib/",
"tensorrt_lib", trt_lib_src, trt_lib_dest)
]
# Set up the symbolic links for the header files.
trt_header_dir = _find_trt_header_dir(repository_ctx, trt_install_path)
src_files = [
"%s/%s" % (trt_header_dir, header) for header in _TF_TENSORRT_HEADERS
]
dest_files = _TF_TENSORRT_HEADERS
genrules.append(
symlink_genrule_for_dir(repository_ctx, None, "tensorrt/include/",
"tensorrt_include", src_files, dest_files))
# Set up config file.
_tpl(repository_ctx, "build_defs.bzl", {"%{tensorrt_is_configured}": "True"})
# Set up BUILD file.
substitutions = {
"%{tensorrt_genrules}": "\n".join(genrules),
"%{tensorrt_headers}": '":tensorrt_include"',
}
for lib in _TF_TENSORRT_LIBS:
k = "%%{%s}" % lib.replace("nv", "nv_")
v = '"tensorrt/lib/%s"' % trt_libs[lib].dst_file_name
substitutions.update({k: v})
_tpl(repository_ctx, "BUILD", substitutions)
tensorrt_configure = repository_rule(
implementation=_tensorrt_configure_impl,
environ=[
_TENSORRT_INSTALL_PATH,
_TF_TENSORRT_VERSION,
],
)
"""Detects and configures the local CUDA toolchain.
Add the following to your WORKSPACE FILE:
```python
tensorrt_configure(name = "local_config_tensorrt")
```
Args:
name: A unique name for this workspace rule.
"""
|
