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
|
/* Copyright 2017 The TensorFlow Authors. All Rights Reserved.
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.
==============================================================================*/
// Legacy flags for XLA's cpu_runtime module.
#include <mutex> // NOLINT(build/c++11): only using std::call_once, not mutex.
#include <vector>
#include "tensorflow/compiler/xla/legacy_flags/cpu_runtime_flags.h"
#include "tensorflow/compiler/xla/legacy_flags/parse_flags_from_env.h"
#include "tensorflow/core/platform/types.h"
#include "tensorflow/core/util/command_line_flags.h"
namespace xla {
namespace legacy_flags {
// Pointers to the parsed value of the flags and flag descriptors, initialized
// via flags_init.
static CpuRuntimeFlags* flags;
static std::vector<tensorflow::Flag>* flag_list;
static std::once_flag flags_init;
// Allocate *flags. Called via call_once(&flags_init,...).
static void AllocateFlags() {
flags = new CpuRuntimeFlags;
flags->xla_cpu_use_eigen = true;
flags->xla_cpu_multi_thread_eigen = true;
flag_list = new std::vector<tensorflow::Flag>({
tensorflow::Flag(
"xla_cpu_use_eigen", &flags->xla_cpu_use_eigen,
"Use Eigen for matrix multiply on the CPU platform. This "
"is a useful hack for performance comparisons against "
"XLA's implementation."),
tensorflow::Flag(
"xla_cpu_multi_thread_eigen", &flags->xla_cpu_multi_thread_eigen,
"When generating calls to Eigen for matmul and conv, should "
"single or multi-threaded eigen be used? "
"Only used when --xla_cpu_use_eigen is true."),
});
ParseFlagsFromEnv(*flag_list);
}
// Append to *append_to flag definitions associated with XLA's cpu_runtime
// module.
void AppendCpuRuntimeFlags(std::vector<tensorflow::Flag>* append_to) {
std::call_once(flags_init, &AllocateFlags);
append_to->insert(append_to->end(), flag_list->begin(), flag_list->end());
}
// Return a pointer to the CpuRuntimeFlags struct;
// repeated calls return the same pointer.
// This should be called only after Flags::Parse() has returned.
CpuRuntimeFlags* GetCpuRuntimeFlags() {
std::call_once(flags_init, &AllocateFlags);
return flags;
}
} // namespace legacy_flags
} // namespace xla
|
