1 /* Copyright 2015 The TensorFlow Authors. All Rights Reserved.
2
3 Licensed under the Apache License, Version 2.0 (the "License");
4 you may not use this file except in compliance with the License.
5 You may obtain a copy of the License at
6
7 http://www.apache.org/licenses/LICENSE-2.0
8
9 Unless required by applicable law or agreed to in writing, software
10 distributed under the License is distributed on an "AS IS" BASIS,
11 WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
12 See the License for the specific language governing permissions and
13 limitations under the License.
14 ==============================================================================*/
15
16 #include "tensorflow/core/util/util.h"
17
18 #include <string>
19 #include <vector>
20
21 #include "absl/base/call_once.h"
22 #include "tensorflow/core/framework/device_factory.h"
23 #include "tensorflow/core/lib/gtl/inlined_vector.h"
24 #include "tensorflow/core/lib/strings/strcat.h"
25 #include "tensorflow/core/platform/cpu_info.h"
26 #include "tensorflow/core/platform/logging.h"
27 #include "tensorflow/core/util/env_var.h"
28
29 namespace tensorflow {
30
NodeNamePrefix(const StringPiece & op_name)31 StringPiece NodeNamePrefix(const StringPiece& op_name) {
32 StringPiece sp(op_name);
33 auto p = sp.find('/');
34 if (p == StringPiece::npos || p == 0) {
35 return "";
36 } else {
37 return StringPiece(sp.data(), p);
38 }
39 }
40
NodeNameFullPrefix(const StringPiece & op_name)41 StringPiece NodeNameFullPrefix(const StringPiece& op_name) {
42 StringPiece sp(op_name);
43 auto p = sp.rfind('/');
44 if (p == StringPiece::npos || p == 0) {
45 return "";
46 } else {
47 return StringPiece(sp.data(), p);
48 }
49 }
50
MovingAverage(int window)51 MovingAverage::MovingAverage(int window)
52 : window_(window),
53 sum_(0.0),
54 data_(new double[window_]),
55 head_(0),
56 count_(0) {
57 CHECK_GE(window, 1);
58 }
59
~MovingAverage()60 MovingAverage::~MovingAverage() { delete[] data_; }
61
Clear()62 void MovingAverage::Clear() {
63 count_ = 0;
64 head_ = 0;
65 sum_ = 0;
66 }
67
GetAverage() const68 double MovingAverage::GetAverage() const {
69 if (count_ == 0) {
70 return 0;
71 } else {
72 return static_cast<double>(sum_) / count_;
73 }
74 }
75
AddValue(double v)76 void MovingAverage::AddValue(double v) {
77 if (count_ < window_) {
78 // This is the warmup phase. We don't have a full window's worth of data.
79 head_ = count_;
80 data_[count_++] = v;
81 } else {
82 if (window_ == ++head_) {
83 head_ = 0;
84 }
85 // Toss the oldest element
86 sum_ -= data_[head_];
87 // Add the newest element
88 data_[head_] = v;
89 }
90 sum_ += v;
91 }
92
93 static char hex_char[] = "0123456789abcdef";
94
PrintMemory(const char * ptr,size_t n)95 string PrintMemory(const char* ptr, size_t n) {
96 string ret;
97 ret.resize(n * 3);
98 for (int i = 0; i < n; ++i) {
99 ret[i * 3] = ' ';
100 ret[i * 3 + 1] = hex_char[ptr[i] >> 4];
101 ret[i * 3 + 2] = hex_char[ptr[i] & 0xf];
102 }
103 return ret;
104 }
105
SliceDebugString(const TensorShape & shape,const int64_t flat)106 string SliceDebugString(const TensorShape& shape, const int64_t flat) {
107 // Special case rank 0 and 1
108 const int dims = shape.dims();
109 if (dims == 0) return "";
110 if (dims == 1) return strings::StrCat("[", flat, "]");
111
112 // Compute strides
113 gtl::InlinedVector<int64_t, 32> strides(dims);
114 strides.back() = 1;
115 for (int i = dims - 2; i >= 0; i--) {
116 strides[i] = strides[i + 1] * shape.dim_size(i + 1);
117 }
118
119 // Unflatten index
120 int64_t left = flat;
121 string result;
122 for (int i = 0; i < dims; i++) {
123 strings::StrAppend(&result, i ? "," : "[", left / strides[i]);
124 left %= strides[i];
125 }
126 strings::StrAppend(&result, "]");
127 return result;
128 }
129
IsMKLEnabled()130 bool IsMKLEnabled() {
131 #ifndef INTEL_MKL
132 return false;
133 #endif // !INTEL_MKL
134 static absl::once_flag once;
135 #ifdef ENABLE_MKL
136 // Keeping TF_DISABLE_MKL env variable for legacy reasons.
137 static bool oneDNN_disabled = false;
138 absl::call_once(once, [&] {
139 TF_CHECK_OK(ReadBoolFromEnvVar("TF_DISABLE_MKL", false, &oneDNN_disabled));
140 if (oneDNN_disabled) VLOG(2) << "TF-MKL: Disabling oneDNN";
141 });
142 return (!oneDNN_disabled);
143 #else
144 // Linux: Turn oneDNN on by default for CPUs with neural network features.
145 // Windows: oneDNN is off by default.
146 // No need to guard for other platforms here because INTEL_MKL is only defined
147 // for non-mobile Linux or Windows.
148 static bool oneDNN_enabled =
149 #ifdef __linux__
150 port::TestCPUFeature(port::CPUFeature::AVX512_VNNI) ||
151 port::TestCPUFeature(port::CPUFeature::AVX512_BF16) ||
152 port::TestCPUFeature(port::CPUFeature::AVX_VNNI) ||
153 port::TestCPUFeature(port::CPUFeature::AMX_TILE) ||
154 port::TestCPUFeature(port::CPUFeature::AMX_INT8) ||
155 port::TestCPUFeature(port::CPUFeature::AMX_BF16);
156 #else
157 false;
158 #endif // __linux__
159 absl::call_once(once, [&] {
160 auto status = ReadBoolFromEnvVar("TF_ENABLE_ONEDNN_OPTS", oneDNN_enabled,
161 &oneDNN_enabled);
162 if (!status.ok()) {
163 LOG(WARNING) << "TF_ENABLE_ONEDNN_OPTS is not set to either '0', 'false',"
164 << " '1', or 'true'. Using the default setting: "
165 << oneDNN_enabled;
166 }
167 if (oneDNN_enabled) {
168 #ifndef DNNL_AARCH64_USE_ACL
169 LOG(INFO) << "oneDNN custom operations are on. "
170 << "You may see slightly different numerical results due to "
171 << "floating-point round-off errors from different computation "
172 << "orders. To turn them off, set the environment variable "
173 << "`TF_ENABLE_ONEDNN_OPTS=0`.";
174 #else
175 LOG(INFO) << "Experimental oneDNN custom operations are on. "
176 << "If you experience issues, please turn them off by setting "
177 << "the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.";
178 #endif // !DNNL_AARCH64_USE_ACL
179 }
180 });
181 return oneDNN_enabled;
182 #endif // ENABLE_MKL
183 }
184
185 } // namespace tensorflow
186