/
utils.py
194 lines (160 loc) · 5.89 KB
/
utils.py
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
# Copyright (c) 2022 PaddlePaddle 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.
from typing import Any
from warnings import warn
import functools
from contextlib import ContextDecorator
from paddle.fluid import core
from paddle.fluid.core import _RecordEvent, TracerEventType
_is_profiler_used = False
_has_optimizer_wrapped = False
_AllowedEventTypeList = [
TracerEventType.Dataloader,
TracerEventType.ProfileStep,
TracerEventType.Forward,
TracerEventType.Backward,
TracerEventType.Optimization,
TracerEventType.PythonOp,
TracerEventType.PythonUserDefined,
]
class RecordEvent(ContextDecorator):
r"""
Interface for recording a time range by user defined.
Args:
name (str): Name of the record event.
event_type (TracerEventType, optional): Optional, default value is
`TracerEventType.PythonUserDefined`. It is reserved for internal
purpose, and it is better not to specify this parameter.
Examples:
.. code-block:: python
:name: code-example1
import paddle
import paddle.profiler as profiler
# method1: using context manager
with profiler.RecordEvent("record_add"):
data1 = paddle.randn(shape=[3])
data2 = paddle.randn(shape=[3])
result = data1 + data2
# method2: call begin() and end()
record_event = profiler.RecordEvent("record_add")
record_event.begin()
data1 = paddle.randn(shape=[3])
data2 = paddle.randn(shape=[3])
result = data1 + data2
record_event.end()
**Note**:
RecordEvent will take effect only when :ref:`Profiler <api_paddle_profiler_Profiler>` is on and at the state of `RECORD`.
"""
def __init__(
self,
name: str,
event_type: TracerEventType = TracerEventType.PythonUserDefined,
):
self.name = name
self.event_type = event_type
self.event = None
def __enter__(self):
self.begin()
return self
def __exit__(self, exc_type: Any, exc_value: Any, traceback: Any):
self.end()
def begin(self):
r"""
Record the time of beginning.
Examples:
.. code-block:: python
:name: code-example2
import paddle
import paddle.profiler as profiler
record_event = profiler.RecordEvent("record_sub")
record_event.begin()
data1 = paddle.randn(shape=[3])
data2 = paddle.randn(shape=[3])
result = data1 - data2
record_event.end()
"""
if not _is_profiler_used:
return
if self.event_type not in _AllowedEventTypeList:
warn(
"Only TracerEvent Type in [{}, {}, {}, {}, {}, {},{}]\
can be recorded.".format(
*_AllowedEventTypeList
)
)
self.event = None
else:
self.event = _RecordEvent(self.name, self.event_type)
def end(self):
r'''
Record the time of ending.
Examples:
.. code-block:: python
:name: code-example3
import paddle
import paddle.profiler as profiler
record_event = profiler.RecordEvent("record_mul")
record_event.begin()
data1 = paddle.randn(shape=[3])
data2 = paddle.randn(shape=[3])
result = data1 * data2
record_event.end()
'''
if self.event:
self.event.end()
def load_profiler_result(filename: str):
r"""
Load dumped profiler data back to memory.
Args:
filename(str): Name of the exported protobuf file of profiler data.
Returns:
``ProfilerResult`` object, which stores profiling data.
Examples:
.. code-block:: python
# required: gpu
import paddle.profiler as profiler
with profiler.Profiler(
targets=[profiler.ProfilerTarget.CPU, profiler.ProfilerTarget.GPU],
scheduler = (3, 10)) as p:
for iter in range(10):
#train()
p.step()
p.export('test_export_protobuf.pb', format='pb')
profiler_result = profiler.load_profiler_result('test_export_protobuf.pb')
"""
return core.load_profiler_result(filename)
def in_profiler_mode():
return _is_profiler_used == True
def wrap_optimizers():
def optimizer_warpper(func):
@functools.wraps(func)
def warpper(*args, **kwargs):
if in_profiler_mode():
with RecordEvent(
'Optimization Step', event_type=TracerEventType.Optimization
):
return func(*args, **kwargs)
else:
return func(*args, **kwargs)
return warpper
global _has_optimizer_wrapped
if _has_optimizer_wrapped == True:
return
import paddle.optimizer as optimizer
for classname in optimizer.__all__:
if classname != 'Optimizer':
classobject = getattr(optimizer, classname)
if getattr(classobject, 'step', None) != None:
classobject.step = optimizer_warpper(classobject.step)
_has_optimizer_wrapped = True