# Copyright (c) 2018 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.
import argparse
import json
import six
import sys
import unittest
import google.protobuf.text_format as text_format
import paddle.fluid.proto.profiler.profiler_pb2 as profiler_pb2
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument(
'--profile_path',
type=str,
default='',
help='Input profile file name. If there are multiple file, the format '
'should be trainer1=file1,trainer2=file2,ps=file3')
parser.add_argument(
'--timeline_path', type=str, default='', help='Output timeline file name.')
args = parser.parse_args()
class _ChromeTraceFormatter(object):
def __init__(self):
self._events = []
self._metadata = []
def _create_event(self, ph, category, name, pid, tid, timestamp):
"""Creates a new Chrome Trace event.
For details of the file format, see:
https://github.com/catapult-project/catapult/blob/master/tracing/README.md
Args:
ph: The type of event - usually a single character.
category: The event category as a string.
name: The event name as a string.
pid: Identifier of the process generating this event as an integer.
tid: Identifier of the thread generating this event as an integer.
timestamp: The timestamp of this event as a long integer.
Returns:
A JSON compatible event object.
"""
event = {}
event['ph'] = ph
event['cat'] = category
event['name'] = name
event['pid'] = pid
event['tid'] = tid
event['ts'] = timestamp
return event
def emit_pid(self, name, pid):
"""Adds a process metadata event to the trace.
Args:
name: The process name as a string.
pid: Identifier of the process as an integer.
"""
event = {}
event['name'] = 'process_name'
event['ph'] = 'M'
event['pid'] = pid
event['args'] = {'name': name}
self._metadata.append(event)
def emit_region(self, timestamp, duration, pid, tid, category, name, args):
"""Adds a region event to the trace.
Args:
timestamp: The start timestamp of this region as a long integer.
duration: The duration of this region as a long integer.
pid: Identifier of the process generating this event as an integer.
tid: Identifier of the thread generating this event as an integer.
category: The event category as a string.
name: The event name as a string.
args: A JSON-compatible dictionary of event arguments.
"""
event = self._create_event('X', category, name, pid, tid, timestamp)
event['dur'] = duration
event['args'] = args
self._events.append(event)
def emit_counter(self, category, name, pid, timestamp, counter, value):
"""Emits a record for a single counter.
Args:
category: The event category as string
name: The event name as string
pid: Identifier of the process generating this event as integer
timestamp: The timestamps of this event as long integer
counter: Name of the counter as string
value: Value of the counter as integer
tid: Thread id of the allocation as integer
"""
event = self._create_event('C', category, name, pid, 0, timestamp)
event['args'] = {counter: value}
self._events.append(event)
def format_to_string(self, pretty=False):
"""Formats the chrome trace to a string.
Args:
pretty: (Optional.) If True, produce human-readable JSON output.
Returns:
A JSON-formatted string in Chrome Trace format.
"""
trace = {}
trace['traceEvents'] = self._metadata + self._events
if pretty:
return json.dumps(trace, indent=4, separators=(',', ': '))
else:
return json.dumps(trace, separators=(',', ':'))
class Timeline(object):
def __init__(self, profile_dict):
self._profile_dict = profile_dict
self._pid = 0
self._devices = dict()
self._mem_devices = dict()
self._chrome_trace = _ChromeTraceFormatter()
def _allocate_pid(self):
cur_pid = self._pid
self._pid += 1
return cur_pid
def _allocate_pids(self):
for k, profile_pb in six.iteritems(self._profile_dict):
for event in profile_pb.events:
if event.type == profiler_pb2.Event.CPU:
if (k, event.device_id, "CPU") not in self._devices:
pid = self._allocate_pid()
self._devices[(k, event.device_id, "CPU")] = pid
# -1 device id represents CUDA API(RunTime) call.(e.g. cudaLaunch, cudaMemcpy)
if event.device_id == -1:
self._chrome_trace.emit_pid("%s:cuda_api" % k, pid)
else:
self._chrome_trace.emit_pid(
"%s:cpu:block:%d" % (k, event.device_id), pid)
elif event.type == profiler_pb2.Event.GPUKernel:
if (k, event.device_id, "GPUKernel") not in self._devices:
pid = self._allocate_pid()
self._devices[(k, event.device_id, "GPUKernel")] = pid
self._chrome_trace.emit_pid("%s:gpu:%d" %
(k, event.device_id), pid)
if not hasattr(profile_pb, "mem_events"):
continue
for mevent in profile_pb.mem_events:
if mevent.place == profiler_pb2.MemEvent.CUDAPlace:
if (k, mevent.device_id, "GPU") not in self._mem_devices:
pid = self._allocate_pid()
self._mem_devices[(k, mevent.device_id, "GPU")] = pid
self._chrome_trace.emit_pid(
"memory usage on %s:gpu:%d" % (k, mevent.device_id),
pid)
elif mevent.place == profiler_pb2.MemEvent.CPUPlace:
if (k, mevent.device_id, "CPU") not in self._mem_devices:
pid = self._allocate_pid()
self._mem_devices[(k, mevent.device_id, "CPU")] = pid
self._chrome_trace.emit_pid(
"memory usage on %s:cpu:%d" % (k, mevent.device_id),
pid)
elif mevent.place == profiler_pb2.MemEvent.CUDAPinnedPlace:
if (k, mevent.device_id, "CUDAPinnedPlace"
) not in self._mem_devices:
pid = self._allocate_pid()
self._mem_devices[(k, mevent.device_id,
"CUDAPinnedPlace")] = pid
self._chrome_trace.emit_pid(
"memory usage on %s:cudapinnedplace:%d" %
(k, mevent.device_id), pid)
if (k, 0, "CPU") not in self._mem_devices:
pid = self._allocate_pid()
self._mem_devices[(k, 0, "CPU")] = pid
self._chrome_trace.emit_pid("memory usage on %s:cpu:%d" %
(k, 0), pid)
if (k, 0, "GPU") not in self._mem_devices:
pid = self._allocate_pid()
self._mem_devices[(k, 0, "GPU")] = pid
self._chrome_trace.emit_pid("memory usage on %s:gpu:%d" %
(k, 0), pid)
if (k, 0, "CUDAPinnedPlace") not in self._mem_devices:
pid = self._allocate_pid()
self._mem_devices[(k, 0, "CUDAPinnedPlace")] = pid
self._chrome_trace.emit_pid(
"memory usage on %s:cudapinnedplace:%d" % (k, 0), pid)
def _allocate_events(self):
for k, profile_pb in six.iteritems(self._profile_dict):
for event in profile_pb.events:
if event.type == profiler_pb2.Event.CPU:
type = "CPU"
elif event.type == profiler_pb2.Event.GPUKernel:
type = "GPUKernel"
pid = self._devices[(k, event.device_id, type)]
args = {'name': event.name}
if event.memcopy.bytes > 0:
args['mem_bytes'] = event.memcopy.bytes
if hasattr(event, "detail_info") and event.detail_info:
args['detail_info'] = event.detail_info
# TODO(panyx0718): Chrome tracing only handles ms. However, some
# ops takes micro-seconds. Hence, we keep the ns here.
self._chrome_trace.emit_region(
event.start_ns, (event.end_ns - event.start_ns) / 1.0, pid,
event.sub_device_id, 'Op', event.name, args)
def _allocate_memory_event(self):
if not hasattr(profiler_pb2, "MemEvent"):
return
place_to_str = {
profiler_pb2.MemEvent.CPUPlace: "CPU",
profiler_pb2.MemEvent.CUDAPlace: "GPU",
profiler_pb2.MemEvent.CUDAPinnedPlace: "CUDAPinnedPlace"
}
for k, profile_pb in six.iteritems(self._profile_dict):
mem_list = []
end_profiler = 0
for mevent in profile_pb.mem_events:
crt_info = dict()
crt_info['time'] = mevent.start_ns
crt_info['size'] = mevent.bytes
if mevent.place in place_to_str:
place = place_to_str[mevent.place]
else:
place = "UnDefine"
crt_info['place'] = place
pid = self._mem_devices[(k, mevent.device_id, place)]
crt_info['pid'] = pid
crt_info['thread_id'] = mevent.thread_id
crt_info['device_id'] = mevent.device_id
mem_list.append(crt_info)
crt_info = dict()
crt_info['place'] = place
crt_info['pid'] = pid
crt_info['thread_id'] = mevent.thread_id
crt_info['device_id'] = mevent.device_id
crt_info['time'] = mevent.end_ns
crt_info['size'] = -mevent.bytes
mem_list.append(crt_info)
end_profiler = max(end_profiler, crt_info['time'])
mem_list.sort(key=lambda tmp: (tmp.get('time', 0)))
i = 0
total_size = 0
while i < len(mem_list):
total_size += mem_list[i]['size']
while i < len(mem_list) - 1 and mem_list[i]['time'] == mem_list[
i + 1]['time']:
total_size += mem_list[i + 1]['size']
i += 1
self._chrome_trace.emit_counter(
"Memory", "Memory", mem_list[i]['pid'], mem_list[i]['time'],
0, total_size)
i += 1
def generate_chrome_trace(self):
self._allocate_pids()
self._allocate_events()
self._allocate_memory_event()
return self._chrome_trace.format_to_string()
profile_path = '/tmp/profile'
if args.profile_path:
profile_path = args.profile_path
timeline_path = '/tmp/timeline'
if args.timeline_path:
timeline_path = args.timeline_path
profile_paths = profile_path.split(',')
profile_dict = dict()
if len(profile_paths) == 1:
with open(profile_path, 'rb') as f:
profile_s = f.read()
profile_pb = profiler_pb2.Profile()
profile_pb.ParseFromString(profile_s)
profile_dict['trainer'] = profile_pb
else:
for profile_path in profile_paths:
k, v = profile_path.split('=')
with open(v, 'rb') as f:
profile_s = f.read()
profile_pb = profiler_pb2.Profile()
profile_pb.ParseFromString(profile_s)
profile_dict[k] = profile_pb
tl = Timeline(profile_dict)
with open(timeline_path, 'w') as f:
f.write(tl.generate_chrome_trace())