Files
pytorch/benchmarks/upload_scribe.py
Will Constable 65066d779b Add fastrnns benchmark to CI and upload data to scribe (#42030)
Summary:
Run fastrnns benchmark using pytest-benchmark infra, then parse its json format and upload to scribe.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/42030

Reviewed By: malfet

Differential Revision: D22970270

Pulled By: wconstab

fbshipit-source-id: 87da9b7ddf741da14b80d20779771d19123be3c5
2020-08-06 10:30:27 -07:00

131 lines
4.9 KiB
Python

"""Scribe Uploader for Pytorch Benchmark Data
Currently supports data in pytest-benchmark format but can be extended.
New fields can be added just by modifying the schema in this file, schema
checking is only here to encourage reusing existing fields and avoiding typos.
"""
import argparse
import time
import json
import os
import requests
import subprocess
from collections import defaultdict
class ScribeUploader:
def __init__(self, category):
self.category = category
def format_message(self, field_dict):
assert 'time' in field_dict, "Missing required Scribe field 'time'"
message = defaultdict(dict)
for field, value in field_dict.items():
if field in self.schema['normal']:
message['normal'][field] = str(value)
elif field in self.schema['int']:
message['int'][field] = int(value)
elif field in self.schema['float']:
message['float'][field] = float(value)
else:
raise ValueError("Field {} is not currently used, "
"be intentional about adding new fields".format(field))
return message
def _upload_intern(self, messages):
for m in messages:
json_str = json.dumps(m)
cmd = ['scribe_cat', self.category, json_str]
subprocess.run(cmd)
def upload(self, messages):
if os.environ.get('SCRIBE_INTERN'):
return self._upload_intern(messages)
access_token = os.environ.get("SCRIBE_GRAPHQL_ACCESS_TOKEN")
if not access_token:
raise ValueError("Can't find access token from environment variable")
url = "https://graph.facebook.com/scribe_logs"
r = requests.post(
url,
data={
"access_token": access_token,
"logs": json.dumps(
[
{
"category": self.category,
"message": json.dumps(message),
"line_escape": False,
}
for message in messages
]
),
},
)
print(r.text)
r.raise_for_status()
class PytorchBenchmarkUploader(ScribeUploader):
def __init__(self):
super().__init__('perfpipe_pytorch_benchmarks')
self.schema = {
'int': [
'time', 'rounds',
],
'normal': [
'benchmark_group', 'benchmark_name', 'benchmark_class', 'benchmark_time',
'pytorch_commit_id', 'pytorch_branch', 'pytorch_commit_time', 'pytorch_version',
'pytorch_git_dirty',
'machine_kernel', 'machine_processor', 'machine_hostname',
'circle_build_num', 'circle_project_reponame',
],
'float': [
'stddev', 'min', 'median', 'max', 'mean',
]
}
def post_pytest_benchmarks(self, pytest_json):
machine_info = pytest_json['machine_info']
commit_info = pytest_json['commit_info']
upload_time = int(time.time())
messages = []
for b in pytest_json['benchmarks']:
m = self.format_message({
"time": upload_time,
"benchmark_group": b['group'],
"benchmark_name": b['name'],
"benchmark_class": b['fullname'],
"benchmark_time": pytest_json['datetime'],
"pytorch_commit_id": commit_info['id'],
"pytorch_branch": commit_info['branch'],
"pytorch_commit_time": commit_info['time'],
"pytorch_version": None,
"pytorch_git_dirty": commit_info['dirty'],
"machine_kernel": machine_info['release'],
"machine_processor": machine_info['processor'],
"machine_hostname": machine_info['node'],
"circle_build_num": os.environ.get("CIRCLE_BUILD_NUM"),
"circle_project_reponame": os.environ.get("CIRCLE_PROJECT_REPONAME"),
"stddev": b['stats']['stddev'],
"rounds": b['stats']['rounds'],
"min": b['stats']['min'],
"median": b['stats']['median'],
"max": b['stats']['max'],
"mean": b['stats']['mean'],
})
messages.append(m)
self.upload(messages)
if __name__ == "__main__":
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument("--pytest_bench_json", type=argparse.FileType('r'),
help='Upload json data formatted by pytest-benchmark module')
args = parser.parse_args()
if args.pytest_bench_json:
benchmark_uploader = PytorchBenchmarkUploader()
json_data = json.load(args.pytest_bench_json)
benchmark_uploader.post_pytest_benchmarks(json_data)