taskflow/tfprof/server/tfprof.py at task_isolation · ModuleWorks/taskflow · GitHub

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#!/usr/bin/env python3

# program: tfprof

import logging as logger

import time

import sys

import json

import argparse

import os

import subprocess

import requests

# run_tfprof (default)

# generate profiler data in taskflow profiler format

def run_tfprof(args):

args.output = os.path.abspath(args.output);

logger.info("profiling program \"" + ' '.join(args.program) + "\"")

## open the output file

with open(args.output, "w") as ofs:

ofs.write('[');

os.environ["TF_ENABLE_PROFILER"] = args.output;

## launch the program

prob = time.perf_counter();

subprocess.call(args.program);

proe = time.perf_counter();

logger.info(f"finished with {(proe - prob)*1000:0.2f} milliseconds");

logger.info(f"saved result to {args.output:s}");

if(args.port == None):

return;

logger.info(f"sending the result to localhost:{args.port:d}");

# run_chrome (TODO)

# generate the profiler data in chrome tracing format

# main function

def main():

# configure logger

logger.basicConfig(

#format='%(asctime)s %(name)-12s %(levelname)-8s %(message)s',

format='%(asctime)s %(levelname)s: %(message)s',

datefmt='%m/%d/%Y %I:%M:%S',

level=logger.DEBUG

)

# parse the input arguments

parser = argparse.ArgumentParser();

parser.add_argument(

'-o', '--output',

type=str,

help='file to save the result (default: output.tfp)',

default="output.tfp"

)

parser.add_argument(

'-p', '--port',

type=int,

help='port number of the profiler server (default: None)',

default=None

)

parser.add_argument(

'program',

nargs=argparse.REMAINDER,

help='program to profile (e.g., path/to/binary args)'

)

args = parser.parse_args();

if(len(args.program) == 0) :

logger.error("no program specified");

sys.exit(1);

run_tfprof(args);

# main entry

if __name__ == "__main__":

main();

taskflow/tfprof/server/tfprof.py at task_isolation · ModuleWorks/taskflow · GitHub

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