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#!/usr/bin/env python
from __future__ import print_function
import config.config as conf
import os
import parse.ft as ft
import parse.sched as st
import pickle
import shutil as sh
import sys
from collections import namedtuple
from common import load_params
from optparse import OptionParser
from parse.dir_map import DirMap
from parse.point import ExpPoint
from parse.tuple_table import TupleTable,ReducedTupleTable
from parse.col_map import ColMapBuilder
from multiprocessing import Pool, cpu_count
def parse_args():
# TODO: convert data-dir to proper option, clean 'dest' options
parser = OptionParser("usage: %prog [options] [data_dir]...")
print("default to no params.py")
print("save measurements in temp directory for faster reloading")
parser.add_option('-o', '--out', dest='out',
help='file or directory for data output', default='parse-data')
parser.add_option('-c', '--clean', action='store_true', default=False,
dest='clean', help='do not output single-point csvs')
parser.add_option('-i', '--ignore', metavar='[PARAM...]', default="",
help='ignore changing parameter values')
parser.add_option('-f', '--force', action='store_true', default=False,
dest='force', help='overwrite existing data')
parser.add_option('-v', '--verbose', action='store_true', default=False,
dest='verbose', help='print out data points')
parser.add_option('-m', '--write-map', action='store_true', default=False,
dest='write_map',
help='Output map of values instead of csv tree')
return parser.parse_args()
ExpData = namedtuple('ExpData', ['path', 'params', 'work_dir'])
def get_exp_params(data_dir, cm_builder):
param_file = "%s/%s" % (data_dir, conf.DEFAULTS['params_file'])
if not os.path.isfile:
raise Exception("No param file '%s' exists!" % param_file)
params = load_params(param_file)
# Store parameters in cm_builder, which will track which parameters change
# across experiments
for key, value in params.iteritems():
cm_builder.try_add(key, value)
# Cycles must be present for feather-trace measurement parsing
if conf.PARAMS['cycles'] not in params:
params[conf.PARAMS['cycles']] = conf.DEFAULTS['cycles']
return params
def load_exps(exp_dirs, cm_builder, clean):
exps = []
sys.stderr.write("Loading experiments...\n")
for data_dir in exp_dirs:
if not os.path.isdir(data_dir):
raise IOError("Invalid experiment '%s'" % os.path.abspath(data_dir))
# Used to store error output and debugging info
work_dir = data_dir + "/tmp"
if os.path.exists(work_dir) and clean:
sh.rmtree(work_dir)
if not os.path.exists(work_dir):
os.mkdir(work_dir)
params = get_exp_params(data_dir, cm_builder)
exps += [ ExpData(data_dir, params, work_dir) ]
return exps
def parse_exp(exp, force):
result_file = exp.work_dir + "/exp_point.pkl"
should_load = not force and os.path.exists(result_file)
mode = 'r' if should_load else 'w'
with open(result_file, mode + 'b') as f:
if should_load:
# No need to go through this work twice
result = pickle.load(f)
else:
result = ExpPoint(exp.path)
cycles = exp.params[conf.PARAMS['cycles']]
# Write overheads into result
ft.extract_ft_data(result, exp.path, exp.work_dir, cycles)
# Write scheduling statistics into result
st.extract_sched_data(result, exp.path, exp.work_dir)
pickle.dump(result, f)
return (exp, result)
def main():
opts, args = parse_args()
args = args or [os.getcwd()]
# Load exp parameters into a ColMap
builder = ColMapBuilder()
exps = load_exps(args, builder, opts.force)
# Don't track changes in ignored parameters
if opts.ignore:
for param in opts.ignore.split(","):
builder.try_remove(param)
col_map = builder.build()
result_table = TupleTable(col_map)
sys.stderr.write("Parsing data...\n")
procs = min(len(exps), cpu_count()/2)
pool = Pool(processes=procs)
enum = pool.imap_unordered(parse_exp, exps, [opts.force]*len(exps))
for i, (exp, result) in enumerate(enum):
if opts.verbose:
print(result)
else:
sys.stderr.write('\r {0:.2%}'.format(float(i)/len(exps)))
result_table[exp.params] += [result]
sys.stderr.write('\n')
if opts.force and os.path.exists(opts.out):
sh.rmtree(opts.out)
result_table = result_table.reduce()
sys.stderr.write("Writing result...\n")
if opts.write_map:
# Write summarized results into map
result_table.write_map(opts.out)
else:
# Write out csv directories for all variable params
dir_map = result_table.to_dir_map()
dir_map.write(opts.out)
if __name__ == '__main__':
main()
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