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#!/usr/bin/env python
from __future__ import print_function
import os
import parse.ft as ft
import parse.sched as st
import pickle
import shutil as sh
import sys
import traceback
from collections import namedtuple
from common import load_params
from config.config import DEFAULTS,PARAMS
from optparse import OptionParser
from parse.point import ExpPoint
from parse.tuple_table import TupleTable
from parse.col_map import ColMapBuilder
from multiprocessing import Pool, cpu_count
def parse_args():
parser = OptionParser("usage: %prog [options] [data_dir]...")
parser.add_option('-o', '--out', dest='out',
help='file or directory for data output',
default=DEFAULTS['out-parse'])
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')
parser.add_option('-p', '--processors', default=max(cpu_count() - 1, 1),
type='int', dest='processors',
help='number of threads for processing')
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, DEFAULTS['params_file'])
if os.path.isfile(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)
else:
params = {}
# Cycles must be present for feather-trace measurement parsing
if PARAMS['cycles'] not in params:
params[PARAMS['cycles']] = DEFAULTS['cycles']
return params
def load_exps(exp_dirs, cm_builder, force):
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 force:
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):
# Tupled for multiprocessing
exp, force = exp_force
result_file = exp.work_dir + "/exp_point.pkl"
should_load = not force and os.path.exists(result_file)
result = None
if should_load:
with open(result_file, 'rb') as f:
try:
# No need to go through this work twice
result = pickle.load(f)
except:
pass
if not result:
try:
result = ExpPoint(exp.path)
cycles = exp.params[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)
with open(result_file, 'wb') as f:
pickle.dump(result, f)
except:
traceback.print_exc()
return (exp, result)
def get_exps(args):
if args:
return args
elif os.path.exists(DEFAULTS['out-run']):
sys.stderr.write("Reading data from %s/*\n" % DEFAULTS['out-run'])
sched_dirs = os.listdir(DEFAULTS['out-run'])
return ['%s/%s' % (DEFAULTS['out-run'], d) for d in sched_dirs]
else:
sys.stderr.write("Reading data from current directory.\n")
return [os.getcwd()]
def main():
opts, args = parse_args()
exp_dirs = get_exps(args)
# Load exp parameters into a ColMap
builder = ColMapBuilder()
exps = load_exps(exp_dirs, builder, opts.force)
# Don't track changes in ignored parameters
if opts.ignore:
for param in opts.ignore.split(","):
builder.try_remove(param)
# Always average multiple trials
builder.try_remove(PARAMS['trial'])
col_map = builder.build()
result_table = TupleTable(col_map)
sys.stderr.write("Parsing data...\n")
procs = min(len(exps), opts.processors)
pool = Pool(processes=procs)
pool_args = zip(exps, [opts.force]*len(exps))
enum = pool.imap_unordered(parse_exp, pool_args, 1)
try:
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]
pool.close()
except:
pool.terminate()
traceback.print_exc()
raise Exception("Failed parsing!")
finally:
pool.join()
sys.stderr.write('\n')
if opts.force and os.path.exists(opts.out):
sh.rmtree(opts.out)
reduced_table = result_table.reduce()
if opts.write_map:
sys.stderr.write("Writing python map into %s...\n" % opts.out)
# Write summarized results into map
reduced_table.write_map(opts.out)
else:
# Write out csv directories for all variable params
dir_map = reduced_table.to_dir_map()
# No csvs to write, assume user meant to print out data
if dir_map.is_empty():
if not opts.verbose:
sys.stderr.write("Too little data to make csv files, " +
"printing results.\n")
for key, exp in result_table:
for e in exp:
print(e)
else:
sys.stderr.write("Writing csvs into %s...\n" % opts.out)
dir_map.write(opts.out)
if __name__ == '__main__':
main()
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