# Copyright 2011 The Chromium OS Authors. All rights reserved.
# Use of this source code is governed by a BSD-style license that can be
# found in the LICENSE file.
"""The class to show the banner."""
from __future__ import print_function
import collections
import datetime
import time
class ExperimentStatus(object):
"""The status class."""
def __init__(self, experiment):
self.experiment = experiment
self.num_total = len(self.experiment.benchmark_runs)
self.completed = 0
self.new_job_start_time = time.time()
self.log_level = experiment.log_level
def _GetProgressBar(self, num_complete, num_total):
ret = 'Done: %s%%' % int(100.0 * num_complete / num_total)
bar_length = 50
done_char = '>'
undone_char = ' '
num_complete_chars = bar_length * num_complete / num_total
num_undone_chars = bar_length - num_complete_chars
ret += ' [%s%s]' % (num_complete_chars * done_char,
num_undone_chars * undone_char)
return ret
def GetProgressString(self):
"""Get the elapsed_time, ETA."""
current_time = time.time()
if self.experiment.start_time:
elapsed_time = current_time - self.experiment.start_time
else:
elapsed_time = 0
try:
if self.completed != self.experiment.num_complete:
self.completed = self.experiment.num_complete
self.new_job_start_time = current_time
time_completed_jobs = (elapsed_time -
(current_time - self.new_job_start_time))
# eta is calculated as:
# ETA = (num_jobs_not_yet_started * estimated_time_per_job)
# + time_left_for_current_job
#
# where
# num_jobs_not_yet_started = (num_total - num_complete - 1)
#
# estimated_time_per_job = time_completed_jobs / num_run_complete
#
# time_left_for_current_job = estimated_time_per_job -
# time_spent_so_far_on_current_job
#
# The biggest problem with this calculation is its assumption that
# all jobs have roughly the same running time (blatantly false!).
#
# ETA can come out negative if the time spent on the current job is
# greater than the estimated time per job (e.g. you're running the
# first long job, after a series of short jobs). For now, if that
# happens, we set the ETA to "Unknown."
#
eta_seconds = (float(self.num_total - self.experiment.num_complete - 1) *
time_completed_jobs / self.experiment.num_run_complete +
(time_completed_jobs / self.experiment.num_run_complete -
(current_time - self.new_job_start_time)))
eta_seconds = int(eta_seconds)
if eta_seconds > 0:
eta = datetime.timedelta(seconds=eta_seconds)
else:
eta = 'Unknown'
except ZeroDivisionError:
eta = 'Unknown'
strings = []
strings.append('Current time: %s Elapsed: %s ETA: %s' %
(datetime.datetime.now(),
datetime.timedelta(seconds=int(elapsed_time)), eta))
strings.append(self._GetProgressBar(self.experiment.num_complete,
self.num_total))
return '\n'.join(strings)
def GetStatusString(self):
"""Get the status string of all the benchmark_runs."""
status_bins = collections.defaultdict(list)
for benchmark_run in self.experiment.benchmark_runs:
status_bins[benchmark_run.timeline.GetLastEvent()].append(benchmark_run)
status_strings = []
for key, val in status_bins.iteritems():
if key == 'RUNNING':
get_description = self._GetNamesAndIterations
else:
get_description = self._GetCompactNamesAndIterations
status_strings.append('%s: %s' % (key, get_description(val)))
thread_status = ''
thread_status_format = 'Thread Status: \n{}\n'
if (self.experiment.schedv2() is None and
self.experiment.log_level == 'verbose'):
# Add the machine manager status.
thread_status = thread_status_format.format(
self.experiment.machine_manager.AsString())
elif self.experiment.schedv2():
# In schedv2 mode, we always print out thread status.
thread_status = thread_status_format.format(self.experiment.schedv2(
).threads_status_as_string())
result = '{}{}'.format(thread_status, '\n'.join(status_strings))
return result
def _GetNamesAndIterations(self, benchmark_runs):
strings = []
t = time.time()
for benchmark_run in benchmark_runs:
t_last = benchmark_run.timeline.GetLastEventTime()
elapsed = str(datetime.timedelta(seconds=int(t - t_last)))
strings.append("'{0}' {1}".format(benchmark_run.name, elapsed))
return ' %s (%s)' % (len(strings), ', '.join(strings))
def _GetCompactNamesAndIterations(self, benchmark_runs):
grouped_benchmarks = collections.defaultdict(list)
for benchmark_run in benchmark_runs:
grouped_benchmarks[benchmark_run.label.name].append(benchmark_run)
output_segs = []
for label_name, label_runs in grouped_benchmarks.iteritems():
strings = []
benchmark_iterations = collections.defaultdict(list)
for benchmark_run in label_runs:
assert benchmark_run.label.name == label_name
benchmark_name = benchmark_run.benchmark.name
benchmark_iterations[benchmark_name].append(benchmark_run.iteration)
for key, val in benchmark_iterations.iteritems():
val.sort()
iterations = ','.join(map(str, val))
strings.append('{} [{}]'.format(key, iterations))
output_segs.append(' ' + label_name + ': ' + ', '.join(strings) + '\n')
return ' %s \n%s' % (len(benchmark_runs), ''.join(output_segs))