def merge_checkpoint_benchmark_results(checkpoint_dir):
checkpoint_files = glob.glob(os.path.join(checkpoint_dir,
"**/*.ckpnt"),
recursive=True)
merged_result = BenchmarkResult()
# merge all checkpoints with new results
for checkpoint_file in checkpoint_files:
logging.info("Loading checkpoint {}".format(
os.path.abspath(checkpoint_file)))
next_result = BenchmarkResult.load(os.path.abspath(checkpoint_file), \
load_configs=True, load_histories=True)
merged_result.extend(next_result)
# dump merged result
if len(merged_result.get_result_dict()) > 0:
logging.info("Dumping merged result")
merged_result_filename = os.path.join(checkpoint_dir,
"merged_results.ckpnt")
merged_result.dump(merged_result_filename, \
dump_configs=True, dump_histories=True)
# delete checkpoints
for checkpoint_file in checkpoint_files:
if checkpoint_file == merged_result_filename:
continue
os.remove(checkpoint_file)
logging.info(
"Removed old checkpoint file {}".format(checkpoint_file))
return merged_result
def test_dump_and_partial_load(self):
result_num = 100
confs, result_data, histories = random_benchmark_conf_data(result_num, 2000000, hist_size=1500000)
br = BenchmarkResult(result_dict=result_data,
benchmark_configs=confs, histories=histories)
br.dump("./results_all", dump_configs=True, dump_histories=True, max_mb_per_file = 5)
br_loaded = BenchmarkResult.load("./results_all")
loaded_dict = br_loaded.get_result_dict()
self.assertEqual(br.get_result_dict(), loaded_dict)
loaded_configs_idx = list(range(10, 20))
processed_files = br_loaded.load_benchmark_configs(config_idx_list = loaded_configs_idx)
loaded_confs = br_loaded.get_benchmark_configs()
self.assertEqual(len(loaded_confs), 10)
# 2mb per conf, max 5 mb per file -> 2 confs per file -> 10/2 = 5files
self.assertEqual(len(processed_files), 5)
for conf_idx in loaded_configs_idx:
self.assertEqual(br_loaded.get_benchmark_config(conf_idx), confs[conf_idx])
loaded_configs_idx = list(range(10, 27))
processed_files = br_loaded.load_histories(config_idx_list = loaded_configs_idx)
loaded_histories = br_loaded.get_histories()
self.assertEqual(len(loaded_histories), 18) # one more as specified since it was in the last file
# 1.5mb per history, max 5 mb per file -> 3 confs per file -> 17/3 = 6files
self.assertEqual(len(processed_files), 6)
for conf_idx in loaded_configs_idx:
self.assertEqual(br_loaded.get_history(conf_idx), histories[conf_idx])
def run(self, viewer=None, maintain_history=False, checkpoint_every=None):
results = []
histories = {}
for idx, bmark_conf in enumerate(self.configs_to_run):
self.logger.info(
"Running config idx {} being {}/{}: Scenario {} of set \"{}\" for behavior \"{}\""
.format(bmark_conf.config_idx, idx,
len(self.benchmark_configs) - 1,
bmark_conf.scenario_idx, bmark_conf.scenario_set_name,
bmark_conf.behavior_config.behavior_name))
bmark_conf = copy.deepcopy(
bmark_conf) if self._deepcopy else bmark_conf
result_dict, scenario_history = self._run_benchmark_config(
bmark_conf, viewer, maintain_history)
results.append(result_dict)
histories[bmark_conf.config_idx] = scenario_history
if self.log_eval_avg_every and (idx +
1) % self.log_eval_avg_every == 0:
self._log_eval_average(results, self.configs_to_run)
if checkpoint_every and (idx + 1) % checkpoint_every == 0:
intermediate_result = BenchmarkResult(results, \
self.configs_to_run[0:idx+1], histories=histories)
checkpoint_file = os.path.join(self.checkpoint_dir,
self.get_checkpoint_file_name())
intermediate_result.dump(checkpoint_file,
dump_configs=True,
dump_histories=maintain_history)
self.logger.info("Saved checkpoint {}".format(checkpoint_file))
benchmark_result = BenchmarkResult(results,
self.configs_to_run,
histories=histories)
self.existing_benchmark_result.extend(benchmark_result)
return self.existing_benchmark_result
def test_dump_and_load_results(self):
result_data = random_result_data(size = 10)
br = BenchmarkResult(result_dict=result_data)
br.dump("./results")
br_loaded = BenchmarkResult.load("./results")
loaded_dict = br_loaded.get_result_dict()
self.assertEqual(result_data, loaded_dict)
def test_dump_and_load_benchmark_configs(self):
result_num = 100
confs, result_data, _ = random_benchmark_conf_data(result_num, 2000000)
br = BenchmarkResult(result_dict=result_data, benchmark_configs=confs)
br.dump("./results_with_confs", dump_configs=True, max_mb_per_file = 5)
br_loaded = BenchmarkResult.load("./results_with_confs")
br_loaded.load_benchmark_configs(config_idx_list = list(range(0, result_num)))
loaded_confs = br_loaded.get_benchmark_configs()
self.assertEqual(confs, loaded_confs)
loaded_dict = br_loaded.get_result_dict()
self.assertEqual(br.get_result_dict(), loaded_dict)
def test_dump_and_load_histories_one(self):
result_num = 2
result_data = random_result_data(size = result_num)
histories = random_history_data(result_num, 20)
br = BenchmarkResult(result_dict=result_data, histories=histories)
br.dump("./results_with_history", dump_histories=True, max_mb_per_file = 2)
br_loaded = BenchmarkResult.load("./results_with_history")
br_loaded.load_histories(config_idx_list = list(histories.keys()))
loaded_histories = br_loaded.get_histories()
self.assertEqual(histories, loaded_histories)
loaded_dict = br_loaded.get_result_dict()
self.assertEqual(result_data, loaded_dict)
def run(self, viewer=None, maintain_history=False, checkpoint_every=None):
last_results = []
last_histories = {}
last_run_configs = []
results = []
checkpoint_file = os.path.abspath(os.path.join(self.checkpoint_dir, self.get_checkpoint_file_name()))
last_result_file = os.path.abspath(os.path.join(self.checkpoint_dir, "tmp_{}".format(self.get_checkpoint_file_name())))
checkpoint_result = BenchmarkResult(file_name=checkpoint_file)
for idx, bmark_conf in enumerate(self.configs_to_run):
self.logger.info("Running config idx {} being {}/{}: Scenario {} of set \"{}\" for behavior \"{}\"".format(
bmark_conf.config_idx, idx, len(self.benchmark_configs) - 1, bmark_conf.scenario_idx,
bmark_conf.scenario_set_name, bmark_conf.behavior_config.behavior_name))
bmark_conf = copy.deepcopy(bmark_conf) if self._deepcopy else bmark_conf
result_dict, scenario_history = self._run_benchmark_config(bmark_conf, viewer,
maintain_history)
results.append(result_dict)
last_results.append(result_dict)
last_histories[bmark_conf.config_idx] = scenario_history
last_run_configs.append(bmark_conf)
if self.log_eval_avg_every and (idx + 1) % self.log_eval_avg_every == 0:
self._log_eval_average(results, self.configs_to_run)
if checkpoint_every and (idx+1) % checkpoint_every == 0:
# append results since last checkpoint
last_benchmark_result = BenchmarkResult(result_dict=last_results, file_name = last_result_file, \
benchmark_configs=last_run_configs, histories=last_histories)
last_benchmark_result.dump(last_result_file, dump_configs=True, dump_histories=maintain_history, append=False)
checkpoint_result.extend(benchmark_result=last_benchmark_result, file_level=True)
self.logger.info("Extended checkpoint {} with last result.".format(checkpoint_file))
last_histories.clear()
last_run_configs.clear()
last_results.clear()
# append results of last run
last_benchmark_result = BenchmarkResult(result_dict=last_results, file_name = last_result_file, \
benchmark_configs=last_run_configs, histories=last_histories)
last_benchmark_result.dump(last_result_file, dump_configs=True, dump_histories=maintain_history, append=False)
checkpoint_result.extend(benchmark_result=last_benchmark_result, file_level=True)
os.remove(last_result_file)
self.logger.info("Extended checkpoint {} with final result.".format(checkpoint_file))
checkpoint_result.extend(benchmark_result=self.existing_benchmark_result, file_level=True)
return checkpoint_result
def test_extend_from_file(self):
try:
os.remove("./br1")
os.remove("./br2")
os.remove("./br3")
except:
pass
result_num = 100
confs, result_data, histories1 = random_benchmark_conf_data(result_num, 2000000, hist_size=1500000, offset=0)
br1 = BenchmarkResult(result_dict=result_data,
benchmark_configs=confs, histories=histories1)
br1.dump("./br1", dump_histories=True, dump_configs=True)
br1_df = br1.get_data_frame().copy()
result_num = 30
confs2, result_data2, histories2 = random_benchmark_conf_data(result_num, 2000000, hist_size=1500000, offset=200)
br2 = BenchmarkResult(result_dict=result_data2,
benchmark_configs=confs2, histories=histories2)
br2.dump(filename="./br2", dump_histories=True, dump_configs=True)
result_num = 10
confs3, result_data3, histories3 = random_benchmark_conf_data(result_num, 2000000, hist_size=1500000, offset=400)
br3 = BenchmarkResult(result_dict=result_data3,
benchmark_configs=confs3, histories=histories3)
br3.dump(filename="./br3", dump_histories=True, dump_configs=True)
br1.extend(benchmark_result=br2, file_level=True)
br1.extend(benchmark_result=br3, file_level=True)
br_loaded = BenchmarkResult.load("./br1", load_histories=True, load_configs=True)
df_desired = br1_df
df_desired = pd.concat([df_desired, br2.get_data_frame()])
df_desired = pd.concat([df_desired, br3.get_data_frame()])
self.assertEqual(len(br_loaded.get_data_frame().index), len(df_desired.index))
extended_confs = br_loaded.get_benchmark_configs()
self.assertEqual(len(extended_confs), 140)
extended_histories = br_loaded.get_histories()
self.assertEqual(len(extended_histories), 140)
extended_histories = histories1
extended_histories.update(histories2)
extended_histories.update(histories3)
for bc in extended_confs:
self.assertEqual(br_loaded.get_history(bc.config_idx), extended_histories[bc.config_idx])