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@ -39,7 +39,6 @@ DEFAULT_BUCK_OUT_GEN = os.path.join(DEFAULT_BUCK_OUT, 'gen')
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INFER_JSON_REPORT = os.path.join(config.BUCK_INFER_OUT,
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config.JSON_REPORT_FILENAME)
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INFER_STATS = os.path.join(config.BUCK_INFER_OUT, config.STATS_FILENAME)
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INFER_SCRIPT = """\
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#!/usr/bin/env {python_executable}
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@ -138,136 +137,10 @@ def get_normalized_targets(targets):
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raise e
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def init_stats(args, start_time):
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"""Returns dictionary with target independent statistics.
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"""
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return {
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'float': {},
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'int': {
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'cores': multiprocessing.cpu_count(),
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'time': int(time.time()),
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'start_time': int(round(start_time)),
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},
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'normal': {
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'debug': str(args.debug),
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'analyzer': args.analyzer,
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'machine': platform.machine(),
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'node': platform.node(),
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'project': utils.decode(os.path.basename(os.getcwd())),
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'revision': utils.vcs_revision(),
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'branch': utils.vcs_branch(),
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'system': platform.system(),
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'infer_version': utils.infer_version(),
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'infer_branch': utils.infer_branch(),
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}
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}
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def store_performances_csv(infer_out, stats):
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"""Stores the statistics about perfromances into a CSV file to be exported
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to a database"""
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perf_filename = os.path.join(infer_out, config.CSV_PERF_FILENAME)
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with open(perf_filename, 'w') as csv_file_out:
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csv_writer = csv.writer(csv_file_out)
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keys = ['infer_version', 'project', 'revision', 'files', 'lines',
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'cores', 'system', 'machine', 'node', 'total_time',
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'capture_time', 'analysis_time', 'reporting_time', 'time']
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int_stats = list(stats['int'].items())
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normal_stats = list(stats['normal'].items())
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flat_stats = dict(int_stats + normal_stats)
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values = []
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for key in keys:
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if key in flat_stats:
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values.append(flat_stats[key])
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csv_writer.writerow(keys)
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csv_writer.writerow(values)
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csv_file_out.flush()
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def get_harness_code():
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all_harness_code = '\nGenerated harness code:\n'
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for filename in os.listdir(DEFAULT_BUCK_OUT_GEN):
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if 'InferGeneratedHarness' in filename:
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all_harness_code += '\n' + filename + ':\n'
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with open(os.path.join(DEFAULT_BUCK_OUT_GEN,
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filename), 'r') as file_in:
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all_harness_code += file_in.read()
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return all_harness_code + '\n'
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def get_basic_stats(stats):
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files_analyzed = '{0} files ({1} lines) analyzed in {2}s\n\n'.format(
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stats['int'].get('files', 0),
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stats['int'].get('lines', 0),
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stats['int']['total_time'],
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)
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phase_times = 'Capture time: {0}s\nAnalysis time: {1}s\n\n'.format(
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stats['int'].get('capture_time', 0),
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stats['int'].get('analysis_time', 0),
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)
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to_skip = {
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'files',
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'procedures',
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'lines',
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'cores',
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'time',
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'start_time',
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'capture_time',
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'analysis_time',
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'reporting_time',
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'total_time',
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'makefile_generation_time'
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}
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bugs_found = 'Errors found:\n\n'
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for key, value in sorted(stats['int'].items()):
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if key not in to_skip:
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bugs_found += ' {0:>8} {1}\n'.format(value, key)
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basic_stats_message = files_analyzed + phase_times + bugs_found + '\n'
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return basic_stats_message
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def get_buck_stats():
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trace_filename = os.path.join(
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DEFAULT_BUCK_OUT,
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'log',
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'traces',
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'build.trace'
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)
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ARGS = 'args'
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SUCCESS_STATUS = 'success_type'
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buck_stats = {}
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try:
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trace = utils.load_json_from_path(trace_filename)
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for t in trace:
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if SUCCESS_STATUS in t[ARGS]:
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status = t[ARGS][SUCCESS_STATUS]
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count = buck_stats.get(status, 0)
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buck_stats[status] = count + 1
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buck_stats_message = 'Buck build statistics:\n\n'
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for key, value in sorted(buck_stats.items()):
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buck_stats_message += ' {0:>8} {1}\n'.format(value, key)
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return buck_stats_message
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except IOError as e:
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logging.error('Caught %s: %s' % (e.__class__.__name__, str(e)))
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logging.error(traceback.format_exc())
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return ''
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class NotFoundInJar(Exception):
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pass
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def load_stats(opened_jar):
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try:
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return json.loads(opened_jar.read(INFER_STATS).decode())
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except KeyError:
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raise NotFoundInJar
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def load_json_report(opened_jar):
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try:
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return json.loads(opened_jar.read(INFER_JSON_REPORT).decode())
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@ -289,13 +162,7 @@ def collect_results(args, start_time, targets):
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"""Walks through buck-gen, collects results for the different buck targets
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and stores them in in args.infer_out/results.csv.
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"""
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buck_stats = get_buck_stats()
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logging.info(buck_stats)
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with open(os.path.join(args.infer_out, ANALYSIS_SUMMARY_OUTPUT), 'w') as f:
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f.write(buck_stats)
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all_json_rows = set()
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stats = init_stats(args, start_time)
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accumulation_whitelist = list(map(re.compile, [
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'^cores$',
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@ -304,36 +171,12 @@ def collect_results(args, start_time, targets):
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'.*_pc',
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]))
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expected_analyzer = stats['normal']['analyzer']
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expected_version = stats['normal']['infer_version']
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for path in get_output_jars(targets):
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try:
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with zipfile.ZipFile(path) as jar:
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# Accumulate integers and float values
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target_stats = load_stats(jar)
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found_analyzer = target_stats['normal']['analyzer']
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found_version = target_stats['normal']['infer_version']
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if found_analyzer != expected_analyzer \
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or found_version != expected_version:
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continue
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else:
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for type_k in ['int', 'float']:
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items = target_stats.get(type_k, {}).items()
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for key, value in items:
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if not any(map(lambda r: r.match(key),
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accumulation_whitelist)):
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old_value = stats[type_k].get(key, 0)
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stats[type_k][key] = old_value + value
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json_rows = load_json_report(jar)
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for row in json_rows:
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all_json_rows.add(json.dumps(row))
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# Override normals
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stats['normal'].update(target_stats.get('normal', {}))
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except NotFoundInJar:
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pass
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except zipfile.BadZipfile:
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@ -341,13 +184,6 @@ def collect_results(args, start_time, targets):
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json_report = os.path.join(args.infer_out, config.JSON_REPORT_FILENAME)
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# Convert all float values to integer values
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for key, value in stats.get('float', {}).items():
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stats['int'][key] = int(round(value))
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# Delete the float entries before exporting the results
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del(stats['float'])
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with open(json_report, 'w') as report:
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json_string = '['
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json_string += ','.join(all_json_rows)
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@ -355,29 +191,10 @@ def collect_results(args, start_time, targets):
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report.write(json_string)
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report.flush()
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print('\n')
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json_report = os.path.join(args.infer_out, config.JSON_REPORT_FILENAME)
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bugs_out = os.path.join(args.infer_out, config.BUGS_FILENAME)
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issues.print_and_save_errors(args.infer_out, args.project_root,
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json_report, bugs_out, args.pmd_xml)
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stats['int']['total_time'] = int(round(utils.elapsed_time(start_time)))
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store_performances_csv(args.infer_out, stats)
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stats_filename = os.path.join(args.infer_out, config.STATS_FILENAME)
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utils.dump_json_to_path(stats, stats_filename)
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basic_stats = get_basic_stats(stats)
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if args.print_harness:
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harness_code = get_harness_code()
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basic_stats += harness_code
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logging.info(basic_stats)
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with open(os.path.join(args.infer_out, ANALYSIS_SUMMARY_OUTPUT), 'a') as f:
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f.write(basic_stats)
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shutil.copy(bugs_out, os.path.join(args.infer_out, ANALYSIS_SUMMARY_OUTPUT))
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def cleanup(temp_files):
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Josh Berdine
8 years ago
committed by
Facebook Github Bot