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c8a609b98e
If heapy is installed print the "average" in-memory remark size. This is estimated by dividing the total heap size by the number of unique remarks. llvm-svn: 308537
79 lines
2.5 KiB
Python
Executable File
79 lines
2.5 KiB
Python
Executable File
#!/usr/bin/env python2.7
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from __future__ import print_function
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desc = '''Generate statistics about optimization records from the YAML files
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generated with -fsave-optimization-record and -fdiagnostics-show-hotness.
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The tools requires PyYAML and Pygments Python packages.'''
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import optrecord
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import argparse
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import operator
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from collections import defaultdict
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from multiprocessing import cpu_count, Pool
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try:
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from guppy import hpy
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hp = hpy()
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except ImportError:
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print("Memory consumption not shown because guppy is not installed")
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hp = None
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if __name__ == '__main__':
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parser = argparse.ArgumentParser(description=desc)
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parser.add_argument(
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'yaml_dirs_or_files',
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nargs='+',
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help='List of optimization record files or directories searched '
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'for optimization record files.')
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parser.add_argument(
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'--jobs',
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'-j',
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default=cpu_count(),
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type=int,
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help='Max job count (defaults to %(default)s, the current CPU count)')
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parser.add_argument(
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'--no-progress-indicator',
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'-n',
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action='store_true',
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default=False,
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help='Do not display any indicator of how many YAML files were read.')
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args = parser.parse_args()
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print_progress = not args.no_progress_indicator
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files = optrecord.find_opt_files(args.yaml_dirs_or_files)
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if not files:
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parser.error("No *.opt.yaml files found")
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sys.exit(1)
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all_remarks, file_remarks, _ = optrecord.gather_results(
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files, args.jobs, print_progress)
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if print_progress:
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print('\n')
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bypass = defaultdict(int)
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byname = defaultdict(int)
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for r in optrecord.itervalues(all_remarks):
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bypass[r.Pass] += 1
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byname[r.Pass + "/" + r.Name] += 1
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total = len(all_remarks)
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print("{:24s} {:10d}".format("Total number of remarks", total))
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if hp:
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h = hp.heap()
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print("{:24s} {:10d}".format("Memory per remark",
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h.size / len(all_remarks)))
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print('\n')
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print("Top 10 remarks by pass:")
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for (passname, count) in sorted(bypass.items(), key=operator.itemgetter(1),
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reverse=True)[:10]:
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print(" {:30s} {:2.0f}%". format(passname, count * 100. / total))
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print("\nTop 10 remarks:")
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for (name, count) in sorted(byname.items(), key=operator.itemgetter(1),
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reverse=True)[:10]:
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print(" {:30s} {:2.0f}%". format(name, count * 100. / total))
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