Import prebuilt clang toolchain for linux.
diff --git a/linux-x64/clang/share/opt-viewer/opt-stats.py b/linux-x64/clang/share/opt-viewer/opt-stats.py
new file mode 100755
index 0000000..03de23b
--- /dev/null
+++ b/linux-x64/clang/share/opt-viewer/opt-stats.py
@@ -0,0 +1,78 @@
+#!/usr/bin/env python2.7
+
+from __future__ import print_function
+
+desc = '''Generate statistics about optimization records from the YAML files
+generated with -fsave-optimization-record and -fdiagnostics-show-hotness.
+
+The tools requires PyYAML and Pygments Python packages.'''
+
+import optrecord
+import argparse
+import operator
+from collections import defaultdict
+from multiprocessing import cpu_count, Pool
+
+try:
+ from guppy import hpy
+ hp = hpy()
+except ImportError:
+ print("Memory consumption not shown because guppy is not installed")
+ hp = None
+
+if __name__ == '__main__':
+ parser = argparse.ArgumentParser(description=desc)
+ parser.add_argument(
+ 'yaml_dirs_or_files',
+ nargs='+',
+ help='List of optimization record files or directories searched '
+ 'for optimization record files.')
+ parser.add_argument(
+ '--jobs',
+ '-j',
+ default=None,
+ type=int,
+ help='Max job count (defaults to %(default)s, the current CPU count)')
+ parser.add_argument(
+ '--no-progress-indicator',
+ '-n',
+ action='store_true',
+ default=False,
+ help='Do not display any indicator of how many YAML files were read.')
+ args = parser.parse_args()
+
+ print_progress = not args.no_progress_indicator
+
+ files = optrecord.find_opt_files(*args.yaml_dirs_or_files)
+ if not files:
+ parser.error("No *.opt.yaml files found")
+ sys.exit(1)
+
+ all_remarks, file_remarks, _ = optrecord.gather_results(
+ files, args.jobs, print_progress)
+ if print_progress:
+ print('\n')
+
+ bypass = defaultdict(int)
+ byname = defaultdict(int)
+ for r in optrecord.itervalues(all_remarks):
+ bypass[r.Pass] += 1
+ byname[r.Pass + "/" + r.Name] += 1
+
+ total = len(all_remarks)
+ print("{:24s} {:10d}".format("Total number of remarks", total))
+ if hp:
+ h = hp.heap()
+ print("{:24s} {:10d}".format("Memory per remark",
+ h.size / len(all_remarks)))
+ print('\n')
+
+ print("Top 10 remarks by pass:")
+ for (passname, count) in sorted(bypass.items(), key=operator.itemgetter(1),
+ reverse=True)[:10]:
+ print(" {:30s} {:2.0f}%". format(passname, count * 100. / total))
+
+ print("\nTop 10 remarks:")
+ for (name, count) in sorted(byname.items(), key=operator.itemgetter(1),
+ reverse=True)[:10]:
+ print(" {:30s} {:2.0f}%". format(name, count * 100. / total))