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140647ea6f
The compare_strings.py option unconditionally generates a graph PNG image of the input data, which can be unnecessary and slow. Put this behind an optional flag -g. * benchtests/scripts/compare_strings.py: New option -g. (draw_graph): Print a message that a graph is being generated. (process_results): Generate graph only if -g is passed. (main): Process option -g.
158 lines
4.8 KiB
Python
Executable File
158 lines
4.8 KiB
Python
Executable File
#!/usr/bin/python
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# Copyright (C) 2017 Free Software Foundation, Inc.
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# This file is part of the GNU C Library.
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#
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# The GNU C Library is free software; you can redistribute it and/or
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# modify it under the terms of the GNU Lesser General Public
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# License as published by the Free Software Foundation; either
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# version 2.1 of the License, or (at your option) any later version.
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#
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# The GNU C Library is distributed in the hope that it will be useful,
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# but WITHOUT ANY WARRANTY; without even the implied warranty of
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# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
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# Lesser General Public License for more details.
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#
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# You should have received a copy of the GNU Lesser General Public
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# License along with the GNU C Library; if not, see
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# <http://www.gnu.org/licenses/>.
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"""Compare results of string functions
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Given a string benchmark result file, print a table with comparisons with a
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baseline. The baseline is the first function, which typically is the builtin
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function.
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"""
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import matplotlib as mpl
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mpl.use('Agg')
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import sys
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import os
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import json
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import pylab
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import argparse
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try:
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import jsonschema as validator
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except ImportError:
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print('Could not find jsonschema module.')
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raise
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def parse_file(filename, schema_filename):
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with open(schema_filename, 'r') as schemafile:
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schema = json.load(schemafile)
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with open(filename, 'r') as benchfile:
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bench = json.load(benchfile)
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validator.validate(bench, schema)
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return bench
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def draw_graph(f, v, ifuncs, results):
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"""Plot graphs for functions
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Plot line graphs for each of the ifuncs
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Args:
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f: Function name
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v: Benchmark variant for the function.
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ifuncs: List of ifunc names
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results: Dictionary of results for each test criterion
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"""
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print('Generating graph for %s, variant \'%s\'' % (f, v))
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xkeys = results.keys()
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pylab.clf()
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fig = pylab.figure(frameon=False)
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fig.set_size_inches(32, 18)
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pylab.ylabel('Performance improvement from base')
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X = range(len(xkeys))
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pylab.xticks(X, xkeys)
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i = 0
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while i < len(ifuncs):
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Y = [results[k][i] for k in xkeys]
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lines = pylab.plot(X, Y, label=':'+ifuncs[i])
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i = i + 1
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pylab.legend()
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pylab.grid()
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pylab.savefig('%s-%s.png' % (f, v), bbox_inches='tight')
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def process_results(results, attrs, base_func, graph):
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""" Process results and print them
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Args:
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results: JSON dictionary of results
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attrs: Attributes that form the test criteria
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"""
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for f in results['functions'].keys():
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print('Function: %s' % f)
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v = results['functions'][f]['bench-variant']
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print('Variant: %s' % v)
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base_index = 0
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if base_func:
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base_index = results['functions'][f]['ifuncs'].index(base_func)
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print("%36s%s" % (' ', '\t'.join(results['functions'][f]['ifuncs'])))
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print("=" * 120)
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graph_res = {}
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for res in results['functions'][f]['results']:
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attr_list = ['%s=%s' % (a, res[a]) for a in attrs]
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i = 0
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key = ', '.join(attr_list)
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sys.stdout.write('%36s: ' % key)
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graph_res[key] = res['timings']
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for t in res['timings']:
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sys.stdout.write ('%12.2f' % t)
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if i != base_index:
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base = res['timings'][base_index]
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diff = (base - t) * 100 / base
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sys.stdout.write (' (%6.2f%%)' % diff)
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sys.stdout.write('\t')
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i = i + 1
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print('')
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if graph:
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draw_graph(f, v, results['functions'][f]['ifuncs'], graph_res)
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def main(args):
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"""Program Entry Point
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Take a string benchmark output file and compare timings.
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"""
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base_func = None
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filename = args.input
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schema_filename = args.schema
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base_func = args.base
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attrs = args.attributes.split(',')
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results = parse_file(args.input, args.schema)
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process_results(results, attrs, base_func, args.graph)
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if __name__ == '__main__':
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parser = argparse.ArgumentParser()
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# The required arguments.
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req = parser.add_argument_group(title='required arguments')
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req.add_argument('-a', '--attributes', required=True,
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help='Comma separated list of benchmark attributes.')
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req.add_argument('-i', '--input', required=True,
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help='Input JSON benchmark result file.')
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req.add_argument('-s', '--schema', required=True,
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help='Schema file to validate the result file.')
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# Optional arguments.
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parser.add_argument('-b', '--base',
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help='IFUNC variant to set as baseline.')
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parser.add_argument('-g', '--graph', action='store_true',
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help='Generate a graph from results.')
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args = parser.parse_args()
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main(args)
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