| #!/usr/bin/env python3 |
| # Copyright 2016 Google Inc. All Rights Reserved. |
| # |
| # Licensed under the Apache License, Version 2.0 (the "License"); |
| # you may not use this file except in compliance with the License. |
| # You may obtain a copy of the License at |
| # |
| # http://www.apache.org/licenses/LICENSE-2.0 |
| # |
| # Unless required by applicable law or agreed to in writing, software |
| # distributed under the License is distributed on an "AS-IS" BASIS, |
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
| # See the License for the specific language governing permissions and |
| # limitations under the License. |
| |
| import argparse |
| import json |
| import yaml |
| from collections import defaultdict |
| |
| def extract_results(bench_results, fixed_benchmark_params, column_dimension, row_dimension, result_dimension): |
| table_data = defaultdict(lambda: dict()) |
| remaining_dimensions_by_row_column = dict() |
| for bench_result in bench_results: |
| try: |
| params = {dimension_name: make_immutable(dimension_value) |
| for dimension_name, dimension_value in bench_result['benchmark'].items()} |
| results = bench_result['results'] |
| for param_name, param_value in fixed_benchmark_params.items(): |
| if params.get(param_name) != param_value: |
| # fixed_benchmark_params not satisfied by this result, skip |
| break |
| if result_dimension not in results: |
| # result_dimension not found in this result, skip |
| break |
| params.pop(param_name) |
| else: |
| # fixed_benchmark_params were satisfied by these params (and were removed) |
| assert row_dimension in params.keys(), '%s not in %s' % (row_dimension, params.keys()) |
| assert column_dimension in params.keys(), '%s not in %s' % (column_dimension, params.keys()) |
| assert result_dimension in results, '%s not in %s' % (result_dimension, results) |
| row_value = params[row_dimension] |
| column_value = params[column_dimension] |
| remaining_dimensions = params.copy() |
| remaining_dimensions.pop(row_dimension) |
| remaining_dimensions.pop(column_dimension) |
| if column_value in table_data[row_value]: |
| previous_remaining_dimensions = remaining_dimensions_by_row_column[(row_value, column_value)] |
| raise Exception( |
| 'Found multiple benchmark results with the same fixed benchmark params, benchmark param for row and benchmark param for column, so a result can\'t be uniquely determined. ' |
| + 'Consider adding additional values in fixed_benchmark_params. Remaining dimensions: %s vs %s' % ( |
| remaining_dimensions, previous_remaining_dimensions)) |
| table_data[row_value][column_value] = results[result_dimension] |
| remaining_dimensions_by_row_column[(row_value, column_value)] = remaining_dimensions |
| except Exception as e: |
| raise Exception('While processing %s' % bench_result) from e |
| return table_data |
| |
| |
| def identity(x): |
| return x |
| |
| |
| # Takes a 2-dimensional array (list of lists) and prints a markdown table with that content. |
| def print_markdown_table(table_data): |
| max_content_length_by_column = [max([len(str(row[column_index])) for row in table_data]) |
| for column_index in range(len(table_data[0]))] |
| for row_index in range(len(table_data)): |
| row = table_data[row_index] |
| cell_strings = [] |
| for column_index in range(len(row)): |
| value = str(row[column_index]) |
| # E.g. if max_content_length_by_column=20, table_cell_format='%20s' |
| table_cell_format = '%%%ss' % max_content_length_by_column[column_index] |
| cell_strings += [table_cell_format % value] |
| print('| ' + ' | '.join(cell_strings) + ' |') |
| if row_index == 0: |
| # Print the separator line, e.g. |---|-----|---| |
| print('|-' |
| + '-|-'.join(['-' * max_content_length_by_column[column_index] |
| for column_index in range(len(row))]) |
| + '-|') |
| |
| def compute_min_max(table_data, row_headers, column_headers): |
| values_by_row = {row_header: [table_data[row_header][column_header] |
| for column_header in column_headers |
| if column_header in table_data[row_header]] |
| for row_header in row_headers} |
| # We compute min and max and pass it to the value pretty-printer, so that it can determine a unit that works well for all values in the table. |
| min_in_table = min([min([min(interval[0][0], interval[1][0]) for interval in values_by_row[row_header]]) |
| for row_header in row_headers]) |
| max_in_table = max([max([max(interval[0][1], interval[1][1]) for interval in values_by_row[row_header]]) |
| for row_header in row_headers]) |
| return (min_in_table, max_in_table) |
| |
| |
| def pretty_print_percentage_difference(baseline_value, current_value): |
| baseline_min = baseline_value[0] |
| baseline_max = baseline_value[1] |
| current_min = current_value[0] |
| current_max = current_value[1] |
| percentage_min = (current_min / baseline_max - 1) * 100 |
| percentage_max = (current_max / baseline_min - 1) * 100 |
| percentage_min_s = "%+.1f%%" % percentage_min |
| percentage_max_s = "%+.1f%%" % percentage_max |
| if percentage_min_s == percentage_max_s: |
| return percentage_min_s |
| else: |
| return "%s - %s" % (percentage_min_s, percentage_max_s) |
| |
| |
| # Takes a table as a dict of dicts (where each table_data[row_key][column_key] is a confidence interval) and prints it as a markdown table using |
| # the specified pretty print functions for column keys, row keys and values respectively. |
| # column_header_pretty_printer and row_header_pretty_printer must be functions taking a single value and returning the pretty-printed version. |
| # value_pretty_printer must be a function taking (value_confidence_interval, min_in_table, max_in_table). |
| # baseline_table_data is an optional table (similar to table_data) that contains the "before" state. If present, the values in two tables will be compared. |
| def print_confidence_intervals_table(table_name, |
| table_data, |
| baseline_table_data, |
| column_header_pretty_printer=identity, |
| row_header_pretty_printer=identity, |
| value_pretty_printer=identity): |
| if table_data == {}: |
| print('%s: (no data)' % table_name) |
| return |
| |
| row_headers = sorted(list(table_data.keys())) |
| # We need to compute the union of the headers of all rows; some rows might be missing values for certain columns. |
| column_headers = sorted(set().union(*[list(row_values.keys()) for row_values in table_data.values()])) |
| if baseline_table_data: |
| baseline_row_headers = sorted(list(baseline_table_data.keys())) |
| baseline_column_headers = sorted(set().union(*[list(row_values.keys()) for row_values in baseline_table_data.values()])) |
| unmached_baseline_column_headers = set(baseline_row_headers) - set(row_headers) |
| if unmached_baseline_column_headers: |
| print('Found baseline column headers with no match in new results (they will be ignored): ', unmached_baseline_column_headers) |
| unmached_baseline_row_headers = set(baseline_row_headers) - set(row_headers) |
| if unmached_baseline_row_headers: |
| print('Found baseline row headers with no match in new results (they will be ignored): ', unmached_baseline_row_headers) |
| |
| min_in_table, max_in_table = compute_min_max(table_data, row_headers, column_headers) |
| if baseline_table_data: |
| min_in_baseline_table, max_in_baseline_table = compute_min_max(table_data, row_headers, column_headers) |
| min_in_table = min(min_in_table, min_in_baseline_table) |
| max_in_table = max(max_in_table, max_in_baseline_table) |
| |
| table_content = [] |
| table_content.append([table_name] + [column_header_pretty_printer(column_header) for column_header in column_headers]) |
| for row_header in row_headers: |
| row_content = [row_header_pretty_printer(row_header)] |
| for column_header in column_headers: |
| if column_header in table_data[row_header]: |
| value = table_data[row_header][column_header] |
| raw_confidence_interval, rounded_confidence_interval = value |
| pretty_printed_value = value_pretty_printer(rounded_confidence_interval, min_in_table, max_in_table) |
| if baseline_table_data and row_header in baseline_table_data and column_header in baseline_table_data[row_header]: |
| baseline_value = baseline_table_data[row_header][column_header] |
| raw_baseline_confidence_interval, rounded_baseline_confidence_interval = baseline_value |
| pretty_printed_baseline_value = value_pretty_printer(rounded_baseline_confidence_interval, min_in_table, max_in_table) |
| pretty_printed_percentage_difference = pretty_print_percentage_difference(raw_baseline_confidence_interval, raw_confidence_interval) |
| row_content.append("%s -> %s (%s)" % (pretty_printed_baseline_value, pretty_printed_value, pretty_printed_percentage_difference)) |
| else: |
| row_content.append(pretty_printed_value) |
| else: |
| row_content.append("N/A") |
| table_content.append(row_content) |
| print_markdown_table(table_content) |
| |
| |
| def format_string_pretty_printer(format_string): |
| def pretty_print(s): |
| return format_string % s |
| |
| return pretty_print |
| |
| |
| def interval_pretty_printer(interval, unit, multiplier): |
| interval = interval.copy() |
| interval[0] *= multiplier |
| interval[1] *= multiplier |
| |
| # This prevents the format strings below from printing '.0' for numbers that already have 2 digits: |
| # 23.0 -> 23 |
| # 2.0 -> 2.0 (here we don't remove the '.0' because printing just '2' might suggest a lower precision) |
| if int(interval[0]) == interval[0] and interval[0] >= 10: |
| interval[0] = int(interval[0]) |
| else: |
| interval[0] = '%.3g' % interval[0] |
| if int(interval[1]) == interval[1] and interval[1] >= 10: |
| interval[1] = int(interval[1]) |
| else: |
| interval[1] = '%.3g' % interval[1] |
| |
| if interval[0] == interval[1]: |
| return '%s %s' % (interval[0], unit) |
| else: |
| return '%s-%s %s' % (interval[0], interval[1], unit) |
| |
| |
| # Finds the best unit to represent values in the range [min_value, max_value]. |
| # The units must be specified as an ordered list [multiplier1, ..., multiplierN] |
| def find_best_unit(units, min_value, max_value): |
| assert min_value <= max_value |
| if max_value <= units[0]: |
| return units[0] |
| for i in range(len(units) - 1): |
| if min_value > units[i] and max_value < units[i + 1]: |
| return units[i] |
| if min_value > units[-1]: |
| return units[-1] |
| # There is no unit that works very well for all values, first let's try relaxing the min constraint |
| for i in range(len(units) - 1): |
| if min_value > units[i] * 0.2 and max_value < units[i + 1]: |
| return units[i] |
| if min_value > units[-1] * 0.2: |
| return units[-1] |
| # That didn't work either, just use a unit that works well for the min values then |
| for i in reversed(range(len(units))): |
| if min_value > units[i]: |
| return units[i] |
| assert min_value <= min(units) |
| # Pick the smallest unit |
| return units[0] |
| |
| |
| def time_interval_pretty_printer(time_interval, min_in_table, max_in_table): |
| sec = 1 |
| milli = 0.001 |
| micro = milli * milli |
| units = [micro, milli, sec] |
| unit_name_by_unit = {micro: 'μs', milli: 'ms', sec: 's'} |
| |
| unit = find_best_unit(units, min_in_table, max_in_table) |
| unit_name = unit_name_by_unit[unit] |
| |
| return interval_pretty_printer(time_interval, unit=unit_name, multiplier=1 / unit) |
| |
| |
| def file_size_interval_pretty_printer(file_size_interval, min_in_table, max_in_table): |
| byte = 1 |
| kb = 1024 |
| mb = kb * kb |
| units = [byte, kb, mb] |
| unit_name_by_unit = {byte: 'bytes', kb: 'KB', mb: 'MB'} |
| |
| unit = find_best_unit(units, min_in_table, max_in_table) |
| unit_name = unit_name_by_unit[unit] |
| |
| return interval_pretty_printer(file_size_interval, unit=unit_name, multiplier=1 / unit) |
| |
| |
| def make_immutable(x): |
| if isinstance(x, list): |
| return tuple(make_immutable(elem) for elem in x) |
| return x |
| |
| |
| def dict_pretty_printer(dict_data): |
| if isinstance(dict_data, list): |
| dict_data = {make_immutable(mapping['from']): mapping['to'] for mapping in dict_data} |
| |
| def pretty_print(s): |
| if s in dict_data: |
| return dict_data[s] |
| else: |
| raise Exception('dict_pretty_printer(%s) can\'t handle the value %s' % (dict_data, s)) |
| |
| return pretty_print |
| |
| |
| def determine_column_pretty_printer(pretty_printer_definition): |
| if 'format_string' in pretty_printer_definition: |
| return format_string_pretty_printer(pretty_printer_definition['format_string']) |
| |
| if 'fixed_map' in pretty_printer_definition: |
| return dict_pretty_printer(pretty_printer_definition['fixed_map']) |
| |
| raise Exception("Unrecognized pretty printer description: %s" % pretty_printer_definition) |
| |
| |
| def determine_row_pretty_printer(pretty_printer_definition): |
| return determine_column_pretty_printer(pretty_printer_definition) |
| |
| |
| def determine_value_pretty_printer(unit): |
| if unit == "seconds": |
| return time_interval_pretty_printer |
| if unit == "bytes": |
| return file_size_interval_pretty_printer |
| raise Exception("Unrecognized unit: %s" % unit) |
| |
| |
| def main(): |
| parser = argparse.ArgumentParser(description='Runs all the benchmarks whose results are on the Fruit website.') |
| parser.add_argument('--benchmark-results', |
| help='The input file where benchmark results will be read from (1 per line, with each line in JSON format). You can use the run_benchmarks.py to run a benchmark and generate results in this format.') |
| parser.add_argument('--baseline-benchmark-results', |
| help='Optional. If specified, compares this file (considered the "before" state) with the one specified in --benchmark-results.') |
| parser.add_argument('--benchmark-tables-definition', help='The YAML file that defines the benchmark tables (e.g. fruit_wiki_bench_tables.yaml).') |
| args = parser.parse_args() |
| |
| if args.benchmark_results is None: |
| raise Exception("You must specify a benchmark results file using --benchmark-results.") |
| |
| if args.benchmark_tables_definition is None: |
| raise Exception("You must specify a benchmark tables definition file using --benchmark-tables-definition.") |
| |
| with open(args.benchmark_results, 'r') as f: |
| bench_results = [json.loads(line) for line in f.readlines()] |
| |
| if args.baseline_benchmark_results: |
| with open(args.baseline_benchmark_results, 'r') as f: |
| baseline_bench_results = [json.loads(line) for line in f.readlines()] |
| else: |
| baseline_bench_results = None |
| |
| with open(args.benchmark_tables_definition, 'r') as f: |
| for table_definition in yaml.load(f)["tables"]: |
| try: |
| fixed_benchmark_params = {dimension_name: make_immutable(dimension_value) for dimension_name, dimension_value in table_definition['benchmark_filter'].items()} |
| table_data = extract_results( |
| bench_results, |
| fixed_benchmark_params=fixed_benchmark_params, |
| column_dimension=table_definition['columns']['dimension'], |
| row_dimension=table_definition['rows']['dimension'], |
| result_dimension=table_definition['results']['dimension']) |
| if baseline_bench_results: |
| baseline_table_data = extract_results( |
| baseline_bench_results, |
| fixed_benchmark_params=fixed_benchmark_params, |
| column_dimension=table_definition['columns']['dimension'], |
| row_dimension=table_definition['rows']['dimension'], |
| result_dimension=table_definition['results']['dimension']) |
| else: |
| baseline_table_data = None |
| rows_pretty_printer_definition = table_definition['rows']['pretty_printer'] |
| columns_pretty_printer_definition = table_definition['columns']['pretty_printer'] |
| results_unit = table_definition['results']['unit'] |
| print_confidence_intervals_table(table_definition['name'], |
| table_data, |
| baseline_table_data, |
| column_header_pretty_printer=determine_column_pretty_printer(columns_pretty_printer_definition), |
| row_header_pretty_printer=determine_row_pretty_printer(rows_pretty_printer_definition), |
| value_pretty_printer=determine_value_pretty_printer(results_unit)) |
| print() |
| print() |
| except Exception as e: |
| print('While processing table:\n' + table_definition) |
| print() |
| raise e |
| |
| |
| if __name__ == "__main__": |
| main() |
