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[hexagon][testing] refactor benchmark-table code (#11400)
Generalize the benchmark-table code to support arbitrary independent values. This supports future changes to the benchmark code.
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Christian Convey
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May 26, 2022
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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1,141 @@ | ||
| # Licensed to the Apache Software Foundation (ASF) under one | ||
| # or more contributor license agreements. See the NOTICE file | ||
| # distributed with this work for additional information | ||
| # regarding copyright ownership. The ASF licenses this file | ||
| # to you 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. | ||
|
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| import csv | ||
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| class BenchmarksTable: | ||
| """ | ||
| Stores/reports the result of benchmark runs. | ||
| Each line item has a status: success, fail, or skip. | ||
| Each 'success' line item must include benchmark data, | ||
| in the form provided by TVM's `time_evaluator` mechanism. | ||
| Each line item may also specify values for any subset of | ||
| the columns provided to the table's construstor. | ||
| """ | ||
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| BUILTIN_COLUMN_NAMES = set( | ||
| [ | ||
| "row_status", | ||
| "timings_min_usecs", | ||
| "timings_max_usecs", | ||
| "timings_median_usecs", | ||
| "timings_mean_usecs", | ||
| "timings_stddev_usecs", | ||
| ] | ||
| ) | ||
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| def __init__(self): | ||
| self._line_items = [] | ||
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| def validate_user_supplied_kwargs(self, kwarg_dict): | ||
| name_conflicts = set(kwarg_dict).intersection(self.BUILTIN_COLUMN_NAMES) | ||
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| if name_conflicts: | ||
| name_list = ", ".join(name_conflicts) | ||
| raise Exception(f"Attempting to supply values for built-in column names: {name_list}") | ||
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| def record_success(self, timings, **kwargs): | ||
| """ | ||
| `timings` : Assumed to have the structure and meaning of | ||
| the timing results provided by TVM's `time_evaluator` | ||
| mechanism. | ||
| `kwargs` : Optional values for any of the other columns | ||
| defined for this benchmark table. | ||
| """ | ||
| self.validate_user_supplied_kwargs(kwargs) | ||
| line_item = kwargs | ||
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| line_item["row_status"] = "SUCCESS" | ||
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| line_item["timings_min_usecs"] = timings.min * 1000000 | ||
| line_item["timings_max_usecs"] = timings.max * 1000000 | ||
| line_item["timings_median_usecs"] = timings.median * 1000000 | ||
| line_item["timings_stddev_usecs"] = timings.std * 1000000 | ||
| line_item["timings_mean_usecs"] = timings.mean * 1000000 | ||
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| self._line_items.append(line_item) | ||
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| def record_skip(self, **kwargs): | ||
| self.validate_user_supplied_kwargs(kwargs) | ||
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| line_item = dict(kwargs) | ||
| line_item["row_status"] = "SKIP" | ||
| self._line_items.append(line_item) | ||
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| def record_fail(self, **kwargs): | ||
| self.validate_user_supplied_kwargs(kwargs) | ||
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| line_item = dict(kwargs) | ||
| line_item["row_status"] = "FAIL" | ||
| self._line_items.append(line_item) | ||
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| def has_fail(self): | ||
| """ | ||
| Returns True if the table contains at least one 'fail' line item, | ||
| otherwise returns False. | ||
| """ | ||
| return any(item["row_status"] == "FAIL" for item in self._line_items) | ||
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| def print_csv(self, f, column_name_order, timing_decimal_places=3): | ||
| """ | ||
| Print the benchmark results as a csv. | ||
| `f` : The output stream. | ||
| `column_name_order`: an iterable sequence of column names, indicating the | ||
| left-to-right ordering of columns in the CSV output. | ||
| The CSV output will contain only those columns that are mentioned in | ||
| this list. | ||
| `timing_decimal_places`: for the numeric timing values, this is the | ||
| number of decimal places to provide in the printed output. | ||
| For example, a value of 3 is equivalent to the Python formatting string | ||
| `'{:.3f}'` | ||
| """ | ||
| writer = csv.DictWriter( | ||
| f, column_name_order, dialect="excel-tab", restval="", extrasaction="ignore" | ||
| ) | ||
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| writer.writeheader() | ||
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| for line_item_dict in self._line_items: | ||
| # Use a copy of the line-item dictionary, because we might do some modifications | ||
| # for the sake of rendering... | ||
| csv_line_dict = dict(line_item_dict) | ||
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| for col_name in [ | ||
| "timings_min_usecs", | ||
| "timings_max_usecs", | ||
| "timings_median_usecs", | ||
| "timings_stddev_usecs", | ||
| "timings_mean_usecs", | ||
| ]: | ||
| if col_name in csv_line_dict: | ||
| old_value = csv_line_dict[col_name] | ||
| assert isinstance( | ||
| old_value, float | ||
| ), f"Formatting code assumes that column {col_name} is some col_nameind of float, but its actual type is {type(old_value)}" | ||
| str_value = f"{old_value:>0.{timing_decimal_places}f}" | ||
| csv_line_dict[col_name] = str_value | ||
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| writer.writerow(csv_line_dict) |