125 lines
4.7 KiB
Python
125 lines
4.7 KiB
Python
# SPDX-FileCopyrightText: 2021-2022 Blender Authors
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#
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# SPDX-License-Identifier: Apache-2.0
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from . import TestQueue
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import json
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import pathlib
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from typing import Dict, List
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class TestGraph:
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def __init__(self, json_filepaths: List[pathlib.Path]):
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# Initialize graph from JSON file. Note that this is implemented without
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# accessing any benchmark environment or configuration. This ways benchmarks
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# run on various machines can be aggregated and the graph generated on another
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# machine.
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# Gather entries for each device.
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devices = {}
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for json_filepath in json_filepaths:
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queue = TestQueue(json_filepath)
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for entry in queue.entries:
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if entry.status in {'done', 'outdated'}:
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device_name = entry.device_name + " (" + entry.device_type + ")"
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if device_name in devices.keys():
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devices[device_name].append(entry)
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else:
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devices[device_name] = [entry]
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data = []
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for device_name, device_entries in devices.items():
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# Gather used categories.
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categories = {}
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for entry in device_entries:
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category = entry.category
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if category in categories.keys():
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categories[category].append(entry)
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else:
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categories[category] = [entry]
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# Generate one graph for every device x category x result key combination.
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for category, category_entries in categories.items():
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entries = sorted(category_entries, key=lambda entry: (entry.date, entry.revision, entry.test))
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outputs = set()
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for entry in entries:
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for output in entry.output.keys():
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outputs.add(output)
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chart_type = 'line' if entries[0].benchmark_type == 'time_series' else 'comparison'
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for output in outputs:
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chart_name = f"{category} ({output})"
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data.append(self.chart(device_name, chart_name, entries, chart_type, output))
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self.json = json.dumps(data, indent=2)
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def chart(self, device_name: str, chart_name: str, entries: List, chart_type: str, output: str) -> Dict:
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# Gather used tests.
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tests = {}
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for entry in entries:
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test = entry.test
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if test not in tests.keys():
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tests[test] = len(tests)
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# Gather used revisions.
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revisions = {}
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revision_dates = {}
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for entry in entries:
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revision = entry.revision
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if revision not in revisions.keys():
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revisions[revision] = len(revisions)
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revision_dates[revision] = int(entry.date)
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# Google Charts JSON data layout is like a spreadsheet table, with
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# columns, rows, and cells. We create one column for revision labels,
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# and one column for each test.
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cols = []
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if chart_type == 'line':
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cols.append({'id': '', 'label': 'Date', 'type': 'date'})
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else:
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cols.append({'id': '', 'label': ' ', 'type': 'string'})
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for test, test_index in tests.items():
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cols.append({'id': '', 'label': test, 'type': 'number'})
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rows = []
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for revision, revision_index in revisions.items():
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if chart_type == 'line':
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date = revision_dates[revision]
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row = [{'f': None, 'v': 'Date({0})'.format(date * 1000)}]
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else:
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row = [{'f': None, 'v': revision}]
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row += [{}] * len(tests)
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rows.append({'c': row})
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for entry in entries:
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test_index = tests[entry.test]
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revision_index = revisions[entry.revision]
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output_value = entry.output[output] if output in entry.output else -1.0
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if output.find("memory") != -1:
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formatted_value = '%.2f MB' % (output_value / (1024 * 1024))
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else:
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formatted_value = "%.4f" % output_value
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cell = {'f': formatted_value, 'v': output_value}
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rows[revision_index]['c'][test_index + 1] = cell
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data = {'cols': cols, 'rows': rows}
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return {'device': device_name, 'name': chart_name, 'data': data, 'chart_type': chart_type}
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def write(self, filepath: pathlib.Path) -> None:
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# Write HTML page with JSON graph data embedded.
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template_dir = pathlib.Path(__file__).parent
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with open(template_dir / 'graph.template.html', 'r') as f:
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template = f.read()
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contents = template.replace('%JSON_DATA%', self.json)
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with open(filepath, "w") as f:
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f.write(contents)
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