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#!/usr/bin/python3
#
# This is a script that will run the synfig rendering multiple times on a set of
# .sif files. Record the time it took each pass to render, and then store those
# readings into a .csv file. To properly run this:
#
# 1. This script needs to be placed in the root of the build directory, and run
# from that directory
# 2. The `synfig-tests` repo needs to be cloned (in the build directory as well.
# The repo is found here: https://gitlab.com/synfig/synfig-tests
# 3. Don't have any applications running at the same time. It can mess with the
# performance measurements.
#
# It can take an extremely long time to run (.e.g 25 mintues right now). Before
# trying to do any perf tweaking in the rendering code, make sure you generate
# a reference/baseline to go off from. This should be the latest commit on
# `master`. Don't forget to copy this CSV file to another location in case you
# accidentally purge it. Every so often (as new commits come in), you'll need
# to run the script to get a new baseline. But as the renderer gets faster,
# it shouldn't have to run as long.
#
# Be sure to see the `view_comparison_graph.py` script to see how to make use
# of the generated CSV file
import os
import time, datetime
import csv
import subprocess
from collections import OrderedDict
SIF_DIR = 'synfig-tests/export/lottie/'
SIF_EXE = 'output/bin/synfig'
NUM_PASSES = 10 # if you want to work on this script, setting this value to `3` helps
COMMIT_ID = 'perf_imps-' # TODO see list below
# TODO list:
# - get the current working branch and commit id and put it into the `COMMIT_ID` variable
# - results files should not only be a CSV. It should also contain the metadata
# about the environment & setup). So instead there should be a JSON file generated
# - Add a way of getting the current environment (e.g. Ubuntu 18.04) and put it the
# metadata
# - Add a way of polling the current CPU and put it into the metadata
# - Add a way of polling the compiler used by CMake (and build type) and put it into
# the metadata
def main():
# Get all of the .sif files
all_sif = os.listdir(SIF_DIR)
all_sif = list(filter(lambda x: x.endswith('.sif'), all_sif))
all_sif.sort()
# all_sif = all_sif[:10] # Uncomment this line when you want to do some development on the script. It's help to limit the amount of .sif files
# Result of all the renders, key=<render filename>, value=list[float]
all_renders = OrderedDict()
print('Doing (%i x %i) render tests' % (len(all_sif), NUM_PASSES))
total_render_time = 0.0
for sif in all_sif:
# Create the path to the file
sif_path = os.path.join(SIF_DIR, sif)
# Create result store
render_times = []
for i in range(0, NUM_PASSES):
# Run (and time) the render
st = time.time()
subprocess.run(
[SIF_EXE, sif_path, '-t', 'null', '--quiet'],
cwd=os.getcwd()
)
et = time.time()
# Store result
rt = et - st
render_times.append(rt)
total_render_time += rt
# Print it
print('%s [%02i] :: %.4f' % (sif, i + 1, rt))
# Store in dict
all_renders[sif] = render_times
# Write the results
time_str = datetime.datetime.now().strftime('%Y_%m_%d-%H_%M_%S')
result_filename = '%s_n%s_%s.csv' % (COMMIT_ID, NUM_PASSES, time_str)
with open(result_filename, 'w') as csv_file:
# Make the header, will be: ['.sif file', 'Pass 1', 'Pass 2', ... 'Pass 10']
fieldnames = ['.sif file'] + ['Pass %i time' % (x + 1) for x in range(0, NUM_PASSES)]
wr = csv.writer(csv_file)
wr.writerow(fieldnames)
# Write each result
for sif, render_times in all_renders.items():
wr.writerow([sif] + render_times)
print('Wrote results to %s' % result_filename)
print('Total Render Time: %.4f sec (%.2f min)' % (total_render_time, total_render_time / 60.0))
if __name__ == '__main__':
main()
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