Files
nvbench/scripts/nvbench_compare.py
Vyas Ramasubramani 38ec66dc0f Add small comment.
2021-06-22 12:30:05 -04:00

81 lines
2.8 KiB
Python

#!/usr/bin/env python
import json
import keyword
import sys
import tabulate
if len(sys.argv) != 3:
print("Usage: %s reference.json compare.json\n" % sys.argv[0])
sys.exit(1)
with open(sys.argv[1], "r") as ref_file:
ref_root = json.load(ref_file)
with open(sys.argv[2], "r") as cmp_file:
cmp_root = json.load(cmp_file)
# This is blunt but works for now:
if ref_root["devices"] != cmp_root["devices"]:
print("Device sections do not match.")
sys.exit(1)
ref_benches = ref_root["benchmarks"]
cmp_benches = cmp_root["benchmarks"]
def find_matching_bench(needle, haystack):
for hay in haystack:
if hay["name"] == needle["name"] and hay["axes"] == needle["axes"]:
return hay
return None
def get_row(cmp_benches, ref_benches):
for cmp_bench in cmp_benches:
ref_bench = find_matching_bench(cmp_bench, ref_benches)
if not ref_bench:
continue
for cmp_state_description, cmp_state in cmp_bench["states"].items():
ref_state = ref_bench["states"].get(cmp_state_description)
if not ref_state:
continue
cmp_summaries = cmp_state["summaries"]
ref_summaries = ref_state["summaries"]
if not ref_summaries or not cmp_summaries:
continue
cmp_time_summary = cmp_summaries.get("Average GPU Time (Cold)")
ref_time_summary = ref_summaries.get("Average GPU Time (Cold)")
cmp_noise_summary = cmp_summaries.get("GPU Relative Standard Deviation (Cold)")
ref_noise_summary = ref_summaries.get("GPU Relative Standard Deviation (Cold)")
# TODO: Determine whether empty outputs could be present based on
# user requests not to perform certain timings.
if cmp_time_summary is None or ref_time_summary is None or \
cmp_noise_summary is None or ref_noise_summary is None:
continue
# TODO Ugly. The JSON needs to be changed to let us look up names directly.
# Change arrays to maps.
cmp_time = cmp_time_summary["value"]["value"]
ref_time = ref_time_summary["value"]["value"]
cmp_noise = cmp_noise_summary["value"]["value"]
ref_noise = ref_noise_summary["value"]["value"]
# Relative time comparison
yield [cmp_bench['name'], cmp_state_description] + f"{cmp_time - ref_time} {cmp_time} {ref_time} {cmp_noise:0.6f}% {ref_noise:0.6f}%\n".split()
print(tabulate.tabulate((row for row in get_row(cmp_benches, ref_benches)),
# TODO: Reduce precision once we have really different
# numbers for comparison.
floatfmt="0.12f",
headers=("Name", "Parameters", "Old - New", "New Time", "Old Time", "New Std", "Old Std"),
))