Files
diffusers/benchmarks/run_all.py
Sayak Paul e6639fef70 [benchmarks] overhaul benchmarks (#11565)
* start overhauling the benchmarking suite.

* fixes

* fixes

* checking.

* checking

* fixes.

* error handling and logging.

* add flops and params.

* add more models.

* utility to fire execution of all benchmarking scripts.

* utility to push to the hub.

* push utility improvement

* seems to be working.

* okay

* add torchprofile dep.

* remove total gpu memory

* fixes

* fix

* need a big gpu

* better

* what's happening.

* okay

* separate requirements and make it nightly.

* add db population script.

* update secret name

* update secret.

* population db update

* disable db population for now.

* change to every monday

* Update .github/workflows/benchmark.yml

Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>

* quality improvements.

* reparate hub upload step.

* repository

* remove csv

* check

* update

* update

* threading.

* update

* update

* updaye

* update

* update

* update

* remove peft dep

* upgrade runner.

* fix

* fixes

* fix merging csvs.

* push dataset to the Space repo for analysis.

* warm up.

* add a readme

* Apply suggestions from code review

Co-authored-by: Luc Georges <McPatate@users.noreply.github.com>

* address feedback

* Apply suggestions from code review

* disable db workflow.

* update to bi weekly.

* enable population

* enable

* updaye

* update

* metadata

* fix

---------

Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>
Co-authored-by: Luc Georges <McPatate@users.noreply.github.com>
2025-07-04 11:04:17 +05:30

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import glob
import logging
import os
import subprocess
import pandas as pd
logging.basicConfig(level=logging.INFO, format="%(asctime)s %(levelname)s %(name)s: %(message)s")
logger = logging.getLogger(__name__)
PATTERN = "benchmarking_*.py"
FINAL_CSV_FILENAME = "collated_results.csv"
GITHUB_SHA = os.getenv("GITHUB_SHA", None)
class SubprocessCallException(Exception):
pass
def run_command(command: list[str], return_stdout=False):
try:
output = subprocess.check_output(command, stderr=subprocess.STDOUT)
if return_stdout and hasattr(output, "decode"):
return output.decode("utf-8")
except subprocess.CalledProcessError as e:
raise SubprocessCallException(f"Command `{' '.join(command)}` failed with:\n{e.output.decode()}") from e
def merge_csvs(final_csv: str = "collated_results.csv"):
all_csvs = glob.glob("*.csv")
all_csvs = [f for f in all_csvs if f != final_csv]
if not all_csvs:
logger.info("No result CSVs found to merge.")
return
df_list = []
for f in all_csvs:
try:
d = pd.read_csv(f)
except pd.errors.EmptyDataError:
# If a file existed but was zerobytes or corrupted, skip it
continue
df_list.append(d)
if not df_list:
logger.info("All result CSVs were empty or invalid; nothing to merge.")
return
final_df = pd.concat(df_list, ignore_index=True)
if GITHUB_SHA is not None:
final_df["github_sha"] = GITHUB_SHA
final_df.to_csv(final_csv, index=False)
logger.info(f"Merged {len(all_csvs)} partial CSVs → {final_csv}.")
def run_scripts():
python_files = sorted(glob.glob(PATTERN))
python_files = [f for f in python_files if f != "benchmarking_utils.py"]
for file in python_files:
script_name = file.split(".py")[0].split("_")[-1] # example: benchmarking_foo.py -> foo
logger.info(f"\n****** Running file: {file} ******")
partial_csv = f"{script_name}.csv"
if os.path.exists(partial_csv):
logger.info(f"Found {partial_csv}. Removing for safer numbers and duplication.")
os.remove(partial_csv)
command = ["python", file]
try:
run_command(command)
logger.info(f"{file} finished normally.")
except SubprocessCallException as e:
logger.info(f"Error running {file}:\n{e}")
finally:
logger.info(f"→ Merging partial CSVs after {file}")
merge_csvs(final_csv=FINAL_CSV_FILENAME)
logger.info(f"\nAll scripts attempted. Final collated CSV: {FINAL_CSV_FILENAME}")
if __name__ == "__main__":
run_scripts()