peacock-data-public-datasets-idc-14.backup.output
/
lm-evaluation-harness
/scripts
/make_table_tasks.py
""" | |
Usage: | |
python make_table_tasks.py --output <markdown_filename> | |
""" | |
import argparse | |
import logging | |
from pytablewriter import MarkdownTableWriter | |
from lm_eval import tasks | |
logging.basicConfig(level=logging.INFO) | |
logger = logging.getLogger(__name__) | |
def check(tf): | |
if tf: | |
return "✓" | |
else: | |
return " " | |
if __name__ == "__main__": | |
parser = argparse.ArgumentParser() | |
parser.add_argument("--output", type=str, default="task_table.md") | |
args = parser.parse_args() | |
writer = MarkdownTableWriter() | |
writer.headers = ["Task Name", "Train", "Val", "Test", "Val/Test Docs", "Metrics"] | |
values = [] | |
tasks = tasks.TASK_REGISTRY.items() | |
tasks = sorted(tasks, key=lambda x: x[0]) | |
for tname, Task in tasks: | |
task = Task() | |
v = [ | |
tname, | |
check(task.has_training_docs()), | |
check(task.has_validation_docs()), | |
check(task.has_test_docs()), | |
len( | |
list( | |
task.test_docs() if task.has_test_docs() else task.validation_docs() | |
) | |
), | |
", ".join(task.aggregation().keys()), | |
] | |
logger.info(v) | |
values.append(v) | |
writer.value_matrix = values | |
table = writer.dumps() | |
with open(args.output, "w", encoding="utf-8") as f: | |
f.write(table) | |