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import glob

import sys

import pandas as pd

from huggingface_hub import hf_hub_download, upload_file

from huggingface_hub.utils._errors import EntryNotFoundError

sys.path.append(".")

from utils import BASE_PATH, FINAL_CSV_FILE, GITHUB_SHA, REPO_ID, collate_csv # noqa: E402

def has_previous_benchmark() -> str:

csv_path = None

try:

csv_path = hf_hub_download(repo_id=REPO_ID, repo_type="dataset", filename=FINAL_CSV_FILE)

except EntryNotFoundError:

csv_path = None

return csv_path

def filter_float(value):

if isinstance(value, str):

return float(value.split()[0])

return value

def push_to_hf_dataset():

all_csvs = sorted(glob.glob(f"{BASE_PATH}/*.csv"))

collate_csv(all_csvs, FINAL_CSV_FILE)

# If there's an existing benchmark file, we should report the changes.

csv_path = has_previous_benchmark()

if csv_path is not None:

current_results = pd.read_csv(FINAL_CSV_FILE)

previous_results = pd.read_csv(csv_path)

numeric_columns = current_results.select_dtypes(include=["float64", "int64"]).columns

numeric_columns = [

c for c in numeric_columns if c not in ["batch_size", "num_inference_steps", "actual_gpu_memory (gbs)"]

]

for column in numeric_columns:

previous_results[column] = previous_results[column].map(lambda x: filter_float(x))

# Calculate the percentage change

current_results[column] = current_results[column].astype(float)

previous_results[column] = previous_results[column].astype(float)

percent_change = ((current_results[column] - previous_results[column]) / previous_results[column]) * 100

# Format the values with '+' or '-' sign and append to original values

current_results[column] = current_results[column].map(str) + percent_change.map(

lambda x: f" ({'+' if x > 0 else ''}{x:.2f}%)"

)

# There might be newly added rows. So, filter out the NaNs.

current_results[column] = current_results[column].map(lambda x: x.replace(" (nan%)", ""))

# Overwrite the current result file.

current_results.to_csv(FINAL_CSV_FILE, index=False)

commit_message = f"upload from sha: {GITHUB_SHA}" if GITHUB_SHA is not None else "upload benchmark results"

upload_file(

repo_id=REPO_ID,

path_in_repo=FINAL_CSV_FILE,

path_or_fileobj=FINAL_CSV_FILE,

repo_type="dataset",

commit_message=commit_message,

)

if __name__ == "__main__":

push_to_hf_dataset()