Update quality tooling for formatting (#21480)

* Result of black 23.1

* Update target to Python 3.7

* Switch flake8 to ruff

* Configure isort

* Configure isort

* Apply isort with line limit

* Put the right black version

* adapt black in check copies

* Fix copies
This commit is contained in:
Sylvain Gugger
2023-02-06 18:10:56 -05:00
committed by GitHub
parent b7bb2b59f7
commit 6f79d26442
1211 changed files with 1532 additions and 2687 deletions

View File

@@ -34,14 +34,13 @@ from pathlib import Path
from urllib.parse import urlparse
from zipfile import ZipFile, is_zipfile
import numpy as np
from PIL import Image
from tqdm.auto import tqdm
import cv2
import numpy as np
import requests
import wget
from filelock import FileLock
from PIL import Image
from tqdm.auto import tqdm
from yaml import Loader, dump, load
@@ -181,7 +180,6 @@ class Config:
@classmethod
def get_config_dict(cls, pretrained_model_name_or_path: str, **kwargs):
cache_dir = kwargs.pop("cache_dir", None)
force_download = kwargs.pop("force_download", False)
resume_download = kwargs.pop("resume_download", False)
@@ -225,14 +223,13 @@ class Config:
# quick compare tensors
def compare(in_tensor):
out_tensor = torch.load("dump.pt", map_location=in_tensor.device)
n1 = in_tensor.numpy()
n2 = out_tensor.numpy()[0]
print(n1.shape, n1[0, 0, :5])
print(n2.shape, n2[0, 0, :5])
assert np.allclose(n1, n2, rtol=0.01, atol=0.1), (
f"{sum([1 for x in np.isclose(n1, n2, rtol=0.01, atol=0.1).flatten() if x == False])/len(n1.flatten())*100:.4f} %"
f"{sum([1 for x in np.isclose(n1, n2, rtol=0.01, atol=0.1).flatten() if x is False])/len(n1.flatten())*100:.4f} %"
" element-wise mismatch"
)
raise Exception("tensors are all good")
@@ -300,7 +297,6 @@ def get_from_cache(
user_agent=None,
local_files_only=False,
):
if cache_dir is None:
cache_dir = TRANSFORMERS_CACHE
if isinstance(cache_dir, Path):
@@ -355,7 +351,6 @@ def get_from_cache(
# Prevent parallel downloads of the same file with a lock.
lock_path = cache_path + ".lock"
with FileLock(lock_path):
# If the download just completed while the lock was activated.
if os.path.exists(cache_path) and not force_download:
# Even if returning early like here, the lock will be released.
@@ -406,7 +401,6 @@ def get_from_cache(
def url_to_filename(url, etag=None):
url_bytes = url.encode("utf-8")
url_hash = sha256(url_bytes)
filename = url_hash.hexdigest()