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Black preview (#17217)

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* Black preview

* Fixup too!

* Fix check copies

* Use the same version as the CI

* Bump black
This commit is contained in:
Sylvain Gugger
2022-05-12 16:25:55 -04:00
committed by GitHub
parent 9bd67ac7bb
commit afe5d42d8d
578 changed files with 8274 additions and 3296 deletions
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19
examples/research_projects/pplm/run_pplm_discrim_train.py
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@@ -175,8 +175,7 @@ def evaluate_performance(data_loader, discriminator, device="cpu"):
test_loss /= len(data_loader.dataset)
print(
"Performance on test set: "
"Average loss: {:.4f}, Accuracy: {}/{} ({:.0f}%)".format(
"Performance on test set: Average loss: {:.4f}, Accuracy: {}/{} ({:.0f}%)".format(
test_loss, correct, len(data_loader.dataset), 100.0 * correct / len(data_loader.dataset)
)
)
@@ -309,7 +308,7 @@ def train_discriminator(
x.append(seq)
y.append(d["label"])
except Exception:
print("Error evaluating / tokenizing" " line {}, skipping it".format(i))
print("Error evaluating / tokenizing line {}, skipping it".format(i))
pass
full_dataset = Dataset(x, y)
@@ -349,7 +348,7 @@ def train_discriminator(
x.append(seq)
y.append(int(np.sum(d["label"]) > 0))
except Exception:
print("Error evaluating / tokenizing" " line {}, skipping it".format(i))
print("Error evaluating / tokenizing line {}, skipping it".format(i))
pass
full_dataset = Dataset(x, y)
@@ -370,7 +369,7 @@ def train_discriminator(
# class \t text
if dataset_fp is None:
raise ValueError("When generic dataset is selected, " "dataset_fp needs to be specified aswell.")
raise ValueError("When generic dataset is selected, dataset_fp needs to be specified aswell.")
classes = set()
with open(dataset_fp) as f:
@@ -490,15 +489,17 @@ if __name__ == "__main__":
type=str,
default="SST",
choices=("SST", "clickbait", "toxic", "generic"),
help="dataset to train the discriminator on."
"In case of generic, the dataset is expected"
"to be a TSBV file with structure: class \\t text",
help=(
"dataset to train the discriminator on."
"In case of generic, the dataset is expected"
"to be a TSBV file with structure: class \\t text"
),
)
parser.add_argument(
"--dataset_fp",
type=str,
default="",
help="File path of the dataset to use. " "Needed only in case of generic datadset",
help="File path of the dataset to use. Needed only in case of generic datadset",
)
parser.add_argument(
"--pretrained_model", type=str, default="gpt2-medium", help="Pretrained model to use as encoder"