Datasets:
Tasks:
Text Classification
Modalities:
Text
Formats:
parquet
Languages:
Portuguese
Size:
1K - 10K
License:
remove comments
Browse files- aes_enem_dataset.py +0 -3
aes_enem_dataset.py
CHANGED
@@ -257,15 +257,12 @@ class AesEnemDataset(datasets.GeneratorBasedBuilder):
|
|
257 |
len(set(val_df["id_prompt"]).intersection(set(test_df["id_prompt"]))) == 0
|
258 |
), "Overlap between val and test id_prompt"
|
259 |
dirname = os.path.dirname(filepath)
|
260 |
-
import ipdb; ipdb.set_trace()
|
261 |
train_df.to_csv(f"{dirname}/train.csv", index=False)
|
262 |
val_df.to_csv(f"{dirname}/validation.csv", index=False)
|
263 |
test_df.to_csv(f"{dirname}/test.csv", index=False)
|
264 |
|
265 |
# method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
|
266 |
def _generate_examples(self, filepath, split):
|
267 |
-
# TODO: This method handles input defined in _split_generators to yield (key, example) tuples from the dataset.
|
268 |
-
# The `key` is for legacy reasons (tfds) and is not important in itself, but must be unique for each example.
|
269 |
if self.config.name == "sourceA":
|
270 |
with open(filepath, encoding="utf-8") as csvfile:
|
271 |
next(csvfile)
|
|
|
257 |
len(set(val_df["id_prompt"]).intersection(set(test_df["id_prompt"]))) == 0
|
258 |
), "Overlap between val and test id_prompt"
|
259 |
dirname = os.path.dirname(filepath)
|
|
|
260 |
train_df.to_csv(f"{dirname}/train.csv", index=False)
|
261 |
val_df.to_csv(f"{dirname}/validation.csv", index=False)
|
262 |
test_df.to_csv(f"{dirname}/test.csv", index=False)
|
263 |
|
264 |
# method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
|
265 |
def _generate_examples(self, filepath, split):
|
|
|
|
|
266 |
if self.config.name == "sourceA":
|
267 |
with open(filepath, encoding="utf-8") as csvfile:
|
268 |
next(csvfile)
|