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When using the new padding/truncation paradigm setting padding="max_length" + max_length=X actually pads the input up to max_length.

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This result in every sample going through QA pipelines to be of size 384 whatever the actual input size is making the overall pipeline very slow.

Signed-off-by: Morgan Funtowicz <funtowiczmo@gmail.com>
This commit is contained in:
Morgan Funtowicz 2020-07-01 10:39:09 +02:00
parent 90fbc544ca
commit 1b00a9a2ff
1 changed files with 2 additions and 2 deletions
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4
src/transformers/data/processors/squad.py
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@ -10,7 +10,7 @@ from tqdm import tqdm
from ...file_utils import is_tf_available, is_torch_available
from ...tokenization_bert import whitespace_tokenize
from .utils import DataProcessor
from ...tokenization_utils_base import PaddingStrategy
if is_torch_available():
import torch
@ -137,7 +137,7 @@ def squad_convert_example_to_features(example, max_seq_length, doc_stride, max_q
truncated_query if tokenizer.padding_side == "right" else span_doc_tokens,
span_doc_tokens if tokenizer.padding_side == "right" else truncated_query,
truncation="only_second" if tokenizer.padding_side == "right" else "only_first",
padding="max_length",
padding=PaddingStrategy.DO_NOT_PAD,
max_length=max_seq_length,
return_overflowing_tokens=True,
stride=max_seq_length - doc_stride - len(truncated_query) - sequence_pair_added_tokens,