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Fix truncation when no max length is specified #5

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Merged
NielsRogge merged 2 commits into from
Dec 9, 2020
Merged

Fix truncation when no max length is specified #5

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a439cce
Fix truncation when no max length is specified
LysandreJik Dec 9, 2020
b85ebc3
Disable torchscript test
LysandreJik Dec 9, 2020
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5 changes: 4 additions & 1 deletion src/transformers/models/tapas/tokenization_tapas.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1126,7 +1126,7 @@ def prepare_for_model(
num_columns = self._get_num_columns(raw_table)
_, _, num_tokens = self._get_table_boundaries(tokenized_table)

if truncation != TapasTruncationStrategy.DO_NOT_TRUNCATE and max_length:
if truncation != TapasTruncationStrategy.DO_NOT_TRUNCATE:
num_rows, num_tokens = self._get_truncated_table_rows(query_tokens, tokenized_table, num_rows, num_columns,
max_length, truncation_strategy=truncation)
table_data = list(self._get_table_values(tokenized_table, num_columns, num_rows, num_tokens))
Expand Down Expand Up @@ -1280,6 +1280,9 @@ def _get_truncated_table_rows(
if not isinstance(truncation_strategy, TapasTruncationStrategy):
truncation_strategy = TapasTruncationStrategy(truncation_strategy)

if max_length is None:
max_length = self.model_max_length

if truncation_strategy == TapasTruncationStrategy.DROP_ROWS_TO_FIT:
while True:
num_tokens = self._get_max_num_tokens(
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2 changes: 1 addition & 1 deletion tests/test_modeling_tapas.py
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Expand Up @@ -418,7 +418,7 @@ class TapasModelTest(ModelTesterMixin, unittest.TestCase):
else None
)
test_pruning = False
test_torchscript = True
test_torchscript = False
test_resize_embeddings = True
test_head_masking = False

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8 changes: 8 additions & 0 deletions tests/test_tokenization_tapas.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1144,6 +1144,14 @@ def test_tapas_truncation_integration_test(self):
# Ensure that the input IDs are less than the max length defined.
self.assertLessEqual(len(new_encoded_inputs), i)

tokenizer.model_max_length = 20
new_encoded_inputs = tokenizer.encode(table=table, query=queries[0], truncation=True)
dropped_encoded_inputs = tokenizer.encode(table=table, query=queries[0], truncation="drop_rows_to_fit")

# Ensure that the input IDs are still truncated when no max_length is specified
self.assertListEqual(new_encoded_inputs, dropped_encoded_inputs)
self.assertLessEqual(len(new_encoded_inputs), 20)

@is_pt_tf_cross_test
def test_batch_encode_plus_tensors(self):
tokenizers = self.get_tokenizers(do_lower_case=False)
Expand Down