Remove tolerance + drop_rows_to_fit by default (#9507)
* Remove tolerance + drop_rows_to_fit by default * remove drop_rows_to_fit
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@@ -255,7 +255,7 @@ class TapasTokenizer(PreTrainedTokenizer):
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value for :obj:`lowercase` (as in the original BERT).
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cell_trim_length (:obj:`int`, `optional`, defaults to -1):
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If > 0: Trim cells so that the length is <= this value. Also disables further cell trimming, should thus be
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used with 'drop_rows_to_fit' below.
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used with :obj:`truncation` set to :obj:`True`.
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max_column_id (:obj:`int`, `optional`):
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Max column id to extract.
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max_row_id (:obj:`int`, `optional`):
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@@ -264,8 +264,6 @@ class TapasTokenizer(PreTrainedTokenizer):
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Whether to add empty strings instead of column names.
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update_answer_coordinates (:obj:`bool`, `optional`, defaults to :obj:`False`):
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Whether to recompute the answer coordinates from the answer text.
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drop_rows_to_fit (:obj:`bool`, `optional`, defaults to :obj:`False`):
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Whether to drop the last rows if a table doesn't fit within max sequence length.
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"""
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@@ -292,7 +290,6 @@ class TapasTokenizer(PreTrainedTokenizer):
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max_row_id: int = None,
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strip_column_names: bool = False,
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update_answer_coordinates: bool = False,
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drop_rows_to_fit: bool = False,
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model_max_length: int = 512,
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additional_special_tokens: Optional[List[str]] = None,
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**kwargs
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@@ -323,7 +320,6 @@ class TapasTokenizer(PreTrainedTokenizer):
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max_row_id=max_row_id,
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strip_column_names=strip_column_names,
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update_answer_coordinates=update_answer_coordinates,
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drop_rows_to_fit=drop_rows_to_fit,
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model_max_length=model_max_length,
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additional_special_tokens=additional_special_tokens,
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**kwargs,
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@@ -352,7 +348,6 @@ class TapasTokenizer(PreTrainedTokenizer):
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self.max_row_id = max_row_id if max_row_id is not None else self.model_max_length
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self.strip_column_names = strip_column_names
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self.update_answer_coordinates = update_answer_coordinates
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self.drop_rows_to_fit = drop_rows_to_fit
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@property
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def do_lower_case(self):
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@@ -1122,7 +1117,7 @@ class TapasTokenizer(PreTrainedTokenizer):
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prev_answer_coordinates = kwargs["prev_answer_coordinates"]
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prev_answer_text = kwargs["prev_answer_text"]
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num_rows = self._get_num_rows(raw_table, self.drop_rows_to_fit)
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num_rows = self._get_num_rows(raw_table, truncation != TapasTruncationStrategy.DO_NOT_TRUNCATE)
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num_columns = self._get_num_columns(raw_table)
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_, _, num_tokens = self._get_table_boundaries(tokenized_table)
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