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Reorganized max_len warning
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e18f786cd5
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@ -671,10 +671,6 @@ class PreTrainedTokenizer(object):
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ids = []
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ids = []
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for token in tokens:
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for token in tokens:
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ids.append(self._convert_token_to_id_with_added_voc(token))
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ids.append(self._convert_token_to_id_with_added_voc(token))
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if len(ids) > self.max_len:
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logger.warning("Token indices sequence length is longer than the specified maximum sequence length "
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"for this model ({} > {}). Running this sequence through the model will result in "
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"indexing errors".format(len(ids), self.max_len))
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return ids
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return ids
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def _convert_token_to_id_with_added_voc(self, token):
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def _convert_token_to_id_with_added_voc(self, token):
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@ -877,6 +873,11 @@ class PreTrainedTokenizer(object):
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encoded_inputs["token_type_ids"] = encoded_inputs["token_type_ids"][:max_length]
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encoded_inputs["token_type_ids"] = encoded_inputs["token_type_ids"][:max_length]
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encoded_inputs["special_tokens_mask"] = encoded_inputs["special_tokens_mask"][:max_length]
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encoded_inputs["special_tokens_mask"] = encoded_inputs["special_tokens_mask"][:max_length]
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if max_length is None and len(encoded_inputs["input_ids"]) > self.max_len:
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logger.warning("Token indices sequence length is longer than the specified maximum sequence length "
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"for this model ({} > {}). Running this sequence through the model will result in "
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"indexing errors".format(len(ids), self.max_len))
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return encoded_inputs
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return encoded_inputs
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def truncate_sequences(self, ids, pair_ids=None, num_tokens_to_remove=0, truncation_strategy='longest_first', stride=0):
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def truncate_sequences(self, ids, pair_ids=None, num_tokens_to_remove=0, truncation_strategy='longest_first', stride=0):
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