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#: ../source/paddlenlp.transformers.unified_transformer.tokenizer.rst:2
msgid "tokenizer"
msgstr ""

#: of paddlenlp.transformers.unified_transformer.tokenizer:1
msgid "Tokenization class for UnifiedTransformer model."
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer:1
msgid "基类：:class:`paddlenlp.transformers.tokenizer_utils.PretrainedTokenizer`"
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer:1
msgid ""
"Constructs an UnifiedTransformer tokenizer based on `SentencePiece "
"<https://github.com/google/sentencepiece>`__."
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer:3
msgid ""
"This tokenizer inherits from "
":class:`~paddlenlp.transformers.tokenizer_utils.PretrainedTokenizer` "
"which contains most of the main methods. For more information regarding "
"those methods, please refer to this superclass."
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.build_inputs_with_special_tokens
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.build_offset_mapping_with_special_tokens
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.convert_ids_to_string
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.convert_tokens_to_string
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.create_token_type_ids_from_sequences
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.dialogue_encode
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.get_special_tokens_mask
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.load_vocabulary
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.num_special_tokens_to_add
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.save_resources
msgid "参数"
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer:7
msgid "The path of file to construct vocabulary."
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer:9
msgid ""
"The sentencepiece model file (ends with '.spm') required to instantiate a"
" `SentencePiece <https://github.com/google/sentencepiece>`__."
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer:12
msgid ""
"Whether or not to lowercase the input when tokenizing. Defaults to False "
"and **does not** lowercase the input."
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer:15
msgid ""
"A special token representing the *unknown (out-of-vocabulary)* token. An "
"unknown token is set to be `unk_token` inorder to be converted to an ID. "
"Defaults to \"[UNK]\"."
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer:19
msgid ""
"A special token used to make arrays of tokens the same size for batching "
"purposes. Defaults to \"[PAD]\"."
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer:22
msgid ""
"A special token representing the beginning of a sequence. Defaults to "
"\"[CLS]\"."
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer:25
msgid ""
"A special token representing the end of a sequence or separating two "
"different sentences in the same input. Defaults to \"[SEP]\"."
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer:28
msgid "A special token representing a masked token. Defaults to \"[MASK]\"."
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer:30
msgid ""
"The path of file that contains additional special tokens to be used by "
"the tokenizer. Defaults to \"\"."
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.vocab_size:1
msgid "Returns the size of vocabulary."
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.convert_ids_to_string:14
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.convert_tokens_to_string:15
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.dialogue_encode:107
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.vocab_size:4
msgid "示例"
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.convert_tokens_to_string:1
msgid ""
"Converts a sequence of tokens (list of string) in a single string. Since "
"the usage of WordPiece introducing `__` to concat subwords, also remove "
"`__` when converting."
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.convert_tokens_to_string:5
msgid "A list of string representing tokens to be converted."
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.convert_ids_to_string:6
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.convert_tokens_to_string:7
msgid "Whether or not to keep the segmentation with space. Defaults to True."
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.build_inputs_with_special_tokens
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.build_offset_mapping_with_special_tokens
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.convert_ids_to_string
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.convert_tokens_to_string
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.create_token_type_ids_from_sequences
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.dialogue_encode
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.get_special_tokens_mask
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.load_vocabulary
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.num_special_tokens_to_add
msgid "返回"
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.convert_tokens_to_string:11
msgid "Converted string from tokens."
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.build_inputs_with_special_tokens
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.build_offset_mapping_with_special_tokens
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.convert_ids_to_string
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.convert_tokens_to_string
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.create_token_type_ids_from_sequences
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.dialogue_encode
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.get_special_tokens_mask
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.load_vocabulary
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.num_special_tokens_to_add
msgid "返回类型"
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.convert_ids_to_string:1
msgid ""
"Converts a single index or a sequence of indices to a token or a sequence"
" of tokens."
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.convert_ids_to_string:4
msgid "The token id (or token ids) to be converted to token(s)."
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.convert_ids_to_string:10
msgid "The decoded token(s)."
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.num_special_tokens_to_add:1
msgid ""
"Returns the number of added tokens when encoding a sequence with special "
"tokens."
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.num_special_tokens_to_add:3
msgid ""
"Whether the number of added tokens should be computed in the case of a "
"sequence pair or a single sequence. Defaults to `False`."
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.num_special_tokens_to_add:7
msgid "Number of special tokens added to sequences."
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.build_inputs_with_special_tokens:1
msgid ""
"Build model inputs from a sequence or a pair of sequence for sequence "
"classification tasks by concatenating and adding special tokens."
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.build_inputs_with_special_tokens:4
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.build_offset_mapping_with_special_tokens:3
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.create_token_type_ids_from_sequences:3
msgid ""
"Should be overridden in a subclass if the model has a special way of "
"building those."
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.build_inputs_with_special_tokens:6
msgid "List of IDs to which the special tokens will be added."
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.build_inputs_with_special_tokens:8
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.create_token_type_ids_from_sequences:10
msgid "Optional second list of IDs for sequence pairs."
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.build_inputs_with_special_tokens:11
msgid "List of input_id with the appropriate special tokens."
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.build_offset_mapping_with_special_tokens:1
msgid ""
"Build offset map from a pair of offset map by concatenating and adding "
"offsets of special tokens."
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.build_offset_mapping_with_special_tokens:5
msgid "List of char offsets to which the special tokens will be added."
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.build_offset_mapping_with_special_tokens:7
msgid "Optional second list of char offsets for offset mapping pairs."
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.build_offset_mapping_with_special_tokens:10
msgid "List of char offsets with the appropriate offsets of special tokens."
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.create_token_type_ids_from_sequences:1
msgid ""
"Create a mask from the two sequences passed to be used in a sequence-pair"
" classification task."
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.create_token_type_ids_from_sequences:6
msgid ""
"If `token_ids_1` is `None`, this method only returns the first portion of"
" the mask (0s)."
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.create_token_type_ids_from_sequences:8
msgid "List of IDs."
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.create_token_type_ids_from_sequences:13
msgid "List of token_type_id according to the given sequence(s)."
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.get_special_tokens_mask:1
msgid ""
"Retrieves sequence ids from a token list that has no special tokens "
"added. This method is called when adding special tokens using the "
"tokenizer ``encode`` methods."
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.get_special_tokens_mask:4
msgid "List of ids of the first sequence."
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.get_special_tokens_mask:6
msgid "List of ids of the second sequence."
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.get_special_tokens_mask:8
msgid ""
"Whether or not the token list is already formatted with special tokens "
"for the model. Defaults to None."
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.get_special_tokens_mask:12
msgid ""
"The list of integers in the range [0, 1]:     1 for a special token, 0 "
"for a sequence token."
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.get_special_tokens_mask:14
msgid "The list of integers in the range [0, 1]:"
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.get_special_tokens_mask:15
msgid "1 for a special token, 0 for a sequence token."
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.save_resources:1
msgid ""
"Save tokenizer related resources to `resource_files_names` indicating "
"files under `save_directory` by copying directly. Override it if "
"necessary."
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.save_resources:4
msgid "Directory to save files into."
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.load_vocabulary:1
msgid ""
"Instantiate an instance of `Vocab` from a file reserving all tokens by "
"using `Vocab.from_dict`. The file contains a token per line, and the line"
" number would be the index of corresponding token."
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.load_vocabulary:5
msgid "path of file to construct vocabulary."
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.load_vocabulary:7
msgid ""
"special token for unknown token. If no need, it also could be `None`. "
"Defaults to `None`."
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.load_vocabulary:10
msgid ""
"special token for padding token. If no need, it also could be `None`. "
"Defaults to `None`."
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.load_vocabulary:13
msgid ""
"special token for bos token. If no need, it also could be `None`. "
"Defaults to `None`."
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.load_vocabulary:16
msgid ""
"special token for eos token. If no need, it also could be `None`. "
"Defaults to `None`."
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.load_vocabulary:19
msgid "keyword arguments for `Vocab.from_dict`."
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.load_vocabulary:22
msgid "An instance of `Vocab`."
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.dialogue_encode:1
msgid ""
"Main method to encode the single-turn or multi-turn dialogue "
"conversation. It will return a dictionary containing the encoded sequence"
" and other relative informations which meets the input format "
"requirements of the UnifiedTransformer model. See detail at "
"https://github.com/PaddlePaddle/Knover/tree/luge-dialogue/luge-dialogue"
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.dialogue_encode:8
msgid ""
"The history of dialogue conversation. It is an utterance or list of "
"utterances to be encoded. Each utterance is a string."
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.dialogue_encode:12
msgid ""
"The response of dialogue conversation. It should be set when training the"
" model. It should not be set when running inference. Defaults to None."
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.dialogue_encode:16
msgid ""
"The knowledge information of dialogue conversation. It should be set if "
"the `task_type` is \"knowledge\" or \"recommend\". Defaults to None."
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.dialogue_encode:20
msgid ""
"The type of dialogue conversation. It is one of \"chitchat\", "
"\"knowledge\" and \"recommend\". They represent the chitchat dialogue, "
"knowledge grounded dialogue and conversational recommendation "
"respectively. Defaults to None, which means there is no `special_token` "
"added in output sequence for identifying different conversation types."
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.dialogue_encode:27
msgid "The maximum encoded sequence length. Defaults to 512."
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.dialogue_encode:30
msgid ""
"The maximum encoded sequence length of the input `response`. Defaults to "
"128."
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.dialogue_encode:33
msgid ""
"The maximum encoded sequence length of the input `knowledge`. Defaults to"
" 128."
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.dialogue_encode:36
msgid "Whether to return the position_ids. Defaults to True."
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.dialogue_encode:39
msgid "Whether to return the token_type_ids. Defaults to True."
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.dialogue_encode:42
msgid "Whether to return the role_ids. Defaults to False."
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.dialogue_encode:45
msgid "Whether to return the attention_mask. Defaults to True."
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.dialogue_encode:48
msgid "Whether to return the length of the encoded sequence. Defaults to False."
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.dialogue_encode:51
msgid ""
"Whether to add the special token \"[CLS]\" at the end of sequence as the "
"beginning of the response when running inference to force the model to "
"start generating response sequence. Defaults to False."
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.dialogue_encode:56
msgid ""
"Whether to pad the returned sequences to the `max_seq_len`. Note that, in"
" this method, returned sequences will be padded on the left. Defaults to "
"False."
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.dialogue_encode:60
msgid "Whether to convert the returned sequences to Tensor. Defaults to False."
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.dialogue_encode:63
msgid ""
"Whether or not the input text (`history`, `response` and `knowledge`) has"
" been pretokenized. Defaults to True."
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.dialogue_encode:67
msgid ""
"Specify the involved positional style which must be one of [relative, "
"continuous]. Defaults to continuous which means start from 0 to maximum "
"length of history."
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.dialogue_encode:72
msgid ""
"A dictionary containing the encoded sequence and other relative "
"informations.  With the corresponding fields:  - input_ids "
"(list[int]|Tensor):     A list of indices of input tokens to be feed to "
"UnifiedTransformer     model. If `return_tensors` is True, it is a Tensor"
" with shape     [1, sequence_length] and data type 'int64'. - role_ids "
"(list[int]|Tensor, optional):     A list of indices of role indices. If "
"`return_role_ids` is True,     it is a Tensor with shape [1, "
"sequence_length] and data type 'int64'. - token_type_ids "
"(list[int]|Tensor, optional):     A list of segment token indices to "
"indicate whether the token     belongs to the dialogue response. If "
"`return_tensors` is True,     it is a Tensor with shape [1, "
"sequence_length] and data type     'int64'.     Being returned when "
"`return_token_type_ids` is set to True. - position_ids (list[int]|Tensor,"
" optional):     A list of The position indices. If `return_tensors` is "
"True,     it is a Tensor with shape [1, sequence_length] and data type"
"     'int64'.     Being returned when `return_position_ids` is set to "
"True. - attention_mask (numpy.ndarray|Tensor, optional):     A "
"numpy.ndarray to prevents attention to some unwanted positions,     with "
"shape [sequence_length, sequence_length] and data type     'float32'. If "
"`return_tensors` is True, it is a Tensor with shape     [1, 1, "
"sequence_length, sequence_length] and data type 'float32'.     Being "
"returned when `return_attention_mask` is set to True. - seq_len (int, "
"optional):     The actual length of the `input_ids`, excluding the pad "
"token.     Being returned when `return_length` is set to True."
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.dialogue_encode:72
msgid ""
"A dictionary containing the encoded sequence and other relative "
"informations."
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.dialogue_encode:75
msgid "With the corresponding fields:"
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.dialogue_encode:79
msgid "input_ids (list[int]|Tensor):"
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.dialogue_encode:78
msgid ""
"A list of indices of input tokens to be feed to UnifiedTransformer model."
" If `return_tensors` is True, it is a Tensor with shape [1, "
"sequence_length] and data type 'int64'."
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.dialogue_encode:82
msgid "role_ids (list[int]|Tensor, optional):"
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.dialogue_encode:82
msgid ""
"A list of indices of role indices. If `return_role_ids` is True, it is a "
"Tensor with shape [1, sequence_length] and data type 'int64'."
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.dialogue_encode:88
msgid "token_type_ids (list[int]|Tensor, optional):"
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.dialogue_encode:85
msgid ""
"A list of segment token indices to indicate whether the token belongs to "
"the dialogue response. If `return_tensors` is True, it is a Tensor with "
"shape [1, sequence_length] and data type 'int64'. Being returned when "
"`return_token_type_ids` is set to True."
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.dialogue_encode:93
msgid "position_ids (list[int]|Tensor, optional):"
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.dialogue_encode:91
msgid ""
"A list of The position indices. If `return_tensors` is True, it is a "
"Tensor with shape [1, sequence_length] and data type 'int64'. Being "
"returned when `return_position_ids` is set to True."
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.dialogue_encode:99
msgid "attention_mask (numpy.ndarray|Tensor, optional):"
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.dialogue_encode:96
msgid ""
"A numpy.ndarray to prevents attention to some unwanted positions, with "
"shape [sequence_length, sequence_length] and data type 'float32'. If "
"`return_tensors` is True, it is a Tensor with shape [1, 1, "
"sequence_length, sequence_length] and data type 'float32'. Being returned"
" when `return_attention_mask` is set to True."
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.dialogue_encode:102
msgid "seq_len (int, optional):"
msgstr ""

#: of
#: paddlenlp.transformers.unified_transformer.tokenizer.UnifiedTransformerTokenizer.dialogue_encode:102
msgid ""
"The actual length of the `input_ids`, excluding the pad token. Being "
"returned when `return_length` is set to True."
msgstr ""

