# txt¶

class hanlp.datasets.tokenization.loaders.txt.TextTokenizingDataset(data: Union[str, List], transform: Union[Callable, List] = None, cache=None, generate_idx=None, delimiter=None, max_seq_len=None, sent_delimiter=None, char_level=False, hard_constraint=False)[source]

A dataset for tagging tokenization tasks.

Parameters
• data – The local or remote path to a dataset, or a list of samples where each sample is a dict.

• transform – Predefined transform(s).

• cacheTrue to enable caching, so that transforms won’t be called twice.

• generate_idx – Create a IDX field for each sample to store its order in dataset. Useful for prediction when samples are re-ordered by a sampler.

• delimiter – Delimiter between tokens used to split a line in the corpus.

• max_seq_len – Sentences longer than max_seq_len will be split into shorter ones if possible.

• sent_delimiter – Delimiter between sentences, like period or comma, which indicates a long sentence can be split here.

• char_level – Whether the sequence length is measured at char level.

• hard_constraint – Whether to enforce hard length constraint on sentences. If there is no sent_delimiter in a sentence, it will be split at a token anyway.

load_file(filepath: str)[source]

Load tokenized corpus. The format is one sentence per line, where each line consisits of tokens seperated by a delimiter (usually space).

\$ head train.txt


Parameters

filepath – The path to the corpus.