def _dict_to_samples(self, dictionary: dict, **kwargs) -> [Sample]:
n_special_tokens = self.tokenizer.num_added_tokens(pair=True)
samples = create_samples_squad(dictionary=dictionary,
max_query_len=self.max_query_length,
max_seq_len=self.max_seq_len,
doc_stride=self.doc_stride,
n_special_tokens=n_special_tokens)
return samples
def _dict_to_samples(self, dictionary: dict, **kwargs) -> [Sample]:
if "paragraphs" not in dictionary: # TODO change this inference mode hack
dictionary = self._convert_rest_api_dict(infer_dict=dictionary)
samples = create_samples_squad(entry=dictionary)
for sample in samples:
tokenized = tokenize_with_metadata(text=" ".join(
sample.clear_text["doc_tokens"]),
tokenizer=self.tokenizer)
sample.tokenized = tokenized
return samples
def _dict_to_samples(cls, dict: dict, **kwargs) -> [Sample]:
# TODO split samples that are too long in this function, related to todo in self._sample_to_features
if "paragraphs" not in dict: # TODO change this inference mode hack
dict = cls._convert_inference(infer_dict=dict)
samples = create_samples_squad(entry=dict)
for sample in samples:
tokenized = tokenize_with_metadata(
text=" ".join(sample.clear_text["doc_tokens"]),
tokenizer=cls.tokenizer,
max_seq_len=cls.max_seq_len,
)
sample.tokenized = tokenized
return samples