def create_sent_report(self, src: sent.Sentence,
output: sent.ReadableSentence,
attentions: np.ndarray, ref_file: Optional[str],
**kwargs) -> None:
"""
Create report.
Args:
src: source-side input
output: generated output
attentions: attention matrices
ref_file: path to reference file
**kwargs: arguments to be ignored
"""
self.cur_sent_no += 1
if self.max_num_sents and self.cur_sent_no > self.max_num_sents: return
reference = utils.cached_file_lines(ref_file)[output.idx]
idx = src.idx
self.add_sent_heading(idx)
src_tokens = src.str_tokens() if isinstance(
src, sent.ReadableSentence) else []
trg_tokens = output.str_tokens()
src_str = src.sent_str() if isinstance(src,
sent.ReadableSentence) else ""
trg_str = output.sent_str()
self.add_charcut_diff(trg_str, reference)
self.add_fields_if_set({"Src": src_str})
self.add_atts(
attentions,
src.get_array() if isinstance(src, sent.ArraySentence) else
src_tokens, trg_tokens, idx)
self.finish_sent()
def create_sent_report(self, segment_actions, src: sent.Sentence,
**kwargs):
if self.report_fp is None:
utils.make_parent_dir(self.report_path)
self.report_fp = open(self.report_path, "w")
actions = segment_actions[0]
src = src.str_tokens()
words = []
start = 0
for end in actions:
if start < end + 1:
words.append("".join(map(str, src[start:end + 1])))
start = end + 1
print(" ".join(words), file=self.report_fp)