def handle(self, t_input: sockeye.inference.TranslatorInput, t_output: sockeye.inference.TranslatorOutput):
"""
:param t_input: Translator input.
:param t_output: Translator output.
"""
alignments = " ".join(
["%d-%d" % (s, t) for s, t in get_alignments(t_output.attention_matrix, threshold=self.threshold)])
self.stream.write("%s\t%s\n" % (t_output.translation, alignments))
self.stream.flush()
def test_get_alignments():
attention_matrix = np.asarray([[0.1, 0.4, 0.5], [0.2, 0.8, 0.0],
[0.4, 0.4, 0.2]])
test_cases = [(0.5, [(1, 1)]), (0.8, []),
(0.1, [(0, 1), (0, 2), (1, 0), (1, 1), (1, 2), (2, 0),
(2, 2)])]
for threshold, expected_alignment in test_cases:
alignment = list(
utils.get_alignments(attention_matrix, threshold=threshold))
assert alignment == expected_alignment
def handle(self,
t_input: inference.TranslatorInput,
t_output: inference.TranslatorOutput,
t_walltime: float = 0.):
"""
:param t_input: Translator input.
:param t_output: Translator output.
:param t_walltime: Total wall-clock time for translation.
"""
alignments = " ".join(
["%d-%d" % (s, t) for s, t in get_alignments(t_output.attention_matrix, threshold=self.threshold)])
self.stream.write("%s\t%s\n" % (t_output.translation, alignments))
self.stream.flush()
def handle(self,
t_input: inference.TranslatorInput,
t_output: inference.TranslatorOutput,
t_walltime: float = 0.):
"""
:param t_input: Translator input.
:param t_output: Translator output.
:param t_walltime: Total wall-clock time for translation.
"""
alignments = " ".join(
["%d-%d" % (s, t) for s, t in get_alignments(t_output.attention_matrix, threshold=self.threshold)])
self.stream.write("%s\t%s\n" % (t_output.translation, alignments))
self.stream.flush()
def handle(self,
t_input: inference.TranslatorInput,
t_output: inference.TranslatorOutput,
t_walltime: float = 0.):
extracted_alignments = []
for alignment_matrix in t_output.nbest_attention_matrices:
extracted_alignments.append(
list(get_alignments(alignment_matrix,
threshold=self.threshold)))
d_ = {
"translations": t_output.nbest_translations,
"scores": t_output.nbest_scores,
"alignments": extracted_alignments
}
self.stream.write("%s\n" % json.dumps(d_, sort_keys=True))
