def translate_and_compute_bleu(model, subtokenizer, bleu_source, bleu_ref):
"""Translate file and report the cased and uncased bleu scores."""
# Create temporary file to store translation.
tmp = tempfile.NamedTemporaryFile(delete=False)
tmp_filename = tmp.name
translate.translate_file(model,
subtokenizer,
bleu_source,
output_file=tmp_filename,
print_all_translations=False)
# Compute uncased and cased bleu scores.
uncased_score = compute_bleu.bleu_wrapper(bleu_ref, tmp_filename, False)
cased_score = compute_bleu.bleu_wrapper(bleu_ref, tmp_filename, True)
os.remove(tmp_filename)
return uncased_score, cased_score
def translate_and_compute_bleu(model,
params,
subtokenizer,
bleu_source,
bleu_ref,
distribution_strategy=None):
"""Translate file and report the cased and uncased bleu scores.
Args:
model: A Keras model, used to generate the translations.
params: A dictionary, containing the translation related parameters.
subtokenizer: A subtokenizer object, used for encoding and decoding source
and translated lines.
bleu_source: A file containing source sentences for translation.
bleu_ref: A file containing the reference for the translated sentences.
distribution_strategy: A platform distribution strategy, used for TPU based
translation.
Returns:
uncased_score: A float, the case insensitive BLEU score.
cased_score: A float, the case sensitive BLEU score.
"""
# Create temporary file to store translation.
tmp = tempfile.NamedTemporaryFile(delete=False)
tmp_filename = tmp.name
translate.translate_file(
model,
params,
subtokenizer,
bleu_source,
output_file=tmp_filename,
print_all_translations=False,
distribution_strategy=distribution_strategy)
# Compute uncased and cased bleu scores.
uncased_score = compute_bleu.bleu_wrapper(bleu_ref, tmp_filename, False)
cased_score = compute_bleu.bleu_wrapper(bleu_ref, tmp_filename, True)
os.remove(tmp_filename)
return uncased_score, cased_score
