def postprocess_output(outputs,
sentence_id,
eos,
bpe_delimiter,
number_token=None,
name_token=None):
"""Given batch decoding outputs, select a sentence and postprocess it."""
# Select the sentence
output = outputs[sentence_id, :].tolist()
# It doesn't cut off at </s> because of mismatch between </s> and b'</s>', the output of the lookup table
# The lookup-table outputs are in bytes. We need this for the equality check
eos = bytes(eos, encoding='utf-8')
if eos and eos in output:
output = output[:output.index(eos)]
if number_token:
number_token_bytes = bytes(number_token, encoding='utf8')
output = [
b"53" if word == number_token_bytes else word for word in output
]
if name_token:
name_token_bytes = bytes(name_token, encoding='utf8')
output = [
b"Batman" if word == name_token_bytes else word for word in output
]
if bpe_delimiter:
response = utils.format_bpe_text(output, bpe_delimiter)
else:
response = utils.format_text(output)
return response
def get_translation(nmt_outputs, infer_logits, sent_id, tgt_eos,
subword_option):
"""Given batch decoding outputs, select a sentence and turn to text."""
if tgt_eos: tgt_eos = tgt_eos.encode("utf-8")
# Select a sentence
output = nmt_outputs[sent_id, :].tolist()
scores = infer_logits[sent_id]
#fw=open('sample_res/scores_logits_{}'.format(sent_id),'w+')
#for i in scores:
#fw.write('\n'.join([' '.join(str(a)for a in e)for e in scores]))
#fw.close()
#print ("output",output)
#print ("scores",scores)
# If there is an eos symbol in outputs, cut them at that point.
if tgt_eos and tgt_eos in output:
output = output[:output.index(tgt_eos)]
if subword_option == "bpe": # BPE
#print ("subword_option ==bpe")
translation = utils.format_bpe_text(output)
elif subword_option == "spm": # SPM
#print ("subword_option ==spm")
translation = utils.format_spm_text(output)
else:
#print ("scores in format_text!")
translation = utils.format_text(output, scores)
return translation
def get_translation(nmt_outputs, sent_id, tgt_eos):
"""Given batch decoding outputs, select a sentence and turn to text."""
# Select a sentence
output = nmt_outputs[sent_id, :].tolist()
if tgt_eos and tgt_eos in output:
output = output[:output.index(tgt_eos)]
translation = utils.format_text(output)
return translation
def decode_inference_indices(model, sess):
nmt_outputs, infer_summary = model.decode(sess)
assert nmt_outputs.shape[0] == 1
output = nmt_outputs[0, :].tolist()
translation = utils.format_text(output)
return translation
def get_translation_cut_both(nmt_outputs, sent_id, start_token, end_token):
"""Given batch decoding outputs, select a sentence and turn to text."""
# Select a sentence
output = nmt_outputs[sent_id, :].tolist()
if start_token and start_token in output:
output = output[:output.index(start_token)]
if end_token and end_token in output:
output = output[:output.index(end_token)]
translation = utils.format_text(output)
return translation
def _get_translation(outputs, sent_id, tgt_eos, subword_option):
"""Given batch decoding outputs, select a sentence and turn to text."""
if tgt_eos: tgt_eos = tgt_eos.encode("utf-8")
# Select a sentence
output = outputs[sent_id, :].tolist()
# If there is an eos symbol in outputs, cut them at that point.
if tgt_eos and tgt_eos in output:
output = output[:output.index(tgt_eos)]
translation = utils.format_text(output)
return translation
def get_translation(nmt_outputs, sent_id, tgt_eos, subword_option):
if tgt_eos: tgt_eos = tgt_eos.encode("utf-8")
output = nmt_outputs[sent_id, :].tolist()
if tgt_eos and tgt_eos in output:
output = output[:output.index(tgt_eos)]
if subword_option == "bpe":
translation = utils.format_bpe_text(output)
elif subword_option == "spm":
translation = utils.format_spm_text(output)
else:
translation = utils.format_text(output)
return translation
def get_translation(nmt_outputs, sent_id, tgt_eos, bpe_delimiter):
"""Given batch decoding outputs, select a sentence and turn to text."""
# Select a sentence
output = nmt_outputs[sent_id, :].tolist()
# If there is an eos symbol in outputs, cut them at that point.
if tgt_eos and tgt_eos in output:
output = output[:output.index(tgt_eos)]
if not bpe_delimiter:
translation = utils.format_text(output)
else: # BPE
translation = utils.format_bpe_text(output, delimiter=bpe_delimiter)
return translation
def decode_inference_indices(model, sess):
nmt_outputs, infer_summary = model.decode(sess)
assert nmt_outputs.shape[0] == 1
# if tgt_eos: tgt_eos = tgt_eos.encode("utf-8")
# Select a sentence
output = nmt_outputs[0, :].tolist()
#
# # If there is an eos symbol in outputs, cut them at that point.
if "</s>" in output:
output = output[:output.index("</s>")]
translation = utils.format_text(output)
return translation
def get_translation(nmt_outputs, sent_id, tgt_eos, subword_option):
"""Given batch decoding outputs, select a sentence and turn to text."""
if tgt_eos: tgt_eos = tgt_eos.encode("utf-8")
# Select a sentence
output = nmt_outputs[sent_id, :].tolist()
# If there is an eos symbol in outputs, cut them at that point.
if tgt_eos and tgt_eos in output:
output = output[:output.index(tgt_eos)]
if subword_option == "bpe": # BPE
translation = utils.format_bpe_text(output)
elif subword_option == "spm": # SPM
translation = utils.format_spm_text(output)
else:
translation = utils.format_text(output)
return translation
