def forward_request(self, model_info, inputs, outputs=None, options=None):
return [
[TranslationOutput(translation)]
for translation in self.translate_batch(
inputs, model_info["source"], model_info["target"]
)
]
def forward_request(self, batch_inputs, info, timeout=None):
return [[
TranslationOutput(translation)
] for translation in translate_list(self._credentials,
batch_inputs,
source_language=info['source'],
target_language=info['target'])]
def forward_request(self, batch_inputs, info, timeout=None):
return [[TranslationOutput(translation)] for translation in translate_list(
self.httpClient,
self._appid,
self._key,
batch_inputs,
source_language=info['source'],
target_language=info['target'])]
def forward_request(self, model_info, inputs, outputs=None, options=None):
translate_fn = model_info
hypotheses = []
for i, source in enumerate(inputs):
target = outputs[i] if outputs is not None else None
output = translate_fn(source, target)
hypotheses.append([TranslationOutput(output)])
return hypotheses
def forward_request(self, batch_inputs, info, timeout=None):
batch_inputs = [{'src': ' '.join(tokens)} for tokens in batch_inputs]
try:
batch_results = requests.post(
info['endpoint'], json=batch_inputs, timeout=timeout).json()
except requests.exceptions.Timeout as e:
logger.error('%s', e)
return None
batch_outputs = []
for hypotheses in batch_results:
outputs = []
for hyp in hypotheses:
tokens = hyp['tgt'].split()
score = hyp['pred_score'] / len(tokens)
outputs.append(TranslationOutput(tokens, score=score, attention=hyp['attn']))
batch_outputs.append(outputs)
return batch_outputs
def forward_request(self, batch_inputs, info, timeout=None):
return [[TranslationOutput(translation)]
for translation in self.translate_batch(
batch_inputs, info['source'], info['target'])]