def infer(self, features=None, decode_length=1, beam_size=1, top_beams=1, alpha=0.0, use_tpu=False): """Predict.""" features["targets"] = tf.identity(features["inputs"]) logits, _ = self(features) log_probs = common_layers.log_prob_from_logits(logits) predictions, scores = common_layers.argmax_with_score(log_probs) return { "outputs": predictions, "scores": scores, }
def infer(self, features=None, decode_length=1, beam_size=1, top_beams=1, alpha=0.0, use_tpu=False): """Predict.""" del decode_length, beam_size, top_beams, alpha, use_tpu assert features is not None logits, _ = self(features) assert len(logits.get_shape()) == 5 logits = tf.squeeze(logits, [1, 2, 3]) log_probs = common_layers.log_prob_from_logits(logits) predictions, scores = common_layers.argmax_with_score(log_probs) return { "outputs": predictions, "scores": scores, }
def infer(self, features=None, decode_length=50, beam_size=1, top_beams=1, alpha=0.0, use_tpu=False): """Predict.""" del decode_length, beam_size, top_beams, alpha, use_tpu assert features is not None logits, _ = self(features) # pylint: disable=not-callable assert len(logits.get_shape()) == 5 logits = tf.squeeze(logits, [1, 2, 3]) log_probs = common_layers.log_prob_from_logits(logits) predictions, scores = common_layers.argmax_with_score(log_probs) return { "outputs": predictions, "scores": scores, }