bec15911e08fe5fe3c705c24a23cfd926cc0da95,service.py,LabelService,label,#LabelService#Any#,33

Before Change

            A (most likely label, probability) tuple
        
        output = self.sess.graph.get_tensor_by_name("labels_softmax:0")
        predictions, = self.sess.run(output, {"wav_data:0": wav_data})
        return (self.labels[np.argmax(predictions)], max(predictions))


def encode_audio(wav_data):

After Change

        wav_data = np.frombuffer(wav_data, dtype=np.int16) / 32768.
        model_in = model.preprocess_audio(wav_data, 40, self.filters).unsqueeze(0)
        model_in = torch.autograd.Variable(model_in, requires_grad=False).cuda()
        predictions = F.softmax(self.model(model_in).squeeze(0).cpu()).data.numpy()
        return (self.labels[np.argmax(predictions)], max(predictions))

def set_speech_format(f):
    f.setnchannels(1)

Instances