Create app.py

app.py

@@ -0,0 +1,34 @@
+import torch
+import torchaudio
+
+#fixes second prediction bug
+torch._C._jit_override_can_fuse_on_cpu(False)
+torch._C._jit_override_can_fuse_on_gpu(False)
+torch._C._jit_set_texpr_fuser_enabled(False)
+torch._C._jit_set_nvfuser_enabled(False)
+
+loader = torch.jit.load("audio_loader.pt")
+model = torch.jit.load('QuartzNet_thunderspeech_3.pt')
+
+vocab = model.text_transform.vocab.itos
+vocab[-1] = ''
+
+def convert_probs(probs):
+  ids = probs.argmax(1)[0]
+  s = []
+  if vocab[ids[0]]: s.append(vocab[ids[0]])
+  for i in range(1,len(ids)):
+    if ids[i-1] != ids[i]:
+      new = vocab[ids[i]]
+      if new: s.append(new)
+  #return '.'.join(s)
+  return s
+
+def predict(path):
+  audio = loader(path)
+  probs = model(audio, torch.tensor(audio.shape[0] * [audio.shape[-1]], device=audio.device))[0]
+  return convert_probs(probs)
+  
+  gr.Interface(fn=predict,
+             inputs=[gr.inputs.Audio(source='microphone', type='filepath', optional=True)],
+              outputs= 'text').launch(debug=Tru