Spaces:
Running
Running
no multithreading
Browse files
app.py
CHANGED
@@ -1033,10 +1033,10 @@ def synthandreturn(text, request: gr.Request):
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break
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except Exception as e:
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attempt_count += 1
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-
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-
print(f"{model}: Unable to call API (attempt: {attempt_count})")
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# sleep for three seconds to avoid spamming the server with requests
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-
time.sleep(3)
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# Fetch and store client again
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# hf_clients[model] = Client(model, hf_token=hf_token, headers=hf_headers)
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@@ -1061,6 +1061,7 @@ def synthandreturn(text, request: gr.Request):
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audio.export(f.name, format="wav")
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os.unlink(result)
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result = f.name
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except:
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print(f"{model}: [WARN] Unable to resample audio")
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pass
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@@ -1107,13 +1108,15 @@ def synthandreturn(text, request: gr.Request):
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if mdl2 in AVAILABLE_MODELS.keys(): mdl2k=AVAILABLE_MODELS[mdl2]
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results = {}
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print(f"Sending models {mdl1k} and {mdl2k} to API")
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-
thread1 = threading.Thread(target=predict_and_update_result, args=(text, mdl1k, results, request))
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-
thread2 = threading.Thread(target=predict_and_update_result, args=(text, mdl2k, results, request))
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thread1.start()
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thread2.start()
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thread1.join(180)
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thread2.join(180)
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#debug
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# print(results)
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# print(list(results.keys())[0])
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break
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except Exception as e:
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attempt_count += 1
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+
raise gr.Error(f"{model}:"+ repr(e))
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+
# print(f"{model}: Unable to call API (attempt: {attempt_count})")
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# sleep for three seconds to avoid spamming the server with requests
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+
# time.sleep(3)
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# Fetch and store client again
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# hf_clients[model] = Client(model, hf_token=hf_token, headers=hf_headers)
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audio.export(f.name, format="wav")
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os.unlink(result)
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result = f.name
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gr.Info('Audio from a TTS model received')
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except:
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print(f"{model}: [WARN] Unable to resample audio")
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pass
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if mdl2 in AVAILABLE_MODELS.keys(): mdl2k=AVAILABLE_MODELS[mdl2]
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results = {}
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print(f"Sending models {mdl1k} and {mdl2k} to API")
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+
# thread1 = threading.Thread(target=predict_and_update_result, args=(text, mdl1k, results, request))
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# thread2 = threading.Thread(target=predict_and_update_result, args=(text, mdl2k, results, request))
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# thread1.start()
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# thread2.start()
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# thread1.join(180)
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# thread2.join(180)
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predict_and_update_result(text, mdl1k, results, request)
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predict_and_update_result(text, mdl2k, results, request)
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#debug
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# print(results)
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# print(list(results.keys())[0])
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