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Update app.py
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app.py
CHANGED
@@ -39,16 +39,16 @@ _ = utils.load_checkpoint("fr_wa_finetuned_pho/G_125000.pth", net_g, None)
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def tts(text):
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if len(text) >
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return "Error: Text is too long", None
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sid = torch.LongTensor([1]) # speaker identity
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stn_tst = get_text(text,
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with torch.no_grad():
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x_tst = stn_tst.unsqueeze(0)
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x_tst_lengths = torch.LongTensor([stn_tst.size(0)])
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# print(stn_tst.size())
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audio =
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0, 0].data.float().numpy()
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return "Success", (hps.data.sampling_rate, audio)
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@@ -56,7 +56,7 @@ app = gr.Blocks()
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with app:
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with gr.Tabs():
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with gr.TabItem("Basic"):
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tts_input1 = gr.TextArea(label="Text in
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# tts_input2 = gr.Dropdown(label="Speaker", choices=hps.speakers, type="index", value=hps.speakers[0])
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tts_submit = gr.Button("Generate", variant="primary")
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tts_output1 = gr.Textbox(label="Message")
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def tts(text):
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if len(text) > 350:
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return "Error: Text is too long", None
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sid = torch.LongTensor([1]) # speaker identity
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stn_tst = get_text(text, hps)
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with torch.no_grad():
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x_tst = stn_tst.unsqueeze(0)
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x_tst_lengths = torch.LongTensor([stn_tst.size(0)])
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# print(stn_tst.size())
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audio = net_g.infer(x_tst, x_tst_lengths, sid=sid, noise_scale=.667, noise_scale_w=0.8, length_scale=1)[0][
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0, 0].data.float().numpy()
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return "Success", (hps.data.sampling_rate, audio)
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with app:
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with gr.Tabs():
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with gr.TabItem("Basic"):
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tts_input1 = gr.TextArea(label="Text in Walloon (350 words limitation)", value="")
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# tts_input2 = gr.Dropdown(label="Speaker", choices=hps.speakers, type="index", value=hps.speakers[0])
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tts_submit = gr.Button("Generate", variant="primary")
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tts_output1 = gr.Textbox(label="Message")
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