resume thread
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@ -108,12 +108,6 @@ def fused_add_tanh_sigmoid_multiply(input_a, input_b, n_channels):
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return acts
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return acts
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def convert_pad_shape(pad_shape):
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l = pad_shape[::-1]
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pad_shape = [item for sublist in l for item in sublist]
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return pad_shape
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def shift_1d(x):
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def shift_1d(x):
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x = F.pad(x, convert_pad_shape([[0, 0], [0, 0], [1, 0]]))[:, :, :-1]
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x = F.pad(x, convert_pad_shape([[0, 0], [0, 0], [1, 0]]))[:, :, :-1]
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return x
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return x
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@ -121,7 +121,7 @@ def subsequent_mask(length):
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return mask
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return mask
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#@torch.jit.script
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# @torch.jit.script
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@torch.jit._script_if_tracing
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@torch.jit._script_if_tracing
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def fused_add_tanh_sigmoid_multiply(input_a, input_b, n_channels):
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def fused_add_tanh_sigmoid_multiply(input_a, input_b, n_channels):
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n_channels_int = n_channels[0]
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n_channels_int = n_channels[0]
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@ -1,6 +1,7 @@
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import json
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import json
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import os
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import os
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import shutil
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import shutil
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import threading
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import numpy as np
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import numpy as np
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from downloader.SampleDownloader import downloadSample, getSampleInfos
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from downloader.SampleDownloader import downloadSample, getSampleInfos
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from voice_changer.Local.ServerDevice import ServerDevice, ServerDeviceCallbacks
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from voice_changer.Local.ServerDevice import ServerDevice, ServerDeviceCallbacks
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@ -66,8 +67,8 @@ class VoiceChangerManager(ServerDeviceCallbacks):
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self.serverDevice = ServerDevice(self)
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self.serverDevice = ServerDevice(self)
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# thread = threading.Thread(target=self.serverDevice.start, args=())
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thread = threading.Thread(target=self.serverDevice.start, args=())
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# thread.start()
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thread.start()
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# 設定保存用情報
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# 設定保存用情報
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self.stored_setting: dict[str, str | int | float] = {}
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self.stored_setting: dict[str, str | int | float] = {}
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