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sherpa-pyannote-segmentation-3-0

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• "__torch__.torch.nn.modules.container.ModuleList",
• "__torch__.torch.nn.modules.rnn.LSTM",
• "torch.jit._pickle.restore_type_tag",
• "__torch__.torch.nn.modules.instancenorm.___torch_mangle_3.InstanceNorm1d",
• "__torch__.torch.nn.modules.linear.___torch_mangle_5.Linear",
• "__torch__.torch.nn.modules.linear.Linear",
• "__torch__.torch.nn.modules.container.___torch_mangle_6.ModuleList",
• "__torch__.torch.nn.modules.instancenorm.InstanceNorm1d",
• "torch.FloatStorage",
• "__torch__.torch.nn.modules.pooling.MaxPool1d",
• "__torch__.torch.nn.modules.container.___torch_mangle_4.ModuleList",
• "__torch__.torch.nn.modules.conv.___torch_mangle_0.Conv1d",
• "__torch__.asteroid_filterbanks.param_sinc_fb.ParamSincFB",
• "torch.jit._pickle.build_intlist",
• "torch._utils._rebuild_tensor_v2",
• "__torch__.pyannote.audio.models.blocks.sincnet.SincNet",
• "__torch__.asteroid_filterbanks.enc_dec.Encoder",
• "__torch__.torch.nn.modules.instancenorm.___torch_mangle_2.InstanceNorm1d",
• "collections.OrderedDict",
• "__torch__.torch.nn.modules.container.___torch_mangle_1.ModuleList",
• "__torch__.torch.nn.modules.activation.LogSoftmax",
• "torch.jit._pickle.build_tensorlist",
• "__torch__.torch.nn.modules.linear.___torch_mangle_7.Linear",
• "__torch__.torch.nn.modules.conv.Conv1d",
• "__torch__.PyanNet"

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