sagemaker-voice-classification/notebook/train.py [34:41]:
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        data_resampled, target_resampled = ros.fit_resample(np.squeeze(data), target)
        data = torch.from_numpy(data_resampled)
        data = data.unsqueeze_(-2)
        target = torch.tensor(target_resampled)
        
        data, target = data.to(device), target.to(device)
        output = model(data)
        output = output.permute(1, 0, 2)[0]  # original output dimensions are batchSizex1x10
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sagemaker-voice-classification/notebook/train.py [66:73]:
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            data_resampled, target_resampled = ros.fit_resample(np.squeeze(data), target)
            data = torch.from_numpy(data_resampled)
            data = data.unsqueeze_(-2)
            target = torch.tensor(target_resampled)

            data, target = data.to(device), target.to(device)
            output = model(data)
            output = output.permute(1, 0, 2)[0]
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