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| from tensorboardX import SummaryWriter | |
| from .plotting import plot_waveform_to_numpy | |
| class MyWriter(SummaryWriter): | |
| def __init__(self, hp, logdir): | |
| super(MyWriter, self).__init__(logdir) | |
| self.sample_rate = hp.audio.sampling_rate | |
| self.is_first = True | |
| def log_training(self, g_loss, d_loss, step): | |
| self.add_scalar('train.g_loss', g_loss, step) | |
| self.add_scalar('train.d_loss', d_loss, step) | |
| def log_validation(self, g_loss, d_loss, generator, discriminator, target, prediction, step): | |
| self.add_scalar('validation.g_loss', g_loss, step) | |
| self.add_scalar('validation.d_loss', d_loss, step) | |
| self.add_audio('raw_audio_predicted', prediction, step, self.sample_rate) | |
| self.add_image('waveform_predicted', plot_waveform_to_numpy(prediction), step) | |
| self.log_histogram(generator, step) | |
| self.log_histogram(discriminator, step) | |
| if self.is_first: | |
| self.add_audio('raw_audio_target', target, step, self.sample_rate) | |
| self.add_image('waveform_target', plot_waveform_to_numpy(target), step) | |
| self.is_first = False | |
| def log_histogram(self, model, step): | |
| for tag, value in model.named_parameters(): | |
| self.add_histogram(tag.replace('.', '/'), value.cpu().detach().numpy(), step) | |