45 lines
1.7 KiB
Python
45 lines
1.7 KiB
Python
from torch import nn
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from trainer.losses import ConfigurableLoss
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class Tacotron2Loss(ConfigurableLoss):
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def __init__(self, opt_loss, env):
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super().__init__(opt_loss, env)
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self.mel_target_key = opt_loss['mel_target_key']
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self.mel_output_key = opt_loss['mel_output_key']
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self.mel_output_postnet_key = opt_loss['mel_output_postnet_key']
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self.gate_target_key = opt_loss['gate_target_key']
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self.gate_output_key = opt_loss['gate_output_key']
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def forward(self, _, state):
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mel_target, gate_target = state[self.mel_target_key], state[self.gate_target_key]
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mel_target.requires_grad = False
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gate_target.requires_grad = False
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gate_target = gate_target.view(-1, 1)
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mel_out, mel_out_postnet, gate_out = state[self.mel_output_key], state[self.mel_output_postnet_key], state[self.gate_output_key]
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gate_out = gate_out.view(-1, 1)
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mel_loss = nn.MSELoss()(mel_out, mel_target) + \
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nn.MSELoss()(mel_out_postnet, mel_target)
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gate_loss = nn.BCEWithLogitsLoss()(gate_out, gate_target)
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return mel_loss + gate_loss
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class Tacotron2LossRaw(nn.Module):
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def __init__(self):
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super().__init__()
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def forward(self, model_output, targets):
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mel_target, gate_target = targets[0], targets[1]
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mel_target.requires_grad = False
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gate_target.requires_grad = False
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gate_target = gate_target.view(-1, 1)
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mel_out, mel_out_postnet, gate_out, _ = model_output
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gate_out = gate_out.view(-1, 1)
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mel_loss = nn.MSELoss()(mel_out, mel_target) + \
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nn.MSELoss()(mel_out_postnet, mel_target)
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gate_loss = nn.BCEWithLogitsLoss()(gate_out, gate_target)
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return mel_loss + gate_loss
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