Multi_Forecasting/src/loss_functions.py at main · MatZar01/Multi_Forecasting · GitHub

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import torch
from torchmetrics import MeanSquaredLogError


class RMSELoss(torch.nn.Module):
    def __init__(self):
        super().__init__()
        self.mse = torch.nn.MSELoss()

    def forward(self, yhat, y):
        return torch.sqrt(self.mse(yhat, y))


class MSE(torch.nn.Module):
    def __init__(self):
        super().__init__()
        self.loss = torch.nn.MSELoss()

    def forward(self, yhat, y):
        return self.loss(yhat, y)


class MSLE(torch.nn.Module):
    def __init__(self):
        super().__init__()
        self.loss = MeanSquaredLogError()

    def forward(self, yhat, y):
        return self.loss(yhat, y)


class RMSLE(torch.nn.Module):
    def __init__(self):
        super().__init__()
        self.msle = MeanSquaredLogError()

    def forward(self, yhat, y):
        return torch.sqrt(self.msle(yhat, y))