#!/usr/bin/env python
# -*- coding: utf-8 -*-
# @Time : 2021/10/5 20:47
# @Author : SuenDanny
# @Site : 
# @File : nn_loss.py
# @Software: PyCharm
import torch
from torch.nn import L1Loss, MSELoss
from torch import nn

inputs = torch.tensor([1, 2, 3], dtype=torch.float32)
targets = torch.tensor([1, 2, 5], dtype=torch.float32)

inputs = torch.reshape(inputs, (1, 1, 1, 3),)
targets = torch.reshape(targets, (1, 1, 1, 3))

loss = L1Loss(reduction='sum')
result = loss(inputs, targets)
print(result)


loss_mse = nn.MSELoss()
result_mse = loss_mse(inputs, targets)
print(result_mse)



x = torch.tensor([0.1, 0.2, 0.3])
y = torch.tensor([1])
x = torch.reshape(x, (1, 3))


loss_cross = nn.CrossEntropyLoss()
result_cross = loss_cross(x, y)
print(result_cross)


