PyTorch中非线性激活函数

非线性激活

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import torch
import torchvision
from torch import nn
from torch.nn import ReLU, Sigmoid
from torch.utils.data import DataLoader
from torch.utils.tensorboard import SummaryWriter

input = torch.tensor([[1, -0.5],
                      [-1, 3]])

input = torch.reshape(input, (-1, 1, 2, 2))
print(input.shape)

dataset = torchvision.datasets.CIFAR10(root = "../dataset", train = False,transform = torchvision.transforms.ToTensor(), download = True)
dataloader = DataLoader(dataset, batch_size = 64)


class Model(nn.Module):
    def __init__(self):
        super(Model, self).__init__()
        self.rulu1 = ReLU()
        self.sigmoid1 = Sigmoid()

    def forward(self, input):
        output = self.sigmoid1(input)
        return output


model = Model()

writer = SummaryWriter("logs_rule")
step = 0
for data in dataloader:
    imgs, targets = data
    writer.add_images("input", imgs, global_step = step)
    output = model(imgs)
    writer.add_images("output", output, step)
    step += 1

writer.close()

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