changing the model to use resnet about pytorch-template HOT 1 CLOSED

import torch.nn as nn
import torch.nn.functional as F
from base import BaseModel
import torchvision.models as models

class MnistModel(BaseModel):
    def init(self, num_classes=10):
        super(MnistModel, self).init()
        models.resnet18()

    def forward(self, x):
        x = F.relu(F.max_pool2d(self.conv1(x), 2))
        x = F.relu(F.max_pool2d(self.conv2_drop(self.conv2(x)), 2))
        x = x.view(-1, 320)
        x = F.relu(self.fc1(x))
        x = F.dropout(x, training=self.training)
        x = self.fc2(x)
        return F.log_softmax(x, dim=1)

class Resnet18(BaseModel):
    def __init__(self, num_classes=10):
        super(Resnet18, self).__init__()
        self.resnet = models.resnet18()
        self.resnet.avgpool = nn.AdaptiveMaxPool2d(1)
        self.resnet.fc = nn.Linear(512, num_classes)

    def forward(self, x_input):
        output = self.resnet(x_input)
        return torch.sigmoid(output)