In your case your first layer has 1 Conv2d, 1 ReLU, and 1 MaxPool2d
You can get the weights of your Conv2d of layer1 by doing
# Just a sample CustomConvNet
net = CustomConvNet(num_classes=10)
# Print the weights of Conv2d of layer1
print(net.layer1[0].weight.data)
# Print the bias of Conv2d of layer1
print(net.layer1[0].bias.data)

[0] because nn.Conv2d is the first in your nn.Sequential
So if you print(net.layer1) you will see
Sequential(
  (0): Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))
  (1): ReLU()
  (2): MaxPool2d(kernel_size=(2, 2), stride=(2, 2), padding=0, dilation=1, ceil_mode=False)
)