I had problems when loading the weights of model. Here’s some parts of the model:
class InceptionV4(nn.Module):

   def __init__(self, num_classes=1001):
       super(InceptionV4, self).__init__()
       # Special attributs
       self.input_space = None
       self.input_size = (299, 299, 3)
       self.mean = None
       self.std = None
       # Modules
       self.features = nn.Sequential(
           BasicConv2d(3, 32, kernel_size=3, stride=2),
           BasicConv2d(32, 32, kernel_size=3, stride=1),
           BasicConv2d(32, 64, kernel_size=3, stride=1, padding=1),
           Mixed_3a(),
           Mixed_4a(),
           Mixed_5a(),
           ...
       )
       self.avg_pool = nn.AvgPool2d(8, count_include_pad=False)
       self.last_linear = nn.Linear(1536, num_classes)

I have tried to save the weights, something like torch.save(model.state_dict(), weight_name) and then reload again model.load_state_dict(torch.load(weight_name)) but got these errors:
Missing key(s) in state_dict: "features.0.conv.weight", "features.0.bn.weight", "features.0.bn.bias", "features.0.bn.running_mean", "features.0.bn.running_var", "features.1.conv.weight", "features.1.bn.weight", "features.1.bn.bias", "features.1.bn.running_mean", "features.1.bn.running_var", "features.2.conv.weight", "features.2.bn.weight

and also:
Unexpected key(s) in state_dict: "conv.0.conv1.0.weight", "conv.0.conv1.0.bias", "conv.0.conv1.2.weight", "conv.0.conv1.2.bias", "conv.0.conv1.2.running_mean", "conv.0.conv1.2.running_var", "conv.0.conv1.2.num_batches_tracked", "conv.0.conv2.0.weight", "conv.0.conv2.0.bias", "conv.0.conv2.2.weight", "conv.0.conv2.2.bias", "conv.0.conv2.2.running_mean", "conv.0.conv2.2.running_var", "conv.0.conv2.2.num_batches_tracked", "conv.1.conv1.0.weight", "conv.1.conv1.0.bias", "conv.1.conv1.2.weight", "conv.1.conv1.2.bias", "conv.1.conv1.2.running_mean", "conv.1.conv1.2.running_var", "conv.1.conv1.2.num_batches_tracked

Any hints on this? Thanks in advance.