understanding_pytorch___10___state_dict_model_fc.py

for key in model.fc.state_dict():
    print('key: ', key)
    param = model.fc.state_dict()[key]
    print('param.shape: ', param.shape)
    print('param.requires_grad: ', param.requires_grad)
    print('param.shape, param.requires_grad: ', param.shape, param.requires_grad)
    print('isinstance(param, nn.Module) ', isinstance(param, nn.Module))
    print('isinstance(param, nn.Parameter) ', isinstance(param, nn.Parameter))
    print('isinstance(param, torch.Tensor): ', isinstance(param, torch.Tensor))
    print('=====')

understanding_pytorch___10___state_dict_model_fc_output.py

key:  weight
param.shape:  torch.Size([128, 295936])
param.requires_grad:  False
param.shape, param.requires_grad:  torch.Size([128, 295936]) False
isinstance(param, nn.Module)  False
isinstance(param, nn.Parameter)  False
isinstance(param, torch.Tensor):  True
=====
key:  bias
param.shape:  torch.Size([128])
param.requires_grad:  False
param.shape, param.requires_grad:  torch.Size([128]) False
isinstance(param, nn.Module)  False
isinstance(param, nn.Parameter)  False
isinstance(param, torch.Tensor):  True
=====