Repository: pytorch
Issue: Models saved in C++ LibTorch with torch::save, cannot be loaded in python using torch.load
Labels: module: cpp,module: serialization,triaged

## 🐛 Bug

Models saved in C++ LibTorch with torch::save, cannot be loaded in python using torch.load. When I save a custom model (a class which inherits from torch::nn::Module) using torch::save(model, filepath), the result is a zip archive (.pt). The archive has the same structure as [it should](https://github.com/pytorch/pytorch/blob/master/torch/csrc/jit/docs/serialization.md) but python comes up with the error 

## To Reproduce

Steps to reproduce the behavior:

1. Save a class which inherits from the torch::nn::Module class in C++ using torch::save
2. Try to load that saved archive in python using torch.load
3. Find this error below: 

`Traceback (most recent call last):
  File "torch_plotting.py", line 59, in <module>
    policy_model, value_model = load_models(containing_path, model_number)
  File "torch_plotting.py", line 37, in load_models
    policy_model = torch.load(policy_file)
  File "/home/jamie/anaconda3/envs/tensorflow/lib/python3.7/site-packages/torch/serialization.py", line 528, in load
    return _load(opened_zipfile, map_location, pickle_module, **pickle_load_args)
  File "/home/jamie/anaconda3/envs/tensorflow/lib/python3.7/site-packages/torch/serialization.py", line 782, in _load
    result = unpickler.load()
ModuleNotFoundError: No module named '__torch__'`

## Expected behavior

Expect to have a fully loaded model that behaves the same way as the c++ one which I can use to perform inference.

## Environment

PyTorch version: 1.4.0
Is debug build: No
CUDA used to build PyTorch: 10.1

OS: Ubuntu 19.10
GCC version: (Ubuntu 9.2.1-9ubuntu2) 9.2.1 20191008
CMake version: version 3.16.4

Python version: 3.7
Is CUDA available: Yes
CUDA runtime version: Could not collect
GPU models and configuration: GPU 0: GeForce GTX 1050 Ti
Nvidia driver version: 440.33.01
cuDNN version: Probably one of the following:
/usr/lib/x86_64-linux-gnu/libcudnn.so.7.6.5
/usr/local/cuda-10.2/targets/x86_64-linux/lib/libcudnn.so.7.6.5

Versions of relevant libraries:
[pip3] numpy==1.17.2
[pip3] numpydoc==0.9.1
[pip3] torch==1.4.0
[pip3] torchvision==0.5.0
[conda] blas                      1.0                         mkl  
[conda] mkl                       2019.4                      243  
[conda] mkl-service               2.3.0            py37he904b0f_0  
[conda] mkl_fft                   1.0.14           py37ha843d7b_0  
[conda] mkl_random                1.1.0            py37hd6b4f25_0  
[conda] torch                     1.4.0                    pypi_0    pypi
[conda] torchvision               0.5.0                    pypi_0    pypi

## Additional context

I am using the libtorch provided by [this link](https://download.pytorch.org/libtorch/cpu/libtorch-shared-with-deps-1.4.0%2Bcpu.zip) and using cmake to build my project. The file to open is 
[policy_9999.zip](https://github.com/pytorch/pytorch/files/4255490/policy_9999.zip) (renamed to policy_9999.zip instead of the original policy_9999.pt so it could be uploaded.)




cc @yf225 @glaringlee @SsnL