Issues of observation_space and action_space of costumed environment

[hrjtju]

Python version: 3.10.14
joyrl version: 0.6.5.1
Pytorch version: torch 2.2.1+cu121
torchaudio 2.2.1+cu121
torchvision 0.17.1+cu121

I intend to define observation space as follows:
[Image_of_one_channel, 1d-vector, 1d-vector]
And output space as follows:
[1d-vector]

For the observation spaces, I defined it as follows:

self.observation_space = spaces.Tuple(spaces=[
    spaces.Box(low=0, high=float("inf"), shape=(1, N, N)),
    spaces.Box(low=0, high=float("inf"), shape=(A,)),
    spaces.Box(low=0, high=float("inf"), shape=(B, ))
])
self.action_space = spaces.Box(low=0, high=float("inf"), shape=(B, 1))

in which capitalized letters represent numbers. But I notice that functions for spaces.Tuple is not yet implemented, as shown below:

# run.py, class Launcher
...
    def _check_obs_action_space_info(self, env):
        obs_space = env.observation_space
        if isinstance(obs_space, Box):
            if len(obs_space.shape) == 3:
                state_type_list = [ObsType.IMAGE]
                state_size_list = [[obs_space.shape[0], obs_space.shape[1], obs_space.shape[2]]]
            else:
                state_type_list = [ObsType.VECTOR]
                state_size_list = [[obs_space.shape[0]]]
        elif isinstance(obs_space, Discrete):
            state_type_list = [ObsType.VECTOR]
            state_size_list = [[obs_space.n]]
        else:
            raise ValueError('obs_space type error')
...

The second problem arises when I try to assign action space to continuous vector in $\mathbf{R}^k$ but I didn't save the error log. In general, the action layers is parsed to have the last layer with output shape 0, and raise the error. When I tried to modify the source code to force it not be 0, other errors ocurrs.

Finally, the corresponding network architecture field in the .yaml file is

algo_cfg:
  branch_layers:
    - name: view
      layers:
      - layer_type: conv2d
        in_channel: 1
        out_channel: 16 
        kernel_size: 4
        stride: 2
        activation: relu
      - layer_type: pooling
        pooling_type: max2d
        kernel_size: 2
        stride: 2
        padding: 0
      - layer_type: flatten
      - layer_type: norm
        norm_type: LayerNorm
        normalized_shape: 512
      - layer_type: linear
        layer_size: [128]
        activation: relu
    - name: lwh
      layers:
      - layer_type: linear
        layer_size: [32]
        activation: relu
      - layer_type: linear
        layer_size: [32]
        activation: relu
    - name: parts
      layers:
      - layer_type: linear
        layer_size: [256]
        activation: relu
      - layer_type: linear
        layer_size: [256]
        activation: relu
  merge_layers:
    - layer_type: linear
      layer_size: [256]
      activation: relu
    - layer_type: linear
      layer_size: [256]
      activation: relu
...