Data type for Spaces

[el3ment]

I think the various spaces objects should have a dtype property that specifies the correct type. This will make creating tensorflow placeholders and database-like structures that are memory efficient.

For example a Box(low=0, high=255, shape(255, 255, 3)) could have Box(low=0, high=255, shape(255, 255, 3), dtype=np.uint8) . This would allow someone to use env.observation_space.dtype in a meaningful way.

[tlbtlbtlb]

There is a dtype, at env.observation_space.lo.dtype. Unfortunately all the envs implicitly set it to np.float64 even if their observations are bytes.

In practice, all my agents end up converting bytes to floats before using them in tensorflow, at least because I want to multiply by 1.0/255.0 to get normalized values.

But it seems reasonable to have pixel-based envs set the dtype to np.uint8.

[hholst80]

A proper serialization format would be nice for all gym.spaces

[tlbtlbtlb]

@hholst80 Pickle should work for all spaces and points in the space.
Additionally, spaces have a .to_jsonable method if you want to exchange data with non-Python programs.

[hholst80]

@tlbtlbtlb .to_jsonable only works with samples from the space not for the actual space class itself.

But Pickle could be a good solution. Too bad its hard to use between C# and Python. If we could serialize it to a dict we could easily use json to serialize it over network / between applications.

[tlbtlbtlb]

To interchange data with other languages, consider the gym-http-api package. It has a JSON representation of spaces, as well as everything else.