• I have marked all applicable categories:
  • exception-raising bug
  • RL algorithm bug
  • documentation request (i.e. "X is missing from the documentation.")
  • new feature request
• I have visited the source website
• I have searched through the issue tracker for duplicates
• I have mentioned version numbers, operating system and environment, where applicable:

  import tianshou, torch, sys
  print(tianshou.__version__, torch.__version__, sys.version, sys.platform)
  0.2.5 1.6.0 3.7.7
  [GCC 7.3.0] linux

The collector raised the memory error when I training under the self-defined environment with PPO algorithm. The full error message is as below:
MemoryError: Unable to allocate 8.05 GiB for an array with shape (20000, 54006) and data type float64
The self-defined environment uses List state observation and List discrete action. Is there any necessary to change the observation type to dict to fit tianshou and use a smaller buffer size?
I tried to change the sample size of on-policy but it will raise the dimension matching problem(of course). Any answer is welcome for the stupid problem.