Error code:   JWTInvalidSignature
Exception:    InvalidSignatureError
Message:      Signature verification failed
Traceback:    Traceback (most recent call last):
                File "/src/libs/libapi/src/libapi/jwt_token.py", line 286, in validate_jwt
                  decoded = jwt.decode(
                      jwt=token,
                  ...<2 lines>...
                      options=options,
                  )
                File "/usr/local/lib/python3.14/site-packages/jwt/api_jwt.py", line 368, in decode
                  decoded = self.decode_complete(
                      jwt,
                  ...<8 lines>...
                      leeway=leeway,
                  )
                File "/usr/local/lib/python3.14/site-packages/jwt/api_jwt.py", line 265, in decode_complete
                  decoded = self._jws.decode_complete(
                      jwt,
                  ...<3 lines>...
                      detached_payload=detached_payload,
                  )
                File "/usr/local/lib/python3.14/site-packages/jwt/api_jws.py", line 270, in decode_complete
                  self._verify_signature(
                  ~~~~~~~~~~~~~~~~~~~~~~^
                      signing_input,
                      ^^^^^^^^^^^^^^
                  ...<4 lines>...
                      options=merged_options,
                      ^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/usr/local/lib/python3.14/site-packages/jwt/api_jws.py", line 417, in _verify_signature
                  raise InvalidSignatureError("Signature verification failed")
              jwt.exceptions.InvalidSignatureError: Signature verification failed

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VisGym Pacman2D Deterministic Trajectories

This dataset contains behavior-cloning trajectories for the custom VisGym Pacman2D environment.

Each row is one successful oracle episode. The history entries include image_prev, image, and image_next; no synthetic thinking traces are stored. Images are JPEG base64 strings rendered from the greyblue9/pacman-python visual assets used by the environment.

Environment summary:

Grid size is constrained to 7x7 through 12x12.
Easy uses the 9x9 setting; hard uses the 11x11 setting.
Entities are Pacman, sparse food, walls, and exactly one deterministic ghost.
The ghost chases Pacman by BFS distance with fixed tie-break order up, down, left, right.
The movement action space is four directions; VisGym records can also end with ('stop', 'stop').

Splits:

data/pacman_2d_easy_v0/train/*.jsonl.gz
data/pacman_2d_easy_v0/test/*.jsonl.gz
data/pacman_2d_hard_v0/train/*.jsonl.gz
data/pacman_2d_hard_v0/test/*.jsonl.gz

Train/test initial states are checked to be disjoint by init_state_hash; see metadata/init_state_hash_audit.json.

Target Hub repo: https://huggingface.co/datasets/novastar111/pacman_v0

Downloads last month: 14

Total file size:

70.7 GB