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43a95f4 8875bd7 43a95f4 301be88 43a95f4 301be88 43a95f4 301be88 8875bd7 301be88 43a95f4 301be88 43a95f4 301be88 43a95f4 301be88 43a95f4 301be88 43a95f4 301be88 43a95f4 8875bd7 301be88 43a95f4 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 | # spatial-memory-checkpoints
DD-PPO PointNav checkpoints (Habitat, GPS-PointGoal task), full training
trajectory from initialisation to convergence.
| folder | # checkpoints | frames per checkpoint |
| -------------------- | ------------- | --------------------- |
| `blind/` | 35 (`0..34`) | 10.06 M |
| `coarse/` | 50 (`0..49`) | 5.0 M |
| `foveated/` | 50 (`0..49`) | 5.0 M |
| `foveated_logpolar/` | 50 (`0..49`) | 5.0 M |
| `uniform/` | 50 (`0..49`) | 5.0 M |
`frames per ckpt` differs across folders, so to align at the same training
step, convert ckpt index to absolute frame count (`blind/ckpt.20.pth` ≈
`coarse/ckpt.40.pth` ≈ 200 M frames).
## Load a checkpoint
```python
import torch
from huggingface_hub import hf_hub_download
ckpt_path = hf_hub_download(
repo_id="alunxu/spatial-memory-checkpoints",
filename="foveated/ckpt.49.pth",
)
ckpt = torch.load(ckpt_path, map_location="cpu", weights_only=False)
state_dict = ckpt["state_dict"]
config = ckpt["config"]
```
Each `.pth` is a habitat-baselines checkpoint with keys `state_dict`,
`config`, and `extra_state`.
## Rebuild the policy and run rollouts
```python
from habitat_baselines.common.baseline_registry import baseline_registry
# Build env from ckpt's config (env_config = config.habitat).
policy_cls = baseline_registry.get_policy(
config.habitat_baselines.rl.policy.name)
policy = policy_cls.from_config(
config=config,
observation_space=env.observation_space,
action_space=env.action_space,
)
policy.load_state_dict(state_dict)
policy.eval()
# policy.act(...) returns (action, recurrent_hidden_states) where
# recurrent_hidden_states has shape (num_envs, num_layers, hidden_dim).
# Pass it back at the next step to keep the recurrent state.
```
Code: <https://github.com/alunxu/foveated-cog-map>.
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