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best_checkpoint.pt: PyTorch checkpoint (1047.9 MB)1import torch
2from aesop.models.policy import AesopPolicy
3
4# Load checkpoint
5checkpoint = torch.load("warm_up_best.pt", map_location="cpu")
6model = AesopPolicy()
7model.load_state_dict(checkpoint['model_state_dict'])1{
2 "stage": "warm_up",
3 "keys": [
4 "epoch",
5 "global_step",
6 "best_val_acc",
7 "model_state_dict",
8 "tactic_pool",
9 "wandb_run_id",
10 "random_seed",
11 "random_state",
12 "numpy_random_state",
13 "torch_rng_state",
14 "global_moving_avg",
15 "global_moving_std",
16 "optimizer_0_state_dict",
17 "optimizer_1_state_dict",
18 "optimizer_2_state_dict",
19 "cuda_rng_state",
20 "scaler_state_dict",
21 "trainer_state_dict",
22 "metrics"
23 ],
24 "epoch": 10,
25 "best_val_acc": 0.3319672131147541,
26 "model_architecture": {
27 "is_valid": true,
28 "components": [
29 {
30 "name": "lemma_heads",
31 "found_keys": 2,
32 "total_expected": 2
33 },
34 {
35 "name": "config_heads",
36 "found_keys": 2,
37 "total_expected": 2
38 },
39 {
40 "name": "base_encoder",
41 "found_keys": 208,
42 "total_expected": "variable"
43 }
44 ],
45 "warnings": [
46 "Component 'shared_mlp' not found in state_dict",
47 "Component 'tactic_heads' not found in state_dict"
48 ],
49 "errors": []
50 },
51 "file_size_mb": 1047.9129619598389,
52 "files_description": "- `best_checkpoint.pt`: PyTorch checkpoint (1047.9 MB)"
53}