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diffusion_pusht

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osanseviero alexandersoare commited on
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·
verified ·
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Duplicate from lerobot/diffusion_pusht

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Co-authored-by: Alexander Soare <[email protected]>

Files changed (11) hide show
  1. .gitattributes +35 -0
  2. README.md +61 -0
  3. config.json +53 -0
  4. config.yaml +141 -0
  5. demo.gif +0 -0
  6. eval_avg_max_reward.csv +21 -0
  7. eval_info.json +3523 -0
  8. eval_pc_success.csv +21 -0
  9. model.safetensors +3 -0
  10. train_loss.csv +801 -0
  11. training_curves.png +0 -0
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1
+ ---
2
+ license: apache-2.0
3
+ datasets:
4
+ - lerobot/pusht
5
+ pipeline_tag: robotics
6
+ ---
7
+ # Model Card for Diffusion Policy / PushT
8
+
9
+ Diffusion Policy (as per [Diffusion Policy: Visuomotor Policy
10
+ Learning via Action Diffusion](https://arxiv.org/abs/2303.04137)) trained for the `PushT` environment from [gym-pusht](https://github.com/huggingface/gym-pusht).
11
+
12
+ ![demo](demo.gif)
13
+
14
+ ## How to Get Started with the Model
15
+
16
+ See the [LeRobot library](https://github.com/huggingface/lerobot) (particularly the [evaluation script](https://github.com/huggingface/lerobot/blob/main/lerobot/scripts/eval.py)) for instructions on how to load and evaluate this model.
17
+
18
+ ## Training Details
19
+
20
+ The model was trained using [LeRobot's training script](https://github.com/huggingface/lerobot/blob/d747195c5733c4f68d4bfbe62632d6fc1b605712/lerobot/scripts/train.py) and with the [pusht](https://huggingface.co/datasets/lerobot/pusht/tree/v1.3) dataset, using this command:
21
+
22
+ ```bash
23
+ python lerobot/scripts/train.py \
24
+ hydra.run.dir=outputs/train/diffusion_pusht \
25
+ hydra.job.name=diffusion_pusht \
26
+ policy=diffusion training.save_model=true \
27
+ env=pusht \
28
+ env.task=PushT-v0 \
29
+ dataset_repo_id=lerobot/pusht \
30
+ training.offline_steps=200000 \
31
+ training.save_freq=20000 \
32
+ training.eval_freq=10000 \
33
+ eval.n_episodes=50 \
34
+ wandb.enable=true \
35
+ wandb.disable_artifact=true \
36
+ device=cuda
37
+ ```
38
+
39
+
40
+ The training curves may be found at https://wandb.ai/alexander-soare/Alexander-LeRobot/runs/508luayd.
41
+
42
+ This took about 7 hours to train on an Nvida RTX 3090.
43
+
44
+ _Note: At the time of training, [this PR](https://github.com/huggingface/lerobot/pull/129) was also incorporated._
45
+
46
+ ## Evaluation
47
+
48
+ The model was evaluated on the `PushT` environment from [gym-pusht](https://github.com/huggingface/gym-pusht) and compared to a similar model trained with the original [Diffusion Policy code](https://github.com/real-stanford/diffusion_policy). There are two evaluation metrics on a per-episode basis:
49
+
50
+ - Maximum overlap with target (seen as `eval/avg_max_reward` in the charts above). This ranges in [0, 1].
51
+ - Success: whether or not the maximum overlap is at least 95%.
52
+
53
+ Here are the metrics for 500 episodes worth of evaluation. For the succes rate we add an extra row with confidence bounds. This assumes a uniform prior over success probability and computes the beta posterior, then calculates the mean and lower/upper confidence bounds (with a 68.2% confidence interval centered on the mean). The "Theirs" column is for an equivalent model trained on the original Diffusion Policy repository and evaluated on LeRobot (the model weights may be found in the [`original_dp_repo`](https://huggingface.co/lerobot/diffusion_pusht/tree/original_dp_repo) branch of this respository).
54
+
55
+ <blank>|Ours|Theirs
56
+ -|-|-
57
+ Average max. overlap ratio | 0.959 | 0.957
58
+ Success rate for 500 episodes (%) | 63.8 | 64.2
59
+ Beta distribution lower/mean/upper (%) | 61.6 / 63.7 / 65.9 | 62.0 / 64.1 / 66.3
60
+
61
+ The results of each of the individual rollouts may be found in [eval_info.json](eval_info.json).
config.json ADDED
@@ -0,0 +1,53 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "n_obs_steps": 2,
3
+ "horizon": 16,
4
+ "n_action_steps": 8,
5
+ "input_shapes": {
6
+ "observation.image": [
7
+ 3,
8
+ 96,
9
+ 96
10
+ ],
11
+ "observation.state": [
12
+ 2
13
+ ]
14
+ },
15
+ "output_shapes": {
16
+ "action": [
17
+ 2
18
+ ]
19
+ },
20
+ "input_normalization_modes": {
21
+ "observation.image": "mean_std",
22
+ "observation.state": "min_max"
23
+ },
24
+ "output_normalization_modes": {
25
+ "action": "min_max"
26
+ },
27
+ "vision_backbone": "resnet18",
28
+ "crop_shape": [
29
+ 84,
30
+ 84
31
+ ],
32
+ "crop_is_random": true,
33
+ "pretrained_backbone_weights": null,
34
+ "use_group_norm": true,
35
+ "spatial_softmax_num_keypoints": 32,
36
+ "down_dims": [
37
+ 512,
38
+ 1024,
39
+ 2048
40
+ ],
41
+ "kernel_size": 5,
42
+ "n_groups": 8,
43
+ "diffusion_step_embed_dim": 128,
44
+ "use_film_scale_modulation": true,
45
+ "num_train_timesteps": 100,
46
+ "beta_schedule": "squaredcos_cap_v2",
47
+ "beta_start": 0.0001,
48
+ "beta_end": 0.02,
49
+ "prediction_type": "epsilon",
50
+ "clip_sample": true,
51
+ "clip_sample_range": 1.0,
52
+ "num_inference_steps": 100
53
+ }
config.yaml ADDED
@@ -0,0 +1,141 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ device: cuda
2
+ use_amp: false
3
+ seed: 100000
4
+ dataset_repo_id: lerobot/pusht
5
+ training:
6
+ offline_steps: 200000
7
+ online_steps: 0
8
+ online_steps_between_rollouts: 1
9
+ online_sampling_ratio: 0.5
10
+ online_env_seed: ???
11
+ eval_freq: 10000
12
+ save_freq: 20000
13
+ log_freq: 250
14
+ save_model: true
15
+ batch_size: 64
16
+ grad_clip_norm: 10
17
+ lr: 0.0001
18
+ lr_scheduler: cosine
19
+ lr_warmup_steps: 500
20
+ adam_betas:
21
+ - 0.95
22
+ - 0.999
23
+ adam_eps: 1.0e-08
24
+ adam_weight_decay: 1.0e-06
25
+ delta_timestamps:
26
+ observation.image:
27
+ - -0.1
28
+ - 0.0
29
+ observation.state:
30
+ - -0.1
31
+ - 0.0
32
+ action:
33
+ - -0.1
34
+ - 0.0
35
+ - 0.1
36
+ - 0.2
37
+ - 0.3
38
+ - 0.4
39
+ - 0.5
40
+ - 0.6
41
+ - 0.7
42
+ - 0.8
43
+ - 0.9
44
+ - 1.0
45
+ - 1.1
46
+ - 1.2
47
+ - 1.3
48
+ - 1.4
49
+ n_end_keyframes_dropped: ${policy.horizon} - ${policy.n_action_steps} - ${policy.n_obs_steps}
50
+ + 1
51
+ eval:
52
+ n_episodes: 50
53
+ batch_size: 50
54
+ use_async_envs: false
55
+ wandb:
56
+ enable: true
57
+ disable_artifact: true
58
+ project: lerobot
59
+ notes: ''
60
+ fps: 10
61
+ env:
62
+ name: pusht
63
+ task: PushT-v0
64
+ image_size: 96
65
+ state_dim: 2
66
+ action_dim: 2
67
+ fps: ${fps}
68
+ episode_length: 300
69
+ gym:
70
+ obs_type: pixels_agent_pos
71
+ render_mode: rgb_array
72
+ visualization_width: 384
73
+ visualization_height: 384
74
+ override_dataset_stats:
75
+ observation.image:
76
+ mean:
77
+ - - - 0.5
78
+ - - - 0.5
79
+ - - - 0.5
80
+ std:
81
+ - - - 0.5
82
+ - - - 0.5
83
+ - - - 0.5
84
+ observation.state:
85
+ min:
86
+ - 13.456424
87
+ - 32.938293
88
+ max:
89
+ - 496.14618
90
+ - 510.9579
91
+ action:
92
+ min:
93
+ - 12.0
94
+ - 25.0
95
+ max:
96
+ - 511.0
97
+ - 511.0
98
+ policy:
99
+ name: diffusion
100
+ n_obs_steps: 2
101
+ horizon: 16
102
+ n_action_steps: 8
103
+ input_shapes:
104
+ observation.image:
105
+ - 3
106
+ - 96
107
+ - 96
108
+ observation.state:
109
+ - ${env.state_dim}
110
+ output_shapes:
111
+ action:
112
+ - ${env.action_dim}
113
+ input_normalization_modes:
114
+ observation.image: mean_std
115
+ observation.state: min_max
116
+ output_normalization_modes:
117
+ action: min_max
118
+ vision_backbone: resnet18
119
+ crop_shape:
120
+ - 84
121
+ - 84
122
+ crop_is_random: true
123
+ pretrained_backbone_weights: null
124
+ use_group_norm: true
125
+ spatial_softmax_num_keypoints: 32
126
+ down_dims:
127
+ - 512
128
+ - 1024
129
+ - 2048
130
+ kernel_size: 5
131
+ n_groups: 8
132
+ diffusion_step_embed_dim: 128
133
+ use_film_scale_modulation: true
134
+ num_train_timesteps: 100
135
+ beta_schedule: squaredcos_cap_v2
136
+ beta_start: 0.0001
137
+ beta_end: 0.02
138
+ prediction_type: epsilon
139
+ clip_sample: true
140
+ clip_sample_range: 1.0
141
+ num_inference_steps: 100
demo.gif ADDED
eval_avg_max_reward.csv ADDED
@@ -0,0 +1,21 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ Step,diffusion_pusht_final - eval/avg_max_reward
2
+ 10000,0.727783498535056
3
+ 20000,0.926793976568431
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+ 30000,0.928166216058858
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+ 40000,0.958328167172369
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+ 50000,0.943188394510958
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+ 60000,0.937613393970094
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+ 70000,0.964618642115711
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+ 80000,0.978192933234
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+ 90000,0.953355139113338
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+ 100000,0.950833988995675
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+ 110000,0.982668314916378
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+ 120000,0.939619379505442
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+ 130000,0.959122695767039
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+ 140000,0.968145088219487
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+ 150000,0.959675288643079
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+ 160000,0.988640977099844
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+ 170000,0.943671615378961
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+ 180000,0.965194043468211
20
+ 190000,0.963914309028651
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+ 200000,0.959864101861565
eval_info.json ADDED
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