j
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b0f6b8583d
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fix a few typo bugs. Support info in return signature of environment step. Temporarily turn off flex attention when the kv_cache is used to avoid bug.
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2025-11-04 17:29:12 -05:00 |
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lucidrains
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c0a6cd56a1
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link to new discord
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2025-10-31 09:06:44 -07:00 |
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lucidrains
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d756d1bb8c
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addressing issues raised by an independent researcher with llm assistance
0.1.2
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2025-10-31 08:37:39 -07:00 |
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lucidrains
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60681fce1d
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fix generation so that one more step is taken to decode agent embeds off the final cleaned set of latents, update readme
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2025-10-31 06:48:49 -07:00 |
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Phil Wang
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6870294d95
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no longer needed
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2025-10-30 09:23:27 -07:00 |
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lucidrains
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3beae186da
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some more control over whether to normalize advantages
0.0.102
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2025-10-30 08:46:03 -07:00 |
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lucidrains
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0904e224ab
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make the reverse kl optional
0.0.101
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2025-10-30 08:22:50 -07:00 |
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lucidrains
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767789d0ca
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they decided on 0.3 for the behavioral prior loss weight
0.0.100
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2025-10-29 13:24:58 -07:00 |
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lucidrains
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35b87c4fa1
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oops
0.0.99
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2025-10-29 13:04:02 -07:00 |
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lucidrains
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c4a3cb09d5
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swap for discrete kl div, thanks to Dirk for pointing this out on the discord
0.0.98
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2025-10-29 11:54:18 -07:00 |
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lucidrains
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cb54121ace
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sim trainer needs to take care of agent embedding and old actions
0.0.96
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2025-10-29 11:15:11 -07:00 |
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lucidrains
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586379f2c8
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sum the kl div loss across number of actions by default for action embedder .kl_div
0.0.95
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2025-10-29 10:46:42 -07:00 |
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lucidrains
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a358a44a53
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always store old agent embeds and old action parameters when possible
0.0.94
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2025-10-29 10:39:15 -07:00 |
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lucidrains
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3547344312
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take care of storing the old action logits and mean log var, and calculate kl div for pmpo based off that during learn from experience
0.0.93
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2025-10-29 10:31:32 -07:00 |
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lucidrains
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691d9ca007
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add kl div on action embedder, working way towards the kl div loss in pmpo
0.0.92
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2025-10-29 10:02:25 -07:00 |
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lucidrains
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91d697f8ca
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fix pmpo
0.0.91
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2025-10-28 18:55:22 -07:00 |
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lucidrains
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7acaa764f6
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evolutionary policy optimization on dreams will be interesting
0.0.90
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2025-10-28 10:17:01 -07:00 |
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lucidrains
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c0450359f3
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allow for evolutionary policy optimization
0.0.89
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2025-10-28 10:11:13 -07:00 |
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lucidrains
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46f86cd247
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fix storing of agent embedding
0.0.88
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2025-10-28 09:36:58 -07:00 |
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lucidrains
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903c43b770
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use the agent embeds off the stored experience if available
0.0.87
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2025-10-28 09:14:02 -07:00 |
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lucidrains
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d476fa7b14
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able to store the agent embeddings during rollouts with imagination or environment, for efficient policy optimization (but will also allow for finetuning world model for the heads)
0.0.85
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2025-10-28 09:02:26 -07:00 |
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lucidrains
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789f091c63
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redo so that max timesteps is treated as truncation at the last timestep, then allow for accepting the truncation signal from the environment and reuse same logic
0.0.83
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2025-10-28 08:04:48 -07:00 |
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lucidrains
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41ab83f691
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fix mock
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2025-10-27 10:47:24 -07:00 |
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lucidrains
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995b1f64e5
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handle environments that return a terminate flag, also make sure episode lens are logged in vectorized env
0.0.82
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2025-10-27 10:14:28 -07:00 |
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lucidrains
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fd1e87983b
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quantile filter
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2025-10-27 09:08:26 -07:00 |
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lucidrains
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fe79bfa951
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optionally keep track of returns statistics and normalize with them before advantage
0.0.81
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2025-10-27 09:02:08 -07:00 |
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lucidrains
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f808b1c1d2
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oops
0.0.80
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2025-10-27 08:34:22 -07:00 |
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lucidrains
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349a03acd7
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redo so lens is always the episode length, including the bootstrap value timestep, and use is_truncated to mask out the bootstrap node from being learned on
0.0.79
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2025-10-27 08:06:21 -07:00 |
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lucidrains
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59c458aea3
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introduce an is_truncated field on Experience, and mask out rewards and values before calculating gae appropriately
0.0.78
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2025-10-27 07:55:00 -07:00 |
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lucidrains
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fbfd59e42f
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handle variable lengthed experiences when doing policy optimization
0.0.77
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2025-10-27 06:09:09 -07:00 |
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lucidrains
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46432aee9b
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fix an issue with bc
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2025-10-25 12:30:08 -07:00 |
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lucidrains
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f97d9adc97
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oops, forgot to add the view embedding for robotics
0.0.75
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2025-10-25 11:39:06 -07:00 |
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lucidrains
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32cf142b4d
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take another step for variable len experiences
0.0.74
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2025-10-25 11:31:41 -07:00 |
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lucidrains
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1ed6a15cb0
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fix tests
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2025-10-25 11:13:22 -07:00 |
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lucidrains
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4d8f5613cc
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start storing the experience lens
0.0.73
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2025-10-25 10:55:47 -07:00 |
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lucidrains
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3d5617d769
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take a step towards variable lengthed experiences during training
0.0.72
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2025-10-25 10:45:34 -07:00 |
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lucidrains
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77a40e8701
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validate that we can generate multiple video streams for robotics use-case
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2025-10-25 09:23:07 -07:00 |
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lucidrains
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4ce82f34df
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given the VAT paper, add multiple video streams (third person, wrist camera, etc), geared for robotics. need to manage an extra dimension for multiple viewpoints
0.0.71
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2025-10-25 09:20:55 -07:00 |
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lucidrains
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a9b728c611
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incorporate proprioception into the dynamics world model
0.0.70
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2025-10-24 11:24:22 -07:00 |
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lucidrains
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35c1db4c7d
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sketch of training from sim env
0.0.69
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2025-10-24 09:13:09 -07:00 |
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lucidrains
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27ac05efb0
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function for combining experiences
0.0.67
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2025-10-24 08:00:10 -07:00 |
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lucidrains
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d0ffc6bfed
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with or without signed advantage
0.0.66
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2025-10-23 16:24:29 -07:00 |
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lucidrains
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fb3e026fe0
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handle vectorized env
0.0.65
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2025-10-22 11:19:44 -07:00 |
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lucidrains
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7ecc5d03e8
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wire up the time kv cache when interacting with sim / env
0.0.62
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2025-10-22 08:39:11 -07:00 |
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lucidrains
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d82debb7a6
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first pass through gathering experience with a mock env for online rl
0.0.61
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2025-10-22 08:32:46 -07:00 |
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lucidrains
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03b16a48f2
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sketch out the dream trainer, seems like they only fine tune the heads
0.0.60
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2025-10-22 06:41:10 -07:00 |
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lucidrains
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6f1a7a24ed
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try to fix ci
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2025-10-21 11:47:39 -07:00 |
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lucidrains
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e316499047
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naming
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2025-10-21 10:57:55 -07:00 |
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lucidrains
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40da985c6b
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tweak bc trainer
0.0.59
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2025-10-21 10:55:24 -07:00 |
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lucidrains
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2fc3b17149
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take a gradient step with behavioral clone trainer, make sure it works with and without actions and rewards
0.0.57
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2025-10-21 10:20:08 -07:00 |
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