Add files using upload-large-folder tool

halfcheetah_medium_expert_sparse/diffusion_42/scheduler/scheduler_config.json

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+{
+  "_class_name": "DDIMScheduler",
+  "_diffusers_version": "0.36.0",
+  "beta_end": 0.02,
+  "beta_schedule": "linear",
+  "beta_start": 0.0001,
+  "clip_sample": true,
+  "clip_sample_range": 1.0,
+  "dynamic_thresholding_ratio": 0.995,
+  "num_train_timesteps": 50000,
+  "prediction_type": "epsilon",
+  "rescale_betas_zero_snr": false,
+  "sample_max_value": 1.0,
+  "set_alpha_to_one": true,
+  "steps_offset": 0,
+  "thresholding": false,
+  "timestep_spacing": "leading",
+  "trained_betas": null
+}

halfcheetah_medium_expert_sparse/diffusion_42/used_config.yaml

@@ -0,0 +1,21 @@
+npz: /public/d4rl/sparse_datasets/diffusion_processed/halfcheetah_medium_expert_sparse_72.5_train.npz
+out: /public/gormpo/models/halfcheetah_medium_expert_sparse_3/diffusion
+epochs: 100
+batch: 512
+lr: 0.0002
+wd: 0.0
+timesteps: 50000
+checkpoint_every_epochs: 10
+seed: 0
+device: cuda
+model: mlp
+hidden: 512
+time_emb: 128
+layers: 3
+dropout: 0.0
+wandb: false
+wandb_project: GORMPO
+wandb_entity: jhhuang_chloe
+wandb_run: unconditional_ddim_mlp_halfcheetah_medium_expert_sparse_72.5
+log_every: 100
+samples_every: 1

halfcheetah_medium_expert_sparse/mobile_based/diffusion/seed_123&timestamp_26-0318-131209/record/hyper_param.json

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+{"config": "config_gormpo/halfcheetah_medium_expert_72.5_diffusion.yaml", "algo_name": "mobile_gormpo", "task": "halfcheetah-medium-expert-v2", "seed": 123, "device": "cuda:7", "dataset_path": "/public/d4rl/sparse_datasets/halfcheetah_medium_expert_sparse_72.5.pkl", "dynamics_path": "log/halfcheetah-medium-expert-v2/mobile&penalty_coef=1.0&rollout_length=5/seed_123&timestamp_26-0117-063103/model", "reward_penalty_coef": 0.5, "classifier_model_name": "/public/gormpo/models/halfcheetah_medium_expert_sparse_3/diffusion/checkpoint.pt", "use_wandb": true, "wandb_project": "mobile-gormpo", "wandb_entity": null, "domain": "gym", "actor_lr": 0.0001, "critic_lr": 0.0003, "hidden_dims": [256, 256], "gamma": 0.99, "tau": 0.005, "alpha": 0.2, "auto_alpha": true, "target_entropy": -6.0, "alpha_lr": 0.0001, "deterministic_backup": true, "max_q_backup": false, "norm_reward": false, "num_q_ensemble": 2, "dynamics_lr": 0.001, "dynamics_max_epochs": null, "max_epochs_since_update": 5, "dynamics_hidden_dims": [200, 200, 200, 200], "dynamics_weight_decay": [2.5e-05, 5e-05, 7.5e-05, 7.5e-05, 0.0001], "n_ensemble": 7, "n_elites": 5, "rollout_freq": 1000, "rollout_batch_size": 50000, "rollout_length": 5, "penalty_coef": 1.0, "num_samples": 10, "model_retain_epochs": 5, "real_ratio": 0.5, "load_dynamics_path": null, "epoch": 3000, "step_per_epoch": 1000, "eval_episodes": 100, "batch_size": 256, "lr_scheduler": true, "density_model": "diffusion", "data_path": "/public/d4rl/sparse_datasets/halfcheetah_medium_expert_sparse_72.5.pkl", "penalty_type": "tanh", "obs_shape": [17], "action_dim": 6.0, "max_action": 1.0, "classifier_type": "diffusion"}

halfcheetah_medium_expert_sparse/mobile_based/diffusion/seed_123&timestamp_26-0318-131209/record/policy_training_progress.csv

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halfcheetah_medium_expert_sparse/mobile_based/neuralODE/seed_123&timestamp_26-0506-193213/record/hyper_param.json

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halfcheetah_medium_expert_sparse/mobile_based/neuralODE/seed_456&timestamp_26-0506-193213/record/hyper_param.json

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halfcheetah_medium_expert_sparse/mobile_based/neuralODE/seed_456&timestamp_26-0506-193213/record/policy_training_progress.csv

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halfcheetah_medium_expert_sparse/mobile_based/realnvp/seed_123&timestamp_26-0318-124415/record/hyper_param.json

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halfcheetah_medium_expert_sparse/mobile_based/realnvp/seed_123&timestamp_26-0318-124415/record/policy_training_progress.csv

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halfcheetah_medium_expert_sparse/mobile_based/realnvp/seed_42&timestamp_26-0316-235600/record/consoleout_backup.txt

@@ -0,0 +1,109 @@
+num rollout transitions: 250000, reward mean: 7.9591
+----------------------------------------------------------------------------------
+| alpha                              | 0.951    |
+| eval/episode_length                | 1e+03    |
+| eval/episode_length_std            | 0        |
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+| eval/normalized_episode_reward_std | 2.26     |
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+| penalty/lcb_std                    | 0.183    |
+| rollout_info/dynamics_penalty_mean | 0.948    |
+| rollout_info/dynamics_penalty_std  | 0.154    |
+| rollout_info/num_transitions       | 2.5e+05  |
+| rollout_info/reward_mean           | 7.96     |
+| timestep                           | 1000     |
+----------------------------------------------------------------------------------
+num rollout transitions: 250000, reward mean: 8.0816
+----------------------------------------------------------------------------------
+| alpha                              | 0.861    |
+| eval/episode_length                | 1e+03    |
+| eval/episode_length_std            | 0        |
+| eval/normalized_episode_reward     | 2.24     |
+| eval/normalized_episode_reward_std | 2.26     |
+| loss/actor                         | -56.7    |
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+| penalty/lcb_std                    | 0.51     |
+| rollout_info/dynamics_penalty_mean | 0.883    |
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+| rollout_info/num_transitions       | 2.5e+05  |
+| rollout_info/reward_mean           | 8.08     |
+| timestep                           | 2000     |
+----------------------------------------------------------------------------------
+num rollout transitions: 250000, reward mean: 8.1632
+----------------------------------------------------------------------------------
+| alpha                              | 0.785    |
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+| rollout_info/dynamics_penalty_mean | 0.798    |
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+| rollout_info/num_transitions       | 2.5e+05  |
+| rollout_info/reward_mean           | 8.16     |
+| timestep                           | 3000     |
+----------------------------------------------------------------------------------
+num rollout transitions: 250000, reward mean: 8.2764
+----------------------------------------------------------------------------------
+| alpha                              | 0.723    |
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+| rollout_info/num_transitions       | 2.5e+05  |
+| rollout_info/reward_mean           | 8.28     |
+| timestep                           | 4000     |
+----------------------------------------------------------------------------------
+num rollout transitions: 250000, reward mean: 8.3717
+----------------------------------------------------------------------------------
+| alpha                              | 0.671    |
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+| penalty/lcb_std                    | 1.65     |
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+| rollout_info/num_transitions       | 2.5e+05  |
+| rollout_info/reward_mean           | 8.37     |
+| timestep                           | 5000     |
+----------------------------------------------------------------------------------
+num rollout transitions: 250000, reward mean: 8.4004
+----------------------------------------------------------------------------------
+| alpha                              | 0.625    |
+| eval/episode_length                | 1e+03    |
+| eval/episode_length_std            | 0        |
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+| eval/normalized_episode_reward_std | 2.97     |
+| loss/actor                         | -184     |
+| loss/alpha                         | -1.55    |
+| loss/critic                        | 40.4     |
+| penalty/lcb_mean                   | 1.62     |
+| penalty/lcb_std                    | 1.72     |
+| rollout_info/dynamics_penalty_mean | 0.489    |
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+| rollout_info/num_transitions       | 2.5e+05  |
+| rollout_info/reward_mean           | 8.4      |
+| timestep                           | 6000     |
+----------------------------------------------------------------------------------
+num rollout transitions: 250000, reward mean: 8.4457

halfcheetah_medium_expert_sparse/mobile_based/realnvp/seed_42&timestamp_26-0316-235600/record/hyper_param.json

@@ -0,0 +1 @@
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halfcheetah_medium_expert_sparse/mobile_based/realnvp/seed_42&timestamp_26-0316-235600/record/policy_training_progress.csv

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halfcheetah_medium_expert_sparse/mobile_based/realnvp/seed_456&timestamp_26-0320-013430/record/hyper_param.json

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halfcheetah_medium_expert_sparse/mobile_based/realnvp/seed_456&timestamp_26-0320-013430/record/policy_training_progress.csv

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