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run.sh
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#!/bin/zsh
source activate cvideos
# python training/train_skills.py --beta 0.1 --conditional_prior 0
#python training/train_skills.py --beta 1 --conditional_prior 0
# python training/train_skills.py --beta 0.001 --conditional_prior 0
# python training/train_skills.py --beta 0.1 --conditional_prior 1
# python training/train_skills.py --beta 0.01 --conditional_prior 1
# python training/train_skills.py --beta 0.001 --conditional_prior 1
#python3 training/collect_diffusion_data.py --skill_model_filename 'skill_model_antmaze-large-diverse-v2_encoderType(gru)_state_dec_autoregressive_policy_dec_autoregressive_H_30_b_1.0_conditionalp_0_diffusion_prior_False_best_a.pth' --horizon 30 --per_element_sigma 1 --conditional_prior 0 --z_dim 64 --append_goals 0 --state_decoder_type autoregressive --save_z_dist 1
#python3 training/collect_diffusion_data.py --skill_model_filename 'skill_model_antmaze-large-diverse-v2_encoderType(gru)_state_dec_autoregressive_policy_dec_autoregressive_H_30_b_1.0_conditionalp_0_diffusion_prior_False_best_a.pth' --horizon 30 --per_element_sigma 1 --conditional_prior 0 --z_dim 64 --append_goals 1 --state_decoder_type autoregressive --save_z_dist 1
#python3 training/collect_diffusion_data.py --skill_model_filename 'skill_model_antmaze-large-diverse-v2_encoderType(gru)_state_dec_autoregressive_policy_dec_autoregressive_H_30_b_1.0_conditionalp_1_diffusion_prior_False_best_a.pth' --horizon 30 --per_element_sigma 1 --conditional_prior 1 --z_dim 64 --append_goals 0 --state_decoder_type autoregressive --save_z_dist 1
#python3 training/collect_diffusion_data.py --skill_model_filename 'skill_model_antmaze-large-diverse-v2_encoderType(gru)_state_dec_autoregressive_policy_dec_autoregressive_H_30_b_1.0_conditionalp_1_diffusion_prior_False_best_a.pth' --horizon 30 --per_element_sigma 1 --conditional_prior 1 --z_dim 64 --append_goals 1 --state_decoder_type autoregressive --save_z_dist 1
#python3 training/train_diffusion.py --skill_model_filename 'skill_model_antmaze-large-diverse-v2_encoderType(gru)_state_dec_autoregressive_policy_dec_autoregressive_H_30_b_1.0_conditionalp_0_diffusion_prior_False_best_a.pth' --append_goals 0 --diffusion_steps 200 --sample_z 1 --n_epoch 1000
#python3 training/train_diffusion.py --skill_model_filename 'skill_model_antmaze-large-diverse-v2_encoderType(gru)_state_dec_autoregressive_policy_dec_autoregressive_H_30_b_1.0_conditionalp_0_diffusion_prior_False_best_a.pth' --append_goals 1 --diffusion_steps 200 --sample_z 1 --n_epoch 1000
#python3 training/train_diffusion.py --skill_model_filename 'skill_model_antmaze-large-diverse-v2_encoderType(gru)_state_dec_autoregressive_policy_dec_autoregressive_H_30_b_1.0_conditionalp_1_diffusion_prior_False_best_a.pth' --append_goals 0 --diffusion_steps 200 --sample_z 1 --n_epoch 1000
#python3 training/train_diffusion.py --skill_model_filename 'skill_model_antmaze-large-diverse-v2_encoderType(gru)_state_dec_autoregressive_policy_dec_autoregressive_H_30_b_1.0_conditionalp_1_diffusion_prior_False_best_a.pth' --append_goals 1 --diffusion_steps 200 --sample_z 1 --n_epoch 1000
# python training/train_skills.py --beta 1 --conditional_prior 0 --z_dim 8 --policy_decoder_type mlp
# python training/train_skills.py --beta 1 --conditional_prior 1 --z_dim 8 --policy_decoder_type mlp
# python training/train_skills.py --beta 1 --conditional_prior 0 --z_dim 16 --policy_decoder_type mlp
#python training/train_skills.py --beta 1 --conditional_prior 1 --z_dim 16 --policy_decoder_type mlp
#python3 training/train_diffusion.py --skill_model_filename 'skill_model_antmaze-large-diverse-v2_encoderType(gru)_state_dec_autoregressive_policy_dec_autoregressive_H_30_b_1.0_conditionalp_0_diffusion_prior_False_zdim_16_best_a.pth' --append_goals 0 --diffusion_steps 200 --sample_z 1 --n_epoch 1000 --net_type unet
#python3 training/train_abstract_dynamics.py --skill_model_filename 'skill_model_antmaze-large-diverse-v2_encoderType(gru)_state_dec_autoregressive_policy_dec_autoregressive_H_30_b_1.0_conditionalp_0_diffusion_prior_False_zdim_16_best_a.pth' --sample_z 1 --n_epoch 1000 --z_dim 16
#python training/train_skills.py --beta 1 --conditional_prior 1 --z_dim 16 --policy_decoder_type 'autoregressive' --state_decoder_type 'mlp'
#python training/train_skills.py --beta 0.1 --conditional_prior 1 --z_dim 16 --policy_decoder_type 'autoregressive' --state_decoder_type 'mlp'
#python training/train_skills.py --beta 1 --conditional_prior 1 --z_dim 16 --policy_decoder_type 'mlp' --state_decoder_type 'mlp'
#python training/train_skills.py --beta 0.1 --conditional_prior 1 --z_dim 16 --policy_decoder_type 'mlp' --state_decoder_type 'mlp'
# python training/train_skills.py --beta 0.05 --conditional_prior 1 --z_dim 16 --policy_decoder_type 'autoregressive' --state_decoder_type 'mlp'
# python training/train_skills.py --beta 0.5 --conditional_prior 1 --z_dim 16 --policy_decoder_type 'autoregressive' --state_decoder_type 'mlp'
# python training/train_skills.py --beta 2 --conditional_prior 1 --z_dim 16 --policy_decoder_type 'autoregressive' --state_decoder_type 'mlp'
# python training/train_skills.py --beta 0.05 --conditional_prior 1 --z_dim 16 --policy_decoder_type 'autoregressive' --state_decoder_type 'autoregressive'
# python training/train_skills.py --beta 0.5 --conditional_prior 1 --z_dim 16 --policy_decoder_type 'autoregressive' --state_decoder_type 'autoregressive'
# python training/train_skills.py --beta 2 --conditional_prior 1 --z_dim 16 --policy_decoder_type 'autoregressive' --state_decoder_type 'autoregressive'
# python training/train_q_net.py --sample_z 1 --skill_model_filename 'skill_model_antmaze-large-diverse-v2_encoderType(gru)_state_dec_mlp_policy_dec_autoregressive_H_30_b_0.1_conditionalp_1_diffusion_prior_False_zdim_16_best_a.pth' --cfg_weight 0
# python training/train_q_net.py --sample_z 1 --skill_model_filename 'skill_model_antmaze-large-diverse-v2_encoderType(gru)_state_dec_mlp_policy_dec_autoregressive_H_30_b_0.1_conditionalp_1_diffusion_prior_False_zdim_16_best_a.pth' --cfg_weight 4
# python training/train_q_net.py --sample_z 1 --skill_model_filename 'skill_model_antmaze-large-diverse-v2_encoderType(gru)_state_dec_mlp_policy_dec_autoregressive_H_30_b_1.0_conditionalp_1_diffusion_prior_False_zdim_16_best_a.pth' --cfg_weight 0
# python training/train_q_net.py --sample_z 1 --skill_model_filename 'skill_model_antmaze-large-diverse-v2_encoderType(gru)_state_dec_mlp_policy_dec_autoregressive_H_30_b_1.0_conditionalp_1_diffusion_prior_False_zdim_16_best_a.pth' --cfg_weight 4
# python3 training/collect_q_learning_dataset.py --skill_model_filename 'skill_model_antmaze-large-diverse-v2_encoderType(gru)_state_dec_mlp_policy_dec_autoregressive_H_30_b_0.1_conditionalp_1_diffusion_prior_False_zdim_16_best_a.pth' --beta 0.1
# python3 training/collect_q_learning_dataset.py --skill_model_filename 'skill_model_antmaze-large-diverse-v2_encoderType(gru)_state_dec_mlp_policy_dec_autoregressive_H_30_b_1.0_conditionalp_1_diffusion_prior_False_zdim_16_best_a.pth' --beta 1.0
#python3 training/collect_diffusion_data.py --skill_model_filename 'skill_model_antmaze-large-diverse-v2_encoderType(gru)_state_dec_mlp_policy_dec_autoregressive_H_30_b_0.05_conditionalp_1_diffusion_prior_False_zdim_16_best_a.pth' --horizon 30 --policy_decoder_type autoregressive --state_decoder_type mlp --beta 0.05 --per_element_sigma 1 --z_dim 16 --conditional_prior 1 --save_z_dist 1
#python3 training/collect_diffusion_data.py --skill_model_filename 'skill_model_antmaze-large-diverse-v2_encoderType(gru)_state_dec_mlp_policy_dec_autoregressive_H_30_b_0.5_conditionalp_1_diffusion_prior_False_zdim_16_best_a.pth' --horizon 30 --policy_decoder_type autoregressive --state_decoder_type mlp --beta 0.5 --per_element_sigma 1 --z_dim 16 --conditional_prior 1 --save_z_dist 1
#python3 training/collect_diffusion_data.py --skill_model_filename 'skill_model_antmaze-large-diverse-v2_encoderType(gru)_state_dec_mlp_policy_dec_autoregressive_H_30_b_2.0_conditionalp_1_diffusion_prior_False_zdim_16_best_a.pth' --horizon 30 --policy_decoder_type autoregressive --state_decoder_type mlp --beta 2.0 --per_element_sigma 1 --z_dim 16 --conditional_prior 1 --save_z_dist 1
#python3 training/collect_diffusion_data.py --skill_model_filename 'skill_model_antmaze-large-diverse-v2_encoderType(gru)_state_dec_autoregressive_policy_dec_autoregressive_H_30_b_0.05_conditionalp_1_diffusion_prior_False_zdim_16_best_a.pth' --horizon 30 --policy_decoder_type autoregressive --state_decoder_type autoregressive --beta 0.05 --per_element_sigma 1 --z_dim 16 --conditional_prior 1 --save_z_dist 1
#python3 training/collect_diffusion_data.py --skill_model_filename 'skill_model_antmaze-large-diverse-v2_encoderType(gru)_state_dec_autoregressive_policy_dec_autoregressive_H_30_b_0.5_conditionalp_1_diffusion_prior_False_zdim_16_best_a.pth' --horizon 30 --policy_decoder_type autoregressive --state_decoder_type autoregressive --beta 0.5 --per_element_sigma 1 --z_dim 16 --conditional_prior 1 --save_z_dist 1
#python3 training/collect_diffusion_data.py --skill_model_filename 'skill_model_antmaze-large-diverse-v2_encoderType(gru)_state_dec_autoregressive_policy_dec_autoregressive_H_30_b_2.0_conditionalp_1_diffusion_prior_False_zdim_16_best_a.pth' --horizon 30 --policy_decoder_type autoregressive --state_decoder_type autoregressive --beta 2.0 --per_element_sigma 1 --z_dim 16 --conditional_prior 1 --save_z_dist 1
#python3 training/train_diffusion.py --skill_model_filename 'skill_model_antmaze-large-diverse-v2_encoderType(gru)_state_dec_mlp_policy_dec_autoregressive_H_30_b_0.05_conditionalp_1_diffusion_prior_False_zdim_16_best_a.pth' --batch_size 32 --predict_noise 0 --diffusion_steps 100 --drop_prob 0.2 --test_split 0.1 --n_epoch 100 --sample_z 0 --net_type unet
#python3 training/train_diffusion.py --skill_model_filename 'skill_model_antmaze-large-diverse-v2_encoderType(gru)_state_dec_mlp_policy_dec_autoregressive_H_30_b_0.5_conditionalp_1_diffusion_prior_False_zdim_16_best_a.pth' --batch_size 32 --predict_noise 0 --diffusion_steps 100 --drop_prob 0.2 --test_split 0.1 --n_epoch 100 --sample_z 0 --net_type unet
#python3 training/train_diffusion.py --skill_model_filename 'skill_model_antmaze-large-diverse-v2_encoderType(gru)_state_dec_mlp_policy_dec_autoregressive_H_30_b_2.0_conditionalp_1_diffusion_prior_False_zdim_16_best_a.pth' --batch_size 32 --predict_noise 0 --diffusion_steps 100 --drop_prob 0.2 --test_split 0.1 --n_epoch 100 --sample_z 0 --net_type unet
#python3 training/train_diffusion.py --skill_model_filename 'skill_model_antmaze-large-diverse-v2_encoderType(gru)_state_dec_autoregressive_policy_dec_autoregressive_H_30_b_0.05_conditionalp_1_diffusion_prior_False_zdim_16_best_a.pth' --batch_size 32 --predict_noise 0 --diffusion_steps 100 --drop_prob 0.2 --test_split 0.1 --n_epoch 100 --sample_z 0 --net_type unet
#python3 training/train_diffusion.py --skill_model_filename 'skill_model_antmaze-large-diverse-v2_encoderType(gru)_state_dec_autoregressive_policy_dec_autoregressive_H_30_b_0.5_conditionalp_1_diffusion_prior_False_zdim_16_best_a.pth' --batch_size 32 --predict_noise 0 --diffusion_steps 100 --drop_prob 0.2 --test_split 0.1 --n_epoch 100 --sample_z 0 --net_type unet
#python3 training/train_diffusion.py --skill_model_filename 'skill_model_antmaze-large-diverse-v2_encoderType(gru)_state_dec_autoregressive_policy_dec_autoregressive_H_30_b_2.0_conditionalp_1_diffusion_prior_False_zdim_16_best_a.pth' --batch_size 32 --predict_noise 0 --diffusion_steps 100 --drop_prob 0.2 --test_split 0.1 --n_epoch 100 --sample_z 0 --net_type unet
# python training/train_q_net.py --sample_z 1 --skill_model_filename 'skill_model_antmaze-large-diverse-v2_encoderType(gru)_state_dec_mlp_policy_dec_autoregressive_H_30_b_0.1_conditionalp_1_diffusion_prior_False_zdim_16_best_a.pth' --cfg_weight 0
# python training/train_q_net.py --sample_z 1 --skill_model_filename 'skill_model_antmaze-large-diverse-v2_encoderType(gru)_state_dec_mlp_policy_dec_autoregressive_H_30_b_0.1_conditionalp_1_diffusion_prior_False_zdim_16_best_a.pth' --cfg_weight 4
# python training/train_q_net.py --sample_z 1 --skill_model_filename 'skill_model_antmaze-large-diverse-v2_encoderType(gru)_state_dec_mlp_policy_dec_autoregressive_H_30_b_1.0_conditionalp_1_diffusion_prior_False_zdim_16_best_a.pth' --cfg_weight 0
# python training/train_q_net.py --sample_z 1 --skill_model_filename 'skill_model_antmaze-large-diverse-v2_encoderType(gru)_state_dec_mlp_policy_dec_autoregressive_H_30_b_1.0_conditionalp_1_diffusion_prior_False_zdim_16_best_a.pth' --cfg_weight 4
# python3 training/collect_q_learning_dataset.py --skill_model_filename 'skill_model_antmaze-large-diverse-v2_encoderType(gru)_state_dec_mlp_policy_dec_autoregressive_H_30_b_0.1_conditionalp_1_diffusion_prior_False_zdim_16_best_a.pth' --beta 0.1
# python3 training/collect_q_learning_dataset.py --skill_model_filename 'skill_model_antmaze-large-diverse-v2_encoderType(gru)_state_dec_mlp_policy_dec_autoregressive_H_30_b_1.0_conditionalp_1_diffusion_prior_False_zdim_16_best_a.pth' --beta 1.0
python training/train_skills.py --beta 0.1 --conditional_prior 0 --z_dim 16 --policy_decoder_type 'autoregressive' --state_decoder_type 'mlp'
python training/train_skills.py --beta 0.01 --conditional_prior 0 --z_dim 16 --policy_decoder_type 'autoregressive' --state_decoder_type 'mlp'
python3 training/collect_q_learning_dataset.py --skill_model_filename 'skill_model_antmaze-large-diverse-v2_encoderType(gru)_state_dec_autoregressive_policy_dec_autoregressive_H_30_b_0.1_conditionalp_1_diffusion_prior_False_zdim_16_adist_softmax_separatetest_True_best_a.pth' --beta 0.1 --horizon 30 --state_decoder_type autoregressive --a_dist softmax