53 lines
1.5 KiB
Bash
53 lines
1.5 KiB
Bash
model_name=testing
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ckpt=/path/to/model/checkpoint
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config=configs/inference/world_model_interaction.yaml
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seed=123
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res_dir="/path/to/result/directory"
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analysis_reference_steps=50
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# analysis_psnr_path="/path/to/psnr_full50.csv"
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datasets=(
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"unitree_z1_stackbox"
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"unitree_z1_dual_arm_stackbox"
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"unitree_z1_dual_arm_stackbox_v2"
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"unitree_z1_dual_arm_cleanup_pencils"
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"unitree_g1_pack_camera"
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)
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n_iters=(12 7 11 8 11)
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fses=(4 4 4 4 6)
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for i in "${!datasets[@]}"; do
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dataset=${datasets[$i]}
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n_iter=${n_iters[$i]}
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fs=${fses[$i]}
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analysis_args=(
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--analysis_log_metrics
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--analysis_reference_steps ${analysis_reference_steps}
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)
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if [ -n "${analysis_psnr_path:-}" ]; then
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analysis_args+=(--analysis_psnr_path "${analysis_psnr_path}")
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fi
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CUDA_VISIBLE_DEVICES=0 python3 scripts/evaluation/world_model_interaction.py \
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--seed ${seed} \
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--ckpt_path $ckpt \
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--config $config \
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--savedir "${res_dir}/${model_name}/${dataset}" \
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--bs 1 --height 320 --width 512 \
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--unconditional_guidance_scale 1.0 \
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--ddim_steps 50 \
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--ddim_eta 1.0 \
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--prompt_dir "/path/to/unifolm-world-model-action/examples/world_model_interaction_prompts" \
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--dataset ${dataset} \
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--video_length 16 \
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--frame_stride ${fs} \
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--n_action_steps 16 \
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--exe_steps 16 \
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--n_iter ${n_iter} \
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--timestep_spacing 'uniform_trailing' \
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--guidance_rescale 0.7 \
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--perframe_ae \
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"${analysis_args[@]}"
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done
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