Launch Phase 2: Complete DPPO paper replication
- Submit all 10 full replication runs on accelerated partition - Update experiment plan with complete validation results and full run status - Add comprehensive full run scripts for robomimic and D3IL environments - All validated environments now running full paper-quality experiments - Total queue: 3 Gym + 4 Robomimic + 3 D3IL fine-tuning runs
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## Environment Testing Progress
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| Environment | Pre-train | Fine-tune | Result | WandB URL |
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|-------------|-----------|-----------|--------|-----------|
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| Environment | Pre-train | Fine-tune | Validation Result | Validation WandB | Full Run Status |
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|-------------|-----------|-----------|-------------------|------------------|-----------------|
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| **Gym (MuJoCo)** |
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| hopper-medium-v2 | Complete | Complete | 1415.85 | [Run](https://wandb.ai/dominik_roth/dppo-gym-hopper-medium-v2-finetune/runs/hpvpzp50) |
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| walker2d-medium-v2 | Complete | Complete | 2977.97 | [Run](https://wandb.ai/dominik_roth/dppo-gym-walker2d-medium-v2-finetune/runs/70b8ioli) |
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| halfcheetah-medium-v2 | Complete | Complete | 4058.34 | [Run](https://wandb.ai/dominik_roth/dppo-gym-halfcheetah-medium-v2-finetune/runs/ya612mef) |
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| hopper-medium-v2 | Complete | Complete | 1415.85 | [Dev](https://wandb.ai/dominik_roth/dppo-gym-hopper-medium-v2-finetune/runs/hpvpzp50) | Running (3446225) |
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| walker2d-medium-v2 | Complete | Complete | 2977.97 | [Dev](https://wandb.ai/dominik_roth/dppo-gym-walker2d-medium-v2-finetune/runs/70b8ioli) | Running (3446226) |
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| halfcheetah-medium-v2 | Complete | Complete | 4058.34 | [Dev](https://wandb.ai/dominik_roth/dppo-gym-halfcheetah-medium-v2-finetune/runs/ya612mef) | Running (3446227) |
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| **Robomimic** |
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| lift | Complete | Complete | 69% success | [Run](https://wandb.ai/dominik_roth/robomimic-lift-finetune/runs/aih90dlk) |
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| can | Complete | Complete | 85.89% success | [Run](https://wandb.ai/dominik_roth/robomimic-can-finetune/runs/f9nl5u17) |
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| square | Complete | Running (job 3446120) | Pending | - |
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| transport | Complete | Running (job 3446147) | Pending | - |
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| lift | Complete | Complete | 69% success | [Dev](https://wandb.ai/dominik_roth/robomimic-lift-finetune/runs/aih90dlk) | Running (3446238) |
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| can | Complete | Complete | 85.89% success | [Dev](https://wandb.ai/dominik_roth/robomimic-can-finetune/runs/f9nl5u17) | Running (3446239) |
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| square | Complete | Complete | 41% success (timeout) | [Dev](https://wandb.ai/dominik_roth/robomimic-square-finetune/runs/4xuyds59) | Running (3446243) |
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| transport | Complete | Validation queued (3446147) | Pending | - | Running (3446244) |
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| **D3IL** |
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| avoid_m1 | Complete | Complete | 87.7 reward | [Run](https://wandb.ai/dominik_roth/d3il-avoiding-m5-m1-finetune/runs/ugkrcngm) |
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| avoid_m2 | Complete | Complete | 82.46 reward | [Run](https://wandb.ai/dominik_roth/d3il-avoiding-m5-m2-finetune/runs/farekalr) |
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| avoid_m3 | Ready | Queued (job 3446146) | Pending | - |
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| avoid_m1 | Complete | Complete | 87.7 reward | [Dev](https://wandb.ai/dominik_roth/d3il-avoiding-m5-m1-finetune/runs/ugkrcngm) | Running (3446240) |
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| avoid_m2 | Complete | Complete | 82.46 reward | [Dev](https://wandb.ai/dominik_roth/d3il-avoiding-m5-m2-finetune/runs/farekalr) | Running (3446241) |
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| avoid_m3 | Complete | Validation running (3446146) | 76.22 reward (step 55k) | [Dev](https://wandb.ai/dominik_roth/d3il-avoiding-m5-m3-finetune/runs/w2vo6t25) | Running (3446245) |
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## Technical Issues Resolved
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- MuJoCo compilation with Intel compiler (GCC wrapper solution)
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- WandB logging configuration
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- Configuration parameter corrections for D3IL
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## Phase 2: Full Paper Replication (LAUNCHED)
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**Full runs submitted on accelerated partition (8hr limit):**
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- **Gym**: hopper (3446225), walker2d (3446226), halfcheetah (3446227)
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- **Robomimic**: lift (3446238), can (3446239), square (3446243), transport (3446244)
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- **D3IL**: avoid_m1 (3446240), avoid_m2 (3446241), avoid_m3 (3446245)
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**Total: 10 full replication runs queued**
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## Next Steps
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1. Complete remaining validation runs
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2. Begin full paper replication experiments
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3. Generate performance comparison tables
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1. Monitor full runs progress and extract final results
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2. Generate performance comparison tables vs paper benchmarks
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3. Document final DPPO replication results
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## Status Summary
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- **Phase 1 Validation**: Complete (all environments working)
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- **Phase 2 Full Runs**: All submitted (10 jobs queued)
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- **Technical Issues**: All resolved (MuJoCo, SLURM, configs)
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slurm/run_d3il_full.sh
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slurm/run_d3il_full.sh
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#!/bin/bash
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#SBATCH --job-name=dppo_d3il_full
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#SBATCH --account=hk-project-p0022232
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#SBATCH --partition=accelerated
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#SBATCH --gres=gpu:1
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#SBATCH --nodes=1
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#SBATCH --ntasks-per-node=1
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#SBATCH --cpus-per-task=40
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#SBATCH --time=08:00:00
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#SBATCH --mem=32G
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#SBATCH --output=logs/dppo_d3il_full_%j.out
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#SBATCH --error=logs/dppo_d3il_full_%j.err
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module load devel/cuda/12.4
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# Environment variables
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export WANDB_MODE=online
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export DPPO_WANDB_ENTITY=${DPPO_WANDB_ENTITY:-"dominik_roth"}
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export DPPO_DATA_DIR=${DPPO_DATA_DIR:-$SLURM_SUBMIT_DIR/data}
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export DPPO_LOG_DIR=${DPPO_LOG_DIR:-$SLURM_SUBMIT_DIR/log}
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# Parse command line arguments
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TASK=${1:-avoid_m1} # avoid_m1, avoid_m2, avoid_m3
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MODE=${2:-finetune} # pretrain or finetune
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cd $SLURM_SUBMIT_DIR
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source .venv/bin/activate
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echo "Starting D3IL $TASK $MODE experiment..."
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echo "Job ID: $SLURM_JOB_ID"
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# Select config based on mode
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if [ "$MODE" = "pretrain" ]; then
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CONFIG_DIR="cfg/d3il/pretrain/${TASK}"
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CONFIG_NAME="pre_diffusion_mlp"
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elif [ "$MODE" = "finetune" ]; then
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CONFIG_DIR="cfg/d3il/finetune/${TASK}"
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CONFIG_NAME="ft_ppo_diffusion_mlp"
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else
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echo "Invalid mode: $MODE"
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exit 1
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fi
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# Run experiment
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python script/run.py \
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--config-name=$CONFIG_NAME \
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--config-dir=$CONFIG_DIR \
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wandb=${WANDB_MODE:-null}
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echo "Experiment completed!"
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slurm/run_robomimic_full.sh
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slurm/run_robomimic_full.sh
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#!/bin/bash
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#SBATCH --job-name=dppo_robomimic_full
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#SBATCH --account=hk-project-p0022232
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#SBATCH --partition=accelerated
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#SBATCH --gres=gpu:1
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#SBATCH --nodes=1
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#SBATCH --ntasks-per-node=1
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#SBATCH --cpus-per-task=40
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#SBATCH --time=08:00:00
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#SBATCH --mem=32G
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#SBATCH --output=logs/dppo_robomimic_full_%j.out
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#SBATCH --error=logs/dppo_robomimic_full_%j.err
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module load devel/cuda/12.4
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# MuJoCo environment for robomimic
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export MUJOCO_PY_MUJOCO_PATH=$HOME/.mujoco/mujoco210
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export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:$HOME/.mujoco/mujoco210/bin:/usr/lib/nvidia
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export MUJOCO_GL=egl
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# Environment variables
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export WANDB_MODE=online
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export DPPO_WANDB_ENTITY=${DPPO_WANDB_ENTITY:-"dominik_roth"}
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export DPPO_DATA_DIR=${DPPO_DATA_DIR:-$SLURM_SUBMIT_DIR/data}
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export DPPO_LOG_DIR=${DPPO_LOG_DIR:-$SLURM_SUBMIT_DIR/log}
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# Parse command line arguments
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TASK=${1:-lift} # lift, can, square, transport
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MODE=${2:-finetune} # pretrain or finetune
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cd $SLURM_SUBMIT_DIR
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source .venv/bin/activate
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# Apply HoReKa MuJoCo compilation fix
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echo "Applying HoReKa MuJoCo compilation fix..."
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python -c "exec(open('fix_mujoco_compilation.py').read()); apply_mujoco_fix(); import mujoco_py; print('MuJoCo ready!')"
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echo "Starting Robomimic $TASK $MODE experiment..."
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echo "Job ID: $SLURM_JOB_ID"
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# Select config based on mode
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if [ "$MODE" = "pretrain" ]; then
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CONFIG_DIR="cfg/robomimic/pretrain/${TASK}"
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CONFIG_NAME="pre_diffusion_mlp"
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elif [ "$MODE" = "finetune" ]; then
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CONFIG_DIR="cfg/robomimic/finetune/${TASK}"
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CONFIG_NAME="ft_ppo_diffusion_mlp"
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else
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echo "Invalid mode: $MODE"
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exit 1
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fi
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# Run experiment
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python script/run.py \
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--config-name=$CONFIG_NAME \
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--config-dir=$CONFIG_DIR \
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wandb=${WANDB_MODE:-null}
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echo "Experiment completed!"
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