new things

2026-05-23 20:50:02 +00:00 · 2025-09-10 11:32:54 +02:00
parent 1ba896598e
commit 5c628f1700
33 changed files with 9085 additions and 39 deletions
@@ -0,0 +1,141 @@
+#!/bin/bash
+# smolvla training with accelerate
+
+set -euo pipefail
+
+# repo/env
+cd ~/lerobot || exit 1
+# conda activate lerobot
+export LC_ALL=C
+
+rm -f core-*
+
+# storage / caches
+RAID=/raid/jade
+export TRANSFORMERS_CACHE=$RAID/.cache/huggingface/transformers
+export HF_HOME=$RAID/.cache/huggingface
+export HF_DATASETS_CACHE=$RAID/.cache/huggingface/datasets
+export HF_LEROBOT_HOME=$RAID/.cache/huggingface/lerobot
+export WANDB_CACHE_DIR=$RAID/.cache/wandb
+export TMPDIR=$RAID/.cache/tmp
+mkdir -p $TMPDIR
+export WANDB_MODE=offline
+# export HF_DATASETS_OFFLINE=1
+# export HF_HUB_OFFLINE=1
+export TOKENIZERS_PARALLELISM=false
+export MUJOCO_GL=egl
+
+# CONFIG
+ENV=libero
+TASK=libero_spatial
+REPO_ID=HuggingfaceVLA/libero
+
+POLICY=smolvla
+VLM=HuggingFaceTB/SmolVLM2-500M-Instruct
+
+# Optim / scheduling
+LR=1e-4
+DECAY_LR=2.5e-6
+DECAY_STEPS=30000
+USE_AMP=true   # set to true for mixed precision
+TRAIN_EXPERT_ONLY=true
+N_ACTION_STEPS=1
+SEED=1000
+LOAD_VLM_WEIGHTS=true
+# Training loop
+OFFLINE_STEPS=100000
+BATCH_SIZE=32
+EVAL_FREQ=0
+SAVE_FREQ=20000
+EVAL_BATCH_SIZE=1
+NUM_EPISODES=1
+ADD_IMAGE_TOKENS=tru
+N_OBS_STEPS=1
+ATTN_MODE=cross_attn
+EXPERT_WIDTH_MULTIPLIER=0.5
+# number of gpus to use
+NUM_PROCESSES=2
+NUM_VLM_LAYERS=0
+SELF_ATTN_EVERY_N_LAYERS=2
+CHUNK_SIZE=50
+export CUDA_VISIBLE_DEVICES=0
+PORT=29522
+PREFIX_LENGTH=0
+LOAD_VLM_WEIGHTS=true
+# naming/output dir
+TRAIN_DIR=$RAID/logs/lerobot/lerobot_new_${REPO_ID//\//_}_${POLICY}_lr${LR}bs${BATCH_SIZE}steps${OFFLINE_STEPS}
+echo "Training dir: $TRAIN_DIR"
+
+rm -rf "$TRAIN_DIR"
+
+# RUN
+# python -m accelerate.commands.launch \
+#   --num_processes $NUM_PROCESSES \
+#   --num_machines 1 \
+#   --main_process_port $PORT \
+#   --mixed_precision=$( [ "$USE_AMP" = true ] && echo "bf16" || echo "no" ) \
+#   src/lerobot/scripts/train_accelerate.py \
+#     --policy.type=$POLICY \
+#     --policy.use_amp=True \
+#     --policy.vlm_model_name=$VLM \
+#     --dataset.repo_id=$REPO_ID \
+#     --dataset.root=$HF_DATASETS_CACHE \
+#     --env.type=$ENV \
+#     --env.task=$TASK \
+#     --output_dir=$TRAIN_DIR \
+#     --batch_size=$BATCH_SIZE \
+#     --steps=$OFFLINE_STEPS \
+#     --eval_freq=$EVAL_FREQ \
+#     --save_freq=$SAVE_FREQ \
+#     --eval.batch_size=$EVAL_BATCH_SIZE \
+#     --eval.n_episodes=$NUM_EPISODES \
+#     --policy.optimizer_lr=$LR \
+#     --policy.repo_id=None \
+#     --policy.scheduler_decay_lr=$DECAY_LR \
+#     --policy.scheduler_decay_steps=$DECAY_STEPS \
+#     --policy.n_action_steps=$N_ACTION_STEPS \
+#     --policy.train_expert_only=$TRAIN_EXPERT_ONLY \
+#     --policy.vlm_model_name=$VLM \
+#     --policy.n_obs_steps=$N_OBS_STEPS \
+#     --policy.attention_mode=$ATTN_MODE \
+#     --policy.prefix_length=$PREFIX_LENGTH \
+#     --policy.num_vlm_layers=$NUM_VLM_LAYERS \
+#     --policy.chunk_size=$CHUNK_SIZE \
+#     --policy.expert_width_multiplier=$EXPERT_WIDTH_MULTIPLIER \
+#     --policy.self_attn_every_n_layers=$SELF_ATTN_EVERY_N_LAYERS \
+#     --seed=$SEED \
+#     --wandb.enable=false
+
+
+python src/lerobot/scripts/train.py \
+    --policy.type=$POLICY \
+    --policy.use_amp=False \
+    --policy.vlm_model_name=$VLM \
+    --dataset.repo_id=$REPO_ID \
+    --dataset.root='/raid/jade/.cache/huggingface/lerobot/HuggingFaceVLA/libero/data' \
+    --env.type=$ENV \
+    --env.task=$TASK \
+    --output_dir=$TRAIN_DIR \
+    --batch_size=$BATCH_SIZE \
+    --steps=$OFFLINE_STEPS \
+    --eval_freq=$EVAL_FREQ \
+    --save_freq=$SAVE_FREQ \
+    --eval.batch_size=$EVAL_BATCH_SIZE \
+    --eval.n_episodes=$NUM_EPISODES \
+    --policy.optimizer_lr=$LR \
+    --policy.repo_id=None \
+    --policy.scheduler_decay_lr=$DECAY_LR \
+    --policy.scheduler_decay_steps=$DECAY_STEPS \
+    --policy.n_action_steps=$N_ACTION_STEPS \
+    --policy.train_expert_only=$TRAIN_EXPERT_ONLY \
+    --policy.vlm_model_name=$VLM \
+    --policy.n_obs_steps=$N_OBS_STEPS \
+    --policy.attention_mode=$ATTN_MODE \
+    --policy.prefix_length=$PREFIX_LENGTH \
+    --policy.num_vlm_layers=$NUM_VLM_LAYERS \
+    --policy.chunk_size=$CHUNK_SIZE \
+    --policy.load_vlm_weights=$LOAD_VLM_WEIGHTS \
+    --policy.expert_width_multiplier=$EXPERT_WIDTH_MULTIPLIER \
+    --policy.self_attn_every_n_layers=$SELF_ATTN_EVERY_N_LAYERS \
+    --seed=$SEED \
+    --wandb.enable=false