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Jade Choghari
43 lines
1.3 KiB
Bash
Executable File
43 lines
1.3 KiB
Bash
Executable File
#!/bin/bash
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# Example script to run synthetic data generation with Qwen VLM
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# This generates user prompts and robot utterances for hierarchical policy training
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# Configuration
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REPO_ID="lerobot/svla_so101_pickplace"
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MODEL="Qwen/Qwen3-VL-30B-A3B-Instruct"
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# Alternative: MODEL="Qwen/Qwen2-VL-7B-Instruct"
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OUTPUT_DIR="/fsx/jade_choghari/outputs/pgen_annotations1"
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BATCH_SIZE=32
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TEMPERATURE=0.9
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SAMPLE_INTERVAL=5.0 # Generate dialogue every 1 second (all episodes processed)
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# Run synthetic data generation (processes ALL episodes)
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python examples/dataset/annotate_pgen.py \
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--repo-id "$REPO_ID" \
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--model "$MODEL" \
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--output-dir "$OUTPUT_DIR" \
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--temperature "$TEMPERATURE" \
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--batch-size "$BATCH_SIZE" \
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--sample-interval "$SAMPLE_INTERVAL" \
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--num-image-views-per-sample 1
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# For faster testing, increase sample interval:
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# --sample-interval 5.0 # Samples every 5 seconds (much faster)
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# To push to hub after generation:
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# Add --push-to-hub flag
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# Efficient batch processing: 4 episodes at once
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# python examples/dataset/annotate_pgen.py \
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# --repo-id "$REPO_ID" \
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# --model "$MODEL" \
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# --output-dir "$OUTPUT_DIR" \
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# --video-mode \
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# --video-key observation.images.up \
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# --video-batch-size "$BATCH_SIZE" \
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# --sample-interval 1.0
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