54 lines
2.4 KiB
Bash
54 lines
2.4 KiB
Bash
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#!/usr/bin/env bash
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# Foreground only. Usage: bash run_easycom_local_baselines.sh [all|baseline|audio|visual|av] [seed ...]
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set -euo pipefail
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cd "$(dirname "$0")"
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FEATURE_ROOT=${FEATURE_ROOT:-/data1/yfzx/wangx/Datasets/easycom/omni_features/open_stream_2fps_8s_last4_stack}
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TARGET_ROOT=${TARGET_ROOT:-/data1/yfzx/wangx/Datasets/easycom/easycom_target_frame}
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LOCAL_ROOT=${LOCAL_ROOT:-/data1/yfzx/wangx/Datasets/easycom/omni_features/local_qwen_1s}
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CHECKPOINT_ROOT=${CHECKPOINT_ROOT:-checkpoints/easycom_local_b1}
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RESULT_ROOT=${RESULT_ROOT:-results/easycom_local_b1}
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LOCAL_PROJECTION_DIM=${LOCAL_PROJECTION_DIM:-256}
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export OMP_NUM_THREADS=${OMP_NUM_THREADS:-4}
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export MKL_NUM_THREADS=${MKL_NUM_THREADS:-4}
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export OPENBLAS_NUM_THREADS=${OPENBLAS_NUM_THREADS:-4}
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variant=${1:-all}
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if (( $# )); then shift; fi
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if (( $# )); then seeds=("$@"); else seeds=(0 1 2); fi
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case "$variant" in
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all) variants=(baseline audio visual av) ;;
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baseline|audio|visual|av) variants=("$variant") ;;
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*) echo "Expected all, baseline, audio, visual, or av" >&2; exit 2 ;;
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esac
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for variant in "${variants[@]}"; do
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train_local=()
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infer_local=()
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if [[ "$variant" != baseline ]]; then
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train_local=(--local-feature-root "$LOCAL_ROOT" --local-modalities "$variant"
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--local-projection-dim "$LOCAL_PROJECTION_DIM")
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infer_local=(--local-feature-root "$LOCAL_ROOT")
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fi
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for seed in "${seeds[@]}"; do
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checkpoint="$CHECKPOINT_ROOT/${variant}_seed${seed}.pth"
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result="$RESULT_ROOT/${variant}_seed${seed}"
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if [[ -e "$checkpoint" || -e "$result/metrics.json" ]]; then
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echo "Refusing to overwrite $checkpoint or $result; select new output roots." >&2
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exit 1
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fi
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python train_turn_head.py \
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--feature-root "$FEATURE_ROOT" --target-root "$TARGET_ROOT" \
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--output "$checkpoint" --sessions 4 5 6 7 8 9 10 11 12 \
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--epochs 4 --batch-size 512 --learning-rate 7e-5 --weight-decay 5e-5 \
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--warmup-epochs 1.6 --warmup-factor 0.3 --dropout 0.2 \
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--loss lstr-mce --transition-objective none --layer-fusion concat-mlp \
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--expected-mode open-stream-replay --seed "$seed" --device cuda:0 \
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"${train_local[@]}"
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python infer_turn_head.py \
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--feature-root "$FEATURE_ROOT" --target-root "$TARGET_ROOT" \
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--checkpoint "$checkpoint" --output-dir "$result" --sessions 3 2 1 \
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--expected-mode open-stream-replay --device cuda:0 "${infer_local[@]}"
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done
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done
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