File size: 3,054 Bytes
d2b26ce | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 | #!/usr/bin/env bash
# AdaptiveDetailCache T2V inference (dev6)
export MASTER_ADDR=localhost
export MASTER_PORT=6007
export GPUS_PER_NODE=1
export NNODES=1
export WORLD_SIZE=1
export CUDA_VISIBLE_DEVICES="${CUDA_VISIBLE_DEVICES:-0}"
export PAD_HQ=1
export PAD_DURATION=1
export PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True
export OFFLOAD_T5_CACHE=true
export OFFLOAD_VAE_CACHE=true
export TORCH_CUDA_ARCH_LIST="8.9;9.0"
set -euo pipefail
if [ -z "${CONDA_DEFAULT_ENV:-}" ] || [ "${CONDA_DEFAULT_ENV}" != "magi" ]; then
if [ -f "${HOME}/miniforge3/etc/profile.d/conda.sh" ]; then
# shellcheck disable=SC1091
source "${HOME}/miniforge3/etc/profile.d/conda.sh"
conda activate magi
elif [ -f "${HOME}/anaconda3/etc/profile.d/conda.sh" ]; then
# shellcheck disable=SC1091
source "${HOME}/anaconda3/etc/profile.d/conda.sh"
conda activate magi
fi
fi
SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
MAGI_ROOT="$(cd "$SCRIPT_DIR/../.." && pwd)"
cd "$MAGI_ROOT"
PROMPT="${PROMPT:-a woman dancing.}"
TIMESTAMP="${RUN_ID:-$(date "+%Y-%m-%d_%H-%M-%S")}"
PROMPT_DIR_NAME="${PROMPT_DIR_NAME:-$(python3 - "$PROMPT" <<'PY'
import re
import sys
import unicodedata
prompt = unicodedata.normalize("NFKC", sys.argv[1]).strip()
prompt = re.sub(r"[\\/:\*\?\"<>\|\x00-\x1f]+", "_", prompt)
prompt = re.sub(r"\s+", "_", prompt)
prompt = prompt.strip("._")
print((prompt or "prompt")[:120])
PY
)}"
OUTPUT_ROOT="${OUTPUT_ROOT:-outputs}"
EXP_DIR="${RUN_DIR:-$OUTPUT_ROOT/${PROMPT_DIR_NAME}_adaptive_$TIMESTAMP}"
mkdir -p "$EXP_DIR"
ADAPTIVE_CONFIG="${ADAPTIVE_CONFIG:-yaml_config/single_run/adaptive_config_best.yaml}"
CONFIG_FILE="${CONFIG_FILE:-config/single_run/flowcache_t2v.json}"
OUTPUT_PATH="${OUTPUT_PATH:-$EXP_DIR/output_$TIMESTAMP.mp4}"
RESIDUAL_JSON="${RESIDUAL_JSON:-$EXP_DIR/residual_stats_$TIMESTAMP.json}"
L1_REL_JSON="${L1_REL_JSON:-$EXP_DIR/l1_rel_stats_$TIMESTAMP.json}"
METRIC_JSON="${METRIC_JSON:-$EXP_DIR/adaptive_metric_stats_$TIMESTAMP.json}"
LOG_FILE="${LOG_FILE:-$EXP_DIR/infer_$TIMESTAMP.log}"
export PYTHONPATH="$MAGI_ROOT:${PYTHONPATH:-}"
python3 inference/pipeline/motioncache.py \
--config_file "$CONFIG_FILE" \
--mode t2v \
--prompt "$PROMPT" \
--output_path "$OUTPUT_PATH" \
--additional_config "$ADAPTIVE_CONFIG" \
--residual_stats_path "$RESIDUAL_JSON" \
--l1_rel_stats_path "$L1_REL_JSON" \
--motioncache_metric_stats_path "$METRIC_JSON" \
2>&1 | tee "$LOG_FILE"
if [ ! -f "$OUTPUT_PATH" ]; then
echo "ERROR: inference failed, output video not found: $OUTPUT_PATH"
exit 1
fi
python3 - "$METRIC_JSON" <<'PY'
import json
import sys
with open(sys.argv[1], "r") as f:
payload = json.load(f)
print("AdaptiveDetailCache hyperparameters:", payload.get("hyperparameters", {}))
print("Per-chunk tau_eff:", payload.get("chunk_tau_effective", {}))
print("Per-chunk difficulty:", payload.get("chunk_difficulty", {}))
PY
echo "Done."
echo " log: $LOG_FILE"
echo " video: $OUTPUT_PATH"
echo " metric json: $METRIC_JSON"
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