FlowCache/FlowCache4MAGI-1-dev6-adaptive/scripts/single_run/adaptive_t2v.sh

#!/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"