# Copyright (c) 2025 SandAI. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. export MASTER_ADDR=localhost export MASTER_PORT=6006 export GPUS_PER_NODE=1 export NNODES=1 export WORLD_SIZE=1 export 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 # MAGI inference requires the `magi` conda environment (flashinfer, etc.) 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}_motioncache_$TIMESTAMP}" mkdir -p "$EXP_DIR" MOTIONCACHE_CONFIG="${MOTIONCACHE_CONFIG:-yaml_config/single_run/motioncache_config.yaml}" OUTPUT_PATH="${OUTPUT_PATH:-$EXP_DIR/output_$TIMESTAMP.mp4}" RESIDUAL_JSON="${RESIDUAL_JSON:-$EXP_DIR/residual_stats_$TIMESTAMP.json}" RESIDUAL_PNG="${RESIDUAL_PNG:-$EXP_DIR/residual_norms_$TIMESTAMP.png}" L1_REL_JSON="${L1_REL_JSON:-$EXP_DIR/l1_rel_stats_$TIMESTAMP.json}" L1_REL_PNG="${L1_REL_PNG:-$EXP_DIR/l1_rel_$TIMESTAMP.png}" MOTIONCACHE_METRIC_JSON="${MOTIONCACHE_METRIC_JSON:-$EXP_DIR/motioncache_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/single_run/flowcache_t2v.json \ --mode t2v \ --prompt "$PROMPT" \ --output_path "$OUTPUT_PATH" \ --additional_config "$MOTIONCACHE_CONFIG" \ --residual_stats_path "$RESIDUAL_JSON" \ --l1_rel_stats_path "$L1_REL_JSON" \ --motioncache_metric_stats_path "$MOTIONCACHE_METRIC_JSON" \ 2>&1 | tee "$LOG_FILE" if [ ! -f "$OUTPUT_PATH" ]; then echo "ERROR: inference failed, output video not found: $OUTPUT_PATH" exit 1 fi if [ -f "$RESIDUAL_JSON" ]; then python3 tools/plot_residual_norms.py "$RESIDUAL_JSON" -o "$RESIDUAL_PNG" fi if [ -f "$L1_REL_JSON" ]; then python3 tools/plot_l1_rel.py "$L1_REL_JSON" -o "$L1_REL_PNG" fi python3 - "$MOTIONCACHE_METRIC_JSON" <<'PY' import json import sys with open(sys.argv[1], "r") as f: payload = json.load(f) print("MotionCache hyperparameters:", payload.get("hyperparameters", {})) summary = payload.get("chunk_execution_summary", {}) print("MotionCache execution summary:") for chunk_id in sorted(summary, key=lambda value: int(value)): item = summary[chunk_id] print( " chunk {chunk_idx}: reuse={reuse_steps}, compute={compute_steps}, " "total={total_steps}, reuse_rate={reuse_rate:.2%}".format(**item) ) PY echo "Done." echo " log: $LOG_FILE" echo " video: $OUTPUT_PATH" echo " motioncache metric json: $MOTIONCACHE_METRIC_JSON"