File size: 4,227 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 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 | # 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"
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