Commit ad0237f9 authored by Zhuguanyu Wu's avatar Zhuguanyu Wu Committed by GitHub
Browse files

update configs for causvid (#34)

parent 165ec807
...@@ -8,11 +8,7 @@ ...@@ -8,11 +8,7 @@
"sample_guide_scale": 6, "sample_guide_scale": 6,
"sample_shift": 8, "sample_shift": 8,
"enable_cfg": false, "enable_cfg": false,
"cpu_offload": true, "cpu_offload": false,
"mm_config": {
"mm_type": "W-fp8-channel-sym-A-fp8-channel-sym-dynamic-Sgl",
"weight_auto_quant": true
},
"num_fragments": 3, "num_fragments": 3,
"num_frames": 21, "num_frames": 21,
"num_frame_per_block": 3, "num_frame_per_block": 3,
......
{
"infer_steps": 9,
"target_video_length": 81,
"target_height": 480,
"target_width": 832,
"attention_type": "flash_attn3",
"seed": 42,
"sample_guide_scale": 6,
"sample_shift": 8,
"enable_cfg": false,
"cpu_offload": false,
"mm_config": {
"mm_type": "W-fp8-channel-sym-A-fp8-channel-sym-dynamic-Sgl"
},
"num_fragments": 3,
"num_frames": 21,
"num_frame_per_block": 3,
"num_blocks": 7,
"frame_seq_length": 1560,
"denoising_step_list": [999, 934, 862, 756, 603, 410, 250, 140, 74]
}
...@@ -35,4 +35,4 @@ python -m lightx2v.infer \ ...@@ -35,4 +35,4 @@ python -m lightx2v.infer \
--config_json ${lightx2v_path}/configs/wan_t2v_causvid.json \ --config_json ${lightx2v_path}/configs/wan_t2v_causvid.json \
--prompt "Two anthropomorphic cats fight intensely on a spotlighted stage; the left cat wearing blue boxing gear with matching gloves, the right cat in bright red boxing attire and gloves." \ --prompt "Two anthropomorphic cats fight intensely on a spotlighted stage; the left cat wearing blue boxing gear with matching gloves, the right cat in bright red boxing attire and gloves." \
--negative_prompt 色调艳丽,过曝,静态,细节模糊不清,字幕,风格,作品,画作,画面,静止,整体发灰,最差质量,低质量,JPEG压缩残留,丑陋的,残缺的,多余的手指,画得不好的手部,画得不好的脸部,畸形的,毁容的,形态畸形的肢体,手指融合,静止不动的画面,杂乱的背景,三条腿,背景人很多,倒着走 \ --negative_prompt 色调艳丽,过曝,静态,细节模糊不清,字幕,风格,作品,画作,画面,静止,整体发灰,最差质量,低质量,JPEG压缩残留,丑陋的,残缺的,多余的手指,画得不好的手部,画得不好的脸部,畸形的,毁容的,形态畸形的肢体,手指融合,静止不动的画面,杂乱的背景,三条腿,背景人很多,倒着走 \
--save_video_path ${lightx2v_path}/save_results/output_lightx2v_wan_t2v_causal.mp4 --save_video_path ${lightx2v_path}/save_results/output_lightx2v_wan_t2v_causvid.mp4
#!/bin/bash
# set path and first
lightx2v_path=
model_path=
# check section
if [ -z "${CUDA_VISIBLE_DEVICES}" ]; then
cuda_devices=0
echo "Warn: CUDA_VISIBLE_DEVICES is not set, using default value: ${cuda_devices}, change at shell script or set env variable."
export CUDA_VISIBLE_DEVICES=${cuda_devices}
fi
if [ -z "${lightx2v_path}" ]; then
echo "Error: lightx2v_path is not set. Please set this variable first."
exit 1
fi
if [ -z "${model_path}" ]; then
echo "Error: model_path is not set. Please set this variable first."
exit 1
fi
export TOKENIZERS_PARALLELISM=false
export PYTHONPATH=${lightx2v_path}:$PYTHONPATH
export ENABLE_PROFILING_DEBUG=true
export ENABLE_GRAPH_MODE=false
# =========================
# save quantization weight
# =========================
export RUNNING_FLAG=save_naive_quant
python -m lightx2v.infer \
--model_cls wan2.1_causvid \
--task t2v \
--model_path $model_path \
--config_json ${lightx2v_path}/configs/wan_t2v_causvid_save_quant.json \
--prompt "Two anthropomorphic cats in comfy boxing gear and bright gloves fight intensely on a spotlighted stage." \
--negative_prompt 色调艳丽,过曝,静态,细节模糊不清,字幕,风格,作品,画作,画面,静止,整体发灰,最差质量,低质量,JPEG压缩残留,丑陋的,残缺的,多余的手指,画得不好的手部,画得不好的脸部,畸形的,毁容的,形态畸形的肢体,手指融合,静止不动的画面,杂乱的背景,三条腿,背景人很多,倒着走 \
--save_video_path ${lightx2v_path}/save_results/output_lightx2v_wan_t2v_causvid.mp4
sleep 2
# =========================
# load quantization weight and inference
# =========================
export RUNNING_FLAG=infer
python -m lightx2v.infer \
--model_cls wan2.1_causvid \
--task t2v \
--model_path $model_path \
--config_json ${lightx2v_path}/configs/wan_t2v_causvid_save_quant.json \
--prompt "Two anthropomorphic cats in comfy boxing gear and bright gloves fight intensely on a spotlighted stage." \
--negative_prompt 色调艳丽,过曝,静态,细节模糊不清,字幕,风格,作品,画作,画面,静止,整体发灰,最差质量,低质量,JPEG压缩残留,丑陋的,残缺的,多余的手指,画得不好的手部,画得不好的脸部,畸形的,毁容的,形态畸形的肢体,手指融合,静止不动的画面,杂乱的背景,三条腿,背景人很多,倒着走 \
--save_video_path ${lightx2v_path}/save_results/output_lightx2v_wan_t2v_causvid.mp4
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