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881f988 | 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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 | #!/usr/bin/env python3
"""
批量推理: 11 张图片 × 随机 WASD 方向变换
每 ~30 latents (~120 帧) 变换一个方向
视频长度 497 帧 (~125 latents, ~20s @24fps)
"""
import random
import subprocess
import os
import time
random.seed(42)
IMAGES = [
"1.png", "2.png", "3.png", "4.png", "5.png",
"6.jpeg", "7.png", "8.png", "9.png", "10.png", "test.png"
]
DIRECTIONS = ["w", "a", "s", "d"]
# 加入转向动作
ALL_MOVES = ["w", "a", "s", "d", "left", "right", "up", "down"]
IMAGE_DIR = "/root/HY-WorldPlay/assets/img"
OUTPUT_BASE = "/root/test_results/batch"
MODEL_PATH = subprocess.check_output(
"find /root/models -maxdepth 3 -name 'HunyuanVideo*' -type d | grep -v temp | head -1",
shell=True
).decode().strip()
WP_PATH = subprocess.check_output(
"find /root/models -maxdepth 3 -name 'HY-WorldPlay' -type d | grep -v temp | head -1",
shell=True
).decode().strip()
ACTION_CKPT = f"{WP_PATH}/ar_distilled_action_model/diffusion_pytorch_model.safetensors"
def generate_random_pose(total_latents=31, segment_latents=8):
"""生成随机 WASD 方向序列，每 segment_latents 变换一次"""
segments = []
remaining = total_latents
while remaining > 0:
direction = random.choice(DIRECTIONS)
# 随机混入转向
if random.random() < 0.3:
turn = random.choice(["left", "right"])
turn_len = min(random.randint(2, 4), remaining)
segments.append(f"{turn}-{turn_len}")
remaining -= turn_len
if remaining <= 0:
break
seg_len = min(segment_latents + random.randint(-2, 2), remaining)
if seg_len <= 0:
break
segments.append(f"{direction}-{seg_len}")
remaining -= seg_len
return ",".join(segments)
def run_inference(image_name, pose, output_dir):
"""运行单次推理"""
image_path = os.path.join(IMAGE_DIR, image_name)
cmd = [
"python3", "/root/scripts/run_fp8_turbo3_gpu.py",
"--model_path", MODEL_PATH,
"--action_ckpt", ACTION_CKPT,
"--prompt", "Explore a vivid 3D world with smooth camera movement.",
"--image_path", image_path,
"--resolution", "480p",
"--aspect_ratio", "16:9",
"--video_length", "125",
"--seed", str(random.randint(0, 99999)),
"--rewrite", "false",
"--sr", "false",
"--pose", pose,
"--output_path", output_dir,
"--few_step", "true",
"--num_inference_steps", "4",
"--model_type", "ar",
"--use_vae_parallel", "false",
"--use_sageattn", "true",
"--use_fp8_gemm", "false",
"--transformer_resident_ar_rollout", "true",
"--width", "832",
"--height", "480",
]
env = os.environ.copy()
env["PYTHONPATH"] = "/root/HY-WorldPlay:" + env.get("PYTHONPATH", "")
env["PYTORCH_CUDA_ALLOC_CONF"] = "expandable_segments:True"
result = subprocess.run(cmd, env=env, cwd="/root/HY-WorldPlay",
capture_output=True, text=True)
return result.returncode, result.stdout, result.stderr
if __name__ == "__main__":
os.makedirs(OUTPUT_BASE, exist_ok=True)
print("=" * 60)
print("批量推理: 11 张图片 × 随机 WASD")
print("=" * 60)
results = []
for i, img in enumerate(IMAGES):
pose = generate_random_pose(total_latents=31, segment_latents=8)
output_dir = os.path.join(OUTPUT_BASE, img.split(".")[0])
os.makedirs(output_dir, exist_ok=True)
print(f"\n[{i+1}/11] {img}")
print(f" pose: {pose}")
print(f" output: {output_dir}")
t0 = time.time()
code, stdout, stderr = run_inference(img, pose, output_dir)
elapsed = time.time() - t0
# 提取关键信息
success = code == 0
peak_mem = ""
total_time = ""
for line in (stdout + stderr).split("\n"):
if "峰值显存" in line:
peak_mem = line.strip()
if "总耗时" in line:
total_time = line.strip()
status = "✅" if success else "❌"
print(f" {status} {elapsed:.0f}s | {peak_mem} | {total_time}")
if not success:
# 打印最后 10 行错误
err_lines = stderr.strip().split("\n")[-10:]
for l in err_lines:
print(f" ERR: {l}")
results.append({
"image": img,
"pose": pose,
"success": success,
"time": elapsed,
})
# 汇总
print("\n" + "=" * 60)
print("汇总")
print("=" * 60)
ok = sum(1 for r in results if r["success"])
print(f"成功: {ok}/11")
print(f"总耗时: {sum(r['time'] for r in results):.0f}s")
for r in results:
s = "✅" if r["success"] else "❌"
print(f" {s} {r['image']:12s} {r['time']:.0f}s pose={r['pose']}")
print(f"\n视频输出目录: {OUTPUT_BASE}/")
print("完成!")
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