########################硬件参数######################## #填写cuda:x, cpu 或 mps, x指代第几张卡,只支持 N卡 / Apple Silicon 加速 device = "cuda:0" #9-10-20-30-40系显卡无脑True,不影响质量,>=20显卡开启有加速 is_half = True #默认0用上所有线程,写数字限制CPU资源使用 n_cpu = 0 ########################硬件参数######################## ##################下为参数处理逻辑,勿动################## ########################命令行参数######################## import argparse parser = argparse.ArgumentParser() parser.add_argument("--port", type=int, default=7865, help="Listen port") parser.add_argument("--pycmd", type=str, default="python", help="Python command") parser.add_argument("--colab", action='store_true', help="Launch in colab") parser.add_argument("--noparallel", action='store_true', help="Disable parallel processing") parser.add_argument("--noautoopen", action='store_true', help="Do not open in browser automatically") cmd_opts = parser.parse_args() python_cmd=cmd_opts.pycmd listen_port=cmd_opts.port iscolab=cmd_opts.colab noparallel=cmd_opts.noparallel noautoopen=cmd_opts.noautoopen ########################命令行参数######################## import sys import torch # has_mps is only available in nightly pytorch (for now) and MasOS 12.3+. # check `getattr` and try it for compatibility def has_mps() -> bool: if sys.platform != "darwin": return False else: if not getattr(torch, 'has_mps', False): return False try: torch.zeros(1).to(torch.device("mps")) return True except Exception: return False if(not torch.cuda.is_available()): if has_mps(): print("没有发现支持的N卡, 使用MPS进行推理") device = "mps" else: print("没有发现支持的N卡, 使用CPU进行推理") device = "cpu" is_half = False if(device not in ["cpu", "mps"]): gpu_name = torch.cuda.get_device_name(int(device.split(":")[-1])) if("16" in gpu_name or "MX" in gpu_name): print("16系显卡/MX系显卡强制单精度") is_half = False from multiprocessing import cpu_count if(n_cpu==0): n_cpu=cpu_count() if(is_half): #6G显存配置 x_pad = 3 x_query = 10 x_center = 60 x_max = 65 else: #5G显存配置 x_pad = 1 x_query = 6 x_center = 38 x_max = 41