2023-04-11 12:14:55 +02:00
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########################硬件参数########################
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2023-04-15 13:44:24 +02:00
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# 填写cuda:x, cpu 或 mps, x指代第几张卡,只支持 N卡 / Apple Silicon 加速
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device = "cuda:0"
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2023-04-11 12:14:55 +02:00
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2023-04-15 13:44:24 +02:00
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# 9-10-20-30-40系显卡无脑True,不影响质量,>=20显卡开启有加速
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is_half = True
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2023-04-11 12:14:55 +02:00
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2023-04-15 13:44:24 +02:00
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# 默认0用上所有线程,写数字限制CPU资源使用
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n_cpu = 0
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2023-04-11 12:14:55 +02:00
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########################硬件参数########################
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##################下为参数处理逻辑,勿动##################
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########################命令行参数########################
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2023-04-01 10:42:19 +02:00
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import argparse
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2023-04-15 13:44:24 +02:00
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2023-04-01 10:42:19 +02:00
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parser = argparse.ArgumentParser()
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parser.add_argument("--port", type=int, default=7865, help="Listen port")
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parser.add_argument("--pycmd", type=str, default="python", help="Python command")
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2023-04-15 13:44:24 +02:00
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parser.add_argument("--colab", action="store_true", help="Launch in colab")
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parser.add_argument(
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"--noparallel", action="store_true", help="Disable parallel processing"
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)
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parser.add_argument(
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"--noautoopen", action="store_true", help="Do not open in browser automatically"
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)
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2023-04-01 10:42:19 +02:00
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cmd_opts = parser.parse_args()
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2023-04-11 12:14:55 +02:00
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2023-04-15 13:44:24 +02:00
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python_cmd = cmd_opts.pycmd
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listen_port = cmd_opts.port
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iscolab = cmd_opts.colab
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noparallel = cmd_opts.noparallel
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noautoopen = cmd_opts.noautoopen
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2023-04-11 12:14:55 +02:00
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########################命令行参数########################
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import sys
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2023-03-31 11:54:38 +02:00
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import torch
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2023-04-11 12:14:55 +02:00
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2023-04-15 13:44:24 +02:00
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2023-04-11 12:14:55 +02:00
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# has_mps is only available in nightly pytorch (for now) and MasOS 12.3+.
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# check `getattr` and try it for compatibility
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def has_mps() -> bool:
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if sys.platform != "darwin":
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return False
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else:
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2023-04-15 13:44:24 +02:00
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if not getattr(torch, "has_mps", False):
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return False
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2023-04-11 12:14:55 +02:00
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try:
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torch.zeros(1).to(torch.device("mps"))
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return True
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except Exception:
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return False
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2023-04-15 13:44:24 +02:00
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if not torch.cuda.is_available():
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2023-04-11 12:14:55 +02:00
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if has_mps():
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print("没有发现支持的N卡, 使用MPS进行推理")
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2023-04-15 13:44:24 +02:00
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device = "mps"
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2023-04-11 12:14:55 +02:00
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else:
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print("没有发现支持的N卡, 使用CPU进行推理")
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2023-04-15 13:44:24 +02:00
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device = "cpu"
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2023-04-11 12:14:55 +02:00
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is_half = False
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2023-04-15 13:44:24 +02:00
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if device not in ["cpu", "mps"]:
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2023-04-11 12:14:55 +02:00
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gpu_name = torch.cuda.get_device_name(int(device.split(":")[-1]))
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2023-04-15 13:44:24 +02:00
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if "16" in gpu_name or "MX" in gpu_name:
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2023-03-31 11:54:38 +02:00
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print("16系显卡/MX系显卡强制单精度")
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2023-04-11 12:14:55 +02:00
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is_half = False
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2023-03-31 11:54:38 +02:00
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from multiprocessing import cpu_count
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2023-04-15 13:44:24 +02:00
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if n_cpu == 0:
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n_cpu = cpu_count()
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if is_half:
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# 6G显存配置
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x_pad = 3
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x_query = 10
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x_center = 60
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x_max = 65
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2023-03-31 11:54:38 +02:00
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else:
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2023-04-15 13:44:24 +02:00
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# 5G显存配置
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x_pad = 1
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x_query = 6
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x_center = 38
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x_max = 41
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