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						import argparse | 
					
					
						
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						import torch | 
					
					
						
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						from multiprocessing import cpu_count | 
					
					
						
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						class Config: | 
					
					
						
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						    def __init__(self): | 
					
					
						
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						        self.device = "cuda:0" | 
					
					
						
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						        self.is_half = True | 
					
					
						
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						        self.n_cpu = 0 | 
					
					
						
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						        self.gpu_name = None | 
					
					
						
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						        self.gpu_mem = None | 
					
					
						
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						        ( | 
					
					
						
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						            self.python_cmd, | 
					
					
						
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						            self.listen_port, | 
					
					
						
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						            self.colab, | 
					
					
						
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						            self.noparallel, | 
					
					
						
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						            self.noautoopen, | 
					
					
						
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						            self.api | 
					
					
						
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						        ) = self.arg_parse() | 
					
					
						
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						        self.x_pad, self.x_query, self.x_center, self.x_max = self.device_config() | 
					
					
						
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						    @staticmethod | 
					
					
						
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						    def arg_parse() -> tuple: | 
					
					
						
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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( | 
					
					
						
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						            "--pycmd", type=str, default="python", help="Python command" | 
					
					
						
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						        ) | 
					
					
						
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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", | 
					
					
						
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						            action="store_true", | 
					
					
						
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						            help="Do not open in browser automatically", | 
					
					
						
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						        ) | 
					
					
						
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						        parser.add_argument("--api", action="store_true", help="Launch with api") | 
					
					
						
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						        cmd_opts = parser.parse_args() | 
					
					
						
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						        cmd_opts.port = cmd_opts.port if 0 <= cmd_opts.port <= 65535 else 7865 | 
					
					
						
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						        return ( | 
					
					
						
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						            cmd_opts.pycmd, | 
					
					
						
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						            cmd_opts.port, | 
					
					
						
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						            cmd_opts.colab, | 
					
					
						
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						            cmd_opts.noparallel, | 
					
					
						
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						            cmd_opts.noautoopen, | 
					
					
						
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						            cmd_opts.api | 
					
					
						
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						        ) | 
					
					
						
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						    def device_config(self) -> tuple: | 
					
					
						
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						        if torch.cuda.is_available(): | 
					
					
						
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						            i_device = int(self.device.split(":")[-1]) | 
					
					
						
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						            self.gpu_name = torch.cuda.get_device_name(i_device) | 
					
					
						
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						            if ( | 
					
					
						
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						                ("16" in self.gpu_name and "V100" not in self.gpu_name.upper()) | 
					
					
						
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						                or "P40" in self.gpu_name.upper() | 
					
					
						
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						                or "1060" in self.gpu_name | 
					
					
						
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						                or "1070" in self.gpu_name | 
					
					
						
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						                or "1080" in self.gpu_name | 
					
					
						
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						            ): | 
					
					
						
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						                print("16系/10系显卡和P40强制单精度") | 
					
					
						
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						                self.is_half = False | 
					
					
						
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						            else: | 
					
					
						
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						                self.gpu_name = None | 
					
					
						
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						            self.gpu_mem = int( | 
					
					
						
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						                torch.cuda.get_device_properties(i_device).total_memory | 
					
					
						
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						                / 1024 | 
					
					
						
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						                / 1024 | 
					
					
						
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						                / 1024 | 
					
					
						
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						                + 0.4 | 
					
					
						
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						            ) | 
					
					
						
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						        elif torch.backends.mps.is_available(): | 
					
					
						
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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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						            self.device = "mps" | 
					
					
						
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						            self.is_half = False | 
					
					
						
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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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						            self.device = "cpu" | 
					
					
						
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						            self.is_half = False | 
					
					
						
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						        if self.n_cpu == 0: | 
					
					
						
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						            self.n_cpu = cpu_count() | 
					
					
						
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						        if self.is_half: | 
					
					
						
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						             | 
					
					
						
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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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						        else: | 
					
					
						
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						             | 
					
					
						
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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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						        if self.gpu_mem != None and self.gpu_mem <= 4: | 
					
					
						
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						            x_pad = 1 | 
					
					
						
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						            x_query = 5 | 
					
					
						
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						            x_center = 30 | 
					
					
						
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						            x_max = 32 | 
					
					
						
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						        return x_pad, x_query, x_center, x_max | 
					
					
						
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