Delete config.py

config.py

@@ -1,99 +0,0 @@
-import argparse
-import sys
-import torch
-from multiprocessing import cpu_count
-
-class Config:
-    def __init__(self):
-        self.device = "cuda:0"
-        self.is_half = True
-        self.n_cpu = 0
-        self.gpu_name = None
-        self.gpu_mem = None
-        (
-            self.colab,
-            self.api,
-            self.unsupported
-        ) = self.arg_parse()
-        self.x_pad, self.x_query, self.x_center, self.x_max = self.device_config()
-
-    @staticmethod
-    def arg_parse() -> tuple:
-        parser = argparse.ArgumentParser()
-        parser.add_argument("--colab", action="store_true", help="Launch in colab")
-        parser.add_argument("--api", action="store_true", help="Launch with api")
-        parser.add_argument("--unsupported", action="store_true", help="Enable unsupported feature")
-        cmd_opts = parser.parse_args()
-
-        return (
-            cmd_opts.colab,
-            cmd_opts.api,
-            cmd_opts.unsupported
-        )
-
-    # has_mps is only available in nightly pytorch (for now) and MasOS 12.3+.
-    # check `getattr` and try it for compatibility
-    @staticmethod
-    def has_mps() -> bool:
-        if not torch.backends.mps.is_available():
-            return False
-        try:
-            torch.zeros(1).to(torch.device("mps"))
-            return True
-        except Exception:
-            return False
-
-    def device_config(self) -> tuple:
-        if torch.cuda.is_available():
-            i_device = int(self.device.split(":")[-1])
-            self.gpu_name = torch.cuda.get_device_name(i_device)
-            if (
-                ("16" in self.gpu_name and "V100" not in self.gpu_name.upper())
-                or "P40" in self.gpu_name.upper()
-                or "1060" in self.gpu_name
-                or "1070" in self.gpu_name
-                or "1080" in self.gpu_name
-            ):
-                print("INFO: Found GPU", self.gpu_name, ", force to fp32")
-                self.is_half = False
-            else:
-                print("INFO: Found GPU", self.gpu_name)
-            self.gpu_mem = int(
-                torch.cuda.get_device_properties(i_device).total_memory
-                / 1024
-                / 1024
-                / 1024
-                + 0.4
-            )
-        elif self.has_mps():
-            print("INFO: No supported Nvidia GPU found, use MPS instead")
-            self.device = "mps"
-            self.is_half = False
-        else:
-            print("INFO: No supported Nvidia GPU found, use CPU instead")
-            self.device = "cpu"
-            self.is_half = False
-
-        if self.n_cpu == 0:
-            self.n_cpu = cpu_count()
-
-        if self.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
-
-        if self.gpu_mem != None and self.gpu_mem <= 4:
-            x_pad = 1
-            x_query = 5
-            x_center = 30
-            x_max = 32
-
-        return x_pad, x_query, x_center, x_max