Update config.py

config.py

@@ -3,7 +3,6 @@ import sys
 import torch
 from multiprocessing import cpu_count
 
-
 class Config:
     def __init__(self):
         self.device = "cuda:0"
@@ -11,54 +10,13 @@ class Config:
         self.n_cpu = 0
         self.gpu_name = None
         self.gpu_mem = None
-        (
-            self.python_cmd,
-            self.listen_port,
-            self.iscolab,
-            self.noparallel,
-            self.noautoopen,
-        ) = self.arg_parse()
+        self.python_cmd = "python"
+        self.listen_port = 7865
+        self.iscolab = False
+        self.noparallel = False
+        self.noautoopen = False
         self.x_pad, self.x_query, self.x_center, self.x_max = self.device_config()
 
-    @staticmethod
-    def arg_parse() -> tuple:
-        exe = sys.executable or "python"
-        parser = argparse.ArgumentParser()
-        parser.add_argument("--port", type=int, default=7865, help="Listen port")
-        parser.add_argument("--pycmd", type=str, default=exe, 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()
-
-        cmd_opts.port = cmd_opts.port if 0 <= cmd_opts.port <= 65535 else 7865
-
-        return (
-            cmd_opts.pycmd,
-            cmd_opts.port,
-            cmd_opts.colab,
-            cmd_opts.noparallel,
-            cmd_opts.noautoopen,
-        )
-
-    # 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])
@@ -69,17 +27,14 @@ class Config:
                 or "1060" in self.gpu_name
                 or "1070" in self.gpu_name
                 or "1080" in self.gpu_name
+                or "T4" in self.gpu_name.upper()  # Add this line to check for T4 GPU
             ):
                 print("Found GPU", self.gpu_name, ", force to fp32")
                 self.is_half = False
             else:
                 print("Found GPU", self.gpu_name)
             self.gpu_mem = int(
-                torch.cuda.get_device_properties(i_device).total_memory
-                / 1024
-                / 1024
-                / 1024
-                + 0.4
+                torch.cuda.get_device_properties(i_device).total_memory / 1024 / 1024 / 1024 + 0.4
             )
         elif self.has_mps():
             print("No supported Nvidia GPU found, use MPS instead")
@@ -106,10 +61,22 @@ class Config:
             x_center = 38
             x_max = 41
 
-        if self.gpu_mem != None and self.gpu_mem <= 4:
+        if self.gpu_mem is not 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
+        return x_pad, x_query, x_center, x_max
+
+    # has_mps is only available in nightly pytorch (for now) and macOS 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