Better fp16 detection

config.py

@@ -3,17 +3,34 @@ import sys
 import torch
 from multiprocessing import cpu_count
 
+global IsFp16Support
+IsFp16Support = False
 
 def use_fp32_config():
-    for config_file in ["32k.json", "40k.json", "48k.json"]:
-        with open(f"configs/{config_file}", "r") as f:
-            strr = f.read().replace("true", "false")
-        with open(f"configs/{config_file}", "w") as f:
-            f.write(strr)
-    with open("trainset_preprocess_pipeline_print.py", "r") as f:
-        strr = f.read().replace("3.7", "3.0")
-    with open("trainset_preprocess_pipeline_print.py", "w") as f:
-        f.write(strr)
+    if torch.cuda.is_available():
+        device = torch.device("cuda:0")  # Assuming you have only one GPU (index 0).
+        if torch.cuda.get_device_capability(device)[0] >= 7:
+            print("Fp16 supported!")
+            IsFp16Support = True
+            for config_file in ["32k.json", "40k.json", "48k.json"]:
+                with open(f"configs/{config_file}", "r+") as f:
+                    strr = f.read().replace("false", "true")
+                    f.write(strr)
+            with open("trainset_preprocess_pipeline_print.py", "r+") as f:
+                strr = f.read().replace("3.0", "3.7")
+                f.write(strr)
+        else:
+            print("fp16 unavailable! Using fp32.....")
+            for config_file in ["32k.json", "40k.json", "48k.json"]:
+                with open(f"configs/{config_file}", "r+") as f:
+                    strr = f.read().replace("true", "false")
+                    f.write(strr)
+            with open("trainset_preprocess_pipeline_print.py", "r+") as f:
+                strr = f.read().replace("3.7", "3.0")
+                f.write(strr)
+    else:
+        print("CUDA is not available. Make sure you have an NVIDIA GPU and CUDA installed.")
+    return (IsFp16Support, torch.cuda.get_device_capability(device)[0])
 
 
 class Config:
@@ -29,7 +46,10 @@ class Config:
             self.iscolab,
             self.noparallel,
             self.noautoopen,
+            self.paperspace,
+            self.is_cli,
         ) = self.arg_parse()
+        
         self.x_pad, self.x_query, self.x_center, self.x_max = self.device_config()
 
     @staticmethod
@@ -47,6 +67,12 @@ class Config:
             action="store_true",
             help="Do not open in browser automatically",
         )
+        parser.add_argument( # Fork Feature. Paperspace integration for web UI
+            "--paperspace", action="store_true", help="Note that this argument just shares a gradio link for the web UI. Thus can be used on other non-local CLI systems."
+        )
+        parser.add_argument( # Fork Feature. Embed a CLI into the infer-web.py
+            "--is_cli", action="store_true", help="Use the CLI instead of setting up a gradio UI. This flag will launch an RVC text interface where you can execute functions from infer-web.py!"
+        )
         cmd_opts = parser.parse_args()
 
         cmd_opts.port = cmd_opts.port if 0 <= cmd_opts.port <= 65535 else 7865
@@ -57,6 +83,8 @@ class Config:
             cmd_opts.colab,
             cmd_opts.noparallel,
             cmd_opts.noautoopen,
+            cmd_opts.paperspace,
+            cmd_opts.is_cli,
         )
 
     # has_mps is only available in nightly pytorch (for now) and MasOS 12.3+.
@@ -84,9 +112,9 @@ class Config:
             ):
                 print("Found GPU", self.gpu_name, ", force to fp32")
                 self.is_half = False
-                use_fp32_config()
             else:
                 print("Found GPU", self.gpu_name)
+                print(use_fp32_config())
             self.gpu_mem = int(
                 torch.cuda.get_device_properties(i_device).total_memory
                 / 1024