Config: Add experimental torch cuda malloc backend

This option saves some VRAM, but does have the chance to error out.
Add this in the experimental config section.

Signed-off-by: kingbri <bdashore3@proton.me>

common/args.py

@@ -140,3 +140,8 @@ def add_developer_args(parser: argparse.ArgumentParser):
         type=str_to_bool,
         help="Disables API request streaming",
     )
+    developer_group.add_argument(
+        "--cuda-malloc-backend",
+        type=str_to_bool,
+        help="Disables API request streaming",
+    )

config_sample.yml

@@ -35,7 +35,7 @@ sampling:
   # WARNING: Using this can result in a generation speed penalty
   #override_preset: 
 
-# Options for development
+# Options for development and experimentation
 developer:
   # Skips exllamav2 version check (default: False)
   # It's highly recommended to update your dependencies rather than enabling this flag
@@ -46,6 +46,10 @@ developer:
   # A kill switch for turning off SSE in the API server
   #disable_request_streaming: False
 
+  # Enable the torch CUDA malloc backend (default: False)
+  # This can save a few MBs of VRAM, but has a risk of errors. Use at your own risk.
+  #cuda_malloc_backend: False
+
 # Options for model overrides and loading
 model:
   # Overrides the directory to look for models (default: models)

main.py

@@ -1,4 +1,5 @@
 """The main tabbyAPI module. Contains the FastAPI server and endpoints."""
+import os
 import pathlib
 import uvicorn
 from asyncio import CancelledError
@@ -600,6 +601,11 @@ def entrypoint(args: Optional[dict] = None):
     else:
         check_exllama_version()
 
+    # Enable CUDA malloc backend
+    if unwrap(developer_config.get("cuda_malloc_backend"), False):
+        os.environ["PYTORCH_CUDA_ALLOC_CONF"] = "backend:cudaMallocAsync"
+        logger.warning("Enabled the experimental CUDA malloc backend.")
+
     network_config = get_network_config()
 
     # Initialize auth keys