Update whisper_cs_dev.py

Added load_cudnn to solve the LD_LIBRARY_PATH issue

whisper_cs_dev.py

@@ -6,9 +6,51 @@ import torchaudio
 import torch
 import re
 import time
+import sys
+from pathlib import Path
+import glob
+import ctypes
 
 from settings import DEBUG_MODE, MODEL_PATH_V2_FAST, MODEL_PATH_V2, LEFT_CHANNEL_TEMP_PATH, RIGHT_CHANNEL_TEMP_PATH, FAKE_AUDIO_PATH, RESAMPLING_FREQ
 
+def load_cudnn():
+
+    if not torch.cuda.is_available():
+        if DEBUG_MODE: print("[INFO] CUDA is not available, skipping cuDNN setup.")
+        return
+
+    if DEBUG_MODE: print(f"[INFO] sys.platform: {sys.platform}")
+    if sys.platform == "win32":
+        torch_lib_dir = Path(torch.__file__).parent / "lib"
+        if torch_lib_dir.exists():
+            os.add_dll_directory(str(torch_lib_dir))
+            if DEBUG_MODE: print(f"[INFO] Added DLL directory: {torch_lib_dir}")
+        else:
+            if DEBUG_MODE: print(f"[WARNING] Torch lib directory not found: {torch_lib_dir}")
+
+    elif sys.platform == "linux":
+        site_packages = Path(torch.__file__).resolve().parents[1]
+        cudnn_dir = site_packages / "nvidia" / "cudnn" / "lib"
+
+        if not cudnn_dir.exists():
+            if DEBUG_MODE: print(f"[ERROR] cudnn dir not found: {cudnn_dir}")
+            return
+
+        pattern = str(cudnn_dir / "libcudnn_cnn*.so*")
+        matching_files = sorted(glob.glob(pattern))
+        if not matching_files:
+            if DEBUG_MODE: print(f"[ERROR] No libcudnn_cnn*.so* found in {cudnn_dir}")
+            return
+
+        for so_path in matching_files:
+            try:
+                ctypes.CDLL(so_path, mode=ctypes.RTLD_GLOBAL)
+                if DEBUG_MODE: print(f"[INFO] Loaded: {so_path}")
+            except OSError as e:
+                if DEBUG_MODE: print(f"[WARNING] Failed to load {so_path}: {e}")
+    else:
+        if DEBUG_MODE: print(f"[WARNING] sys.platform is not win32 or linux")
+                
 
 def get_settings():
 
@@ -310,6 +352,7 @@ def generate(audio_path, use_v2_fast):
 
     start = time.time()
 
+    load_cudnn()
     device, compute_type = get_settings()
     model, fake_model = load_model(use_v2_fast, device, compute_type)
     split_input_stereo_channels(audio_path)