Update app.py

app.py

@@ -1,58 +1,36 @@
 import os
 import ctypes
-import glob
 
-# Load cuDNN libraries explicitly before any other imports
+# Fix for faster-whisper + CUDA/cuDNN issue
+# Based on: https://github.com/SYSTRAN/faster-whisper/issues/1086
+
+# Explicitly load cuDNN libraries before CTranslate2 tries to use them
 try:
     import nvidia.cudnn
     cudnn_lib_path = os.path.join(os.path.dirname(nvidia.cudnn.__file__), 'lib')
     
-    # Add to LD_LIBRARY_PATH
-    current_ld_path = os.environ.get('LD_LIBRARY_PATH', '')
-    os.environ['LD_LIBRARY_PATH'] = f"{cudnn_lib_path}:{current_ld_path}"
-    
-    print(f"cuDNN path: {cudnn_lib_path}")
-    print(f"LD_LIBRARY_PATH: {os.environ['LD_LIBRARY_PATH']}")
-    
-    # List all files in the cuDNN lib directory
-    if os.path.exists(cudnn_lib_path):
-        print(f"\nFiles in {cudnn_lib_path}:")
-        cudnn_libs = []
-        for f in os.listdir(cudnn_lib_path):
-            if 'libcudnn' in f and f.endswith('.so') or '.so.' in f:
-                print(f"  - {f}")
-                cudnn_libs.append(f)
-        
-        # Load ALL cuDNN libraries in the correct order
-        # Order matters: load base libraries before ops libraries
-        lib_order = ['libcudnn.so', 'libcudnn_ops_infer.so', 'libcudnn_ops_train.so', 
-                     'libcudnn_cnn_infer.so', 'libcudnn_cnn_train.so',
-                     'libcudnn_adv_infer.so', 'libcudnn_adv_train.so']
-        
-        loaded_libs = []
-        for lib_name in lib_order:
-            # Find any version of this library
-            matching = [l for l in cudnn_libs if l.startswith(lib_name)]
-            if matching:
-                lib_path = os.path.join(cudnn_lib_path, matching[0])
-                try:
-                    ctypes.CDLL(lib_path, mode=ctypes.RTLD_GLOBAL)
-                    loaded_libs.append(matching[0])
-                    print(f"✅ Loaded: {matching[0]}")
-                except Exception as e:
-                    print(f"⚠️ Failed to load {matching[0]}: {e}")
-        
-        if loaded_libs:
-            print(f"\n✅ Successfully loaded {len(loaded_libs)} cuDNN libraries")
-        else:
-            print(f"⚠️ No cuDNN libraries were loaded")
-    else:
-        print(f"⚠️ cuDNN lib path doesn't exist: {cudnn_lib_path}")
+    print(f"Loading cuDNN from: {cudnn_lib_path}")
+    
+    # Load base cuDNN library first with RTLD_GLOBAL
+    import glob
+    cudnn_base = glob.glob(os.path.join(cudnn_lib_path, 'libcudnn.so*'))
+    if cudnn_base:
+        ctypes.CDLL(cudnn_base[0], mode=ctypes.RTLD_GLOBAL)
+        print(f"✅ Pre-loaded: {os.path.basename(cudnn_base[0])}")
+    
+    # Load cudnn_ops libraries
+    cudnn_ops = glob.glob(os.path.join(cudnn_lib_path, 'libcudnn_ops*.so*'))
+    for lib in cudnn_ops:
+        try:
+            ctypes.CDLL(lib, mode=ctypes.RTLD_GLOBAL)
+            print(f"✅ Pre-loaded: {os.path.basename(lib)}")
+        except Exception as e:
+            print(f"⚠️ Could not load {os.path.basename(lib)}: {e}")
             
+except ImportError:
+    print("⚠️ nvidia-cudnn-cu12 not installed, GPU may not work")
 except Exception as e:
     print(f"⚠️ cuDNN loading error: {e}")
-    import traceback
-    traceback.print_exc()
 
 # NOW import torch and other libraries
 import torch
@@ -74,17 +52,19 @@ try:
     from faster_whisper import WhisperModel
     USE_FASTER_WHISPER = True
     
-    device = "cuda" if torch.cuda.is_available() else "cpu"
-    compute_type = "float16" if torch.cuda.is_available() else "int8"
+    # FORCE CPU MODE - cuDNN issues with faster-whisper on HF Spaces
+    # See: https://github.com/SYSTRAN/faster-whisper/issues/1086
+    device = "cpu"
+    compute_type = "int8"
     
     print(f"Loading faster-whisper...")
-    print(f"  Device: {device}")
+    print(f"  Device: {device} (forced CPU due to cuDNN compatibility issues)")
     print(f"  Compute type: {compute_type}")
     
     model = WhisperModel("large-v3", device=device, compute_type=compute_type)
     
     print("✅ SUCCESS: Using faster-whisper (CTranslate2 backend)")
-    print(f"  Implementation: CTranslate2 backend")
+    print(f"  Implementation: CTranslate2 backend (CPU optimized)")
     print(f"  Model: Whisper Large V3")
     
 except ImportError as e: