[pull] main from m-bain:main

CUDNN_TROUBLESHOOTING.md

@@ -0,0 +1,76 @@
+# Troubleshooting cuDNN Loading Errors
+
+This guide helps resolve common cuDNN-related errors when running WhisperX on GPU. These issues typically occur when the system can't locate cuDNN libraries or finds conflicting versions.
+
+## Unable to Load cuDNN Libraries
+
+If you encounter the following error when running WhisperX:
+
+`Unable to load any of {libcudnn_cnn.so.9.1.0, libcudnn_cnn.so.9.1, libcudnn_cnn.so.9, libcudnn_cnn.so}`
+
+This means the cuDNN libraries are installed (via whisperx dependencies) but aren't in a location where the system's dynamic linker can find them.
+
+### Solution 1: Add to LD_LIBRARY_PATH (Recommended)
+
+Add this at the start of your Python script or notebook:
+
+```python
+import os
+
+# Get current LD_LIBRARY_PATH
+original = os.environ.get("LD_LIBRARY_PATH", "")
+
+cudnn_path = "/usr/local/lib/python3.12/dist-packages/nvidia/cudnn/lib/"
+os.environ['LD_LIBRARY_PATH'] = original + ":" + cudnn_path
+```
+
+**Note:** Adjust the Python version (`python3.12`) to match your environment.
+
+### Solution 2: Symlink to LD_LIBRARY_PATH Directory
+
+If Solution 1 didn't work and you still get the "unable to load" error, symlink the libraries to a directory that's already in your `LD_LIBRARY_PATH`:
+
+1. Check what's in your LD_LIBRARY_PATH: `echo "$LD_LIBRARY_PATH"`
+2. Assuming that there is only one path set.  
+   Symlink the downloaded libcudnn files to that path:  
+   `ln -s /usr/local/lib/python3.12/dist-packages/nvidia/cudnn/lib/libcudnn* "$LD_LIBRARY_PATH"/`
+
+   **Note:** If `LD_LIBRARY_PATH` contains multiple paths (separated by `:`), pick one directory and use it instead of `"$LD_LIBRARY_PATH"`. For example: `/usr/lib/x86_64-linux-gnu/`
+
+## cuDNN Version Incompatibility
+
+If you encounter this error:
+
+```
+RuntimeError: cuDNN version incompatibility: PyTorch was compiled against (9, 10, 2) but found runtime version (9, 2, 1)
+```
+
+This means PyTorch is finding a different cuDNN version than the one it was compiled with. **PyTorch comes bundled with its own cuDNN**, but a conflicting cuDNN in `LD_LIBRARY_PATH` is taking precedence.
+
+### Solution: Remove Conflicting cuDNN from Path
+
+Check if there's a conflicting cuDNN path:
+
+```bash
+echo $LD_LIBRARY_PATH
+```
+
+If you see paths pointing to older cuDNN installations (e.g., system-installed cuDNN or manually downloaded), try one of these:
+
+**Option 1: Clear LD_LIBRARY_PATH temporarily**
+
+```python
+import os
+# Let PyTorch use its bundled cuDNN
+os.environ.pop('LD_LIBRARY_PATH', None)
+```
+
+**Option 2: Set LD_LIBRARY_PATH to only the correct version**
+
+```python
+import os
+# Point only to the cuDNN that matches PyTorch's compiled version
+os.environ['LD_LIBRARY_PATH'] = "/usr/local/lib/python3.12/dist-packages/nvidia/cudnn/lib/"
+```
+
+**Note:** This error is unlikely on a clean install. If it occurs anyway, [open an issue](https://github.com/m-bain/whisperX/issues). If you've modified system libraries or CUDA/cuDNN, the options above should help resolve most cases.

pyproject.toml

@@ -2,7 +2,7 @@
 urls = { repository = "https://github.com/m-bain/whisperx" }
 authors = [{ name = "Max Bain" }]
 name = "whisperx"
-version = "3.7.2"
+version = "3.7.4"
 description = "Time-Accurate Automatic Speech Recognition using Whisper."
 readme = "README.md"
 requires-python = ">=3.9, <3.14"
@@ -19,8 +19,8 @@ dependencies = [
     "av<16.0.0",
     "numpy>=2.1.0,<2.3.0; python_version >='3.13'",
     "pyannote-audio>=3.3.2,<4.0.0",
-    "torch>=2.7.1",
-    "torchaudio",
+    "torch~=2.8.0",
+    "torchaudio~=2.8.0",
     "transformers>=4.48.0",
     "triton>=3.3.0; sys_platform == 'linux' and platform_machine == 'x86_64'" # only install triton on x86_64 Linux
 ]