Add TORCHCODEC_FFMPEG_DIR to specify FFmpeg dynamic libs search path.

README.md

@@ -211,6 +211,10 @@ format you want. Refer to Nvidia's GPU support matrix for more details
    conda install -c conda-forge "torchcodec=*=*cuda*"
    ```
 
+### Specify FFmpeg Path Manually
+
+If torchcodec cannot detect the FFmpeg installation correctly, you can set the `TORCHCODEC_FFMPEG_DIR` environment variable to the directory containing the FFmpeg DLLs.
+
 ## Benchmark Results
 
 The following was generated by running [our benchmark script](./benchmarks/decoders/generate_readme_data.py) on a lightly loaded 22-core machine with an Nvidia A100 with

src/torchcodec/_core/ops.py

@@ -26,12 +26,15 @@
     # On windows we try to locate the FFmpeg DLLs and temporarily add them to
     # the DLL search path. This seems to be needed on some users machine, but
     # not on our CI. We don't know why.
-    if ffmpeg_path := shutil.which("ffmpeg"):
-
-        def expose_ffmpeg_dlls():  # noqa: F811
-            ffmpeg_dir = Path(ffmpeg_path).parent.absolute()
-            return os.add_dll_directory(str(ffmpeg_dir))  # that's the actual CM
+    if ffmpeg_dir := os.getenv("TORCHCODEC_FFMPEG_DIR"):
+        def expose_ffmpeg_dlls():
+            return os.add_dll_directory(str(ffmpeg_dir))
+    else:
+        if ffmpeg_path := shutil.which("ffmpeg"):
 
+            def expose_ffmpeg_dlls():  # noqa: F811
+                ffmpeg_dir = Path(ffmpeg_path).parent
+                return os.add_dll_directory(str(ffmpeg_dir))  # that's the actual CM
 
 with expose_ffmpeg_dlls():
     ffmpeg_major_version, core_library_path, _pybind_ops = (