pykeio/ort v1.14.0

on GitHub

ort 1.14 is updated for ONNX Runtime v1.14.0. Please update to 1.14 as soon as possible, as this release contains important fixes and behaviour changes.

Changes (compared to v1.13)

• Simplified the process for downloading models.
• Made environments easier to use.
  • You can now use Environment::default() to return the global environment, or create a dummy one if one does not exist.
  • Environment::into_arc() automatically converts an Environment into an Arc<Environment> for cleaner code.
• Fixed an issue where tensors being passed to ONNX Runtime were not laid out contiguously in memory before being passed to the session, and using methods like Array::slice on an array before passing it to ort would result in unexpected results.
• Reduced bloat by making the download strategy optional, but enabled by default. See the README for more info. Developers of libraries using ort should consider using default-features = false.
• Added support for zero-copy deserialization for sessions loaded from memory via SessionBuilder::with_model_from_memory. This feature only works with .ort models.
  • Note that SessionBuilder::with_model_from_memory<'s>(&'s array) returns an InMemorySession<'s>, not a Session.
• Now using AllocatorType::Device instead of AllocatorType::Arena to potentially improve memory usage.
• Added support for the ROCm & DirectML execution providers (still working out ROCm build issues, see #16)
• Fixed some issues occurring with the compile strategy.
• Added memory pattern optimization with Session::with_memory_pattern
• ExecutionProvider::x_if_available has been removed, as the functionality is identical to ExecutionProvider::x.
• Removed the disable-build-script feature. Libraries on docs.rs using ort will no longer need to enable the disable-build-script feature in docs.rs build; ort will automatically detect if it is running in docs.rs and disable the build script.
• Removed the prefer-* features, as they were not very useful and potentially added unneeded complexity.
• Added support for scalar inputs (0-dimensional arrays) for models like Silero VAD.