Module ort::tensor

Module containing tensor types.

Two main types of tensors are available.

The first one, [OrtTensor], is an owned tensor that is backed by ndarray. This kind of tensor is used to pass input data for the inference.

The second one, OrtOwnedTensor, is used internally to pass to the ONNX Runtime inference execution to place its output values. Once “extracted” from the runtime environment, this tensor will contain an ndarray::ArrayView containing a view of the data. When going out of scope, this tensor will free the required memory on the C side.

NOTE: Tensors are not meant to be created directly. When performing inference, the Session::run method takes an ndarray::Array as input (taking ownership of it) and will convert it internally to an [OrtTensor]. After inference, a OrtOwnedTensor will be returned by the method which can be derefed into its internal ndarray::ArrayView.

Re-exports

• pub use self::ndarray_tensor::NdArrayExtensions;
• pub use self::ort_owned_tensor::OrtOwnedTensor;

Modules

• ndarray_tensor
• ort_owned_tensor

Enums

• TensorData
  Represents the possible ways tensor data can be accessed.
• TensorElementDataType
  Enum mapping ONNX Runtime’s supported tensor data types.

Traits

• IntoTensorElementDataType
  Trait used to map Rust types (for example f32) to ONNX tensor element data types (for example Float).
• TensorDataToType
  Trait used to map ONNX Runtime types to Rust types.
• Utf8Data
  Adapter for common Rust string types to ONNX strings.