use-ml-tensor

Tensor shape and metadata primitives for RustUse machine-learning workflows.

Experimental

use-ml-tensor is experimental while use-ml remains below 0.3.0.

Example

use use_ml_tensor::{TensorDType, TensorShape};

let shape = TensorShape::new([2, 3, 4])?;

assert_eq!(shape.rank(), 3);
assert_eq!(shape.num_elements(), Some(24));
assert_eq!(TensorDType::Float32.as_str(), "float32");
# Ok::<(), use_ml_tensor::TensorShapeError>(())

Scope

• Tensor shape, dimension, rank, and axis metadata.
• Dtype, layout, device-kind, and memory-format labels.
• Checked shape helpers such as rank and element-count metadata.

Non-goals

• Tensor math, autograd, model execution, tensor allocation, or framework bindings.
• Device APIs, runtime scheduling, kernels, CUDA, ONNX Runtime, or data movement.

License

Licensed under either Apache-2.0 or MIT.