Expand description
§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");§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.