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# Namespace Microsoft.ML.OnnxRuntime.Tensors

### Classes

#### ArrayTensorExtensions

#### DenseTensor<T>

Represents a multi-dimensional collection of objects of type T that can be accessed by indices.
DenseTensor stores values in a contiguous sequential block of memory where all values are represented.

#### Tensor

Various methods for creating and manipulating Tensor<T>

#### Tensor<T>

Represents a multi-dimensional collection of objects of type T that can be accessed by indices.

#### TensorBase

This class is a base for all Tensors. It hosts maps with type traits.

#### TensorElementTypeInfo

Holds TensorElement traits

#### TensorTypeInfo

Helps typecasting. Holds Tensor element type traits.

### Structs

#### BFloat16

This value type represents A BFloat16 value it is blittable as defined in https://docs.microsoft.com/en-us/dotnet/framework/interop/blittable-and-non-blittable-types and as such, represented the same way in managed and native memories. This means that arrays of this type do not have to be copied to be passed to native memory but simply pinnned and read by native code. Thus, one can create a Tensor on top of an array of these structures and feed it directly to Onnxruntime library. Binary wise, it is the same as ushort[] (uint16_t in C++). However, we would like a separate type for type dispatching.

#### Float16

This value type represents A Float16 value it is blittable as defined in https://docs.microsoft.com/en-us/dotnet/framework/interop/blittable-and-non-blittable-types and as such, represented the same way in managed and native memories. This means that arrays of this type do not have to be copied to be passed to native memory but simply pinnned and read by native code. Thus, one can create a Tensor on top of an array of these structures and feed it directly to Onnxruntime library. Binary wise, it is the same as ushort[] (uint16_t in C++). However, we would like a separate type for type dispatching.

### Enums

#### TensorElementType

Supported Tensor DataType