Crate burn_tensor

This library provides multiple tensor implementations hidden behind an easy to use API that supports reverse mode automatic differentiation.

Modules

• activation
  The activation module.
• backend
  The backend module.
• container
  The container module.
• loss
  The loss module.
• module
  The burn module.
• ops
  Operations on tensors module.

Macros

• make_element
  Macro to implement the element trait for a type.

Structs

• Bool
  A type-level representation of the kind of a bool tensor.
• Data
  Data structure for tensors.
• DataSerialize
  Data structure for serializing and deserializing tensor data.
• DimIter
  Iterator given by (Tensor::iter_dim).
• DistributionSampler
  Distribution sampler for random value of a tensor.
• Float
  A type-level representation of the kind of a float tensor
• Int
  A type-level representation of the kind of a int tensor.
• PrintOptions
  Options for Tensor pretty printing
• Shape
  Shape of a tensor.
• T
  Transpose marker (zero-size type). Used to sugar the transpose of a tensor, e.g.
• Tensor
  A tensor with a given backend, shape and data type.
• bf16
  A 16-bit floating point type implementing the bfloat16 format.
• f16
  A 16-bit floating point type implementing the IEEE 754-2008 standard binary16 a.k.a “half” format.

Enums

• Distribution
  Distribution for random value of a tensor.
• DistributionSamplerKind
  Distribution sampler kind for random value of a tensor.
• Precision
  Element precision trait for tensor.
• Reader
  Define how data is read, sync or async.

Traits

• BasicAutodiffOps
  Trait that list all operations that can be applied on all tensors on an autodiff backend.
• BasicOps
  Trait that list all operations that can be applied on all tensors.
• BroadcastArgs
  Trait used for broadcast arguments.
• Element
  Element trait for tensor.
• ElementComparison
  Element ordering trait.
• ElementConversion
  Element conversion trait for tensor.
• ElementPrecision
  Element precision trait for tensor.
• ElementRandom
  Element trait for random value of a tensor.
• Numeric
  Trait that list all operations that can be applied on all numerical tensors.
• ReshapeArgs
  Trait used for reshape arguments.
• TensorKind
  A type-level representation of the kind of a tensor.

Functions

• argsort
  Returns the indices that sort the elements of the input tensor along a given dimension.
• argwhere
  Compute the indices of the elements that are non-zero, grouped by element.
• chunk
  Split the tensor along the given dimension into chunks.
• narrow
  Returns a new tensor with the given dimension narrowed to the given range.
• set_print_options
  Set print options
• sort
  Sort the elements of the input tensor by value along a given dimension.
• sort_with_indices
  Sort the elements of the input tensor by value along a given dimension.

Type Aliases

• Device
  Device type used by the backend.