Module burn::tensor

Module for the tensor.

Modules

• activation
  The activation module.
• backend
  The backend module.
• cast
  Tensor element casting.
• container
  The container module.
• loss
  The loss module.
• module
  The burn module.
• ops
  Operations on tensors module.
• quantization
  Tensor quantization module.
• repr
  Burn Tensor representaton

Macros

• dequant_op_quant
  Automatically applies dequantization -> float operation -> quantization.
• make_element
  Macro to implement the element trait for a type.

Structs

• Bool
  A type-level representation of the kind of a bool tensor.
• DataDeprecated
  Data structure for tensors.
• DataSerializeDeprecated
  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.
• TensorData
  Data structure for tensors.
• 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

• DType
• DataError
  The things that can go wrong when manipulating tensor data.
• Distribution
  Distribution for random value of a tensor.
• DistributionSamplerKind
  Distribution sampler kind for random value of a tensor.
• Precision
  Element precision trait for tensor.
• TensorPrimitive
  A primitive tensor representation.

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.
• MovedimArgs
  Trait used for movedim arguments
• Numeric
  Trait that list all operations that can be applied on all numerical tensors.
• RangesArg
  Trait used for slice arguments
• 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_data
  Compute the indices of the elements that are non-zero, grouped by element.
• cartesian_grid
  Generates a cartesian grid for the given tensor shape on the specified device. The generated tensor is of dimension D2 = D + 1, where each element at dimension D contains the cartesian grid coordinates for that element.
• check_closeness
  Checks the closeness of two tensors and prints the results.
• chunk
  Split the tensor along the given dimension into chunks.
• narrow
  Returns a new tensor with the given dimension narrowed to the given range.
• read_sync
  Read a future synchronously.
• 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.
• try_read_sync
  Read a future synchronously.

Type Aliases

• Device
  Device type used by the backend.