import linalg

type

  Tensor[float32] = float32 or DVector32

  BackProp[T] = proc (gradient: Tensor[T]): Tensor[T] {.noSideEffect.}
    ## Proc for Backward propagation are typed `BackProp` and are (implicit) closures without side-effects
    # To ease search, backward propagation procedures are prefixed with bp_

  Node[T] = object
    ## Represent an operation
    ## Stores the gradient transformation for backprop in weights
    ## Stores indices of parent operation in parents
    weights: array[2, BackProp[T]]
    parents: array[2, int] #ref indices to parent nodes

  Context*[T] = object
    ## Tape / Wengert list. Contains the list of applied operations
    nodes: ref seq[Node[T]]

# Templates in Nim are always inlined. They are used for performance reason to save on function calls costs.

proc newContext*(T: typedesc[SomeReal]): Context[T] {.noSideEffect.} =
  ## Initialize a context (Tape / Wengert list)
  result.nodes = new seq[Node[T]]
  result.nodes[] = @[]

let ctx = newContext(float32)

# Cannot evaluate at compile time: T