package arrayjit

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in-package search v0.2.0

package arrayjit

arrayjit
- Arrayjit
arrayjit.ppx_arrayjit
- Ppx_arrayjit
  - Ppx_helper

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The code for operating on n-dimensional arrays.

module Lazy = Utils.Lazy

module Tn = Tnode

module Debug_runtime = Utils.Debug_runtime

val _get_local_debug_runtime : unit -> (module Minidebug_runtime.Debug_runtime)

type buffer =

| Node of Tn.t
| Merge_buffer of Tn.t

val sexp_of_buffer : buffer -> Sexplib0.Sexp.t

type fetch_op =

| Constant of Base.float
| Imported of Ops.global_identifier
| Slice of {
1. batch_idx : Indexing.static_symbol;
2. sliced : Tn.t;
}
| Embed_symbol of Indexing.static_symbol

Resets a array by performing the specified computation or data fetching.

and t =

| Noop
| Seq of t * t
| Block_comment of Base.string * t
(*
Same as the given code, with a comment.
*)
| Accum_binop of {
1. initialize_neutral : Base.bool;
2. accum : Ops.binop;
3. op : Ops.binop;
4. lhs : Tn.t;
5. rhs1 : buffer;
6. rhs2 : buffer;
7. projections : Indexing.projections Lazy.t;
}
| Accum_unop of {
1. initialize_neutral : Base.bool;
2. accum : Ops.binop;
3. op : Ops.unop;
4. lhs : Tn.t;
5. rhs : buffer;
6. projections : Indexing.projections Lazy.t;
}
| Fetch of {
1. array : Tn.t;
2. fetch_op : fetch_op;
3. dims : Base.int Base.array Lazy.t;
}

val sexp_of_fetch_op : fetch_op -> Sexplib0.Sexp.t

val sexp_of_t : t -> Sexplib0.Sexp.t

val get_name_exn : t -> Base.String.t

val recurrent_nodes : t -> (Tn.t, Tn.comparator_witness) Base.Set.t

val sequential : t Base.List.t -> t

val to_low_level : t -> Low_level.t

val flatten : t -> t list

val is_noop : t -> bool

val get_ident_within_code : ?no_dots:bool -> t -> Tn.t -> Base.String.t

val fprint_hum : 
  ?name:string ->
  ?static_indices:Indexing.static_symbol list ->
  unit ->
  Format.formatter ->
  t ->
  unit

val lower_proc : 
  unoptim_ll_source:Format.formatter Base.Option.t ->
  ll_source:Format.formatter Base.Option.t ->
  cd_source:Format.formatter option ->
  name:Base.string ->
  Indexing.static_symbol Base.list ->
  t ->
  Low_level.optimized