package neural_nets_lib

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module Utils = Arrayjit.Utils
module Debug_runtime = Utils.Debug_runtime
type box = PrintBox.t
val sexp_of_box : 'a -> Sexplib0.Sexp.t
type dag = [
  1. | `Empty
  2. | `Pad of dag
  3. | `Frame of dag
  4. | `Align of [ `Left | `Center | `Right ] * [ `Top | `Center | `Bottom ] * dag
  5. | `Text of Base.string
  6. | `Box of box
  7. | `Vlist of Base.bool * dag Base.list
  8. | `Hlist of Base.bool * dag Base.list
  9. | `Table of dag Base.array Base.array
  10. | `Tree of dag * dag Base.list
  11. | `Embed_subtree_ID of Base.string
  12. | `Subtree_with_ID of Base.string * dag
]
val sexp_of_dag : dag -> Sexplib0.Sexp.t
val boxify : Base.int -> dag -> dag
val dag_to_box : dag -> box
val reformat_dag : Base.int -> dag -> box
type plot_spec =
  1. | Scatterplot of {
    1. points : (Base.float * Base.float) Base.array;
    2. pixel : Base.string;
    }
  2. | Line_plot of {
    1. points : Base.float Base.array;
    2. pixel : Base.string;
    }
  3. | Boundary_map of {
    1. callback : (Base.float * Base.float) -> Base.bool;
    2. pixel_true : Base.string;
    3. pixel_false : Base.string;
    }
  4. | Line_plot_adaptive of {
    1. callback : Base.float -> Base.float;
    2. mutable cache : Base.float Base.Map.M(Base.Float).t;
    3. pixel : Base.string;
    }
val sexp_of_plot_spec : plot_spec -> Sexplib0.Sexp.t
val concise_float : prec:int -> float -> Base.String.t
val plot : ?prec:int -> ?no_axes:bool -> ?canvas:Base.string Base.Array.t Base.Array.t -> ?size:(Base.int * Base.int) -> ?x_label:string -> ?y_label:Base.String.t -> plot_spec Base.list -> PrintBox.t
type table_row_spec =
  1. | Benchmark of {
    1. bench_title : Base.string;
    2. time_in_sec : Base.float;
    3. mem_in_bytes : Base.int;
    4. result_label : Base.string;
    5. result : Base.Sexp.t;
    }
val sexp_of_table_row_spec : table_row_spec -> Sexplib0.Sexp.t
val nolines : Base.String.t -> Base.String.t
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