Source file owl_base_dense_ndarray_generic.ml
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# 1 "src/base/dense/owl_base_dense_ndarray_generic.ml"
[@@@warning "-32"]
open Bigarray
open Owl_types
type ('a, 'b) t = ('a, 'b, c_layout) Genarray.t
type ('a, 'b) kind = ('a, 'b) Bigarray.kind
module Scalar = Owl_base_maths
let _prepend_dims dims desired_len =
let dims_len = Array.length dims in
if dims_len >= desired_len then dims
else (Array.append (Array.make (desired_len - dims_len) 1) dims)
let _get_broadcasted_dims dims_a dims_b =
let len_c = Stdlib.max (Array.length dims_a) (Array.length dims_b) in
let ext_dims_a = _prepend_dims dims_a len_c in
let ext_dims_b = _prepend_dims dims_b len_c in
let dims_c = Array.make len_c 0 in
for i = 0 to len_c - 1 do
let val_a = ext_dims_a.(i) in
let val_b = ext_dims_b.(i) in
if val_a = val_b then
dims_c.(i) <- val_a
else
if val_a != 1 && val_b != 1
then raise (Invalid_argument "The arrays cannot be broadcast into the same shape")
else dims_c.(i) <- (Stdlib.max val_a val_b)
done;
(ext_dims_a, ext_dims_b, dims_c)
let _next_index ind dims =
let num_dims = Array.length ind in
let p = ref (num_dims - 1) in
let ok = ref false in
while !p >= 0 && not !ok do
if ind.(!p) + 1 < dims.(!p) then (
ind.(!p) <- (ind.(!p) + 1);
ok := true;
)
else (
ind.(!p) <- 0;
p := !p - 1;
)
done;
!ok
let _get_broadcasted_index ind dims =
let num_dims = Array.length dims in
let calc_fun =
(fun i ->
let max_ind = dims.(i) in
let ind_val = ind.(i) in
if ind_val < max_ind
then ind_val
else (
if max_ind = 1
then 0
else raise (Invalid_argument "not broadcasted correctly")
)
) in
(Array.init num_dims calc_fun)
let _apply_perm arr perm =
Array.init (Array.length arr) (fun i -> arr.(perm.(i)))
let _draw_int_samples replacement range count =
if not replacement && count > range then
raise (Invalid_argument "cannot draw that many samples from the given range, without replacement")
else (
let pop_cnt = ref range in
let pop = Array.init !pop_cnt (fun i -> i) in
let rand_gen = Random.State.make_self_init() in
let draw_fun = (fun _ ->
let index = Random.State.int rand_gen !pop_cnt in
let sample = pop.(index) in
if replacement then
sample
else (
pop_cnt := !pop_cnt - 1;
pop.(index) <- pop.(!pop_cnt);
sample
)
)
in
Array.init count draw_fun
)
let _enumerate_slice_def dim ?(step) start stop =
let start = if start < 0 then dim + start else start in
let stop = if stop < 0 then dim + stop else stop in
let step = match step with
| Some x -> x
| None -> if (start <= stop) then 1 else -1
in
assert (((start <= stop) && (step > 0)) || ((start > stop) && (step < 0)));
let step_abs = Stdlib.abs step in
let len = ((Stdlib.abs (stop - start)) + step_abs) / step_abs in
(Array.init len (fun i -> start + i * step))
let _expand_slice_indices index_list dims =
let rank = Array.length dims in
let sdef_len = List.length index_list in
let _expand_slice_index = (
fun i ind -> match ind with
| [] -> Array.init dims.(i) (fun i -> i)
| [start] -> _enumerate_slice_def dims.(i) start start
| [start; stop] -> _enumerate_slice_def dims.(i) start stop
| [start; stop; step] -> _enumerate_slice_def dims.(i) ~step:step start stop
| x -> Array.of_list x
) in
Array.append
(Array.of_list (List.mapi _expand_slice_index index_list))
(Array.init (rank - sdef_len)
(fun p -> Array.init dims.(p + sdef_len) (fun i -> i)))
let reset x =
let _kind = Genarray.kind x in
Genarray.fill x (Owl_const.zero _kind)
let empty kind dims = Genarray.create kind c_layout dims
let create kind dims value =
let x = empty kind dims in
Genarray.fill x value;
x
let create_ ~out a = Genarray.fill out a
let zeros kind dims = create kind dims (Owl_const.zero kind)
let zeros_ ~out = reset out
let ones kind dims = create kind dims (Owl_const.one kind)
let ones_ ~out = Genarray.(fill out (Owl_const.one (kind out)))
let shape x = Genarray.dims x
let nth_dim x i = Genarray.nth_dim x i
let num_dims x = Array.length (shape x)
let numel x = Owl_utils.numel x
let kind x = Genarray.kind x
let get x index = (Genarray.get x index)
let set x index value = (Genarray.set x index value)
let eye kind n =
let m = zeros kind [|n; n|] in
for i = 0 to n - 1 do
set m [|i; i|] (Owl_const.one kind)
done;
m
let get_slice index_list varr =
let dims = shape varr in
let rank = Array.length dims in
let index_array = _expand_slice_indices index_list dims in
let slice_dims = Array.map (fun a -> Array.length a) index_array in
let slice_varr = empty (kind varr) slice_dims in
let slice_ind = Array.make rank 0 in
let original_ind = Array.make rank 0 in
let should_stop = ref false in
while not !should_stop do
for i = 0 to rank - 1 do
original_ind.(i) <- (index_array.(i)).(slice_ind.(i))
done;
Genarray.set slice_varr slice_ind (Genarray.get varr original_ind);
if not (_next_index slice_ind slice_dims) then
should_stop := true
done;
slice_varr
let set_slice index_list varr slice_varr =
let dims = shape varr in
let rank = Array.length dims in
let index_array = _expand_slice_indices index_list dims in
let slice_dims = Array.map (fun a -> Array.length a) index_array in
let slice_varr = reshape slice_varr slice_dims in
let slice_ind = Array.make rank 0 in
let original_ind = Array.make rank 0 in
let should_stop = ref false in
while not !should_stop do
for i = 0 to rank - 1 do
original_ind.(i) <- (index_array.(i)).(slice_ind.(i))
done;
Genarray.set varr original_ind (Genarray.get slice_varr slice_ind);
if not (_next_index slice_ind slice_dims) then
should_stop := true
done
let reshape x d =
let minus_one = Owl_utils.Array.count d (-1) in
assert (minus_one <= 1);
if minus_one = 0 then reshape x d
else (
let n = numel x in
let m = Array.fold_right ( * ) d (-1) in
let e = Array.map (fun a -> if a = -1 then n / m else a) d in
reshape x e
)
let flatten x = reshape x [|(numel x)|]
let fill x a = Genarray.fill x a
let copy x =
let y = empty (kind x) (shape x) in
Genarray.blit x y;
y
let copy_ ~out x =
let src = flatten x in
let dst = flatten out in
Genarray.blit src dst
let reshape_ ~out x =
if not (x == out) then
copy_ ~out x
let reverse x =
let n = numel x in
let y = empty (kind x) (shape x) in
let y_flat = reshape y [|n|] in
let x_flat = reshape x [|n|] in
for i = 0 to n - 1 do
set y_flat [|i|] (get x_flat [|n - 1 - i|])
done;
y
let reverse_ ~out x =
let n = numel x in
let y_flat = reshape out [|n|] in
let x_flat = reshape x [|n|] in
for i = 0 to n - 1 do
set y_flat [|i|] (get x_flat [|n - 1 - i|])
done
let map_ f x =
let y = flatten x |> array1_of_genarray in
let length = numel x in
for i = 0 to length - 1 do
(Array1.unsafe_set y i (f (Array1.unsafe_get y i)))
done
let mapi_ f x =
let y = flatten x |> array1_of_genarray in
let length = numel x in
for i = 0 to length - 1 do
(Array1.unsafe_set y i (f i (Array1.unsafe_get y i)))
done
let init kind dims f =
let varr = empty kind dims in
let varr_flat = flatten varr |> array1_of_genarray in
let n = numel varr in
for i = 0 to n - 1 do
Array1.unsafe_set varr_flat i (f i)
done;
varr
let init_nd k d f =
let x = empty k d in
let y = array1_of_genarray (flatten x) in
let n = numel x in
let s = Owl_utils.calc_stride d in
let j = Array.copy s in
for i = 0 to n - 1 do
Owl_utils.index_1d_nd i j s;
Array1.unsafe_set y i (f j)
done;
x
let map f x =
let y = copy x in
map_ f y;
y
let mapi f x =
let y = copy x in
let y' = flatten y |> array1_of_genarray in
for i = 0 to (Array1.dim y') - 1 do
let a = Array1.unsafe_get y' i in
Array1.unsafe_set y' i (f i a)
done;
y
let strides x = x |> shape |> Owl_utils.calc_stride
let slice_size x = x |> shape |> Owl_utils.calc_slice
let foldi ?axis f a x =
let x' = flatten x |> array1_of_genarray in
match axis with
| Some axis -> (
let m, n, o, s = Owl_utils.reduce_params axis x in
let start_x = ref 0 in
let start_y = ref 0 in
let incy = ref 0 in
let k = ref 0 in
let y = create (kind x) s a in
let y' = flatten y |> array1_of_genarray in
for _i = 0 to m - 1 do
for j = 0 to n - 1 do
let b = Array1.unsafe_get y' (!start_y + !incy) in
let c = Array1.unsafe_get x' (!start_x + j) in
Array1.unsafe_set y' (!start_y + !incy) (f !k b c);
if !incy + 1 = o then incy := 0
else incy := !incy + 1;
k := !k + 1;
done;
start_x := !start_x + n;
start_y := !start_y + o;
done;
y
)
| None -> (
let b = ref a in
for i = 0 to (numel x) - 1 do
let c = Array1.unsafe_get x' i in
b := f i !b c
done;
create (kind x) [|1|] !b
)
let fold ?axis f a x = foldi ?axis (fun _ b c -> f b c) a x
let scani ?axis f x =
let d = num_dims x in
let a = match axis with
| Some a -> a
| None -> d - 1
in
assert (0 <= a && a < d);
let _stride = strides x in
let _slicez = slice_size x in
let m = (numel x) / _slicez.(a) in
let n = _slicez.(a) - _stride.(a) in
let incx = _slicez.(a) in
let incy = _slicez.(a) in
let start_x = ref 0 in
let start_y = ref _stride.(a) in
let k = ref 0 in
let y = copy x in
let y' = flatten y |> array1_of_genarray in
for _i = 0 to m - 1 do
for j = 0 to n - 1 do
let b = Array1.unsafe_get y' (!start_x + j) in
let c = Array1.unsafe_get y' (!start_y + j) in
Array1.unsafe_set y' (!start_y + j) (f !k b c);
k := !k + 1
done;
start_x := !start_x + incx;
start_y := !start_y + incy;
done;
y
let scan ?axis f x = scani ?axis (fun _ a b -> f a b) x
let iteri f x =
let x' = flatten x |> array1_of_genarray in
for i = 0 to (Array1.dim x') - 1 do
let a = Array1.unsafe_get x' i in
f i a
done
let iter f x =
let x' = flatten x |> array1_of_genarray in
for i = 0 to (Array1.dim x') - 1 do
let a = Array1.unsafe_get x' i in
f a
done
let filteri f x =
let s = Owl_utils.Stack.make () in
iteri (fun i y ->
if f i y = true then
Owl_utils.Stack.push s i
) x;
Owl_utils.Stack.to_array s
let filter f x = filteri (fun _ y -> f y) x
let sequential_ ?a ?step ~out =
let k = kind out in
let a = match a with
| Some a -> a
| None -> Owl_const.zero k
in
let step = match step with
| Some step -> step
| None -> Owl_const.one k
in
let _add = Owl_base_dense_common._add_elt k in
let _mul = Owl_base_dense_common._mul_elt k in
let _flt = Owl_base_dense_common._float_typ_elt k in
mapi_ (fun i _ ->
_add a (_mul (_flt (float_of_int i)) step)
) out
let sequential k ?a ?step dimension =
let x = empty k dimension in
sequential_ ?a ?step ~out:x;
x
let of_array kind arr dims =
let varr = empty kind dims in
let flat_varr = flatten varr |> array1_of_genarray in
let n = numel varr in
for i = 0 to n - 1 do
Array1.unsafe_set flat_varr i arr.(i)
done;
varr
let uniform k ?a ?b dims =
let a = match a with Some a -> a | None -> Owl_const.zero k in
let b = match b with Some b -> b | None -> Owl_const.one k in
let uniform_fun = Owl_base_dense_common._uniform_elt k a b in
let x = empty k dims in
map_ uniform_fun x;
x
let uniform_ ?a ?b ~out =
let k = kind out in
let a = match a with Some a -> a | None -> Owl_const.zero k in
let b = match b with Some b -> b | None -> Owl_const.one k in
let uniform_fun = Owl_base_dense_common._uniform_elt k a b in
map_ uniform_fun out
let bernoulli k ?(p=0.5) dims =
let bernoulli_fun = fun _ ->
let a = Owl_base_stats.bernoulli_rvs ~p in
Owl_base_dense_common._float_typ_elt k a
in
let x = empty k dims in
map_ bernoulli_fun x;
x
let bernoulli_ ?(p=0.5) ~out =
let k = kind out in
let bernoulli_fun = fun _ ->
let a = Owl_base_stats.bernoulli_rvs ~p in
Owl_base_dense_common._float_typ_elt k a
in
map_ bernoulli_fun out
let gaussian k ?mu ?sigma dims =
let mu = match mu with Some a -> a | None -> Owl_const.zero k in
let sigma = match sigma with Some a -> a | None -> Owl_const.one k in
let gaussian_fun = Owl_base_dense_common._gaussian_elt k mu sigma in
let x = empty k dims in
map_ gaussian_fun x;
x
let gaussian_ ?mu ?sigma ~out =
let k = kind out in
let mu = match mu with Some a -> a | None -> Owl_const.zero k in
let sigma = match sigma with Some a -> a | None -> Owl_const.one k in
let gaussian_fun = Owl_base_dense_common._gaussian_elt k mu sigma in
map_ gaussian_fun out
let print ?max_row ?max_col ?header ?fmt x =
let dims = shape x in
let rank = Array.length dims in
let n = dims.(rank - 1) in
let max_row = match max_row with
| Some a -> Some a
| None -> Some ((numel x) / n)
in
let max_col = match max_col with
| Some a -> Some a
| None -> Some n
in
Owl_pretty.print_dsnda ?max_row ?max_col ?header ?elt_to_str_fun:fmt x
let tile varr reps =
let dims = shape varr in
let result_rank = Stdlib.max (Array.length dims) (Array.length reps) in
let dims = _prepend_dims dims result_rank in
let reps = _prepend_dims reps result_rank in
let varr = reshape varr dims in
let result_dims = Array.map2 (fun a b -> a * b) dims reps in
let result_varr = empty (kind varr) result_dims in
let result_ind = Array.make result_rank 0 in
let original_ind = Array.make result_rank 0 in
let should_stop = ref false in
while not !should_stop do
for i = 0 to result_rank - 1 do
original_ind.(i) <- (Stdlib.(mod) result_ind.(i) dims.(i))
done;
Genarray.set result_varr result_ind (Genarray.get varr original_ind);
if not (_next_index result_ind result_dims) then
should_stop := true
done;
result_varr
let split ?(axis=0) parts varr =
let dims = shape varr in
let rank = Array.length dims in
let pos = ref 0 in
let axis_indices = Array.map (fun d -> (pos := !pos + d; [!pos - d; !pos - 1])) parts in
let slices_defs =
Array.map (fun ind ->
Array.to_list (Array.init rank
(fun i -> if i = axis then ind else [])))
axis_indices
in
(Array.map (fun def -> get_slice def varr) slices_defs)
let squeeze ?(axis=[||]) x =
let a = match Array.length axis with
| 0 -> Array.init (num_dims x) (fun i -> i)
| _ -> axis
in
let s = Owl_utils.Array.filteri (fun i v ->
not (v == 1 && Array.mem i a)
) (shape x)
in
reshape x s
let expand ?(hi=false) x d =
let d0 = d - (num_dims x) in
match d0 > 0 with
| true -> (
if hi = true then
Owl_utils.Array.pad `Right 1 d0 (shape x) |> reshape x
else
Owl_utils.Array.pad `Left 1 d0 (shape x) |> reshape x
)
| false -> x
let draw ?(axis=0) varr count =
let dims = shape varr in
let rank = Array.length dims in
let indices = _draw_int_samples false dims.(axis) count in
(get_slice
(List.init rank
(fun i -> if i = axis then (Array.to_list indices) else []))
varr,
indices)
let _expand_padding_index d s =
let ls = Array.length s in
let ld = Array.length d in
let d = Owl_utils.Array.pad `Right [|0;0|] (ls - ld) d in
Array.map (function
| [||] -> [|0;0|]
| [|x|] -> [|x;x|]
| x -> x
) d
let rec _copy_to_padding p1 ls l0 l1 i0 i1 d0 d1 s0 s1 x0 x1 =
if d0 < d1 then (
for i = 0 to s0.(d0) - 1 do
i0.(d0) <- i;
i1.(d0) <- i + p1.(d0).(0);
_copy_to_padding p1 ls l0 l1 i0 i1 (d0 + 1) d1 s0 s1 x0 x1;
i0.(d0) <- 0;
i1.(d0) <- p1.(d0).(0);
done
)
else (
let j0 = Owl_utils.index_nd_1d i0 l0 in
let j1 = Owl_utils.index_nd_1d i1 l1 in
let subx = Genarray.sub_left x0 j0 ls.(d0) in
let suby = Genarray.sub_left x1 j1 ls.(d0) in
Genarray.blit subx suby
)
let _highest_padding_dimension p =
let l = Array.length p - 1 in
let d = ref l in
(try for i = l downto 0 do
d := i;
if p.(i) <> [|0;0|] then failwith "pad:highest_padding_dimension"
done with _exn -> ());
!d
let pad ?v d x =
let k = kind x in
let v = match v with
| Some v -> v
| None -> Owl_const.zero k
in
let s0 = shape x in
let x' = flatten x in
let p1 = _expand_padding_index (Owl_utils.llss2aarr d) s0 in
let s1 = Array.map2 (fun m n -> m + n.(0) + n.(1)) s0 p1 in
let s' = Owl_utils_array.fold_right ( * ) s1 1 in
let y' = create k [|s'|] v in
let ls = Owl_utils.calc_slice s0 in
let l0 = Owl_utils.calc_stride s0 in
let l1 = Owl_utils.calc_stride s1 in
let i0 = Array.make (num_dims x) 0 in
let i1 = Array.map (fun a -> a.(0)) p1 in
let d0 = 0 in
let d1 = _highest_padding_dimension p1 in
_copy_to_padding p1 ls l0 l1 i0 i1 d0 d1 s0 s1 x' y';
reshape y' s1
let concatenate ?(axis=0) varrs =
let varrs_num = Array.length varrs in
let all_dims = Array.map shape varrs in
let prefix_dims = Array.sub all_dims.(0) 0 axis in
let sum_axis_dims = Array.fold_left (fun x a -> x + a.(axis)) 0 all_dims in
let suffix_dims = Array.sub all_dims.(0)
(axis + 1) ((Array.length all_dims.(0)) - axis - 1)
in
let result_dims =
Array.concat [prefix_dims; [|sum_axis_dims|]; suffix_dims]
in
let result_varr = empty (kind varrs.(0)) result_dims in
let prefix_dims_product = Array.fold_left ( * ) 1 prefix_dims in
let suffix_dims_product = Array.fold_left ( * ) 1 suffix_dims in
let reshaper_fun = (
fun varr ->
let old_shape = shape varr in
let new_shape =
[|prefix_dims_product; old_shape.(axis) * suffix_dims_product|]
in
reshape varr new_shape
) in
let reshaped_result = reshaper_fun result_varr in
let reshaped_varrs = Array.map reshaper_fun varrs in
begin
for i = 0 to prefix_dims_product - 1 do
let start_index = ref 0 in
let result_slice = Genarray.slice_left reshaped_result [|i|] in
for j = 0 to varrs_num - 1 do
let src_slice = Genarray.slice_left reshaped_varrs.(j) [|i|] in
let block_len = all_dims.(j).(axis) * suffix_dims_product in
let result_sub =
Genarray.sub_left result_slice !start_index block_len in
Genarray.blit src_slice result_sub;
start_index := !start_index + block_len
done
done;
result_varr
end
let repeat x reps =
if Array.exists ((>) 1) reps then
failwith "repeat: repetition must be >= 1";
let x_dims = num_dims x in
assert (Array.length reps = x_dims);
if (Array.for_all ((=) 1) reps) = true then
copy x
else (
let _kind = kind x in
let x' = flatten x in
let x_shape = shape x in
let y_shape = Array.map2 ( * ) x_shape reps in
let num = Owl_utils_array.fold_right ( * ) y_shape 1 in
let y' = empty _kind [|num|] in
if x_dims = 1 then (
let ofsy = ref 0 in
for i = 0 to numel x - 1 do
let elemx = get x' [|i|] in
for _j = 0 to reps.(0) - 1 do
set y' [|!ofsy|] elemx;
ofsy := !ofsy + 1
done
done
)
else (
let highest_dim = x_dims - 1 in
let slice_x = Owl_utils.calc_slice x_shape in
let stride_y = Owl_utils.calc_stride y_shape in
let hd = ref (highest_dim + 1) in
while !hd > 1 && reps.(!hd - 1) = 1 do
hd := !hd - 1;
done;
let hd = if !hd = highest_dim + 1 then highest_dim else !hd in
let block_num = Array.make hd 0 in
for i = 0 to hd - 1 do
block_num.(i) <- slice_x.(i) / slice_x.(hd);
done;
let counter = Array.make hd 0 in
let ofsx = ref 0 in
let ofsy = ref 0 in
let block_sz = reps.(hd) in
for _i = 0 to block_num.(0) - 1 do
let ofsy_sub = ref !ofsy in
if block_sz = 1 then (
let subx = Genarray.sub_left x' !ofsx slice_x.(hd) in
let suby = Genarray.sub_left y' !ofsy_sub slice_x.(hd) in
Genarray.blit subx suby
)
else (
for j = 0 to slice_x.(hd) - 1 do
let elemx = get x' [|!ofsx + j|] in
for k = 0 to block_sz - 1 do
set y' [|!ofsy_sub + k|] elemx
done;
ofsy_sub := !ofsy_sub + block_sz
done
);
ofsx := !ofsx + slice_x.(hd);
ofsy := !ofsy + stride_y.(hd - 1) * reps.(hd - 1);
for j = hd - 1 downto 1 do
let c = counter.(j) in
if c + 1 = block_num.(j) then (
ofsy := !ofsy + stride_y.(j - 1) * (reps.(j - 1) - 1);
);
counter.(j) <- if c + 1 = block_num.(j) then 0 else c + 1
done
done;
for d = hd - 1 downto 0 do
let block_num = Array.make (d + 1) 0 in
for i = 0 to d do
block_num.(i) <- slice_x.(i) / slice_x.(d + 1);
done;
let ofsy = ref 0 in
let block_sz = stride_y.(d) in
let counter = Array.make hd 0 in
for _i = 0 to block_num.(0) - 1 do
let ofsy_sub = ref (!ofsy + block_sz) in
for _j = 1 to reps.(d) - 1 do
let subx = Genarray.sub_left y' !ofsy block_sz in
let suby = Genarray.sub_left y' !ofsy_sub block_sz in
Genarray.blit subx suby;
ofsy_sub := !ofsy_sub + block_sz
done;
ofsy := !ofsy + stride_y.(d) * reps.(d);
for j = d - 1 downto 0 do
let c = counter.(j) in
if c + 1 = block_num.(j + 1) then (
ofsy := !ofsy + stride_y.(j) * (reps.(j) - 1);
);
counter.(j) <- if c + 1 = block_num.(j + 1) then 0 else c + 1
done
done
done
);
reshape y' y_shape
)
let abs x =
let _kind = kind x in
let _func = Owl_base_dense_common._abs_elt _kind in
map _func x
let abs_ ?out x =
let _kind = kind x in
let _func = Owl_base_dense_common._abs_elt _kind in
let out = match out with Some o -> o | None -> x in
map_ _func out
let conj x =
let _kind = kind x in
let _func = Owl_base_dense_common._conj_elt _kind in
map _func x
let conj_ ?out x =
let _kind = kind x in
let _func = Owl_base_dense_common._conj_elt _kind in
let out = match out with Some o -> o | None -> x in
map _func out
let neg x =
let _kind = kind x in
let _func = Owl_base_dense_common._neg_elt _kind in
map _func x
let neg_ ?out x =
let _kind = kind x in
let _func = Owl_base_dense_common._neg_elt _kind in
let out = match out with Some o -> o | None -> x in
map_ _func out
let reci x =
let _kind = kind x in
let _func = Owl_base_dense_common._inv_elt _kind in
map _func x
let reci_ ?out x =
let _kind = kind x in
let _func = Owl_base_dense_common._inv_elt _kind in
let out = match out with Some o -> o | None -> x in
map_ _func out
let floor x =
let _kind = kind x in
let _func = Owl_base_dense_common._floor_elt _kind in
map _func x
let floor_ ?out x =
let _kind = kind x in
let _func = Owl_base_dense_common._floor_elt _kind in
let out = match out with Some o -> o | None -> x in
map_ _func out
let ceil x =
let _kind = kind x in
let _func = Owl_base_dense_common._ceil_elt _kind in
map _func x
let ceil_ ?out x =
let _kind = kind x in
let _func = Owl_base_dense_common._ceil_elt _kind in
let out = match out with Some o -> o | None -> x in
map_ _func out
let round x =
let _kind = kind x in
let _func = Owl_base_dense_common._round_elt _kind in
map _func x
let round_ ?out x =
let _kind = kind x in
let _func = Owl_base_dense_common._round_elt _kind in
let out = match out with Some o -> o | None -> x in
map_ _func out
let trunc x =
let _kind = kind x in
let _func = Owl_base_dense_common._trunc_elt _kind in
map _func x
let trunc_ ?out x =
let _kind = kind x in
let _func = Owl_base_dense_common._trunc_elt _kind in
let out = match out with Some o -> o | None -> x in
map_ _func out
let fix x =
let _kind = kind x in
let _func = Owl_base_dense_common._fix_elt _kind in
map _func x
let fix_ ?out x =
let _kind = kind x in
let _func = Owl_base_dense_common._fix_elt _kind in
let out = match out with Some o -> o | None -> x in
map_ _func out
let erf _x = raise (Owl_exception.NOT_IMPLEMENTED "owl_base_dense_ndarray_generic.erf")
let erf_ ?_out _x = raise (Owl_exception.NOT_IMPLEMENTED "owl_base_dense_ndarray_generic.erf_")
let erfc _x = raise (Owl_exception.NOT_IMPLEMENTED "owl_base_dense_ndarray_generic.erfc")
let erfc_ ?_out _x = raise (Owl_exception.NOT_IMPLEMENTED "owl_base_dense_ndarray_generic.erfc_")
let sqr x =
let _kind = kind x in
let _func = Owl_base_dense_common._sqr_elt _kind in
map _func x
let sqr_ ?out x =
let _kind = kind x in
let _func = Owl_base_dense_common._sqr_elt _kind in
let out = match out with Some o -> o | None -> x in
map_ _func out
let sqrt x =
let _kind = kind x in
let _func = Owl_base_dense_common._sqrt_elt _kind in
map _func x
let sqrt_ ?out x =
let _kind = kind x in
let _func = Owl_base_dense_common._sqrt_elt _kind in
let out = match out with Some o -> o | None -> x in
map_ _func out
let cbrt x =
let _kind = kind x in
let b = Owl_base_dense_common._float_typ_elt _kind (1. /. 3.) in
let _func = fun a -> Owl_base_dense_common._pow_elt _kind a b in
map _func x
let cbrt_ ?out x =
let _kind = kind x in
let b = Owl_base_dense_common._float_typ_elt _kind (1. /. 3.) in
let _func = fun a -> Owl_base_dense_common._pow_elt _kind a b in
let out = match out with Some o -> o | None -> x in
map_ _func out
let log x =
let _kind = kind x in
let _func = Owl_base_dense_common._log_elt _kind in
map _func x
let log_ ?out x =
let _kind = kind x in
let _func = Owl_base_dense_common._log_elt _kind in
let out = match out with Some o -> o | None -> x in
map_ Scalar.log out
let log2 x =
let _kind = kind x in
let _func = Owl_base_dense_common._log2_elt _kind in
map _func x
let log2_ ?out x =
let _kind = kind x in
let _func = Owl_base_dense_common._log2_elt _kind in
let out = match out with Some o -> o | None -> x in
map_ _func out
let log10 x =
let _kind = kind x in
let _func = Owl_base_dense_common._log10_elt _kind in
map _func x
let log10_ ?out x =
let _kind = kind x in
let _func = Owl_base_dense_common._log10_elt _kind in
let out = match out with Some o -> o | None -> x in
map_ _func out
let log1p x =
let _kind = kind x in
let _func = Owl_base_dense_common._log1p_elt _kind in
map _func x
let log1p_ ?out x =
let _kind = kind x in
let _func = Owl_base_dense_common._log1p_elt _kind in
let out = match out with Some o -> o | None -> x in
map_ _func out
let exp x =
let _kind = kind x in
let _func = Owl_base_dense_common._exp_elt _kind in
map _func x
let exp_ ?out x =
let _kind = kind x in
let _func = Owl_base_dense_common._exp_elt _kind in
let out = match out with Some o -> o | None -> x in
map_ _func out
let exp2 x =
let _kind = kind x in
let _func = Owl_base_dense_common._exp2_elt _kind in
map _func x
let exp2_ ?out x =
let _kind = kind x in
let _func = Owl_base_dense_common._exp2_elt _kind in
let out = match out with Some o -> o | None -> x in
map_ _func out
let exp10 x =
let _kind = kind x in
let _func = Owl_base_dense_common._exp10_elt _kind in
map _func x
let exp10_ ?out x =
let _kind = kind x in
let _func = Owl_base_dense_common._exp10_elt _kind in
let out = match out with Some o -> o | None -> x in
map_ _func out
let expm1 x =
let _kind = kind x in
let _func = Owl_base_dense_common._expm1_elt _kind in
map _func x
let expm1_ ?out x =
let _kind = kind x in
let _func = Owl_base_dense_common._expm1_elt _kind in
let out = match out with Some o -> o | None -> x in
map_ _func out
let sin x =
let _kind = kind x in
let _func = Owl_base_dense_common._sin_elt _kind in
map _func x
let sin_ ?out x =
let _kind = kind x in
let _func = Owl_base_dense_common._sin_elt _kind in
let out = match out with Some o -> o | None -> x in
map_ _func out
let cos x =
let _kind = kind x in
let _func = Owl_base_dense_common._cos_elt _kind in
map _func x
let cos_ ?out x =
let _kind = kind x in
let _func = Owl_base_dense_common._cos_elt _kind in
let out = match out with Some o -> o | None -> x in
map_ _func out
let tan x =
let _kind = kind x in
let _func = Owl_base_dense_common._tan_elt _kind in
map _func x
let tan_ ?out x =
let _kind = kind x in
let _func = Owl_base_dense_common._tan_elt _kind in
let out = match out with Some o -> o | None -> x in
map_ _func out
let sinh x =
let _kind = kind x in
let _func = Owl_base_dense_common._sinh_elt _kind in
map _func x
let sinh_ ?out x =
let _kind = kind x in
let _func = Owl_base_dense_common._sinh_elt _kind in
let out = match out with Some o -> o | None -> x in
map_ _func out
let cosh x =
let _kind = kind x in
let _func = Owl_base_dense_common._cosh_elt _kind in
map _func x
let cosh_ ?out x =
let _kind = kind x in
let _func = Owl_base_dense_common._cosh_elt _kind in
let out = match out with Some o -> o | None -> x in
map_ _func out
let tanh x =
let _kind = kind x in
let _func = Owl_base_dense_common._tanh_elt _kind in
map _func x
let tanh_ ?out x =
let _kind = kind x in
let _func = Owl_base_dense_common._tanh_elt _kind in
let out = match out with Some o -> o | None -> x in
map_ _func out
let asin x =
let _kind = kind x in
let _func = Owl_base_dense_common._asin_elt _kind in
map _func x
let asin_ ?out x =
let _kind = kind x in
let _func = Owl_base_dense_common._asin_elt _kind in
let out = match out with Some o -> o | None -> x in
map_ _func out
let acos x =
let _kind = kind x in
let _func = Owl_base_dense_common._acos_elt _kind in
map _func x
let acos_ ?out x =
let _kind = kind x in
let _func = Owl_base_dense_common._acos_elt _kind in
let out = match out with Some o -> o | None -> x in
map_ _func out
let atan x =
let _kind = kind x in
let _func = Owl_base_dense_common._atan_elt _kind in
map _func x
let atan_ ?out x =
let _kind = kind x in
let _func = Owl_base_dense_common._atan_elt _kind in
let out = match out with Some o -> o | None -> x in
map_ _func out
let asinh x =
let _kind = kind x in
let _func = Owl_base_dense_common._asinh_elt _kind in
map _func x
let asinh_ ?out x =
let _kind = kind x in
let _func = Owl_base_dense_common._asinh_elt _kind in
let out = match out with Some o -> o | None -> x in
map_ _func out
let acosh x =
let _kind = kind x in
let _func = Owl_base_dense_common._acosh_elt _kind in
map _func x
let acosh_ ?out x =
let _kind = kind x in
let _func = Owl_base_dense_common._acosh_elt _kind in
let out = match out with Some o -> o | None -> x in
map_ _func out
let atanh x =
let _kind = kind x in
let _func = Owl_base_dense_common._atanh_elt _kind in
map _func x
let atanh_ ?out x =
let _kind = kind x in
let _func = Owl_base_dense_common._atanh_elt _kind in
let out = match out with Some o -> o | None -> x in
map_ _func out
let sum_slices ?(axis=0) varr =
let dims = shape varr in
let rank = Array.length dims in
let num_rows = Array.fold_left ( * ) 1 (Array.sub dims 0 (axis + 1)) in
let num_cols = (numel varr) / num_rows in
let varr_mat = reshape varr [|num_rows; num_cols|] in
let result_vec = empty (kind varr) [|num_cols|] in
let result_varr = reshape result_vec
(Array.sub dims (axis + 1) (rank - axis - 1))
in
let row_sum = ref 0. in
for j = 0 to num_cols - 1 do
row_sum := 0.;
for i = 0 to num_rows - 1 do
row_sum := !row_sum +. (Genarray.get varr_mat [|i; j|])
done;
Genarray.set result_vec [|j|] !row_sum
done;
result_varr
let signum x = map Scalar.signum x
let signum_ ?out x =
let out = match out with Some o -> o | None -> x in
map_ Scalar.signum out
let sigmoid x = map Scalar.sigmoid x
let sigmoid_ ?out x =
let out = match out with Some o -> o | None -> x in
map_ Scalar.sigmoid out
let relu x = map Scalar.relu x
let relu_ ?out x =
let out = match out with Some o -> o | None -> x in
map_ Scalar.relu out
let softsign x = map Scalar.softsign x
let softsign_ ?out x =
let out = match out with Some o -> o | None -> x in
map_ Scalar.softsign out
let softplus x = map Scalar.softplus x
let softplus_ ?out x =
let out = match out with Some o -> o | None -> x in
map_ Scalar.softplus out
let _fold_left f a varr =
let aref = ref a in
let varr_linear = flatten varr |> array1_of_genarray in
let length = numel varr in
begin
for i = 0 to length - 1 do
aref := (f !aref (Array1.unsafe_get varr_linear i))
done;
!aref
end
let min' x =
let _kind = kind x in
let _max_val = Owl_base_dense_common._max_val_elt _kind in
_fold_left (Owl_base_dense_common._min_elt _kind) _max_val x
let max' x =
let _kind = kind x in
let _min_val = Owl_base_dense_common._min_val_elt _kind in
_fold_left (Owl_base_dense_common._max_elt _kind) _min_val x
let sum' x =
let _kind = kind x in
_fold_left (Owl_base_dense_common._add_elt _kind) (Owl_const.zero _kind) x
let _fold_along ?out f m n o x ys nelem =
let x = flatten x in
let y = match out with
| Some o -> o |> flatten
| None -> create (kind x) ys nelem |> flatten
in
let idx = ref 0 in
let idy = ref 0 in
let incy = ref 0 in
for _i = 0 to (m - 1) do
for j = 0 to (n - 1) do
let addon = Genarray.get x [|!idx + j|] in
let orig = Genarray.get y [|!idy + !incy|] in
Genarray.set y [|!idy + !incy|] (f orig addon);
incy := if (!incy + 1 = o) then 0 else !incy + 1
done;
idx := !idx + n;
idy := !idy + o;
done;
reshape y ys
let sum ?axis x =
let _kind = kind x in
let zero = Owl_const.zero _kind in
match axis with
| Some a -> (
let m, n, o, s = Owl_utils.reduce_params a x in
let _op = Owl_base_dense_common._add_elt _kind in
_fold_along _op m n o x s zero
)
| None -> create (kind x) (Array.make 1 1) (sum' x)
let sum_ ~out ~axis x =
let _kind = kind x in
let zero = Owl_const.zero _kind in
Genarray.fill out zero;
match axis with
| Some a -> (
let m, n, o, s = Owl_utils.reduce_params a x in
let _op = Owl_base_dense_common._add_elt _kind in
_fold_along _op ~out m n o x s zero
|> ignore
)
| None -> (
let y = flatten out in
set y [|0|] (sum' x)
)
let sum_reduce ?axis x =
let _kind = kind x in
let _dims = num_dims x in
let zero = Owl_const.zero _kind in
match axis with
| Some a -> (
let x_shape = shape x in
let dims' = Owl_utils.squeeze_continuous_dims x_shape a in
if Array.length dims' = 1 then (
create (kind x) (Array.make _dims 1) (sum' x)
)
else (
let y = ref (reshape x dims') in
let flag = ref (Array.mem 0 a) in
for i = 0 to Array.length dims' - 1 do
if !flag = true then (
let m, n, o, s = Owl_utils.reduce_params i !y in
y := _fold_along (Owl_base_dense_common._add_elt _kind) m n o !y s zero
);
flag := not !flag
done;
let y_shape = Array.copy x_shape in
Array.iter (fun j -> y_shape.(j) <- 1) a;
reshape !y y_shape
)
)
| None -> create (kind x) (Array.make _dims 1) (sum' x)
let min ?axis x =
let _kind = kind x in
let max_val = Owl_base_dense_common._max_val_elt _kind in
match axis with
| Some a -> (
let m, n, o, s = Owl_utils.reduce_params a x in
_fold_along (Owl_base_dense_common._min_elt _kind) m n o x s max_val
)
| None -> min' x |> create _kind [|1|]
let min_ ~out ~axis x =
let _kind = kind x in
let max_val = Owl_base_dense_common._max_val_elt _kind in
Genarray.fill out max_val;
match axis with
| Some a -> (
let m, n, o, s = Owl_utils.reduce_params a x in
let _op = Owl_base_dense_common._min_elt _kind in
_fold_along ~out _op m n o x s max_val
|> ignore
)
| None -> (
let y = flatten out in
set y [|0|] (min' x)
)
let max ?axis x =
let _kind = kind x in
let min_val = Owl_base_dense_common._min_val_elt _kind in
match axis with
| Some a -> (
let m, n, o, s = Owl_utils.reduce_params a x in
_fold_along (Owl_base_dense_common._max_elt _kind) m n o x s min_val
)
| None -> max' x |> create _kind [|1|]
let max_ ~out ~axis x =
let _kind = kind x in
let min_val = Owl_base_dense_common._min_val_elt _kind in
Genarray.fill out min_val;
match axis with
| Some a -> (
let m, n, o, s = Owl_utils.reduce_params a x in
_fold_along ~out (Owl_base_dense_common._max_elt _kind) m n o x s min_val
|> ignore
)
| None -> (
let y = flatten out in
set y [|0|] (max' x)
)
let l1norm' varr =
let l1norm_fun =
(fun aggregate elem -> (aggregate +. (Scalar.abs (elem)))) in
(_fold_left l1norm_fun 0. varr)
let l2norm_sqr' varr =
let l2norm_sqr_fun =
(fun aggregate elem -> (aggregate +. (elem *. elem))) in
(_fold_left l2norm_sqr_fun 0. varr)
let l2norm' varr =
let l2norm_sqr_val = l2norm_sqr' varr in
(Scalar.sqrt l2norm_sqr_val)
let _broadcasted_op ?out varr_a varr_b op_fun =
let (dims_a, dims_b, dims_c) =
_get_broadcasted_dims (shape varr_a) (shape varr_b)
in
let _kind = kind varr_a in
let varr_a = reshape varr_a dims_a in
let varr_b = reshape varr_b dims_b in
let varr_c = match out with
| Some out -> out
| None -> empty _kind dims_c
in
let ind = Array.make (Array.length dims_c) 0 in
let should_stop = ref false in
begin
while not !should_stop do
let ind_a = _get_broadcasted_index ind dims_a in
let ind_b = _get_broadcasted_index ind dims_b in
Genarray.set varr_c ind
(op_fun (Genarray.get varr_a ind_a) (Genarray.get varr_b ind_b));
if not (_next_index ind dims_c) then
should_stop := true
done;
varr_c
end
let add x y =
let _op = Owl_base_dense_common._add_elt (kind x) in
_broadcasted_op x y _op
let add_ ?out x y =
let out = match out with Some o -> o | None -> x in
let _op = Owl_base_dense_common._add_elt (kind x) in
let sx = shape x in
let sy = shape y in
let so = Owl_utils_infer_shape.broadcast1 sx sy in
let st = shape out in
let exn = Owl_exception.DIFFERENT_SHAPE (so, st) in
Owl_exception.check (so = st) exn;
_broadcasted_op ~out x y _op
|> ignore
let sub x y =
let _op = Owl_base_dense_common._sub_elt (kind x) in
_broadcasted_op x y _op
let sub_ ?out x y =
let out = match out with Some o -> o | None -> x in
let _op = Owl_base_dense_common._sub_elt (kind x) in
let sx = shape x in
let sy = shape y in
let so = Owl_utils_infer_shape.broadcast1 sx sy in
let st = shape out in
let exn = Owl_exception.DIFFERENT_SHAPE (so, st) in
Owl_exception.check (so = st) exn;
_broadcasted_op ~out x y _op
|> ignore
let mul x y =
let _op = Owl_base_dense_common._mul_elt (kind x) in
_broadcasted_op x y _op
let mul_ ?out x y =
let out = match out with Some o -> o | None -> x in
let _op = Owl_base_dense_common._mul_elt (kind x) in
let sx = shape x in
let sy = shape y in
let so = Owl_utils_infer_shape.broadcast1 sx sy in
let st = shape out in
let exn = Owl_exception.DIFFERENT_SHAPE (so, st) in
Owl_exception.check (so = st) exn;
_broadcasted_op ~out x y _op
|> ignore
let div x y =
let _op = Owl_base_dense_common._div_elt (kind x) in
_broadcasted_op x y _op
let div_ ?out x y =
let out = match out with Some o -> o | None -> x in
let _op = Owl_base_dense_common._div_elt (kind x) in
let sx = shape x in
let sy = shape y in
let so = Owl_utils_infer_shape.broadcast1 sx sy in
let st = shape out in
let exn = Owl_exception.DIFFERENT_SHAPE (so, st) in
Owl_exception.check (so = st) exn;
_broadcasted_op ~out x y _op
|> ignore
let atan2 x y = _broadcasted_op x y (Scalar.atan2)
let atan2_ ?out x y =
let out = match out with Some o -> o | None -> x in
let sx = shape x in
let sy = shape y in
let so = Owl_utils_infer_shape.broadcast1 sx sy in
let st = shape out in
let exn = Owl_exception.DIFFERENT_SHAPE (so, st) in
Owl_exception.check (so = st) exn;
_broadcasted_op x y (Scalar.atan2)
|> ignore
let hypot x y = _broadcasted_op x y (Scalar.hypot)
let hypot_ ?out x y =
let out = match out with Some o -> o | None -> x in
let sx = shape x in
let sy = shape y in
let so = Owl_utils_infer_shape.broadcast1 sx sy in
let st = shape out in
let exn = Owl_exception.DIFFERENT_SHAPE (so, st) in
Owl_exception.check (so = st) exn;
_broadcasted_op x y (Scalar.hypot)
|> ignore
let pow x y =
let _kind = kind x in
let _op = Owl_base_dense_common._pow_elt _kind in
_broadcasted_op x y _op
let pow_ ?out x y =
let _kind = kind x in
let _op = Owl_base_dense_common._pow_elt _kind in
let out = match out with Some o -> o | None -> x in
let sx = shape x in
let sy = shape y in
let so = Owl_utils_infer_shape.broadcast1 sx sy in
let st = shape out in
let exn = Owl_exception.DIFFERENT_SHAPE (so, st) in
Owl_exception.check (so = st) exn;
_broadcasted_op ~out x y _op
|> ignore
let fmod x y = _broadcasted_op x y (Scalar.fmod)
let fmod_ ?out x y =
let out = match out with Some o -> o | None -> x in
let sx = shape x in
let sy = shape y in
let so = Owl_utils_infer_shape.broadcast1 sx sy in
let st = shape out in
let exn = Owl_exception.DIFFERENT_SHAPE (so, st) in
Owl_exception.check (so = st) exn;
_broadcasted_op x y (Scalar.fmod)
|> ignore
let min2 x y =
let _op = Owl_base_dense_common._min_elt (kind x) in
_broadcasted_op x y _op
let min2_ ?out x y =
let out = match out with Some o -> o | None -> x in
let _op = Owl_base_dense_common._min_elt (kind x) in
let sx = shape x in
let sy = shape y in
let so = Owl_utils_infer_shape.broadcast1 sx sy in
let st = shape out in
let exn = Owl_exception.DIFFERENT_SHAPE (so, st) in
Owl_exception.check (so = st) exn;
_broadcasted_op ~out x y _op
|> ignore
let max2 x y =
let _op = Owl_base_dense_common._max_elt (kind x) in
_broadcasted_op x y _op
let max2_ ?out x y =
let out = match out with Some o -> o | None -> x in
let _op = Owl_base_dense_common._max_elt (kind x) in
let sx = shape x in
let sy = shape y in
let so = Owl_utils_infer_shape.broadcast1 sx sy in
let st = shape out in
let exn = Owl_exception.DIFFERENT_SHAPE (so, st) in
Owl_exception.check (so = st) exn;
_broadcasted_op ~out x y _op
|> ignore
let add_scalar x a =
let _op = Owl_base_dense_common._add_elt (kind x) in
map (fun y -> _op y a) x
let add_scalar_ ?out x a =
let out = match out with Some o -> o | None -> x in
let _op = Owl_base_dense_common._add_elt (kind x) in
map_ (fun y -> _op y a) out
let sub_scalar x a =
let _op = Owl_base_dense_common._sub_elt (kind x) in
map (fun y -> _op y a) x
let sub_scalar_ ?out x a =
let out = match out with Some o -> o | None -> x in
let _op = Owl_base_dense_common._sub_elt (kind x) in
map_ (fun y -> _op y a) out
let mul_scalar x a =
let _op = Owl_base_dense_common._mul_elt (kind x) in
map (fun y -> _op y a) x
let mul_scalar_ ?out x a =
let out = match out with Some o -> o | None -> x in
let _op = Owl_base_dense_common._mul_elt (kind x) in
map_ (fun y -> _op y a) out
let div_scalar x a =
let _op = Owl_base_dense_common._div_elt (kind x) in
map (fun y -> _op y a) x
let div_scalar_ ?out x a =
let out = match out with Some o -> o | None -> x in
let _op = Owl_base_dense_common._div_elt (kind x) in
map_ (fun y -> _op y a) out
let pow_scalar x a =
let _op = Owl_base_dense_common._pow_elt (kind x) in
map (fun y -> _op y a) x
let pow_scalar_ ?out x a =
let out = match out with Some o -> o | None -> x in
let _op = Owl_base_dense_common._pow_elt (kind x) in
map_ (fun y -> _op y a) out
let atan2_scalar x a =
let _op = Scalar.atan2 in
map (fun y -> _op y a) x
let atan2_scalar_ ?out x a =
let out = match out with Some o -> o | None -> x in
let _op = Scalar.atan2 in
map_ (fun y -> _op y a) out
let fmod_scalar x a =
let _op = Scalar.fmod in
map (fun y -> _op y a) x
let fmod_scalar_ ?out x a =
let out = match out with Some o -> o | None -> x in
let _op = Scalar.fmod in
map_ (fun y -> _op y a) out
let fma _x _y _z = failwith "Owl_base_dense_ndarray_generic:fma: not implemented"
let scalar_add a x =
let _op = Owl_base_dense_common._add_elt (kind x) in
map (fun y -> _op a y) x
let scalar_add_ ?out a x =
let out = match out with Some o -> o | None -> x in
let _op = Owl_base_dense_common._add_elt (kind x) in
map_ (fun y -> _op a y) out
let scalar_sub a x =
let _op = Owl_base_dense_common._sub_elt (kind x) in
map (fun y -> _op a y) x
let scalar_sub_ ?out a x =
let out = match out with Some o -> o | None -> x in
let _op = Owl_base_dense_common._sub_elt (kind x) in
map_ (fun y -> _op a y) out
let scalar_mul a x =
let _op = Owl_base_dense_common._mul_elt (kind x) in
map (fun y -> _op a y) x
let scalar_mul_ ?out a x =
let out = match out with Some o -> o | None -> x in
let _op = Owl_base_dense_common._mul_elt (kind x) in
map_ (fun y -> _op a y) out
let scalar_div a x =
let _op = Owl_base_dense_common._div_elt (kind x) in
map (fun y -> _op a y) x
let scalar_div_ ?out a x =
let out = match out with Some o -> o | None -> x in
let _op = Owl_base_dense_common._div_elt (kind x) in
map_ (fun y -> _op a y) out
let scalar_pow a x =
let _op = Owl_base_dense_common._pow_elt (kind x) in
map (fun y -> _op a y) x
let scalar_pow_ ?out a x =
let out = match out with Some o -> o | None -> x in
let _op = Owl_base_dense_common._pow_elt (kind x) in
map_ (fun y -> _op a y) out
let scalar_atan2 a x =
let _op = Scalar.atan2 in
map (fun y -> _op a y) x
let scalar_atan2_ ?out a x =
let out = match out with Some o -> o | None -> x in
let _op = Scalar.atan2 in
map_ (fun y -> _op a y) out
let scalar_fmod a x =
let _op =Scalar.fmod in
map (fun y -> _op a y) x
let scalar_fmod_ ?out a x =
let out = match out with Some o -> o | None -> x in
let _op = Scalar.fmod in
map_ (fun y -> _op a y) out
let clip_by_value ?(amin=Stdlib.min_float) ?(amax=Stdlib.max_float) x =
let _op = (fun y -> Stdlib.min amax (Stdlib.max amin y)) in
map _op x
let clip_by_l2norm clip_norm x =
let l2norm_val = l2norm' x in
if l2norm_val > clip_norm then
mul_scalar x (clip_norm /. l2norm_val)
else x
let softmax ?(axis=(-1)) x =
let x = copy x in
let axis = Owl_utils.adjust_index axis (num_dims x) in
sub_ ~out:x x (max ~axis x);
exp_ ~out:x x;
let a = sum ~axis x in
div_ ~out:x x a;
x
let softmax_ ?out ?(axis=(-1)) x =
let out = match out with Some o -> o | None -> x in
let axis = Owl_utils.adjust_index axis (num_dims x) in
sub_ ~out x (max ~axis x);
exp_ ~out x;
let a = sum ~axis x in
div_ ~out x a
(** Return true if for all elements comp_fun (xa, xb) == true, false otherwise.
Returns false as soon as it finds a counterexample. (NOT broadcasted) *)
let _compare_util_shortcircuit varr_a varr_b comp_fun =
let n = numel varr_a in
let m = numel varr_b in
if n != m then
false
else
let varr_a = flatten varr_a |> array1_of_genarray in
let varr_b = flatten varr_b |> array1_of_genarray in
let all_ok = ref true in
let i = ref 0 in (
while !all_ok && (!i < n) do
let x = Array1.unsafe_get varr_a !i in
let y = Array1.unsafe_get varr_b !i in
if (not (comp_fun x y)) then all_ok := false;
i := !i + 1
done;
!all_ok
)
let approx_equal ?eps varr_a varr_b =
let eps = match eps with
| Some eps -> eps
| None -> Owl_utils.eps Float32
in
let approx_equal_fun = (fun x y -> (Scalar.abs (Scalar.sub x y)) < eps) in
(_compare_util_shortcircuit varr_a varr_b approx_equal_fun)
let equal x y =
(_compare_util_shortcircuit x y Stdlib.(=))
let not_equal x y =
(_compare_util_shortcircuit x y Stdlib.(<>))
let less x y =
(_compare_util_shortcircuit x y Stdlib.(<))
let greater x y =
(_compare_util_shortcircuit x y Stdlib.(>))
let less_equal x y =
(_compare_util_shortcircuit x y Stdlib.(<=))
let greater_equal x y =
(_compare_util_shortcircuit x y Stdlib.(>=))
(** Return true if for all elements of a comp_fun (xa, bb) == true, false otherwise.
Returns false as soon as it finds a counterexample. (NOT broadcasted) *)
let _compare_util_shortcircuit_scalar varr_a b comp_fun =
let n = numel varr_a in
let varr_a = flatten varr_a |> array1_of_genarray in
let all_ok = ref true in
let i = ref 0 in (
while !all_ok && (!i < n) do
let x = Array1.unsafe_get varr_a !i in
if (not (comp_fun x b))
then all_ok := false;
i := !i + 1
done;
!all_ok
)
let approx_equal_scalar ?eps varr_a b =
let eps = match eps with
| Some eps -> eps
| None -> Owl_utils.eps Float32
in
let approx_equal_scalar_fun = (fun x y -> (Scalar.abs (Scalar.sub x y)) < eps) in
(_compare_util_shortcircuit_scalar varr_a b approx_equal_scalar_fun)
let equal_scalar x a =
(_compare_util_shortcircuit_scalar x a Stdlib.(=))
let not_equal_scalar x a =
(_compare_util_shortcircuit_scalar x a Stdlib.(<>))
let less_scalar x a =
(_compare_util_shortcircuit_scalar x a Stdlib.(<))
let greater_scalar x a =
(_compare_util_shortcircuit_scalar x a Stdlib.(>))
let less_equal_scalar varr_a b =
(_compare_util_shortcircuit_scalar varr_a b Stdlib.(<=))
let greater_equal_scalar x a =
(_compare_util_shortcircuit_scalar x a Stdlib.(>=))
let _make_elt_compare_fun kind cmp_fun =
let c0 = Owl_const.zero kind in
let c1 = Owl_const.one kind in
let _func a b = if cmp_fun a b then c1 else c0 in
_func
let elt_equal x y =
let _func = _make_elt_compare_fun (kind x) Stdlib.(=) in
_broadcasted_op x y _func
let elt_equal_ ?out x y =
let out = match out with Some o -> o | None -> x in
let _func = _make_elt_compare_fun (kind x) Stdlib.(=) in
_broadcasted_op ~out x y _func
let approx_elt_equal ?eps x y =
let eps = match eps with
| Some eps -> eps
| None -> Owl_utils.eps Float32
in
let approx_equal_fun = (fun x y -> (Scalar.abs (Scalar.sub x y)) < eps) in
let _func = _make_elt_compare_fun (kind x) approx_equal_fun in
_broadcasted_op x y _func
let elt_not_equal x y =
let _func = _make_elt_compare_fun (kind x) Stdlib.(<>) in
_broadcasted_op x y _func
let elt_not_equal_ ?out x y =
let out = match out with Some o -> o | None -> x in
let _func = _make_elt_compare_fun (kind x) Stdlib.(<>) in
_broadcasted_op ~out x y _func
let elt_less x y =
let _func = _make_elt_compare_fun (kind x) Stdlib.(<) in
_broadcasted_op x y _func
let elt_less_ ?out x y =
let out = match out with Some o -> o | None -> x in
let _func = _make_elt_compare_fun (kind x) Stdlib.(<) in
_broadcasted_op ~out x y _func
let elt_greater x y =
let _func = _make_elt_compare_fun (kind x) Stdlib.(>) in
_broadcasted_op x y _func
let elt_greater_ ?out x y =
let out = match out with Some o -> o | None -> x in
let _func = _make_elt_compare_fun (kind x) Stdlib.(>) in
_broadcasted_op ~out x y _func
let elt_less_equal x y =
let _func = _make_elt_compare_fun (kind x) Stdlib.(<=) in
_broadcasted_op x y _func
let elt_less_equal_ ?out x y =
let out = match out with Some o -> o | None -> x in
let _func = _make_elt_compare_fun (kind x) Stdlib.(<=) in
_broadcasted_op ~out x y _func
let elt_greater_equal x y =
let _func = _make_elt_compare_fun (kind x) Stdlib.(>=) in
_broadcasted_op x y _func
let elt_greater_equal_ ?out x y =
let out = match out with Some o -> o | None -> x in
let _func = _make_elt_compare_fun (kind x) Stdlib.(>=) in
_broadcasted_op ~out x y _func
let _make_elt_compare_scalar x cmp_fun =
let _kind = kind x in
let c0 = Owl_const.zero _kind in
let c1 = Owl_const.one _kind in
let _func a = if cmp_fun a then c1 else c0 in
_func
let elt_equal_scalar x a =
let cmp_fun = (fun y -> y = a) in
let _func = _make_elt_compare_scalar x cmp_fun in
map _func x
let elt_equal_scalar_ ?out x a =
let out = match out with Some o -> o | None -> x in
let cmp_fun = (fun y -> y = a) in
let _func = _make_elt_compare_scalar x cmp_fun in
map_ _func out
let approx_elt_equal_scalar ?eps x a =
let eps = match eps with
| Some eps -> eps
| None -> Owl_utils.eps Float32
in
let cmp_fun = (fun y -> (Scalar.abs (Scalar.sub y a)) < eps) in
let _func = _make_elt_compare_scalar x cmp_fun in
map _func x
let elt_not_equal_scalar x a =
let cmp_fun = (fun y -> y <> a) in
let _func = _make_elt_compare_scalar x cmp_fun in
map _func x
let elt_not_equal_scalar_ ?out x a =
let out = match out with Some o -> o | None -> x in
let cmp_fun = (fun y -> y <> a) in
let _func = _make_elt_compare_scalar x cmp_fun in
map_ _func out
let elt_less_scalar x a =
let cmp_fun = (fun y -> y < a) in
let _func = _make_elt_compare_scalar x cmp_fun in
map _func x
let elt_less_scalar_ ?out x a =
let out = match out with Some o -> o | None -> x in
let cmp_fun = (fun y -> y < a) in
let _func = _make_elt_compare_scalar x cmp_fun in
map_ _func out
let elt_greater_scalar x a =
let cmp_fun = (fun y -> y > a) in
let _func = _make_elt_compare_scalar x cmp_fun in
map _func x
let elt_greater_scalar_ ?out x a =
let out = match out with Some o -> o | None -> x in
let cmp_fun = (fun y -> y > a) in
let _func = _make_elt_compare_scalar x cmp_fun in
map_ _func out
let elt_less_equal_scalar x a =
let cmp_fun = (fun y -> y <= a) in
let _func = _make_elt_compare_scalar x cmp_fun in
map _func x
let elt_less_equal_scalar_ ?out x a =
let out = match out with Some o -> o | None -> x in
let cmp_fun = (fun y -> y <= a) in
let _func = _make_elt_compare_scalar x cmp_fun in
map_ _func out
let elt_greater_equal_scalar x a =
let cmp_fun = (fun y -> y >= a) in
let _func = _make_elt_compare_scalar x cmp_fun in
map _func x
let elt_greater_equal_scalar_ ?out x a =
let out = match out with Some o -> o | None -> x in
let cmp_fun = (fun y -> y >= a) in
let _func = _make_elt_compare_scalar x cmp_fun in
map _func out
let exists f x =
let n = numel x in
let x = flatten x |> array1_of_genarray in
let found = ref false in
let i = ref 0 in
while (!i < n) && (not !found) do
let a = Array1.unsafe_get x !i in
if f a then found := true;
i := !i + 1
done;
!found
let not_exists f varr = (not (exists f varr))
let for_all f varr =
let not_f = (fun x -> not (f x)) in
(not_exists not_f varr)
let is_zero varr =
let k = kind varr in
let c0 = Owl_const.zero k in
let non_zero_fun = (fun x -> x <> c0) in
(not_exists non_zero_fun varr)
let is_positive varr =
let k = kind varr in
let c0 = Owl_const.zero k in
let non_positive_fun = (fun x -> x <= c0) in
(not_exists non_positive_fun varr)
let is_negative varr =
let k = kind varr in
let c0 = Owl_const.zero k in
let non_negative_fun = (fun x -> x >= c0) in
(not_exists non_negative_fun varr)
let is_nonpositive varr =
let k = kind varr in
let c0 = Owl_const.zero k in
let positive_fun = (fun x -> x > c0) in
(not_exists positive_fun varr)
let is_nonnegative varr =
let k = kind varr in
let c0 = Owl_const.zero k in
let negative_fun = (fun x -> x < c0) in
(not_exists negative_fun varr)
let is_normal x =
let _kind = kind x in
let is_normal_fun = Owl_base_dense_common._is_normal_elt _kind in
for_all is_normal_fun x
let not_nan x =
let _kind = kind x in
let is_nan_fun = Owl_base_dense_common._is_nan_elt _kind in
not_exists is_nan_fun x
let not_inf x =
let _kind = kind x in
let is_inf_fun = Owl_base_dense_common._is_inf_elt _kind in
not_exists is_inf_fun x
let conv2d ?(padding=SAME) input kernel stride =
let p0 = (num_dims input = 4) in
let p1 = (num_dims kernel = 4) in
let p2 = (Array.length stride = 2) in
let error () =
let s0 = Printf.sprintf "input dimension = %i (should be 4)" (num_dims input) in
let s1 = Printf.sprintf "kernel dimension = %i (should be 4)" (num_dims kernel) in
let s2 = Printf.sprintf "stride dimension = %i (should be 2)" (Array.length stride) in
let s3 = Printf.sprintf "conv2d: %s; %s; %s." s0 s1 s2 in
Owl_exception.INVALID_ARGUMENT s3
in
Owl_exception.verify (p0 && p1 && p2) error;
let input_shp = shape input in
let batches = input_shp.(0) in
let input_cols = input_shp.(1) in
let input_rows = input_shp.(2) in
let in_channel = input_shp.(3) in
let kernel_shp = shape kernel in
let kernel_cols = kernel_shp.(0) in
let kernel_rows = kernel_shp.(1) in
let out_channel = kernel_shp.(3) in
let p3 = (in_channel = kernel_shp.(2)) in
let error () =
let s0 = Owl_utils_array.to_string string_of_int input_shp in
let s1 = Printf.sprintf "input shape is [%s]" s0 in
let s2 = Owl_utils_array.to_string string_of_int kernel_shp in
let s3 = Printf.sprintf "kernel shape is [%s]" s2 in
let s4 = Printf.sprintf "the 4th dimension of input shape should be equal to the 3rd dimension of kernel shape" in
let s5 = Printf.sprintf "conv2d: %s, %s, %s." s1 s3 s4 in
Owl_exception.INVALID_ARGUMENT s5
in
Owl_exception.verify p3 error;
let col_stride = stride.(0) in
let row_stride = stride.(1) in
let (output_cols, output_rows) =
Owl_utils_infer_shape.calc_conv2d_output_shape padding input_cols input_rows
kernel_cols kernel_rows row_stride col_stride
in
let _kind = kind input in
let output = empty _kind [|batches; output_cols; output_rows; out_channel|] in
let (pad_top, pad_left, _, _) = Owl_utils_infer_shape.calc_conv2d_padding
input_cols input_rows kernel_cols kernel_rows output_cols output_rows
row_stride col_stride
in
let sum = ref 0. in
begin
for b = 0 to batches - 1 do
for i = 0 to output_cols - 1 do
for j = 0 to output_rows - 1 do
for k = 0 to out_channel - 1 do
sum := 0.;
for di = 0 to kernel_cols - 1 do
for dj = 0 to kernel_rows - 1 do
for q = 0 to in_channel - 1 do
let in_col = i * col_stride + di - pad_left in
let in_row = j * row_stride + dj - pad_top in
let in_val = (
if ((0 <= in_col) && (in_col < input_cols) &&
(0 <= in_row) && (in_row < input_rows))
then (get input [|b; in_col; in_row; q|])
else 0.
) in
sum := !sum +. in_val *. (get kernel [|di; dj; q; k|])
done;
done;
done;
(set output [|b; i; j; k|] !sum)
done;
done;
done;
done;
output
end
let conv1d ?(padding=SAME) input kernel stride =
let p0 = (num_dims input = 3) in
let p1 = (num_dims kernel = 3) in
let p2 = (Array.length stride = 1) in
let error () =
let s0 = Printf.sprintf "input dimension = %i (should be 3)" (num_dims input) in
let s1 = Printf.sprintf "kernel dimension = %i (should be 3)" (num_dims kernel) in
let s2 = Printf.sprintf "stride dimension = %i (should be 1)" (Array.length stride) in
let s3 = Printf.sprintf "conv1d: %s; %s; %s." s0 s1 s2 in
Owl_exception.INVALID_ARGUMENT s3
in
Owl_exception.verify (p0 && p1 && p2) error;
let input_shp = shape input in
let batches = input_shp.(0) in
let input_cols = input_shp.(1) in
let in_channel = input_shp.(2) in
let input = reshape input [|batches; 1; input_cols; in_channel|] in
let kernel_shp = shape kernel in
let kernel_cols = kernel_shp.(0) in
let out_channel = kernel_shp.(2) in
let p3 = (in_channel = kernel_shp.(1)) in
let error () =
let s0 = Owl_utils_array.to_string string_of_int input_shp in
let s1 = Printf.sprintf "input shape is [%s]" s0 in
let s2 = Owl_utils_array.to_string string_of_int kernel_shp in
let s3 = Printf.sprintf "kernel shape is [%s]" s2 in
let s4 = Printf.sprintf "the 3rd dimension of input shape should be equal to the 2nd dimension of kernel shape" in
let s5 = Printf.sprintf "conv1d: %s, %s, %s." s1 s3 s4 in
Owl_exception.INVALID_ARGUMENT s5
in
Owl_exception.verify p3 error;
let kernel = reshape kernel [|1; kernel_cols; in_channel; out_channel|] in
let col_stride = stride.(0) in
let stride = [|1; col_stride|] in
let output = conv2d ~padding input kernel stride in
let output_shp = shape output in
let output_cols = output_shp.(2) in
let output = reshape output [|batches; output_cols; out_channel|] in
output
let conv3d ?(padding=SAME) input kernel stride =
let p0 = (num_dims input = 5) in
let p1 = (num_dims kernel = 5) in
let p2 = (Array.length stride = 3) in
let error () =
let s0 = Printf.sprintf "input dimension = %i (should be 5)" (num_dims input) in
let s1 = Printf.sprintf "kernel dimension = %i (should be 5)" (num_dims kernel) in
let s2 = Printf.sprintf "stride dimension = %i (should be 3)" (Array.length stride) in
let s3 = Printf.sprintf "conv3d: %s; %s; %s." s0 s1 s2 in
Owl_exception.INVALID_ARGUMENT s3
in
Owl_exception.verify (p0 && p1 && p2) error;
let input_shp = shape input in
let batches = input_shp.(0) in
let input_cols = input_shp.(1) in
let input_rows = input_shp.(2) in
let input_dpts = input_shp.(3) in
let in_channel = input_shp.(4) in
let kernel_shp = shape kernel in
let kernel_cols = kernel_shp.(0) in
let kernel_rows = kernel_shp.(1) in
let kernel_dpts = kernel_shp.(2) in
let out_channel = kernel_shp.(4) in
let p3 = (in_channel = kernel_shp.(3)) in
let error () =
let s0 = Owl_utils_array.to_string string_of_int input_shp in
let s1 = Printf.sprintf "input shape is [%s]" s0 in
let s2 = Owl_utils_array.to_string string_of_int kernel_shp in
let s3 = Printf.sprintf "kernel shape is [%s]" s2 in
let s4 = Printf.sprintf "the 5th dimension of input shape should be equal to the 4th dimension of kernel shape" in
let s5 = Printf.sprintf "conv3d: %s, %s, %s." s1 s3 s4 in
Owl_exception.INVALID_ARGUMENT s5
in
Owl_exception.verify p3 error;
let col_stride = stride.(0) in
let row_stride = stride.(1) in
let dpt_stride = stride.(2) in
let output_cols, output_rows, output_dpts =
Owl_utils_infer_shape.calc_conv3d_output_shape padding
input_cols input_rows input_dpts
kernel_cols kernel_rows kernel_dpts
row_stride col_stride dpt_stride
in
let _kind = kind input in
let output =
empty _kind [|batches; output_cols; output_rows; output_dpts; out_channel|] in
let (pad_top, pad_left, pad_shallow, _, _, _) =
Owl_utils_infer_shape.calc_conv3d_padding
input_cols input_rows input_dpts
kernel_cols kernel_rows kernel_dpts
output_cols output_rows output_dpts
row_stride col_stride dpt_stride
in
let sum = ref 0. in
begin
for b = 0 to batches - 1 do
for i = 0 to output_cols - 1 do
for j = 0 to output_rows - 1 do
for dpt = 0 to output_dpts - 1 do
for k = 0 to out_channel - 1 do
sum := 0.;
for di = 0 to kernel_cols - 1 do
for dj = 0 to kernel_rows - 1 do
for d_dpt = 0 to kernel_dpts -1 do
for q = 0 to in_channel - 1 do
let in_col = i * col_stride + di - pad_left in
let in_row = j * row_stride + dj - pad_top in
let in_dpt = dpt * dpt_stride + d_dpt - pad_shallow in
let in_val = (
if ((0 <= in_col) && (in_col < input_cols) &&
(0 <= in_row) && (in_row < input_rows) &&
(0 <= in_dpt) && (in_dpt < input_dpts))
then (get input [|b; in_col; in_row; in_dpt; q|])
else 0.
) in
sum := !sum +. in_val *. (get kernel [|di; dj; d_dpt; q; k|])
done;
done;
done;
done;
(set output [|b; i; j; dpt; k|] !sum)
done;
done;
done;
done;
done;
output
end
let _pool2d ?(padding=SAME) input kernel stride
init_pool_fun add_val_pool_fun end_pool_fun =
let p0 = (num_dims input = 4) in
let p1 = (Array.length kernel = 2) in
let p2 = (Array.length stride = 2) in
let error () =
let s0 = Printf.sprintf "input dimension = %i (should be 4)" (num_dims input) in
let s1 = Printf.sprintf "kernel dimension = %i (should be 2)" (Array.length kernel) in
let s2 = Printf.sprintf "stride dimension = %i (should be 2)" (Array.length stride) in
let s3 = Printf.sprintf "_pool2d: %s; %s; %s." s0 s1 s2 in
Owl_exception.INVALID_ARGUMENT s3
in
Owl_exception.verify (p0 && p1 && p2) error;
let input_shp = shape input in
let batches = input_shp.(0) in
let input_cols = input_shp.(1) in
let input_rows = input_shp.(2) in
let in_channel = input_shp.(3) in
let kernel_cols = kernel.(0) in
let kernel_rows = kernel.(1) in
let col_stride = stride.(0) in
let row_stride = stride.(1) in
let (output_cols, output_rows) =
Owl_utils_infer_shape.calc_conv2d_output_shape padding
input_cols input_rows
kernel_cols kernel_rows
row_stride col_stride
in
let _kind = kind input in
let output = empty _kind [|batches; output_cols; output_rows; in_channel|] in
let (pad_top, pad_left, _, _) = Owl_utils_infer_shape.calc_conv2d_padding
input_cols input_rows kernel_cols kernel_rows output_cols output_rows
row_stride col_stride
in
begin
for b = 0 to batches - 1 do
for i = 0 to output_cols - 1 do
for j = 0 to output_rows - 1 do
for k = 0 to in_channel - 1 do
init_pool_fun ();
for di = 0 to kernel_cols - 1 do
for dj = 0 to kernel_rows - 1 do
let in_col = i * col_stride + di - pad_left in
let in_row = j * row_stride + dj - pad_top in
if ((0 <= in_col) && (in_col < input_cols) &&
(0 <= in_row) && (in_row < input_rows))
then add_val_pool_fun (get input [|b; in_col; in_row; k|])
done;
done;
(set output [|b; i; j; k|] (end_pool_fun ()))
done;
done;
done;
done;
output
end
let _pool3d ?(padding=SAME) input kernel stride
init_pool_fun add_val_pool_fun end_pool_fun =
let p0 = (num_dims input = 5) in
let p1 = (Array.length kernel = 3) in
let p2 = (Array.length stride = 3) in
let error () =
let s0 = Printf.sprintf "input dimension = %i (should be 5)" (num_dims input) in
let s1 = Printf.sprintf "kernel dimension = %i (should be 3)" (Array.length kernel) in
let s2 = Printf.sprintf "stride dimension = %i (should be 3)" (Array.length stride) in
let s3 = Printf.sprintf "_pool3d: %s; %s; %s." s0 s1 s2 in
Owl_exception.INVALID_ARGUMENT s3
in
Owl_exception.verify (p0 && p1 && p2) error;
let input_shp = shape input in
let batches = input_shp.(0) in
let input_cols = input_shp.(1) in
let input_rows = input_shp.(2) in
let input_dpts = input_shp.(3) in
let in_channel = input_shp.(4) in
let kernel_cols = kernel.(0) in
let kernel_rows = kernel.(1) in
let kernel_dpts = kernel.(2) in
let col_stride = stride.(0) in
let row_stride = stride.(1) in
let dpt_stride = stride.(2) in
let output_cols, output_rows, output_dpts =
Owl_utils_infer_shape.calc_conv3d_output_shape padding
input_cols input_rows input_dpts
kernel_cols kernel_rows kernel_dpts
row_stride col_stride dpt_stride
in
let _kind = kind input in
let output = empty _kind [|batches; output_cols; output_rows; output_dpts; in_channel|] in
let (pad_top, pad_left, pad_shallow, _, _, _) =
Owl_utils_infer_shape.calc_conv3d_padding
input_cols input_rows input_dpts
kernel_cols kernel_rows kernel_dpts
output_cols output_rows output_dpts
row_stride col_stride dpt_stride
in
begin
for b = 0 to batches - 1 do
for i = 0 to output_cols - 1 do
for j = 0 to output_rows - 1 do
for dpt = 0 to output_dpts - 1 do
for k = 0 to in_channel - 1 do
init_pool_fun ();
for di = 0 to kernel_cols - 1 do
for dj = 0 to kernel_rows - 1 do
for d_dpt = 0 to kernel_dpts - 1 do
let in_col = i * col_stride + di - pad_left in
let in_row = j * row_stride + dj - pad_top in
let in_dpt = dpt * dpt_stride + d_dpt - pad_shallow in
if ((0 <= in_col) && (in_col < input_cols) &&
(0 <= in_row) && (in_row < input_rows) &&
(0 <= in_dpt) && (in_dpt < input_dpts))
then add_val_pool_fun
(get input [|b; in_col; in_row; in_dpt; k|])
done;
done;
done;
(set output [|b; i; j; dpt; k|] (end_pool_fun ()))
done;
done;
done;
done;
done;
output
end
let max_pool2d ?(padding=SAME) input kernel stride =
let max_pool = ref 0. in
let init_pool_fun = (fun () -> max_pool := Stdlib.min_float) in
let add_val_pool_fun =
(fun v -> max_pool := Stdlib.max !max_pool v)
in
let end_pool_fun = (fun () -> !max_pool) in
(_pool2d ~padding:padding input kernel stride
init_pool_fun add_val_pool_fun end_pool_fun)
let max_pool1d ?(padding=SAME) input kernel stride =
let p0 = (num_dims input = 3) in
let p1 = (Array.length kernel = 1) in
let p2 = (Array.length stride = 1) in
let error () =
let s0 = Printf.sprintf "input dimension = %i (should be 3)" (num_dims input) in
let s1 = Printf.sprintf "kernel dimension = %i (should be 1)" (Array.length kernel) in
let s2 = Printf.sprintf "stride dimension = %i (should be 1)" (Array.length stride) in
let s3 = Printf.sprintf "max_pool1d: %s; %s; %s." s0 s1 s2 in
Owl_exception.INVALID_ARGUMENT s3
in
Owl_exception.verify (p0 && p1 && p2) error;
let input_shp = shape input in
let batches = input_shp.(0) in
let input_cols = input_shp.(1) in
let in_channel = input_shp.(2) in
let input = reshape input [|batches; 1; input_cols; in_channel|] in
let kernel_cols = kernel.(0) in
let kernel = [|1; kernel_cols|] in
let col_stride = stride.(0) in
let stride = [|1; col_stride|] in
let output = max_pool2d ~padding input kernel stride in
let output_shp = shape output in
let output_cols = output_shp.(2) in
let output = reshape output [|batches; output_cols; in_channel|] in
output
let max_pool3d ?(padding=SAME) input kernel stride =
let max_pool = ref 0. in
let init_pool_fun = (fun () -> max_pool := Stdlib.min_float) in
let add_val_pool_fun =
(fun v -> max_pool := Stdlib.max !max_pool v)
in
let end_pool_fun = (fun () -> !max_pool) in
(_pool3d ~padding:padding input kernel stride
init_pool_fun add_val_pool_fun end_pool_fun)
let avg_pool2d ?(padding=SAME) input kernel stride =
let sum_pool = ref 0. in
let cnt = ref 0. in
let init_pool_fun = (fun () -> (sum_pool := 0.; cnt := 0.)) in
let add_val_pool_fun =
(fun v -> sum_pool := !sum_pool +. v; cnt := !cnt +. 1.)
in
let end_pool_fun = (fun () -> (!sum_pool /. !cnt)) in
(_pool2d ~padding:padding input kernel stride
init_pool_fun add_val_pool_fun end_pool_fun)
let avg_pool1d ?(padding=SAME) input kernel stride =
let p0 = (num_dims input = 3) in
let p1 = (Array.length kernel = 1) in
let p2 = (Array.length stride = 1) in
let error () =
let s0 = Printf.sprintf "input dimension = %i (should be 3)" (num_dims input) in
let s1 = Printf.sprintf "kernel dimension = %i (should be 1)" (Array.length kernel) in
let s2 = Printf.sprintf "stride dimension = %i (should be 1)" (Array.length stride) in
let s3 = Printf.sprintf "avg_pool1d: %s; %s; %s." s0 s1 s2 in
Owl_exception.INVALID_ARGUMENT s3
in
Owl_exception.verify (p0 && p1 && p2) error;
let input_shp = shape input in
let batches = input_shp.(0) in
let input_cols = input_shp.(1) in
let in_channel = input_shp.(2) in
let input = reshape input [|batches; 1; input_cols; in_channel|] in
let kernel_cols = kernel.(0) in
let kernel = [|1; kernel_cols|] in
let col_stride = stride.(0) in
let stride = [|1; col_stride|] in
let output = avg_pool2d ~padding input kernel stride in
let output_shp = shape output in
let output_cols = output_shp.(2) in
let output = reshape output [|batches; output_cols; in_channel|] in
output
let avg_pool3d ?(padding=SAME) input kernel stride =
let sum_pool = ref 0. in
let cnt = ref 0. in
let init_pool_fun = (fun () -> (sum_pool := 0.; cnt := 0.)) in
let add_val_pool_fun =
(fun v -> sum_pool := !sum_pool +. v; cnt := !cnt +. 1.)
in
let end_pool_fun = (fun () -> (!sum_pool /. !cnt)) in
(_pool3d ~padding:padding input kernel stride
init_pool_fun add_val_pool_fun end_pool_fun)
let conv2d_backward_input input kernel stride output' =
let p0 = (num_dims input = 4) in
let p1 = (num_dims kernel = 4) in
let p2 = (num_dims output' = 4) in
let p3 = (Array.length stride = 2) in
let error () =
let s0 = Printf.sprintf "input dimension = %i (should be 4)" (num_dims input) in
let s1 = Printf.sprintf "kernel dimension = %i (should be 4)" (num_dims kernel) in
let s2 = Printf.sprintf "output' dimension = %i (should be 4)" (num_dims output') in
let s3 = Printf.sprintf "stride dimension = %i (should be 2)" (Array.length stride) in
let s4 = Printf.sprintf "conv2d_backward_input: %s; %s; %s; %s." s0 s1 s2 s3 in
Owl_exception.INVALID_ARGUMENT s4
in
Owl_exception.verify (p0 && p1 && p2 && p3) error;
let input_shp = shape input in
let batches = input_shp.(0) in
let input_cols = input_shp.(1) in
let input_rows = input_shp.(2) in
let in_channel = input_shp.(3) in
let kernel_shp = shape kernel in
let kernel_cols = kernel_shp.(0) in
let kernel_rows = kernel_shp.(1) in
let out_channel = kernel_shp.(3) in
let p4 = (in_channel = kernel_shp.(2)) in
let error () =
let s0 = Owl_utils_array.to_string string_of_int input_shp in
let s1 = Printf.sprintf "input shape is [%s]" s0 in
let s2 = Owl_utils_array.to_string string_of_int kernel_shp in
let s3 = Printf.sprintf "kernel shape is [%s]" s2 in
let s4 = Printf.sprintf "the 4th dimension of input shape should be equal to the 3rd dimension of kernel shape" in
let s5 = Printf.sprintf "conv2d_backward_input: %s, %s, %s." s1 s3 s4 in
Owl_exception.INVALID_ARGUMENT s5
in
Owl_exception.verify p4 error;
let output_shp = shape output' in
let output_cols = output_shp.(1) in
let output_rows = output_shp.(2) in
let p5 = (batches = output_shp.(0)) in
let p6 = (out_channel = output_shp.(3)) in
let error () =
let s0 = Owl_utils_array.to_string string_of_int input_shp in
let s1 = Owl_utils_array.to_string string_of_int output_shp in
let s2 = Owl_utils_array.to_string string_of_int kernel_shp in
let s3 = Printf.sprintf "input shape is [%s]" s0 in
let s4 = Printf.sprintf "output' shape is [%s]" s1 in
let s5 = Printf.sprintf "kernel shape is [%s]" s2 in
let s6 = Printf.sprintf "the 1st dimension of input shape should be equal to the 1st dimension of output' shape" in
let s7 = Printf.sprintf "the 4th dimension of kernel shape should be equal to the 4th dimension of output' shape" in
let s8 = Printf.sprintf "conv2d_backward_input: %s; %s; %s; %s; %s." s3 s4 s5 s6 s7 in
Owl_exception.INVALID_ARGUMENT s8
in
Owl_exception.verify (p5 && p6) error;
let col_stride = stride.(0) in
let row_stride = stride.(1) in
let input' = empty (kind input) (shape input) in
let (pad_top, pad_left, _, _) = Owl_utils_infer_shape.calc_conv2d_padding
input_cols input_rows kernel_cols kernel_rows output_cols output_rows
row_stride col_stride
in
begin
for b = 0 to batches - 1 do
for in_i = 0 to input_cols - 1 do
for in_j = 0 to input_rows - 1 do
for q = 0 to in_channel - 1 do
let sum = ref 0. in
for di = 0 to kernel_cols - 1 do
for dj = 0 to kernel_rows - 1 do
if ( ((Stdlib.(mod) (in_i + pad_left - di) col_stride) = 0) &&
((Stdlib.(mod) (in_j + pad_top - dj) row_stride) = 0) )
then
begin
let out_col = (in_i + pad_left - di) / col_stride in
let out_row = (in_j + pad_top - dj) / row_stride in
if ((0 <= out_col) && (out_col < output_cols) &&
(0 <= out_row) && (out_row < output_rows))
then
for k = 0 to out_channel - 1 do
let out_grad = get output' [|b; out_col; out_row; k|] in
let kernel_val = get kernel [|di; dj; q; k|] in
sum := !sum +. out_grad *. kernel_val
done;
end
done;
done;
(set input' [|b; in_i; in_j; q|] !sum)
done;
done;
done;
done;
input'
end
let conv2d_backward_kernel input kernel stride output' =
let p0 = (num_dims input = 4) in
let p1 = (num_dims kernel = 4) in
let p2 = (num_dims output' = 4) in
let p3 = (Array.length stride = 2) in
let error () =
let s0 = Printf.sprintf "input dimension = %i (should be 4)" (num_dims input) in
let s1 = Printf.sprintf "kernel dimension = %i (should be 4)" (num_dims kernel) in
let s2 = Printf.sprintf "output' dimension = %i (should be 4)" (num_dims output') in
let s3 = Printf.sprintf "stride dimension = %i (should be 2)" (Array.length stride) in
let s4 = Printf.sprintf "conv2d_backward_kernel: %s; %s; %s; %s." s0 s1 s2 s3 in
Owl_exception.INVALID_ARGUMENT s4
in
Owl_exception.verify (p0 && p1 && p2 && p3) error;
let input_shp = shape input in
let batches = input_shp.(0) in
let input_cols = input_shp.(1) in
let input_rows = input_shp.(2) in
let in_channel = input_shp.(3) in
let kernel_shp = shape kernel in
let kernel_cols = kernel_shp.(0) in
let kernel_rows = kernel_shp.(1) in
let out_channel = kernel_shp.(3) in
let p4 = (in_channel = kernel_shp.(2)) in
let error () =
let s0 = Owl_utils_array.to_string string_of_int input_shp in
let s1 = Printf.sprintf "input shape is [%s]" s0 in
let s2 = Owl_utils_array.to_string string_of_int kernel_shp in
let s3 = Printf.sprintf "kernel shape is [%s]" s2 in
let s4 = Printf.sprintf "the 4th dimension of input shape should be equal to the 3rd dimension of kernel shape" in
let s5 = Printf.sprintf "conv2d_backward_kernel: %s, %s, %s." s1 s3 s4 in
Owl_exception.INVALID_ARGUMENT s5
in
Owl_exception.verify p4 error;
let output_shp = shape output' in
let output_cols = output_shp.(1) in
let output_rows = output_shp.(2) in
let p5 = (batches = output_shp.(0)) in
let p6 = (out_channel = output_shp.(3)) in
let error () =
let s0 = Owl_utils_array.to_string string_of_int input_shp in
let s1 = Owl_utils_array.to_string string_of_int output_shp in
let s2 = Owl_utils_array.to_string string_of_int kernel_shp in
let s3 = Printf.sprintf "input shape is [%s]" s0 in
let s4 = Printf.sprintf "output' shape is [%s]" s1 in
let s5 = Printf.sprintf "kernel shape is [%s]" s2 in
let s6 = Printf.sprintf "the 1st dimension of input shape should be equal to the 1st dimension of output' shape" in
let s7 = Printf.sprintf "the 4th dimension of kernel shape should be equal to the 4th dimension of output' shape" in
let s8 = Printf.sprintf "conv2d_backward_kernel: %s; %s; %s; %s; %s." s3 s4 s5 s6 s7 in
Owl_exception.INVALID_ARGUMENT s8
in
Owl_exception.verify (p5 && p6) error;
let col_stride = stride.(0) in
let row_stride = stride.(1) in
let kernel' = empty (kind kernel) (shape kernel) in
let (pad_top, pad_left, _, _) = Owl_utils_infer_shape.calc_conv2d_padding
input_cols input_rows kernel_cols kernel_rows output_cols output_rows
row_stride col_stride
in
begin
for di = 0 to kernel_cols - 1 do
for dj = 0 to kernel_rows - 1 do
for q = 0 to in_channel - 1 do
for k = 0 to out_channel - 1 do
let sum = ref 0. in
for b = 0 to batches - 1 do
for i = 0 to output_cols - 1 do
for j = 0 to output_rows - 1 do
let in_col = i * col_stride + di - pad_left in
let in_row = j * row_stride + dj - pad_top in
if ((0 <= in_col) && (in_col < input_cols) &&
(0 <= in_row) && (in_row < input_rows))
then
let out_grad = get output' [|b; i; j; k|] in
let input_val = get input [|b; in_col; in_row; q|] in
sum := !sum +. out_grad *. input_val
done;
done;
done;
set kernel' [|di; dj; q; k|] !sum
done;
done;
done;
done;
kernel'
end
let transpose ?axis varr =
let dims = shape varr in
let rank = Array.length dims in
let axis_perm = match axis with
| Some perm -> perm
| None -> Array.init rank (fun i -> rank - i - 1)
in
let new_dims = _apply_perm dims axis_perm in
let new_varr = empty (kind varr) new_dims in
let ind = Array.make rank 0 in
let should_stop = ref false in
begin
while not !should_stop do
Genarray.set new_varr
(_apply_perm ind axis_perm) (Genarray.get varr ind);
if not (_next_index ind dims) then
should_stop := true
done;
new_varr
end
let transpose_conv2d ?(padding=SAME) input kernel stride =
let p0 = (num_dims input = 4) in
let p1 = (num_dims kernel = 4) in
let p2 = (Array.length stride = 2) in
let error () =
let s0 = Printf.sprintf "input dimension = %i (should be 4)" (num_dims input) in
let s1 = Printf.sprintf "kernel dimension = %i (should be 4)" (num_dims kernel) in
let s2 = Printf.sprintf "stride dimension = %i (should be 2)" (Array.length stride) in
let s3 = Printf.sprintf "transpose_conv2d: %s; %s; %s." s0 s1 s2 in
Owl_exception.INVALID_ARGUMENT s3
in
Owl_exception.verify (p0 && p1 && p2) error;
let input_shp = shape input in
let batches = input_shp.(0) in
let input_cols = input_shp.(1) in
let input_rows = input_shp.(2) in
let in_channel = input_shp.(3) in
let kernel_shp = shape kernel in
let kernel_cols = kernel_shp.(0) in
let kernel_rows = kernel_shp.(1) in
let out_channel = kernel_shp.(3) in
let p3 = (in_channel = kernel_shp.(2)) in
let error () =
let s0 = Owl_utils_array.to_string string_of_int input_shp in
let s1 = Printf.sprintf "input shape is [%s]" s0 in
let s2 = Owl_utils_array.to_string string_of_int kernel_shp in
let s3 = Printf.sprintf "kernel shape is [%s]" s2 in
let s4 = Printf.sprintf "the 4th dimension of input shape should be equal to the 3rd dimension of kernel shape" in
let s5 = Printf.sprintf "transpose_conv2d: %s, %s, %s." s1 s3 s4 in
Owl_exception.INVALID_ARGUMENT s5
in
Owl_exception.verify p3 error;
let col_stride = stride.(0) in
let row_stride = stride.(1) in
let output_cols, output_rows = Owl_utils_infer_shape.calc_transpose_conv2d_output_shape
padding input_cols input_rows kernel_cols kernel_rows
row_stride col_stride
in
let output' = empty (kind input) [|batches; output_cols; output_rows;
out_channel|]
in
let kernel = transpose ~axis:[|0;1;3;2|] kernel in
conv2d_backward_input output' kernel stride input
let transpose_conv2d_backward_input input kernel stride output' =
let p0 = (num_dims input = 4) in
let p1 = (num_dims kernel = 4) in
let p2 = (num_dims output' = 4) in
let p3 = (Array.length stride = 2) in
let error () =
let s0 = Printf.sprintf "input dimension = %i (should be 4)" (num_dims input) in
let s1 = Printf.sprintf "kernel dimension = %i (should be 4)" (num_dims kernel) in
let s2 = Printf.sprintf "output' dimension = %i (should be 4)" (num_dims output') in
let s3 = Printf.sprintf "stride dimension = %i (should be 2)" (Array.length stride) in
let s4 = Printf.sprintf "transpose_conv2d_backward_input: %s; %s; %s; %s." s0 s1 s2 s3 in
Owl_exception.INVALID_ARGUMENT s4
in
Owl_exception.verify (p0 && p1 && p2 && p3) error;
let input_shp = shape input in
let batches = input_shp.(0) in
let input_cols = input_shp.(1) in
let input_rows = input_shp.(2) in
let in_channel = input_shp.(3) in
let kernel_shp = shape kernel in
let kernel_cols = kernel_shp.(0) in
let kernel_rows = kernel_shp.(1) in
let out_channel = kernel_shp.(3) in
let p4 = (in_channel = kernel_shp.(2)) in
let error () =
let s0 = Owl_utils_array.to_string string_of_int input_shp in
let s1 = Printf.sprintf "input shape is [%s]" s0 in
let s2 = Owl_utils_array.to_string string_of_int kernel_shp in
let s3 = Printf.sprintf "kernel shape is [%s]" s2 in
let s4 = Printf.sprintf "the 4th dimension of input shape should be equal to the 3rd dimension of kernel shape" in
let s5 = Printf.sprintf "transpose_conv2d_backward_input: %s, %s, %s." s1 s3 s4 in
Owl_exception.INVALID_ARGUMENT s5
in
Owl_exception.verify p4 error;
let output_shp = shape output' in
let output_cols = output_shp.(1) in
let output_rows = output_shp.(2) in
let p5 = (batches = output_shp.(0)) in
let p6 = (out_channel = output_shp.(3)) in
let error () =
let s0 = Owl_utils_array.to_string string_of_int input_shp in
let s1 = Owl_utils_array.to_string string_of_int output_shp in
let s2 = Owl_utils_array.to_string string_of_int kernel_shp in
let s3 = Printf.sprintf "input shape is [%s]" s0 in
let s4 = Printf.sprintf "output' shape is [%s]" s1 in
let s5 = Printf.sprintf "kernel shape is [%s]" s2 in
let s6 = Printf.sprintf "the 1st dimension of input shape should be equal to the 1st dimension of output' shape" in
let s7 = Printf.sprintf "the 4th dimension of kernel shape should be equal to the 4th dimension of output' shape" in
let s8 = Printf.sprintf "transpose_conv2d_backward_input: %s; %s; %s; %s; %s." s3 s4 s5 s6 s7 in
Owl_exception.INVALID_ARGUMENT s8
in
Owl_exception.verify (p5 && p6) error;
let col_stride = stride.(0) in
let row_stride = stride.(1) in
let padding = SAME in
let output_cols_same, output_rows_same =
Owl_utils_infer_shape.calc_transpose_conv2d_output_shape
padding input_cols input_rows kernel_cols kernel_rows
row_stride col_stride
in
let p = if ((output_cols_same = output_cols)
&& (output_rows_same = output_rows) ) then SAME else VALID
in
let kernel = transpose ~axis:[|0;1;3;2|] kernel in
conv2d ~padding:p output' kernel stride
let transpose_conv2d_backward_kernel input kernel stride output' =
conv2d_backward_kernel output' kernel stride input
let transpose_conv1d ?(padding=SAME) input kernel stride =
let p0 = (num_dims input = 3) in
let p1 = (num_dims kernel = 3) in
let p2 = (Array.length stride = 1) in
let error () =
let s0 = Printf.sprintf "input dimension = %i (should be 3)" (num_dims input) in
let s1 = Printf.sprintf "kernel dimension = %i (should be 3)" (num_dims kernel) in
let s2 = Printf.sprintf "stride dimension = %i (should be 1)" (Array.length stride) in
let s3 = Printf.sprintf "transpose_conv1d: %s; %s; %s." s0 s1 s2 in
Owl_exception.INVALID_ARGUMENT s3
in
Owl_exception.verify (p0 && p1 && p2) error;
let input_shp = shape input in
let batches = input_shp.(0) in
let input_cols = input_shp.(1) in
let in_channel = input_shp.(2) in
let input = reshape input [|batches; 1; input_cols; in_channel|] in
let kernel_shp = shape kernel in
let kernel_cols = kernel_shp.(0) in
let out_channel = kernel_shp.(2) in
let p3 = (in_channel = kernel_shp.(1)) in
let error () =
let s0 = Owl_utils_array.to_string string_of_int input_shp in
let s1 = Printf.sprintf "input shape is [%s]" s0 in
let s2 = Owl_utils_array.to_string string_of_int kernel_shp in
let s3 = Printf.sprintf "kernel shape is [%s]" s2 in
let s4 = Printf.sprintf "the 3rd dimension of input shape should be equal to the 2nd dimension of kernel shape" in
let s5 = Printf.sprintf "transpose_conv1d: %s, %s, %s." s1 s3 s4 in
Owl_exception.INVALID_ARGUMENT s5
in
Owl_exception.verify p3 error;
let kernel = reshape kernel [|1; kernel_cols; in_channel; out_channel|] in
let col_stride = stride.(0) in
let stride = [|1; col_stride|] in
let output = transpose_conv2d ~padding input kernel stride in
let output_shp = shape output in
let output_cols = output_shp.(2) in
let output = reshape output [|batches; output_cols; out_channel|] in
output
let conv1d_backward_input input kernel stride output' =
let p0 = (num_dims input = 3) in
let p1 = (num_dims kernel = 3) in
let p2 = (num_dims output' = 3) in
let p3 = (Array.length stride = 1) in
let error () =
let s0 = Printf.sprintf "input dimension = %i (should be 3)" (num_dims input) in
let s1 = Printf.sprintf "kernel dimension = %i (should be 3)" (num_dims kernel) in
let s2 = Printf.sprintf "output' dimension = %i (should be 3)" (num_dims output') in
let s3 = Printf.sprintf "stride dimension = %i (should be 1)" (Array.length stride) in
let s4 = Printf.sprintf "conv1d_backward_input: %s; %s; %s; %s." s0 s1 s2 s3 in
Owl_exception.INVALID_ARGUMENT s4
in
Owl_exception.verify (p0 && p1 && p2 && p3) error;
let input_shp = shape input in
let batches = input_shp.(0) in
let input_cols = input_shp.(1) in
let in_channel = input_shp.(2) in
let input_rows = 1 in
let input = reshape input [|batches; input_rows; input_cols; in_channel|] in
let kernel_shp = shape kernel in
let kernel_cols = kernel_shp.(0) in
let out_channel = kernel_shp.(2) in
let p4 = (in_channel = kernel_shp.(1)) in
let error () =
let s0 = Owl_utils_array.to_string string_of_int input_shp in
let s1 = Printf.sprintf "input shape is [%s]" s0 in
let s2 = Owl_utils_array.to_string string_of_int kernel_shp in
let s3 = Printf.sprintf "kernel shape is [%s]" s2 in
let s4 = Printf.sprintf "the 3th dimension of input shape should be equal to the 2nd dimension of kernel shape" in
let s5 = Printf.sprintf "conv1d_backward_input: %s, %s, %s." s1 s3 s4 in
Owl_exception.INVALID_ARGUMENT s5
in
Owl_exception.verify p4 error;
let kernel_rows = 1 in
let kernel = reshape kernel [|kernel_rows; kernel_cols; in_channel; out_channel|] in
let output'_shp = shape output' in
let output_cols = output'_shp.(1) in
let p5 = (batches = output'_shp.(0)) in
let p6 = (out_channel = output'_shp.(2)) in
let error () =
let s0 = Owl_utils_array.to_string string_of_int input_shp in
let s1 = Owl_utils_array.to_string string_of_int output'_shp in
let s2 = Owl_utils_array.to_string string_of_int kernel_shp in
let s3 = Printf.sprintf "input shape is [%s]" s0 in
let s4 = Printf.sprintf "output' shape is [%s]" s1 in
let s5 = Printf.sprintf "kernel shape is [%s]" s2 in
let s6 = Printf.sprintf "the 1st dimension of input shape should be equal to the 1st dimension of output' shape" in
let s7 = Printf.sprintf "the 3rd dimension of kernel shape should be equal to the 3rd dimension of output' shape" in
let s8 = Printf.sprintf "conv1d_backward_input: %s; %s; %s; %s; %s." s3 s4 s5 s6 s7 in
Owl_exception.INVALID_ARGUMENT s8
in
Owl_exception.verify (p5 && p6) error;
let output_rows = 1 in
let output' = reshape output' [|batches; output_rows; output_cols; out_channel|] in
let col_stride = stride.(0) in
let row_stride = 1 in
let stride = [|row_stride; col_stride|] in
let input' = conv2d_backward_input input kernel stride output' in
reshape input' input_shp
let conv1d_backward_kernel input kernel stride output' =
let p0 = (num_dims input = 3) in
let p1 = (num_dims kernel = 3) in
let p2 = (num_dims output' = 3) in
let p3 = (Array.length stride = 1) in
let error () =
let s0 = Printf.sprintf "input dimension = %i (should be 3)" (num_dims input) in
let s1 = Printf.sprintf "kernel dimension = %i (should be 3)" (num_dims kernel) in
let s2 = Printf.sprintf "output' dimension = %i (should be 3)" (num_dims output') in
let s3 = Printf.sprintf "stride dimension = %i (should be 1)" (Array.length stride) in
let s4 = Printf.sprintf "conv1d_backward_kernel: %s; %s; %s; %s." s0 s1 s2 s3 in
Owl_exception.INVALID_ARGUMENT s4
in
Owl_exception.verify (p0 && p1 && p2 && p3) error;
let input_shp = shape input in
let batches = input_shp.(0) in
let input_cols = input_shp.(1) in
let in_channel = input_shp.(2) in
let input_rows = 1 in
let input = reshape input [|batches; input_rows; input_cols; in_channel|] in
let kernel_shp = shape kernel in
let kernel_cols = kernel_shp.(0) in
let out_channel = kernel_shp.(2) in
let p4 = (in_channel = kernel_shp.(1)) in
let error () =
let s0 = Owl_utils_array.to_string string_of_int input_shp in
let s1 = Printf.sprintf "input shape is [%s]" s0 in
let s2 = Owl_utils_array.to_string string_of_int kernel_shp in
let s3 = Printf.sprintf "kernel shape is [%s]" s2 in
let s4 = Printf.sprintf "the 3th dimension of input shape should be equal to the 2nd dimension of kernel shape" in
let s5 = Printf.sprintf "conv1d_backward_kernel: %s, %s, %s." s1 s3 s4 in
Owl_exception.INVALID_ARGUMENT s5
in
Owl_exception.verify p4 error;
let kernel_rows = 1 in
let kernel = reshape kernel [|kernel_rows; kernel_cols; in_channel; out_channel|] in
let output'_shp = shape output' in
let output_cols = output'_shp.(1) in
let p5 = (batches = output'_shp.(0)) in
let p6 = (out_channel = output'_shp.(2)) in
let error () =
let s0 = Owl_utils_array.to_string string_of_int input_shp in
let s1 = Owl_utils_array.to_string string_of_int output'_shp in
let s2 = Owl_utils_array.to_string string_of_int kernel_shp in
let s3 = Printf.sprintf "input shape is [%s]" s0 in
let s4 = Printf.sprintf "output' shape is [%s]" s1 in
let s5 = Printf.sprintf "kernel shape is [%s]" s2 in
let s6 = Printf.sprintf "the 1st dimension of input shape should be equal to the 1st dimension of output' shape" in
let s7 = Printf.sprintf "the 3rd dimension of kernel shape should be equal to the 3rd dimension of output' shape" in
let s8 = Printf.sprintf "conv1d_backward_kernel: %s; %s; %s; %s; %s." s3 s4 s5 s6 s7 in
Owl_exception.INVALID_ARGUMENT s8
in
Owl_exception.verify (p5 && p6) error;
let output_rows = 1 in
let output' = reshape output' [|batches; output_rows; output_cols; out_channel|] in
let col_stride = stride.(0) in
let row_stride = 1 in
let stride = [|row_stride; col_stride|] in
let kernel' = conv2d_backward_kernel input kernel stride output' in
reshape kernel' kernel_shp
let transpose_conv1d_backward_input input kernel stride output' =
let p0 = (num_dims input = 3) in
let p1 = (num_dims kernel = 3) in
let p2 = (num_dims output' = 3) in
let p3 = (Array.length stride = 1) in
let error () =
let s0 = Printf.sprintf "input dimension = %i (should be 3)" (num_dims input) in
let s1 = Printf.sprintf "kernel dimension = %i (should be 3)" (num_dims kernel) in
let s2 = Printf.sprintf "output' dimension = %i (should be 3)" (num_dims output') in
let s3 = Printf.sprintf "stride dimension = %i (should be 1)" (Array.length stride) in
let s4 = Printf.sprintf "transpose_conv1d_backward_input: %s; %s; %s; %s." s0 s1 s2 s3 in
Owl_exception.INVALID_ARGUMENT s4
in
Owl_exception.verify (p0 && p1 && p2 && p3) error;
let input_shp = shape input in
let batches = input_shp.(0) in
let input_cols = input_shp.(1) in
let in_channel = input_shp.(2) in
let input_rows = 1 in
let input = reshape input [|batches; input_rows; input_cols; in_channel|] in
let kernel_shp = shape kernel in
let kernel_cols = kernel_shp.(0) in
let out_channel = kernel_shp.(2) in
let p4 = (in_channel = kernel_shp.(1)) in
let error () =
let s0 = Owl_utils_array.to_string string_of_int input_shp in
let s1 = Printf.sprintf "input shape is [%s]" s0 in
let s2 = Owl_utils_array.to_string string_of_int kernel_shp in
let s3 = Printf.sprintf "kernel shape is [%s]" s2 in
let s4 = Printf.sprintf "the 3th dimension of input shape should be equal to the 2nd dimension of kernel shape" in
let s5 = Printf.sprintf "transpose_conv1d_backward_input: %s, %s, %s." s1 s3 s4 in
Owl_exception.INVALID_ARGUMENT s5
in
Owl_exception.verify p4 error;
let kernel_rows = 1 in
let kernel = reshape kernel [|kernel_rows; kernel_cols; in_channel; out_channel|] in
let output'_shp = shape output' in
let output_cols = output'_shp.(1) in
let p5 = (batches = output'_shp.(0)) in
let p6 = (out_channel = output'_shp.(2)) in
let error () =
let s0 = Owl_utils_array.to_string string_of_int input_shp in
let s1 = Owl_utils_array.to_string string_of_int output'_shp in
let s2 = Owl_utils_array.to_string string_of_int kernel_shp in
let s3 = Printf.sprintf "input shape is [%s]" s0 in
let s4 = Printf.sprintf "output' shape is [%s]" s1 in
let s5 = Printf.sprintf "kernel shape is [%s]" s2 in
let s6 = Printf.sprintf "the 1st dimension of input shape should be equal to the 1st dimension of output' shape" in
let s7 = Printf.sprintf "the 3rd dimension of kernel shape should be equal to the 3rd dimension of output' shape" in
let s8 = Printf.sprintf "transpose_conv1d_backward_input: %s; %s; %s; %s; %s." s3 s4 s5 s6 s7 in
Owl_exception.INVALID_ARGUMENT s8
in
Owl_exception.verify (p5 && p6) error;
let output_rows = 1 in
let output' = reshape output' [|batches; output_rows; output_cols; out_channel|] in
let col_stride = stride.(0) in
let row_stride = 1 in
let stride = [|row_stride; col_stride|] in
let input' = transpose_conv2d_backward_input input kernel stride output' in
reshape input' input_shp
let transpose_conv1d_backward_kernel input kernel stride output' =
let p0 = (num_dims input = 3) in
let p1 = (num_dims kernel = 3) in
let p2 = (num_dims output' = 3) in
let p3 = (Array.length stride = 1) in
let error () =
let s0 = Printf.sprintf "input dimension = %i (should be 3)" (num_dims input) in
let s1 = Printf.sprintf "kernel dimension = %i (should be 3)" (num_dims kernel) in
let s2 = Printf.sprintf "output' dimension = %i (should be 3)" (num_dims output') in
let s3 = Printf.sprintf "stride dimension = %i (should be 1)" (Array.length stride) in
let s4 = Printf.sprintf "transpose_conv1d_backward_kernel: %s; %s; %s; %s." s0 s1 s2 s3 in
Owl_exception.INVALID_ARGUMENT s4
in
Owl_exception.verify (p0 && p1 && p2 && p3) error;
let input_shp = shape input in
let batches = input_shp.(0) in
let input_cols = input_shp.(1) in
let in_channel = input_shp.(2) in
let input_rows = 1 in
let input = reshape input [|batches; input_rows; input_cols; in_channel|] in
let kernel_shp = shape kernel in
let kernel_cols = kernel_shp.(0) in
let out_channel = kernel_shp.(2) in
let p4 = (in_channel = kernel_shp.(1)) in
let error () =
let s0 = Owl_utils_array.to_string string_of_int input_shp in
let s1 = Printf.sprintf "input shape is [%s]" s0 in
let s2 = Owl_utils_array.to_string string_of_int kernel_shp in
let s3 = Printf.sprintf "kernel shape is [%s]" s2 in
let s4 = Printf.sprintf "the 3th dimension of input shape should be equal to the 2nd dimension of kernel shape" in
let s5 = Printf.sprintf "transpose_conv1d_backward_kernel: %s, %s, %s." s1 s3 s4 in
Owl_exception.INVALID_ARGUMENT s5
in
Owl_exception.verify p4 error;
let kernel_rows = 1 in
let kernel = reshape kernel [|kernel_rows; kernel_cols; in_channel; out_channel|] in
let output'_shp = shape output' in
let output_cols = output'_shp.(1) in
let p5 = (batches = output'_shp.(0)) in
let p6 = (out_channel = output'_shp.(2)) in
let error () =
let s0 = Owl_utils_array.to_string string_of_int input_shp in
let s1 = Owl_utils_array.to_string string_of_int output'_shp in
let s2 = Owl_utils_array.to_string string_of_int kernel_shp in
let s3 = Printf.sprintf "input shape is [%s]" s0 in
let s4 = Printf.sprintf "output' shape is [%s]" s1 in
let s5 = Printf.sprintf "kernel shape is [%s]" s2 in
let s6 = Printf.sprintf "the 1st dimension of input shape should be equal to the 1st dimension of output' shape" in
let s7 = Printf.sprintf "the 3rd dimension of kernel shape should be equal to the 3rd dimension of output' shape" in
let s8 = Printf.sprintf "transpose_conv1d_backward_kernel: %s; %s; %s; %s; %s." s3 s4 s5 s6 s7 in
Owl_exception.INVALID_ARGUMENT s8
in
Owl_exception.verify (p5 && p6) error;
let output_rows = 1 in
let output' = reshape output' [|batches; output_rows; output_cols; out_channel|] in
let col_stride = stride.(0) in
let row_stride = 1 in
let stride = [|row_stride; col_stride|] in
let kernel' = transpose_conv2d_backward_kernel input kernel stride output' in
reshape kernel' kernel_shp
let conv3d_backward_input input kernel stride output' =
let p0 = (num_dims input = 5) in
let p1 = (num_dims kernel = 5) in
let p2 = (num_dims output' = 5) in
let p3 = (Array.length stride = 3) in
let error () =
let s0 = Printf.sprintf "input dimension = %i (should be 5)" (num_dims input) in
let s1 = Printf.sprintf "kernel dimension = %i (should be 5)" (num_dims kernel) in
let s2 = Printf.sprintf "output' dimension = %i (should be 5)" (num_dims output') in
let s3 = Printf.sprintf "stride dimension = %i (should be 3)" (Array.length stride) in
let s4 = Printf.sprintf "conv3d_backward_input: %s; %s; %s; %s." s0 s1 s2 s3 in
Owl_exception.INVALID_ARGUMENT s4
in
Owl_exception.verify (p0 && p1 && p2 && p3) error;
let input_shp = shape input in
let batches = input_shp.(0) in
let input_cols = input_shp.(1) in
let input_rows = input_shp.(2) in
let input_dpts = input_shp.(3) in
let in_channel = input_shp.(4) in
let kernel_shp = shape kernel in
let kernel_cols = kernel_shp.(0) in
let kernel_rows = kernel_shp.(1) in
let kernel_dpts = kernel_shp.(2) in
let out_channel = kernel_shp.(4) in
let p4 = (in_channel = kernel_shp.(3)) in
let error () =
let s0 = Owl_utils_array.to_string string_of_int input_shp in
let s1 = Printf.sprintf "input shape is [%s]" s0 in
let s2 = Owl_utils_array.to_string string_of_int kernel_shp in
let s3 = Printf.sprintf "kernel shape is [%s]" s2 in
let s4 = Printf.sprintf "the 5th dimension of input shape should be equal to the 4th dimension of kernel shape" in
let s5 = Printf.sprintf "conv3d_backward_input: %s, %s, %s." s1 s3 s4 in
Owl_exception.INVALID_ARGUMENT s5
in
Owl_exception.verify p4 error;
let output_shp = shape output' in
let output_cols = output_shp.(1) in
let output_rows = output_shp.(2) in
let output_dpts = output_shp.(3) in
let p5 = (batches = output_shp.(0)) in
let p6 = (out_channel = output_shp.(4)) in
let error () =
let s0 = Owl_utils_array.to_string string_of_int input_shp in
let s1 = Owl_utils_array.to_string string_of_int output_shp in
let s2 = Owl_utils_array.to_string string_of_int kernel_shp in
let s3 = Printf.sprintf "input shape is [%s]" s0 in
let s4 = Printf.sprintf "output' shape is [%s]" s1 in
let s5 = Printf.sprintf "kernel shape is [%s]" s2 in
let s6 = Printf.sprintf "the 1st dimension of input shape should be equal to the 1st dimension of output' shape" in
let s7 = Printf.sprintf "the 5th dimension of kernel shape should be equal to the 5th dimension of output' shape" in
let s8 = Printf.sprintf "conv3d_backward_input: %s; %s; %s; %s; %s." s3 s4 s5 s6 s7 in
Owl_exception.INVALID_ARGUMENT s8
in
Owl_exception.verify (p5 && p6) error;
let col_stride = stride.(0) in
let row_stride = stride.(1) in
let dpt_stride = stride.(2) in
let input' = empty (kind input) (shape input) in
let (pad_top, pad_left, pad_shallow, _, _, _) =
Owl_utils_infer_shape.calc_conv3d_padding
input_cols input_rows input_dpts
kernel_cols kernel_rows kernel_dpts
output_cols output_rows output_dpts
row_stride col_stride dpt_stride
in
begin
for b = 0 to batches - 1 do
for in_i = 0 to input_cols - 1 do
for in_j = 0 to input_rows - 1 do
for in_dpt = 0 to input_dpts - 1 do
for q = 0 to in_channel - 1 do
let sum = ref 0. in
for di = 0 to kernel_cols - 1 do
for dj = 0 to kernel_rows - 1 do
for d_dpt = 0 to kernel_dpts - 1 do
if ( ((Stdlib.(mod) (in_i + pad_left - di) col_stride) = 0) &&
((Stdlib.(mod) (in_j + pad_top - dj) row_stride) = 0) &&
((Stdlib.(mod) (in_dpt + pad_shallow - d_dpt) dpt_stride) = 0))
then
begin
let out_col = (in_i + pad_left - di) / col_stride in
let out_row = (in_j + pad_top - dj) / row_stride in
let out_dpt = (in_dpt + pad_shallow - d_dpt) / dpt_stride in
if ((0 <= out_col) && (out_col < output_cols) &&
(0 <= out_row) && (out_row < output_rows) &&
(0 <= out_dpt) && (out_dpt < output_dpts))
then
for k = 0 to out_channel - 1 do
let out_grad = get output' [|b; out_col; out_row; out_dpt; k|] in
let kernel_val = get kernel [|di; dj; d_dpt; q; k|] in
sum := !sum +. out_grad *. kernel_val
done;
end
done;
done;
done;
(set input' [|b; in_i; in_j; in_dpt; q|] !sum)
done;
done;
done;
done;
done;
input'
end
let conv3d_backward_kernel input kernel stride output' =
let p0 = (num_dims input = 5) in
let p1 = (num_dims kernel = 5) in
let p2 = (num_dims output' = 5) in
let p3 = (Array.length stride = 3) in
let error () =
let s0 = Printf.sprintf "input dimension = %i (should be 5)" (num_dims input) in
let s1 = Printf.sprintf "kernel dimension = %i (should be 5)" (num_dims kernel) in
let s2 = Printf.sprintf "output' dimension = %i (should be 5)" (num_dims output') in
let s3 = Printf.sprintf "stride dimension = %i (should be 3)" (Array.length stride) in
let s4 = Printf.sprintf "conv3d_backward_kernel: %s; %s; %s; %s." s0 s1 s2 s3 in
Owl_exception.INVALID_ARGUMENT s4
in
Owl_exception.verify (p0 && p1 && p2 && p3) error;
let input_shp = shape input in
let batches = input_shp.(0) in
let input_cols = input_shp.(1) in
let input_rows = input_shp.(2) in
let input_dpts = input_shp.(3) in
let in_channel = input_shp.(4) in
let kernel_shp = shape kernel in
let kernel_cols = kernel_shp.(0) in
let kernel_rows = kernel_shp.(1) in
let kernel_dpts = kernel_shp.(2) in
let out_channel = kernel_shp.(4) in
let p4 = (in_channel = kernel_shp.(3)) in
let error () =
let s0 = Owl_utils_array.to_string string_of_int input_shp in
let s1 = Printf.sprintf "input shape is [%s]" s0 in
let s2 = Owl_utils_array.to_string string_of_int kernel_shp in
let s3 = Printf.sprintf "kernel shape is [%s]" s2 in
let s4 = Printf.sprintf "the 5th dimension of input shape should be equal to the 4th dimension of kernel shape" in
let s5 = Printf.sprintf "conv2d_backward_kernel: %s, %s, %s." s1 s3 s4 in
Owl_exception.INVALID_ARGUMENT s5
in
Owl_exception.verify p4 error;
let output_shp = shape output' in
let output_cols = output_shp.(1) in
let output_rows = output_shp.(2) in
let output_dpts = output_shp.(3) in
let p5 = (batches = output_shp.(0)) in
let p6 = (out_channel = output_shp.(4)) in
let error () =
let s0 = Owl_utils_array.to_string string_of_int input_shp in
let s1 = Owl_utils_array.to_string string_of_int output_shp in
let s2 = Owl_utils_array.to_string string_of_int kernel_shp in
let s3 = Printf.sprintf "input shape is [%s]" s0 in
let s4 = Printf.sprintf "output' shape is [%s]" s1 in
let s5 = Printf.sprintf "kernel shape is [%s]" s2 in
let s6 = Printf.sprintf "the 1st dimension of input shape should be equal to the 1st dimension of output' shape" in
let s7 = Printf.sprintf "the 5th dimension of kernel shape should be equal to the 5th dimension of output' shape" in
let s8 = Printf.sprintf "conv2d_backward_kernel: %s; %s; %s; %s; %s." s3 s4 s5 s6 s7 in
Owl_exception.INVALID_ARGUMENT s8
in
Owl_exception.verify (p5 && p6) error;
let col_stride = stride.(0) in
let row_stride = stride.(1) in
let dpt_stride = stride.(2) in
let kernel' = empty (kind kernel) (shape kernel) in
let (pad_top, pad_left, pad_shallow, _, _, _) =
Owl_utils_infer_shape.calc_conv3d_padding
input_cols input_rows input_dpts
kernel_cols kernel_rows kernel_dpts
output_cols output_rows output_dpts
row_stride col_stride dpt_stride
in
begin
for di = 0 to kernel_cols - 1 do
for dj = 0 to kernel_rows - 1 do
for d_dpt = 0 to kernel_dpts - 1 do
for q = 0 to in_channel - 1 do
for k = 0 to out_channel - 1 do
let sum = ref 0. in
for b = 0 to batches - 1 do
for i = 0 to output_cols - 1 do
for j = 0 to output_rows - 1 do
for dpt = 0 to output_dpts - 1 do
let in_col = i * col_stride + di - pad_left in
let in_row = j * row_stride + dj - pad_top in
let in_dpt = dpt * dpt_stride + d_dpt - pad_shallow in
if ((0 <= in_col) && (in_col < input_cols) &&
(0 <= in_row) && (in_row < input_rows) &&
(0 <= in_dpt) && (in_dpt < input_dpts))
then
let out_grad = get output' [|b; i; j; dpt; k|] in
let input_val = get input [|b; in_col; in_row; in_dpt; q|] in
sum := !sum +. out_grad *. input_val
done;
done;
done;
done;
set kernel' [|di; dj; d_dpt; q; k|] !sum
done;
done;
done;
done;
done;
kernel'
end
let transpose_conv3d ?(padding=SAME) input kernel stride =
let p0 = (num_dims input = 5) in
let p1 = (num_dims kernel = 5) in
let p2 = (Array.length stride = 3) in
let error () =
let s0 = Printf.sprintf "input dimension = %i (should be 5)" (num_dims input) in
let s1 = Printf.sprintf "kernel dimension = %i (should be 5)" (num_dims kernel) in
let s2 = Printf.sprintf "stride dimension = %i (should be 3)" (Array.length stride) in
let s3 = Printf.sprintf "transpose_conv3d: %s; %s; %s." s0 s1 s2 in
Owl_exception.INVALID_ARGUMENT s3
in
Owl_exception.verify (p0 && p1 && p2) error;
let input_shp = shape input in
let batches = input_shp.(0) in
let input_cols = input_shp.(1) in
let input_rows = input_shp.(2) in
let input_dpts = input_shp.(3) in
let in_channel = input_shp.(4) in
let kernel_shp = shape kernel in
let kernel_cols = kernel_shp.(0) in
let kernel_rows = kernel_shp.(1) in
let kernel_dpts = kernel_shp.(2) in
let out_channel = kernel_shp.(4) in
let p3 = (in_channel = kernel_shp.(3)) in
let error () =
let s0 = Owl_utils_array.to_string string_of_int input_shp in
let s1 = Printf.sprintf "input shape is [%s]" s0 in
let s2 = Owl_utils_array.to_string string_of_int kernel_shp in
let s3 = Printf.sprintf "kernel shape is [%s]" s2 in
let s4 = Printf.sprintf "the 5th dimension of input shape should be equal to the 4th dimension of kernel shape" in
let s5 = Printf.sprintf "transpose_conv3d: %s, %s, %s." s1 s3 s4 in
Owl_exception.INVALID_ARGUMENT s5
in
Owl_exception.verify p3 error;
let col_stride = stride.(0) in
let row_stride = stride.(1) in
let dpt_stride = stride.(2) in
let output_cols, output_rows, output_dpts =
Owl_utils_infer_shape.calc_conv3d_output_shape padding input_cols input_rows input_dpts kernel_cols kernel_rows kernel_dpts row_stride col_stride dpt_stride
in
let output = empty (kind input) [|batches; output_cols; output_rows; output_dpts; out_channel|] in
let kernel = transpose ~axis:[|0;1;2;4;3|] kernel in
conv3d_backward_input output kernel stride input
let transpose_conv3d_backward_input input kernel stride output' =
let p0 = (num_dims input = 5) in
let p1 = (num_dims kernel = 5) in
let p2 = (num_dims output' = 5) in
let p3 = (Array.length stride = 3) in
let error () =
let s0 = Printf.sprintf "input dimension = %i (should be 5)" (num_dims input) in
let s1 = Printf.sprintf "kernel dimension = %i (should be 5)" (num_dims kernel) in
let s2 = Printf.sprintf "output' dimension = %i (should be 5)" (num_dims output') in
let s3 = Printf.sprintf "stride dimension = %i (should be 3)" (Array.length stride) in
let s4 = Printf.sprintf "transpose_conv3d_backward_input: %s; %s; %s; %s." s0 s1 s2 s3 in
Owl_exception.INVALID_ARGUMENT s4
in
Owl_exception.verify (p0 && p1 && p2 && p3) error;
let input_shp = shape input in
let batches = input_shp.(0) in
let input_cols = input_shp.(1) in
let input_rows = input_shp.(2) in
let input_dpts = input_shp.(3) in
let in_channel = input_shp.(4) in
let kernel_shp = shape kernel in
let kernel_cols = kernel_shp.(0) in
let kernel_rows = kernel_shp.(1) in
let kernel_dpts = kernel_shp.(2) in
let out_channel = kernel_shp.(4) in
let p4 = (in_channel = kernel_shp.(3)) in
let error () =
let s0 = Owl_utils_array.to_string string_of_int input_shp in
let s1 = Printf.sprintf "input shape is [%s]" s0 in
let s2 = Owl_utils_array.to_string string_of_int kernel_shp in
let s3 = Printf.sprintf "kernel shape is [%s]" s2 in
let s4 = Printf.sprintf "the 5th dimension of input shape should be equal to the 4th dimension of kernel shape" in
let s5 = Printf.sprintf "transpose_conv3d_backward_input: %s, %s, %s." s1 s3 s4 in
Owl_exception.INVALID_ARGUMENT s5
in
Owl_exception.verify p4 error;
let output_shp = shape output' in
let output_cols = output_shp.(1) in
let output_rows = output_shp.(2) in
let output_dpts = output_shp.(3) in
let p5 = (batches = output_shp.(0)) in
let p6 = (out_channel = output_shp.(4)) in
let error () =
let s0 = Owl_utils_array.to_string string_of_int input_shp in
let s1 = Owl_utils_array.to_string string_of_int output_shp in
let s2 = Owl_utils_array.to_string string_of_int kernel_shp in
let s3 = Printf.sprintf "input shape is [%s]" s0 in
let s4 = Printf.sprintf "output' shape is [%s]" s1 in
let s5 = Printf.sprintf "kernel shape is [%s]" s2 in
let s6 = Printf.sprintf "the 1st dimension of input shape should be equal to the 1st dimension of output' shape" in
let s7 = Printf.sprintf "the 5th dimension of kernel shape should be equal to the 5th dimension of output' shape" in
let s8 = Printf.sprintf "transpose_conv3d_backward_input: %s; %s; %s; %s; %s." s3 s4 s5 s6 s7 in
Owl_exception.INVALID_ARGUMENT s8
in
Owl_exception.verify (p5 && p6) error;
let col_stride = stride.(0) in
let row_stride = stride.(1) in
let dpt_stride = stride.(2) in
let padding = SAME in
let output_cols_same, output_rows_same, output_dpts_same =
Owl_utils_infer_shape.calc_conv3d_output_shape padding
input_cols input_rows input_dpts
kernel_cols kernel_rows kernel_dpts
row_stride col_stride dpt_stride
in
let p = if ((output_cols_same = output_cols)
&& (output_rows_same = output_rows)
&& (output_dpts_same = output_dpts)) then SAME else VALID
in
let kernel = transpose ~axis:[|0;1;2;4;3|] kernel in
conv3d ~padding:p output' kernel stride
let transpose_conv3d_backward_kernel input kernel stride output' =
conv3d_backward_kernel output' kernel stride input
let _pool2d_backward _padding input kernel stride output'
init_pool_fun add_val_pool_fun end_pool_fun compute_grad_fun =
let p0 = (num_dims input = 4) in
let p1 = (Array.length kernel = 2) in
let p2 = (Array.length stride = 2) in
let error () =
let s0 = Printf.sprintf "input dimension = %i (should be 4)" (num_dims input) in
let s1 = Printf.sprintf "kernel dimension = %i (should be 2)" (Array.length kernel) in
let s2 = Printf.sprintf "stride dimension = %i (should be 2)" (Array.length stride) in
let s3 = Printf.sprintf "_pool2d_backward: %s; %s; %s." s0 s1 s2 in
Owl_exception.INVALID_ARGUMENT s3
in
Owl_exception.verify (p0 && p1 && p2) error;
let input_shp = shape input in
let batches = input_shp.(0) in
let input_cols = input_shp.(1) in
let input_rows = input_shp.(2) in
let in_channel = input_shp.(3) in
let kernel_cols = kernel.(0) in
let kernel_rows = kernel.(1) in
let col_stride = stride.(0) in
let row_stride = stride.(1) in
let output_shp = shape output' in
let output_cols = output_shp.(1) in
let output_rows = output_shp.(2) in
let p5 = (batches = output_shp.(0)) in
let p6 = (in_channel = output_shp.(3)) in
let error () =
let s0 = Owl_utils_array.to_string string_of_int input_shp in
let s1 = Owl_utils_array.to_string string_of_int output_shp in
let s2 = Printf.sprintf "input shape is [%s]" s0 in
let s3 = Printf.sprintf "output' shape is [%s]" s1 in
let s4 = Printf.sprintf "the 1st dimension of input shape should be equal to the 1st dimension of output' shape" in
let s5 = Printf.sprintf "the 4th dimension of input shape should be equal to the 4th dimension of output' shape" in
let s6 = Printf.sprintf "_pool2d_backward: %s; %s; %s; %s." s2 s3 s4 s5 in
Owl_exception.INVALID_ARGUMENT s6
in
Owl_exception.verify (p5 && p6) error;
let (pad_top, pad_left, _, _) = Owl_utils_infer_shape.calc_conv2d_padding
input_cols input_rows kernel_cols kernel_rows output_cols output_rows
row_stride col_stride
in
let input' = zeros (kind input) (shape input) in
begin
for b = 0 to batches - 1 do
for i = 0 to output_cols - 1 do
for j = 0 to output_rows - 1 do
for k = 0 to in_channel - 1 do
init_pool_fun ();
for di = 0 to kernel_cols - 1 do
for dj = 0 to kernel_rows - 1 do
let in_col = i * col_stride + di - pad_left in
let in_row = j * row_stride + dj - pad_top in
if ((0 <= in_col) && (in_col < input_cols) &&
(0 <= in_row) && (in_row < input_rows))
then add_val_pool_fun (get input [|b; in_col; in_row; k|])
done;
done;
let output_val = end_pool_fun () in
let output_grad = get output' [|b; i; j; k|] in
for di = 0 to kernel_cols - 1 do
for dj = 0 to kernel_rows - 1 do
let in_col = i * col_stride + di - pad_left in
let in_row = j * row_stride + dj - pad_top in
if ((0 <= in_col) && (in_col < input_cols) &&
(0 <= in_row) && (in_row < input_rows))
then
let input_val = (get input [|b; in_col; in_row; k|]) in
let input_grad = (get input' [|b; in_col; in_row; k|]) in
set input' [|b; in_col; in_row; k|] (compute_grad_fun input_val input_grad output_val output_grad)
done;
done;
done;
done;
done;
done;
input'
end
let max_pool2d_backward padding input kernel stride output' =
let max_pool = ref 0. in
let init_pool_fun = (fun () -> max_pool := Stdlib.min_float) in
let add_val_pool_fun =
(fun v -> max_pool := Stdlib.max !max_pool v)
in
let end_pool_fun = (fun () -> !max_pool) in
let compute_grad_fun = (fun input_val input_grad output_val output_grad ->
if ((Scalar.abs (input_val -. output_val)) < 1e-8)
then input_grad +. output_grad
else input_grad
) in
(_pool2d_backward padding input kernel stride output'
init_pool_fun add_val_pool_fun end_pool_fun compute_grad_fun)
let avg_pool2d_backward padding input kernel stride output' =
let sum_pool = ref 0. in
let cnt = ref 0. in
let init_pool_fun = (fun () -> (sum_pool := 0.; cnt := 0.)) in
let add_val_pool_fun =
(fun v -> sum_pool := !sum_pool +. v; cnt := !cnt +. 1.)
in
let end_pool_fun = (fun () -> (!sum_pool /. !cnt)) in
let compute_grad_fun =
(fun _input_val input_grad _output_val output_grad ->
input_grad +. output_grad /. !cnt)
in
(_pool2d_backward padding input kernel stride output'
init_pool_fun add_val_pool_fun end_pool_fun compute_grad_fun)
let _pool3d_backward _padding input kernel stride output'
init_pool_fun add_val_pool_fun end_pool_fun compute_grad_fun =
let p0 = (num_dims input = 5) in
let p1 = (Array.length kernel = 3) in
let p2 = (Array.length stride = 3) in
let error () =
let s0 = Printf.sprintf "input dimension = %i (should be 5)" (num_dims input) in
let s1 = Printf.sprintf "kernel dimension = %i (should be 3)" (Array.length kernel) in
let s2 = Printf.sprintf "stride dimension = %i (should be 3)" (Array.length stride) in
let s3 = Printf.sprintf "_pool3d_backward: %s; %s; %s." s0 s1 s2 in
Owl_exception.INVALID_ARGUMENT s3
in
Owl_exception.verify (p0 && p1 && p2) error;
let input_shp = shape input in
let batches = input_shp.(0) in
let input_cols = input_shp.(1) in
let input_rows = input_shp.(2) in
let input_dpts = input_shp.(3) in
let in_channel = input_shp.(4) in
let kernel_cols = kernel.(0) in
let kernel_rows = kernel.(1) in
let kernel_dpts = kernel.(2) in
let col_stride = stride.(0) in
let row_stride = stride.(1) in
let dpt_stride = stride.(2) in
let output_shp = shape output' in
let output_cols = output_shp.(1) in
let output_rows = output_shp.(2) in
let output_dpts = output_shp.(3) in
let p5 = (batches = output_shp.(0)) in
let p6 = (in_channel = output_shp.(4)) in
let error () =
let s0 = Owl_utils_array.to_string string_of_int input_shp in
let s1 = Owl_utils_array.to_string string_of_int output_shp in
let s2 = Printf.sprintf "input shape is [%s]" s0 in
let s3 = Printf.sprintf "output' shape is [%s]" s1 in
let s4 = Printf.sprintf "the 1st dimension of input shape should be equal to the 1st dimension of output' shape" in
let s5 = Printf.sprintf "the 5th dimension of input shape should be equal to the 5th dimension of output' shape" in
let s6 = Printf.sprintf "_pool3d_backward: %s; %s; %s; %s." s2 s3 s4 s5 in
Owl_exception.INVALID_ARGUMENT s6
in
Owl_exception.verify (p5 && p6) error;
let (pad_top, pad_left, pad_shallow, _, _, _) =
Owl_utils_infer_shape.calc_conv3d_padding
input_cols input_rows input_dpts
kernel_cols kernel_rows kernel_dpts
output_cols output_rows output_dpts
row_stride col_stride dpt_stride
in
let input' = zeros (kind input) (shape input) in
begin
for b = 0 to batches - 1 do
for i = 0 to output_cols - 1 do
for j = 0 to output_rows - 1 do
for dpt = 0 to output_dpts - 1 do
for k = 0 to in_channel - 1 do
init_pool_fun ();
for di = 0 to kernel_cols - 1 do
for dj = 0 to kernel_rows - 1 do
for dk = 0 to kernel_dpts - 1 do
let in_col = i * col_stride + di - pad_left in
let in_row = j * row_stride + dj - pad_top in
let in_dpt = dpt * dpt_stride + dk - pad_shallow in
if ((0 <= in_col) && (in_col < input_cols) &&
(0 <= in_row) && (in_row < input_rows) &&
(0 <= in_dpt) && (in_dpt < input_dpts))
then add_val_pool_fun (get input [|b; in_col; in_row; in_dpt; k|])
done;
done;
done;
let output_val = end_pool_fun () in
let output_grad = get output' [|b; i; j; dpt; k|] in
for di = 0 to kernel_cols - 1 do
for dj = 0 to kernel_rows - 1 do
for dk = 0 to kernel_dpts - 1 do
let in_col = i * col_stride + di - pad_left in
let in_row = j * row_stride + dj - pad_top in
let in_dpt = dpt * dpt_stride + dk - pad_shallow in
if ((0 <= in_col) && (in_col < input_cols) &&
(0 <= in_row) && (in_row < input_rows) &&
(0 <= in_dpt) && (in_dpt < input_dpts))
then
let input_val = (get input [|b; in_col; in_row; in_dpt; k|]) in
let input_grad = (get input' [|b; in_col; in_row; in_dpt; k|]) in
set input' [|b; in_col; in_row; in_dpt; k|]
(compute_grad_fun input_val input_grad output_val output_grad)
done;
done;
done;
done;
done;
done;
done;
done;
input'
end
let max_pool3d_backward padding input kernel stride output' =
let max_pool = ref 0. in
let init_pool_fun = (fun () -> max_pool := Stdlib.min_float) in
let add_val_pool_fun =
(fun v -> max_pool := Stdlib.max !max_pool v)
in
let end_pool_fun = (fun () -> !max_pool) in
let compute_grad_fun = (fun input_val input_grad output_val output_grad ->
if ((Scalar.abs (input_val -. output_val)) < 1e-8)
then input_grad +. output_grad
else input_grad
) in
(_pool3d_backward padding input kernel stride output'
init_pool_fun add_val_pool_fun end_pool_fun compute_grad_fun)
let avg_pool3d_backward padding input kernel stride output' =
let sum_pool = ref 0. in
let cnt = ref 0. in
let init_pool_fun = (fun () -> (sum_pool := 0.; cnt := 0.)) in
let add_val_pool_fun =
(fun v -> sum_pool := !sum_pool +. v; cnt := !cnt +. 1.)
in
let end_pool_fun = (fun () -> (!sum_pool /. !cnt)) in
let compute_grad_fun =
(fun _input_val input_grad _output_val output_grad ->
input_grad +. output_grad /. !cnt)
in
(_pool3d_backward padding input kernel stride output'
init_pool_fun add_val_pool_fun end_pool_fun compute_grad_fun)
let max_pool1d_backward padding input kernel stride output' =
let p0 = (num_dims input = 3) in
let p1 = (Array.length kernel = 1) in
let p2 = (Array.length stride = 1) in
let error () =
let s0 = Printf.sprintf "input dimension = %i (should be 3)" (num_dims input) in
let s1 = Printf.sprintf "kernel dimension = %i (should be 1)" (Array.length kernel) in
let s2 = Printf.sprintf "stride dimension = %i (should be 1)" (Array.length stride) in
let s3 = Printf.sprintf "max_pool1d_backward: %s; %s; %s." s0 s1 s2 in
Owl_exception.INVALID_ARGUMENT s3
in
Owl_exception.verify (p0 && p1 && p2) error;
let input_shp = shape input in
let batches = input_shp.(0) in
let input_cols = input_shp.(1) in
let input_rows = 1 in
let in_channel = input_shp.(2) in
let input = reshape input [|batches; input_rows; input_cols; in_channel|] in
let kernel_cols = kernel.(0) in
let kernel_rows = 1 in
let kernel = [|kernel_rows; kernel_cols|] in
let col_stride = stride.(0) in
let row_stride = 1 in
let stride = [|row_stride; col_stride|] in
let output'_shp = shape output' in
let output_cols = output'_shp.(1) in
let output_rows = 1 in
let out_channel = output'_shp.(2) in
let output' = reshape output' [|batches; output_rows; output_cols; out_channel|] in
let input' = max_pool2d_backward padding input kernel stride output' in
reshape input' input_shp
let avg_pool1d_backward padding input kernel stride output' =
let p0 = (num_dims input = 3) in
let p1 = (Array.length kernel = 1) in
let p2 = (Array.length stride = 1) in
let error () =
let s0 = Printf.sprintf "input dimension = %i (should be 3)" (num_dims input) in
let s1 = Printf.sprintf "kernel dimension = %i (should be 1)" (Array.length kernel) in
let s2 = Printf.sprintf "stride dimension = %i (should be 1)" (Array.length stride) in
let s3 = Printf.sprintf "avg_pool1d_backward: %s; %s; %s." s0 s1 s2 in
Owl_exception.INVALID_ARGUMENT s3
in
Owl_exception.verify (p0 && p1 && p2) error;
let input_shp = shape input in
let batches = input_shp.(0) in
let input_cols = input_shp.(1) in
let input_rows = 1 in
let in_channel = input_shp.(2) in
let input = reshape input [|batches; input_rows; input_cols; in_channel|] in
let kernel_cols = kernel.(0) in
let kernel_rows = 1 in
let kernel = [|kernel_rows; kernel_cols|] in
let col_stride = stride.(0) in
let row_stride = 1 in
let stride = [|row_stride; col_stride|] in
let output'_shp = shape output' in
let output_cols = output'_shp.(1) in
let output_rows = 1 in
let out_channel = output'_shp.(2) in
let output' = reshape output' [|batches; output_rows; output_cols; out_channel|] in
let input' = avg_pool2d_backward padding input kernel stride output' in
reshape input' input_shp
let upsample_kernel2d kernel rate =
if rate = [|1; 1|] then kernel else (
let kernel_shp = shape kernel in
let kernel_cols = kernel_shp.(0) in
let kernel_rows = kernel_shp.(1) in
let in_channel = kernel_shp.(2) in
let out_channel = kernel_shp.(3) in
let col_rate = rate.(0) in
let row_rate = rate.(1) in
let col_up = kernel_cols + (kernel_cols - 1) * (col_rate - 1) in
let row_up = kernel_rows + (kernel_rows - 1) * (row_rate - 1) in
let new_kernel = zeros (kind kernel)
[|col_up; row_up; in_channel; out_channel|] in
for c = 0 to (kernel_cols - 1) do
for r = 0 to (kernel_rows - 1) do
for i = 0 to (in_channel - 1) do
for o = 0 to (out_channel - 1) do
let v = get kernel [|c; r; i; o|] in
set new_kernel [|c * col_rate; r * row_rate; i; o|] v;
done
done
done
done;
new_kernel
)
let downsample_kernel2d kernel rate =
if rate = [|1; 1|] then kernel else (
let kernel_shp = shape kernel in
let kernel_cols = kernel_shp.(0) in
let kernel_rows = kernel_shp.(1) in
let in_channel = kernel_shp.(2) in
let out_channel = kernel_shp.(3) in
let col_rate = rate.(0) in
let row_rate = rate.(1) in
let col_down = (kernel_cols + (col_rate - 1)) / col_rate in
let row_down = (kernel_rows + (row_rate - 1)) / row_rate in
let new_kernel = zeros (kind kernel)
[|col_down; row_down; in_channel; out_channel|] in
for c = 0 to (col_down - 1) do
for r = 0 to (row_down - 1) do
for i = 0 to (in_channel - 1) do
for o = 0 to (out_channel - 1) do
let v = get kernel [|c * col_rate; r * row_rate; i; o|] in
set new_kernel [|c; r; i; o|] v
done
done
done
done;
new_kernel
)
let dilated_conv2d ?(padding=SAME) input kernel stride rate =
let p0 = (Array.length rate = 2) in
let error () =
let s0 = Printf.sprintf "rate dimension = %i (should be 2)" (Array.length rate) in
let s1 = Printf.sprintf "dilated_conv2d: %s." s0 in
Owl_exception.INVALID_ARGUMENT s1
in
Owl_exception.verify p0 error;
let kernel = upsample_kernel2d kernel rate in
conv2d ~padding input kernel stride
let dilated_conv2d_backward_input input kernel stride rate output' =
let p0 = (Array.length rate = 2) in
let error () =
let s0 = Printf.sprintf "rate dimension = %i (should be 2)" (Array.length rate) in
let s1 = Printf.sprintf "dilated_conv2d_backward_input: %s." s0 in
Owl_exception.INVALID_ARGUMENT s1
in
Owl_exception.verify p0 error;
let kernel = upsample_kernel2d kernel rate in
conv2d_backward_input input kernel stride output'
let dilated_conv2d_backward_kernel input kernel stride rate output' =
let p0 = (Array.length rate = 2) in
let error () =
let s0 = Printf.sprintf "rate dimension = %i (should be 2)" (Array.length rate) in
let s1 = Printf.sprintf "dilated_conv2d_backward_kernel: %s." s0 in
Owl_exception.INVALID_ARGUMENT s1
in
Owl_exception.verify p0 error;
let kernel = upsample_kernel2d kernel rate in
let kernel' = conv2d_backward_kernel input kernel stride output' in
downsample_kernel2d kernel' rate
let upsample_kernel3d kernel rate =
if rate = [|1; 1; 1|] then kernel else (
let kernel_shp = shape kernel in
let kernel_cols = kernel_shp.(0) in
let kernel_rows = kernel_shp.(1) in
let kernel_dpts = kernel_shp.(2) in
let in_channel = kernel_shp.(3) in
let out_channel = kernel_shp.(4) in
let col_rate = rate.(0) in
let row_rate = rate.(1) in
let dpt_rate = rate.(2) in
let col_up = kernel_cols + (kernel_cols - 1) * (col_rate - 1) in
let row_up = kernel_rows + (kernel_rows - 1) * (row_rate - 1) in
let dpt_up = kernel_dpts + (kernel_dpts - 1) * (dpt_rate - 1) in
let new_kernel = zeros (kind kernel)
[|col_up; row_up; dpt_up; in_channel; out_channel|] in
for c = 0 to (kernel_cols - 1) do
for r = 0 to (kernel_rows - 1) do
for d = 0 to (kernel_dpts - 1) do
for i = 0 to (in_channel - 1) do
for o = 0 to (out_channel - 1) do
let v = get kernel [|c; r; d; i; o|] in
set new_kernel [|c * col_rate; r * row_rate; d * dpt_rate; i; o|] v;
done
done
done
done
done;
new_kernel
)
let downsample_kernel3d kernel rate =
if rate = [|1; 1; 1|] then kernel else (
let kernel_shp = shape kernel in
let kernel_cols = kernel_shp.(0) in
let kernel_rows = kernel_shp.(1) in
let kernel_dpts = kernel_shp.(2) in
let in_channel = kernel_shp.(3) in
let out_channel = kernel_shp.(4) in
let col_rate = rate.(0) in
let row_rate = rate.(1) in
let dpt_rate = rate.(2) in
let col_down = (kernel_cols + (col_rate - 1)) / col_rate in
let row_down = (kernel_rows + (row_rate - 1)) / row_rate in
let dpt_down = (kernel_dpts + (dpt_rate - 1)) / dpt_rate in
let new_kernel = zeros (kind kernel)
[|col_down; row_down; dpt_down; in_channel; out_channel|] in
for c = 0 to (col_down - 1) do
for r = 0 to (row_down - 1) do
for d = 0 to (dpt_down - 1) do
for i = 0 to (in_channel - 1) do
for o = 0 to (out_channel - 1) do
let v = get kernel [|c * col_rate; r * row_rate; d * dpt_rate; i; o|] in
set new_kernel [|c; r; d; i; o|] v
done
done
done
done
done;
new_kernel
)
let dilated_conv3d ?(padding=SAME) input kernel stride rate =
let p0 = (Array.length rate = 3) in
let error () =
let s0 = Printf.sprintf "rate dimension = %i (should be 3)" (Array.length rate) in
let s1 = Printf.sprintf "dilated_conv3d: %s." s0 in
Owl_exception.INVALID_ARGUMENT s1
in
Owl_exception.verify p0 error;
let kernel = upsample_kernel3d kernel rate in
conv3d ~padding input kernel stride
let dilated_conv3d_backward_input input kernel stride rate output' =
let p0 = (Array.length rate = 3) in
let error () =
let s0 = Printf.sprintf "rate dimension = %i (should be 3)" (Array.length rate) in
let s1 = Printf.sprintf "dilated_conv3d_backward_input: %s." s0 in
Owl_exception.INVALID_ARGUMENT s1
in
Owl_exception.verify p0 error;
let kernel = upsample_kernel3d kernel rate in
conv3d_backward_input input kernel stride output'
let dilated_conv3d_backward_kernel input kernel stride rate output' =
let p0 = (Array.length rate = 3) in
let error () =
let s0 = Printf.sprintf "rate dimension = %i (should be 3)" (Array.length rate) in
let s1 = Printf.sprintf "dilated_conv3d_backward_kernel: %s." s0 in
Owl_exception.INVALID_ARGUMENT s1
in
Owl_exception.verify p0 error;
let kernel = upsample_kernel3d kernel rate in
let kernel' = conv3d_backward_kernel input kernel stride output' in
downsample_kernel3d kernel' rate
let dilated_conv1d ?(padding=SAME) input kernel stride rate =
let p0 = (num_dims input = 3) in
let p1 = (num_dims kernel = 3) in
let p2 = (Array.length stride = 1) in
let error () =
let s0 = Printf.sprintf "input dimension = %i (should be 3)" (num_dims input) in
let s1 = Printf.sprintf "kernel dimension = %i (should be 3)" (num_dims kernel) in
let s2 = Printf.sprintf "stride dimension = %i (should be 1)" (Array.length stride) in
let s3 = Printf.sprintf "dilated_conv1d: %s; %s; %s." s0 s1 s2 in
Owl_exception.INVALID_ARGUMENT s3
in
Owl_exception.verify (p0 && p1 && p2) error;
let input_shp = shape input in
let batches = input_shp.(0) in
let input_cols = input_shp.(1) in
let in_channel = input_shp.(2) in
let input = reshape input [|batches; 1; input_cols; in_channel|] in
let kernel_shp = shape kernel in
let kernel_cols = kernel_shp.(0) in
let out_channel = kernel_shp.(2) in
let p3 = (in_channel = kernel_shp.(1)) in
let error () =
let s0 = Owl_utils_array.to_string string_of_int input_shp in
let s1 = Printf.sprintf "input shape is [%s]" s0 in
let s2 = Owl_utils_array.to_string string_of_int kernel_shp in
let s3 = Printf.sprintf "kernel shape is [%s]" s2 in
let s4 = Printf.sprintf "the 3rd dimension of input shape should be equal to the 2nd dimension of kernel shape" in
let s5 = Printf.sprintf "dilated_conv1d: %s, %s, %s." s1 s3 s4 in
Owl_exception.INVALID_ARGUMENT s5
in
Owl_exception.verify p3 error;
let kernel = reshape kernel [|1; kernel_cols; in_channel; out_channel|] in
let col_stride = stride.(0) in
let stride = [|1; col_stride|] in
let output = dilated_conv2d ~padding input kernel stride rate in
let output_shp = shape output in
let output_cols = output_shp.(2) in
let output = reshape output [|batches; output_cols; out_channel|] in
output
let dilated_conv1d_backward_input input kernel stride rate output' =
let p0 = (num_dims input = 3) in
let p1 = (num_dims kernel = 3) in
let p2 = (num_dims output' = 3) in
let p3 = (Array.length stride = 1) in
let error () =
let s0 = Printf.sprintf "input dimension = %i (should be 3)" (num_dims input) in
let s1 = Printf.sprintf "kernel dimension = %i (should be 3)" (num_dims kernel) in
let s2 = Printf.sprintf "output' dimension = %i (should be 3)" (num_dims output') in
let s3 = Printf.sprintf "stride dimension = %i (should be 1)" (Array.length stride) in
let s4 = Printf.sprintf "dilated_conv1d_backward_input: %s; %s; %s; %s." s0 s1 s2 s3 in
Owl_exception.INVALID_ARGUMENT s4
in
Owl_exception.verify (p0 && p1 && p2 && p3) error;
let input_shp = shape input in
let batches = input_shp.(0) in
let input_cols = input_shp.(1) in
let in_channel = input_shp.(2) in
let input_rows = 1 in
let input = reshape input [|batches; input_rows; input_cols; in_channel|] in
let kernel_shp = shape kernel in
let kernel_cols = kernel_shp.(0) in
let out_channel = kernel_shp.(2) in
let p4 = (in_channel = kernel_shp.(1)) in
let error () =
let s0 = Owl_utils_array.to_string string_of_int input_shp in
let s1 = Printf.sprintf "input shape is [%s]" s0 in
let s2 = Owl_utils_array.to_string string_of_int kernel_shp in
let s3 = Printf.sprintf "kernel shape is [%s]" s2 in
let s4 = Printf.sprintf "the 3th dimension of input shape should be equal to the 2nd dimension of kernel shape" in
let s5 = Printf.sprintf "dilated_conv1d_backward_input: %s, %s, %s." s1 s3 s4 in
Owl_exception.INVALID_ARGUMENT s5
in
Owl_exception.verify p4 error;
let kernel_rows = 1 in
let kernel = reshape kernel [|kernel_rows; kernel_cols; in_channel; out_channel|] in
let output'_shp = shape output' in
let output_cols = output'_shp.(1) in
let p5 = (batches = output'_shp.(0)) in
let p6 = (out_channel = output'_shp.(2)) in
let error () =
let s0 = Owl_utils_array.to_string string_of_int input_shp in
let s1 = Owl_utils_array.to_string string_of_int output'_shp in
let s2 = Owl_utils_array.to_string string_of_int kernel_shp in
let s3 = Printf.sprintf "input shape is [%s]" s0 in
let s4 = Printf.sprintf "output' shape is [%s]" s1 in
let s5 = Printf.sprintf "kernel shape is [%s]" s2 in
let s6 = Printf.sprintf "the 1st dimension of input shape should be equal to the 1st dimension of output' shape" in
let s7 = Printf.sprintf "the 3rd dimension of kernel shape should be equal to the 3rd dimension of output' shape" in
let s8 = Printf.sprintf "dilated_conv1d_backward_input: %s; %s; %s; %s; %s." s3 s4 s5 s6 s7 in
Owl_exception.INVALID_ARGUMENT s8
in
Owl_exception.verify (p5 && p6) error;
let output_rows = 1 in
let output' = reshape output' [|batches; output_rows; output_cols; out_channel|] in
let col_stride = stride.(0) in
let row_stride = 1 in
let stride = [|row_stride; col_stride|] in
let input' = dilated_conv2d_backward_input input kernel stride rate output' in
reshape input' input_shp
let dilated_conv1d_backward_kernel input kernel stride rate output' =
let p0 = (num_dims input = 3) in
let p1 = (num_dims kernel = 3) in
let p2 = (num_dims output' = 3) in
let p3 = (Array.length stride = 1) in
let error () =
let s0 = Printf.sprintf "input dimension = %i (should be 3)" (num_dims input) in
let s1 = Printf.sprintf "kernel dimension = %i (should be 3)" (num_dims kernel) in
let s2 = Printf.sprintf "output' dimension = %i (should be 3)" (num_dims output') in
let s3 = Printf.sprintf "stride dimension = %i (should be 1)" (Array.length stride) in
let s4 = Printf.sprintf "dilated_conv1d_backward_kernel: %s; %s; %s; %s." s0 s1 s2 s3 in
Owl_exception.INVALID_ARGUMENT s4
in
Owl_exception.verify (p0 && p1 && p2 && p3) error;
let input_shp = shape input in
let batches = input_shp.(0) in
let input_cols = input_shp.(1) in
let in_channel = input_shp.(2) in
let input_rows = 1 in
let input = reshape input [|batches; input_rows; input_cols; in_channel|] in
let kernel_shp = shape kernel in
let kernel_cols = kernel_shp.(0) in
let out_channel = kernel_shp.(2) in
let p4 = (in_channel = kernel_shp.(1)) in
let error () =
let s0 = Owl_utils_array.to_string string_of_int input_shp in
let s1 = Printf.sprintf "input shape is [%s]" s0 in
let s2 = Owl_utils_array.to_string string_of_int kernel_shp in
let s3 = Printf.sprintf "kernel shape is [%s]" s2 in
let s4 = Printf.sprintf "the 3th dimension of input shape should be equal to the 2nd dimension of kernel shape" in
let s5 = Printf.sprintf "dilated_conv1d_backward_kernel: %s, %s, %s." s1 s3 s4 in
Owl_exception.INVALID_ARGUMENT s5
in
Owl_exception.verify p4 error;
let kernel_rows = 1 in
let kernel = reshape kernel [|kernel_rows; kernel_cols; in_channel; out_channel|] in
let output'_shp = shape output' in
let output_cols = output'_shp.(1) in
let p5 = (batches = output'_shp.(0)) in
let p6 = (out_channel = output'_shp.(2)) in
let error () =
let s0 = Owl_utils_array.to_string string_of_int input_shp in
let s1 = Owl_utils_array.to_string string_of_int output'_shp in
let s2 = Owl_utils_array.to_string string_of_int kernel_shp in
let s3 = Printf.sprintf "input shape is [%s]" s0 in
let s4 = Printf.sprintf "output' shape is [%s]" s1 in
let s5 = Printf.sprintf "kernel shape is [%s]" s2 in
let s6 = Printf.sprintf "the 1st dimension of input shape should be equal to the 1st dimension of output' shape" in
let s7 = Printf.sprintf "the 3rd dimension of kernel shape should be equal to the 3rd dimension of output' shape" in
let s8 = Printf.sprintf "dilated_conv1d_backward_kernel: %s; %s; %s; %s; %s." s3 s4 s5 s6 s7 in
Owl_exception.INVALID_ARGUMENT s8
in
Owl_exception.verify (p5 && p6) error;
let output_rows = 1 in
let output' = reshape output' [|batches; output_rows; output_cols; out_channel|] in
let col_stride = stride.(0) in
let row_stride = 1 in
let stride = [|row_stride; col_stride|] in
let kernel' = dilated_conv2d_backward_kernel input kernel stride rate output' in
reshape kernel' kernel_shp
let upsampling2d input size =
let p0 = (num_dims input = 4) in
let p1 = (Array.length size = 2) in
let error () =
let s0 = Printf.sprintf "input dimension = %i (should be 4)" (num_dims input) in
let s1 = Printf.sprintf "size dimension = %i (should be 2)" (Array.length size) in
let s2 = Printf.sprintf "upsampling2d: %s; %s." s0 s1 in
Owl_exception.INVALID_ARGUMENT s2
in
Owl_exception.verify (p0 && p1) error;
repeat input [|1; size.(0); size.(1); 1|]
let upsampling2d_backward input size output =
let p0 = (num_dims input = 4) in
let p1 = (Array.length size = 2) in
let error () =
let s0 = Printf.sprintf "input dimension = %i (should be 4)" (num_dims input) in
let s1 = Printf.sprintf "size dimension = %i (should be 2)" (Array.length size) in
let s2 = Printf.sprintf "upsampling2d_backward: %s; %s." s0 s1 in
Owl_exception.INVALID_ARGUMENT s2
in
Owl_exception.verify (p0 && p1) error;
let _kind = kind input in
let input_shp = shape input in
let batches = input_shp.(0) in
let input_cols = input_shp.(1) in
let input_rows = input_shp.(2) in
let in_channel = input_shp.(3) in
let col_scale = size.(0) in
let row_scale = size.(1) in
let output_shp = shape output in
let output_cols = input_cols * col_scale in
let output_rows = input_rows * row_scale in
let p2 = (output_cols = output_shp.(1)) in
let p3 = (output_rows = output_shp.(2)) in
let error () =
let s1 = Owl_utils_array.to_string string_of_int output_shp in
let s2 = Printf.sprintf "output shape is [%s]" s1 in
let s3 = Printf.sprintf "scaled output cols is %i, should be equal to the 2nd dimension of output shape" output_cols in
let s4 = Printf.sprintf "scaled output rows is %i, should be equal to the 3rd dimension of output shape" output_rows in
let s5 = Printf.sprintf "upsampling2d_backward: %s; %s; %s." s2 s3 s4 in
Owl_exception.INVALID_ARGUMENT s5
in
Owl_exception.verify (p2 && p3) error;
let input' = zeros _kind input_shp in
for b = 0 to batches - 1 do
for c = 0 to output_cols - 1 do
let in_c = c / col_scale in
let in_c = Stdlib.min in_c (input_cols - 1) in
for r = 0 to output_rows - 1 do
let in_r = r / row_scale in
let in_r = Stdlib.min in_r (input_rows - 1) in
for i = 0 to in_channel - 1 do
let in_val = get input' [|b; in_c; in_r; i|] in
let out_val = get output [|b; c; r; i|] in
set input' [|b; in_c; in_r; i|] (in_val +. out_val)
done
done
done
done;
input'
let _remove_unit_dims dims =
let removed_ones_list = List.filter (fun x -> x > 1) (Array.to_list dims) in
let not_empty_list = match removed_ones_list with
| [] -> [1]
| _ -> removed_ones_list
in
(Array.of_list not_empty_list)
let _check_is_matrix dims =
if (Array.length dims) != 2
then raise (Invalid_argument "The given NDarray is not a matrix!")
else ()
let row_num varr =
let dims = shape varr in
(_check_is_matrix dims; dims.(0))
let col_num varr =
let dims = shape varr in
(_check_is_matrix dims; dims.(1))
let row varr ind =
let dims = shape varr in
(_check_is_matrix dims; Genarray.slice_left varr [|ind|])
let rows varr indices =
let dims = shape varr in
let _ = _check_is_matrix dims in
let new_rownum = Array.length indices in
let new_colnum = dims.(1) in
let new_varr = empty (kind varr) [|new_rownum; new_colnum|] in
begin
for i = 0 to new_rownum - 1 do
Genarray.blit
(Genarray.slice_left varr [|indices.(i)|])
(Genarray.slice_left new_varr [|i|])
done;
new_varr
end
let copy_row_to vec varr ind =
let dims = shape varr in
let _ = _check_is_matrix dims in
(Genarray.blit vec (Genarray.slice_left varr [|ind|]))
let copy_col_to vec varr ind =
let dims = shape varr in
let _ = _check_is_matrix dims in
let vec_dims = _remove_unit_dims(shape vec) in
let vec_len =
if (Array.length vec_dims) = 1
then vec_dims.(0)
else raise (Invalid_argument "Vector is not a column vector")
in
let num_rows = dims.(0) in
let vec_linear = flatten vec |> array1_of_genarray in
if num_rows != vec_len
then raise (Invalid_argument "Column vector does not have the same length as the number of rows in the matrix")
else
begin
for i = 0 to num_rows - 1 do
Genarray.set varr [|i; ind|] (Array1.unsafe_get vec_linear i)
done
end
let dot varr_a varr_b =
let (dims_a, dims_b) = (shape varr_a, shape varr_b) in
let (_, _) = (_check_is_matrix dims_a, _check_is_matrix dims_b) in
let m = dims_a.(0) in
let cdim = dims_a.(1) in
let n = dims_b.(1) in
if (dims_b.(0)) != cdim
then raise (Invalid_argument "Matrices cannot be multipled")
else
let varr_c = empty (kind varr_a) [|m; n|] in
let sum = ref 0. in
begin
for i = 0 to m - 1 do
for j = 0 to n - 1 do
sum := 0.;
for k = 0 to cdim - 1 do
sum := !sum +. ((Genarray.get varr_a [|i; k|]) *. (Genarray.get varr_b [|k; j|]))
done;
Genarray.set varr_c [|i; j|] !sum
done
done;
varr_c
end
let trace varr =
let dims = shape varr in
let _ = _check_is_matrix dims in
let n = dims.(0) in
if dims.(1) != n
then raise (Invalid_argument "Argument is not a square matrix")
else
let sum = ref 0. in
begin
for i = 0 to n - 1 do
sum := !sum +. (Genarray.get varr [|i; i|])
done;
!sum
end
let to_rows varr =
let dims = shape varr in
let _ = _check_is_matrix dims in
let m = dims.(0) in
(Array.init m (fun i -> (Genarray.slice_left varr [|i|])))
let to_cols _harr = raise (Owl_exception.NOT_IMPLEMENTED "owl_base_dense_ndarray_generic.to_cols")
let of_rows rows =
let m = Array.length rows in
let row_dim = shape (rows.(0)) in
let dims = Array.append [|m|] row_dim in
let varr = empty (kind rows.(0)) dims in
begin
for i = 0 to m - 1 do
Genarray.blit rows.(i) (Genarray.slice_left varr [|i|])
done;
varr
end
let of_cols _cols = raise (Owl_exception.NOT_IMPLEMENTED "owl_base_dense_ndarray_generic.of_cols")
let of_arrays kind arrays =
let m = Array.length arrays in
let n = Array.length (arrays.(0)) in
let varr = empty kind [|m; n|] in
begin
for i = 0 to m - 1 do
for j = 0 to n - 1 do
Genarray.set varr [|i; j|] (Array.unsafe_get (arrays.(i)) j)
done
done;
varr
end
let draw_rows ?(replacement=true) varr count =
let dims = shape varr in
let indices = _draw_int_samples replacement (Array.length dims) count in
let extracted = rows varr indices in
(extracted, indices)
let draw_rows2 ?(replacement=true) varr_a varr_b count =
let extracted_a, indices =
draw_rows ~replacement:replacement varr_a count in
let extracted_b = rows varr_b indices in
(extracted_a, extracted_b, indices)
let inv varr =
let dims = shape varr in
let _ = _check_is_matrix dims in
let n = Array.unsafe_get dims 0 in
if (Array.unsafe_get dims 1) != n
then failwith "no inverse - the matrix is not square"
else
let pivot_row = Array.make n 0. in
let result_varr = copy varr in
begin
for p = 0 to n - 1 do
let pivot_elem = get result_varr [|p; p|] in
if get result_varr [|p; p|] = 0.
then failwith "the matrix does not have an inverse";
for j = 0 to n - 1 do
pivot_row.(j) <- get result_varr [|p; j|];
if j != p
then set result_varr [|p; j|] (pivot_row.(j) /. pivot_elem)
done;
for i = 0 to n - 1 do
if i != p
then set result_varr [|i; p|]
((get result_varr [|i; p|]) /. (~-. pivot_elem))
done;
for i = 0 to n - 1 do
let pivot_col_elem = get result_varr [|i; p|] in
for j = 0 to n - 1 do
if i != p && j != p
then
let pivot_row_elem = pivot_row.(j) in
let old_val = get result_varr [|i; j|] in
let new_val = old_val +. (pivot_row_elem *. pivot_col_elem) in
(set result_varr [|i; j|] new_val)
done;
done;
set result_varr [|p; p|] (1. /. pivot_elem)
done;
result_varr
end
let logdet _x =
raise (Owl_exception.NOT_IMPLEMENTED "owl_base_dense_ndarray_generic.logdet")
let qr _x =
raise (Owl_exception.NOT_IMPLEMENTED "owl_base_dense_ndarray_generic.qr")
let lq _x =
raise (Owl_exception.NOT_IMPLEMENTED "owl_base_dense_ndarray_generic.lq")
let chol ?(upper=true) _x =
upper |> ignore;
raise (Owl_exception.NOT_IMPLEMENTED "owl_base_dense_ndarray_generic.chol")
let svd ?(thin=true) _x =
thin |> ignore;
raise (Owl_exception.NOT_IMPLEMENTED "owl_base_dense_ndarray_generic.svd")
let sylvester _a _b _c =
raise (Owl_exception.NOT_IMPLEMENTED "owl_base_dense_ndarray_generic.sylvester")
let lyapunov _a _q =
raise (Owl_exception.NOT_IMPLEMENTED "owl_base_dense_ndarray_generic.lyapunov")
let discrete_lyapunov ?(solver=`default) _a _q =
solver |> ignore;
raise (Owl_exception.NOT_IMPLEMENTED "owl_base_dense_ndarray_generic.discrete_lyapunov")
let linsolve ?(trans=false) ?(typ=`n) _a _b =
trans |> ignore; typ |> ignore;
raise (Owl_exception.NOT_IMPLEMENTED "owl_base_dense_ndarray_generic.linsolve")
let care ?(diag_r = false)_a _b _q _r =
diag_r |> ignore;
raise (Owl_exception.NOT_IMPLEMENTED "owl_base_dense_ndarray_generic.care")
let diag ?(k=0) _x =
k |> ignore;
raise (Owl_exception.NOT_IMPLEMENTED "owl_base_dense_ndarray_generic.diag")
let diagm ?(k=0) _x =
k |> ignore;
raise (Owl_exception.NOT_IMPLEMENTED "owl_base_dense_ndarray_generic.diagm")
let tril ?(k=0) _x =
k |> ignore;
raise (Owl_exception.NOT_IMPLEMENTED "owl_base_dense_ndarray_generic.tril")
let triu ?(k=0) _x =
k |> ignore;
raise (Owl_exception.NOT_IMPLEMENTED "owl_base_dense_ndarray_generic.triu")
let load _k f = Owl_io.marshal_from_file f
let max_rows varr =
let dims = shape varr in
let _ = _check_is_matrix dims in
let r, c = dims.(0), dims.(1) in
let result = Array.make r (0., 0, 0) in
begin
for i = 0 to r - 1 do
let best = ref Stdlib.min_float in
let best_pos = ref ~- 1 in
for j = 0 to c - 1 do
let x = get varr [|i; j|] in
if (x > !best)
then (best := x; best_pos := j)
done;
result.(i) <- (!best, i, !best_pos)
done;
result
end
let one_hot _depth _x = failwith "Owl_base_dense_ndarray_generic:one_hot: not implemented"
let float_to_elt x = x
let elt_to_float x = x