Source: owl_base_dense_ndarray_intf.ml (u.343d48fb749e8f912732d6ce277abce6.owl-base.1.0.2.doc.src.owl-base)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461# 1 "src/base/dense/owl_base_dense_ndarray_intf.ml" (* * OWL - OCaml Scientific and Engineering Computing * Copyright (c) 2016-2020 Liang Wang <liang.wang@cl.cam.ac.uk> *) open Owl_types_common module type Common = sig (* types and constants *) type arr type elt val number : number (* creation and operation functions *) val empty : int array -> arr val zeros : int array -> arr val ones : int array -> arr val create : int array -> elt -> arr val init : int array -> (int -> elt) -> arr val init_nd : int array -> (int array -> elt) -> arr val sequential : ?a:elt -> ?step:elt -> int array -> arr val uniform : ?a:elt -> ?b:elt -> int array -> arr val gaussian : ?mu:elt -> ?sigma:elt -> int array -> arr val bernoulli : ?p:float -> int array -> arr val shape : arr -> int array val numel : arr -> int val strides : arr -> int array (** Refer to :doc:`owl_dense_ndarray_generic` *) val slice_size : arr -> int array (** Refer to :doc:`owl_dense_ndarray_generic` *) val get : arr -> int array -> elt val set : arr -> int array -> elt -> unit val get_slice : int list list -> arr -> arr val set_slice : int list list -> arr -> arr -> unit val get_fancy : index list -> arr -> arr val set_fancy : index list -> arr -> arr -> unit val copy : arr -> arr val copy_ : out:arr -> arr -> unit val reset : arr -> unit val reshape : arr -> int array -> arr val flatten : arr -> arr val reverse : arr -> arr val tile : arr -> int array -> arr val repeat : arr -> int array -> arr val concatenate : ?axis:int -> arr array -> arr val stack : ?axis:int -> arr array -> arr val squeeze : ?axis:int array -> arr -> arr val expand : ?hi:bool -> arr -> int -> arr val split : ?axis:int -> int array -> arr -> arr array val draw : ?axis:int -> arr -> int -> arr * int array val pad : ?v:elt -> int list list -> arr -> arr val one_hot : int -> arr -> arr val print : ?max_row:int -> ?max_col:int -> ?header:bool -> ?fmt:(elt -> string) -> arr -> unit (* mathematical functions *) val abs : arr -> arr val neg : arr -> arr val floor : arr -> arr val ceil : arr -> arr val round : arr -> arr val sqr : arr -> arr val sqrt : arr -> arr val log : arr -> arr val log2 : arr -> arr val log10 : arr -> arr val exp : arr -> arr val sin : arr -> arr val cos : arr -> arr val tan : arr -> arr val sinh : arr -> arr val cosh : arr -> arr val tanh : arr -> arr val asin : arr -> arr val acos : arr -> arr val atan : arr -> arr val asinh : arr -> arr val acosh : arr -> arr val atanh : arr -> arr val min : ?axis:int -> ?keep_dims:bool -> arr -> arr val max : ?axis:int -> ?keep_dims:bool -> arr -> arr val sum : ?axis:int -> ?keep_dims:bool -> arr -> arr val sum_reduce : ?axis:int array -> arr -> arr val min' : arr -> elt val max' : arr -> elt val sum' : arr -> elt val pow : arr -> arr -> arr val scalar_pow : elt -> arr -> arr val pow_scalar : arr -> elt -> arr val add : arr -> arr -> arr val sub : arr -> arr -> arr val mul : arr -> arr -> arr val div : arr -> arr -> arr val add_scalar : arr -> elt -> arr val sub_scalar : arr -> elt -> arr val mul_scalar : arr -> elt -> arr val div_scalar : arr -> elt -> arr val scalar_add : elt -> arr -> arr val scalar_sub : elt -> arr -> arr val scalar_mul : elt -> arr -> arr val scalar_div : elt -> arr -> arr val fma : arr -> arr -> arr -> arr (** {5 Iterate array elements} *) val iteri : (int -> elt -> unit) -> arr -> unit val iter : (elt -> unit) -> arr -> unit val mapi : (int -> elt -> elt) -> arr -> arr val map : (elt -> elt) -> arr -> arr val filteri : (int -> elt -> bool) -> arr -> int array val filter : (elt -> bool) -> arr -> int array val foldi : ?axis:int -> (int -> elt -> elt -> elt) -> elt -> arr -> arr val fold : ?axis:int -> (elt -> elt -> elt) -> elt -> arr -> arr val scani : ?axis:int -> (int -> elt -> elt -> elt) -> arr -> arr val scan : ?axis:int -> (elt -> elt -> elt) -> arr -> arr (** {5 Examination & Comparison} *) val exists : (elt -> bool) -> arr -> bool val not_exists : (elt -> bool) -> arr -> bool val for_all : (elt -> bool) -> arr -> bool val is_zero : arr -> bool val is_positive : arr -> bool val is_negative : arr -> bool val is_nonpositive : arr -> bool val is_nonnegative : arr -> bool val is_normal : arr -> bool val not_nan : arr -> bool val not_inf : arr -> bool val equal : arr -> arr -> bool val not_equal : arr -> arr -> bool val greater : arr -> arr -> bool val less : arr -> arr -> bool val greater_equal : arr -> arr -> bool val less_equal : arr -> arr -> bool val elt_equal : arr -> arr -> arr val elt_not_equal : arr -> arr -> arr val elt_less : arr -> arr -> arr val elt_greater : arr -> arr -> arr val elt_less_equal : arr -> arr -> arr val elt_greater_equal : arr -> arr -> arr val equal_scalar : arr -> elt -> bool val not_equal_scalar : arr -> elt -> bool val less_scalar : arr -> elt -> bool val greater_scalar : arr -> elt -> bool val less_equal_scalar : arr -> elt -> bool val greater_equal_scalar : arr -> elt -> bool val elt_equal_scalar : arr -> elt -> arr val elt_not_equal_scalar : arr -> elt -> arr val elt_less_scalar : arr -> elt -> arr val elt_greater_scalar : arr -> elt -> arr val elt_less_equal_scalar : arr -> elt -> arr val elt_greater_equal_scalar : arr -> elt -> arr (* matrix functions *) val row_num : arr -> int val col_num : arr -> int val row : arr -> int -> arr val rows : arr -> int array -> arr val copy_row_to : arr -> arr -> int -> unit val copy_col_to : arr -> arr -> int -> unit val diag : ?k:int -> arr -> arr val transpose : ?axis:int array -> arr -> arr val to_rows : arr -> arr array val of_rows : arr array -> arr val to_cols : arr -> arr array val of_cols : arr array -> arr val of_array : elt array -> int array -> arr val of_arrays : elt array array -> arr end module type Real = sig type elt type arr val log_sum_exp' : arr -> elt val log_sum_exp : ?axis:int -> ?keep_dims:bool -> arr -> arr val sum_slices : ?axis:int -> arr -> arr val signum : arr -> arr val sigmoid : arr -> arr val relu : arr -> arr val dawsn : arr -> arr val l1norm' : arr -> elt val l2norm' : arr -> elt val l2norm_sqr' : arr -> elt val clip_by_value : ?amin:elt -> ?amax:elt -> arr -> arr val clip_by_l2norm : elt -> arr -> arr val atan2 : arr -> arr -> arr val scalar_atan2 : elt -> arr -> arr val atan2_scalar : arr -> elt -> arr val approx_equal : ?eps:float -> arr -> arr -> bool val approx_equal_scalar : ?eps:float -> arr -> float -> bool val approx_elt_equal : ?eps:float -> arr -> arr -> arr val approx_elt_equal_scalar : ?eps:float -> arr -> float -> arr val dot : arr -> arr -> arr val trace : arr -> elt (** {5 Helper functions} *) val float_to_elt : float -> elt val elt_to_float : elt -> float end module type NN = sig type arr (* Neural network related functions *) val conv1d : ?padding:padding -> arr -> arr -> int array -> arr val conv2d : ?padding:padding -> arr -> arr -> int array -> arr val conv3d : ?padding:padding -> arr -> arr -> int array -> arr val dilated_conv1d : ?padding:padding -> arr -> arr -> int array -> int array -> arr val dilated_conv2d : ?padding:padding -> arr -> arr -> int array -> int array -> arr val dilated_conv3d : ?padding:padding -> arr -> arr -> int array -> int array -> arr val transpose_conv1d : ?padding:padding -> arr -> arr -> int array -> arr val transpose_conv2d : ?padding:padding -> arr -> arr -> int array -> arr val transpose_conv3d : ?padding:padding -> arr -> arr -> int array -> arr val max_pool1d : ?padding:padding -> arr -> int array -> int array -> arr val max_pool2d : ?padding:padding -> arr -> int array -> int array -> arr val max_pool3d : ?padding:padding -> arr -> int array -> int array -> arr val avg_pool1d : ?padding:padding -> arr -> int array -> int array -> arr val avg_pool2d : ?padding:padding -> arr -> int array -> int array -> arr val avg_pool3d : ?padding:padding -> arr -> int array -> int array -> arr val upsampling2d : arr -> int array -> arr val conv1d_backward_input : arr -> arr -> int array -> arr -> arr val conv1d_backward_kernel : arr -> arr -> int array -> arr -> arr val conv2d_backward_input : arr -> arr -> int array -> arr -> arr val conv2d_backward_kernel : arr -> arr -> int array -> arr -> arr val conv3d_backward_input : arr -> arr -> int array -> arr -> arr val conv3d_backward_kernel : arr -> arr -> int array -> arr -> arr val dilated_conv1d_backward_input : arr -> arr -> int array -> int array -> arr -> arr val dilated_conv1d_backward_kernel : arr -> arr -> int array -> int array -> arr -> arr val dilated_conv2d_backward_input : arr -> arr -> int array -> int array -> arr -> arr val dilated_conv2d_backward_kernel : arr -> arr -> int array -> int array -> arr -> arr val dilated_conv3d_backward_input : arr -> arr -> int array -> int array -> arr -> arr val dilated_conv3d_backward_kernel : arr -> arr -> int array -> int array -> arr -> arr val transpose_conv1d_backward_input : arr -> arr -> int array -> arr -> arr val transpose_conv1d_backward_kernel : arr -> arr -> int array -> arr -> arr val transpose_conv2d_backward_input : arr -> arr -> int array -> arr -> arr val transpose_conv2d_backward_kernel : arr -> arr -> int array -> arr -> arr val transpose_conv3d_backward_input : arr -> arr -> int array -> arr -> arr val transpose_conv3d_backward_kernel : arr -> arr -> int array -> arr -> arr val max_pool1d_backward : padding -> arr -> int array -> int array -> arr -> arr val max_pool2d_backward : padding -> arr -> int array -> int array -> arr -> arr val max_pool3d_backward : padding -> arr -> int array -> int array -> arr -> arr val avg_pool1d_backward : padding -> arr -> int array -> int array -> arr -> arr val avg_pool2d_backward : padding -> arr -> int array -> int array -> arr -> arr val avg_pool3d_backward : padding -> arr -> int array -> int array -> arr -> arr val upsampling2d_backward : arr -> int array -> arr -> arr end