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GeezerVison is showing github.com — arrayfire-python/arrayfire/array_api/array_object.py at master · arrayfire/arrayfire-python Expand file tree/ Copy patharray_object.pyMore file actions 1105 lines (885 loc) · 37.7 KB / Copy patharray_object.pyFile metadata and controls1105 lines (885 loc) · 37.7 KB 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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540 541 542 543 544 545 546 547 548 549 550 551 552 553 554 555 556 557 558 559 560 561 562 563 564 565 566 567 568 569 570 571 572 573 574 575 576 577 578 579 580 581 582 583 584 585 586 587 588 589 590 591 592 593 594 595 596 597 598 599 600 601 602 603 604 605 606 607 608 609 610 611 612 613 614 615 616 617 618 619 620 621 622 623 624 625 626 627 628 629 630 631 632 633 634 635 636 637 638 639 640 641 642 643 644 645 646 647 648 649 650 651 652 653 654 655 656 657 658 659 660 661 662 663 664 665 666 667 668 669 670 671 672 673 674 675 676 677 678 679 680 681 682 683 684 685 686 687 688 689 690 691 692 693 694 695 696 697 698 699 700 701 702 703 704 705 706 707 708 709 710 711 712 713 714 715 716 717 718 719 720 721 722 723 724 725 726 727 728 729 730 731 732 733 734 735 736 737 738 739 740 741 742 743 744 745 746 747 748 749 750 751 752 753 754 755 756 757 758 759 760 761 762 763 764 765 766 767 768 769 770 771 772 773 774 775 776 777 778 779 780 781 782 783 784 785 786 787 788 789 790 791 792 793 794 795 796 797 798 799 800 801 802 803 804 805 806 807 808 809 810 811 812 813 814 815 816 817 818 819 820 821 822 823 824 825 826 827 828 829 830 831 832 833 834 835 836 837 838 839 840 841 842 843 844 845 846 847 848 849 850 851 852 853 854 855 856 857 858 859 860 861 862 863 864 865 866 867 868 869 870 871 872 873 874 875 876 877 878 879 880 881 882 883 884 885 886 887 888 889 890 891 892 893 894 895 896 897 898 899 900 901 902 903 904 905 906 907 908 909 910 911 912 913 914 915 916 917 918 919 920 921 922 923 924 925 926 927 928 929 930 931 932 933 934 935 936 937 938 939 940 941 942 943 944 945 946 947 948 949 950 951 952 953 954 955 956 957 958 959 960 961 962 963 964 965 966 967 968 969 970 971 972 973 974 975 976 977 978 979 980 981 982 983 984 985 986 987 988 989 990 991 992 993 994 995 996 997 998 999 1000 from __future__ import annotations import array as py_array import ctypes import enum import warnings from dataclasses import dataclass from typing import Any, List, Optional, Tuple, Union # TODO replace imports from original lib with refactored ones from arrayfire import backend, safe_call from arrayfire.algorithm import count from arrayfire.array import _get_indices, _in_display_dims_limit from .device import PointerSource from .dtypes import CShape, Dtype from .dtypes import bool as af_bool from .dtypes import c_dim_t from .dtypes import complex64 as af_complex64 from .dtypes import complex128 as af_complex128 from .dtypes import float32 as af_float32 from .dtypes import float64 as af_float64 from .dtypes import int64 as af_int64 from .dtypes import supported_dtypes from .dtypes import uint64 as af_uint64 ShapeType = Tuple[int, ...] # HACK, TODO replace for actual bcast_var after refactoring ~ https://github.com/arrayfire/arrayfire/pull/2871 _bcast_var = False # TODO use int | float in operators -> remove bool | complex support @dataclass class _ArrayBuffer: address: Optional[int] = None length: int = 0 class Array: def __init__( self, x: Union[None, Array, py_array.array, int, ctypes.c_void_p, List[Union[int, float]]] = None, dtype: Union[None, Dtype, str] = None, shape: Optional[ShapeType] = None, pointer_source: PointerSource = PointerSource.host, offset: Optional[ctypes._SimpleCData[int]] = None, strides: Optional[ShapeType] = None) -> None: _no_initial_dtype = False # HACK, FIXME warnings.warn( "Initialisation with __init__ constructor is not a part of array-api specification" " and about to be replaced with asarray() method.", DeprecationWarning, stacklevel=2) # Initialise array object self.arr = ctypes.c_void_p(0) if isinstance(dtype, str): dtype = _str_to_dtype(dtype) # type: ignore[arg-type] if dtype is None: _no_initial_dtype = True dtype = af_float32 if x is None: if not shape: # shape is None or empty tuple safe_call(backend.get().af_create_handle( ctypes.pointer(self.arr), 0, ctypes.pointer(CShape().c_array), dtype.c_api_value)) return # NOTE: applies inplace changes for self.arr safe_call(backend.get().af_create_handle( ctypes.pointer(self.arr), len(shape), ctypes.pointer(CShape(*shape).c_array), dtype.c_api_value)) return if isinstance(x, Array): safe_call(backend.get().af_retain_array(ctypes.pointer(self.arr), x.arr)) return if isinstance(x, py_array.array): _type_char = x.typecode _array_buffer = _ArrayBuffer(*x.buffer_info()) elif isinstance(x, list): _array = py_array.array("f", x) # BUG [True, False] -> dtype: f32 # TODO add int and float _type_char = _array.typecode _array_buffer = _ArrayBuffer(*_array.buffer_info()) elif isinstance(x, int) or isinstance(x, ctypes.c_void_p): # TODO _array_buffer = _ArrayBuffer(x if not isinstance(x, ctypes.c_void_p) else x.value) if not shape: raise TypeError("Expected to receive the initial shape due to the x being a data pointer.") if _no_initial_dtype: raise TypeError("Expected to receive the initial dtype due to the x being a data pointer.") _type_char = dtype.typecode # type: ignore[assignment] # FIXME else: raise TypeError("Passed object x is an object of unsupported class.") _cshape = _get_cshape(shape, _array_buffer.length) if not _no_initial_dtype and dtype.typecode != _type_char: raise TypeError("Can not create array of requested type from input data type") if not (offset or strides): if pointer_source == PointerSource.host: safe_call(backend.get().af_create_array( ctypes.pointer(self.arr), ctypes.c_void_p(_array_buffer.address), _cshape.original_shape, ctypes.pointer(_cshape.c_array), dtype.c_api_value)) return safe_call(backend.get().af_device_array( ctypes.pointer(self.arr), ctypes.c_void_p(_array_buffer.address), _cshape.original_shape, ctypes.pointer(_cshape.c_array), dtype.c_api_value)) return if offset is None: offset = c_dim_t(0) if strides is None: strides = (1, _cshape[0], _cshape[0]*_cshape[1], _cshape[0]*_cshape[1]*_cshape[2]) if len(strides) < 4: strides += (strides[-1], ) * (4 - len(strides)) strides_cshape = CShape(*strides).c_array safe_call(backend.get().af_create_strided_array( ctypes.pointer(self.arr), ctypes.c_void_p(_array_buffer.address), offset, _cshape.original_shape, ctypes.pointer(_cshape.c_array), ctypes.pointer(strides_cshape), dtype.c_api_value, pointer_source.value)) # Arithmetic Operators def __pos__(self) -> Array: """ Evaluates +self_i for each element of an array instance. Parameters ---------- self : Array Array instance. Should have a numeric data type. Returns ------- out : Array An array containing the evaluated result for each element. The returned array must have the same data type as self. """ return self def __neg__(self) -> Array: """ Evaluates +self_i for each element of an array instance. Parameters ---------- self : Array Array instance. Should have a numeric data type. Returns ------- out : Array An array containing the evaluated result for each element in self. The returned array must have a data type determined by Type Promotion Rules. """ return 0 - self # type: ignore[no-any-return, operator] # FIXME def __add__(self, other: Union[int, float, Array], /) -> Array: """ Calculates the sum for each element of an array instance with the respective element of the array other. Parameters ---------- self : Array Array instance (augend array). Should have a numeric data type. other: Union[int, float, Array] Addend array. Must be compatible with self (see Broadcasting). Should have a numeric data type. Returns ------- out : Array An array containing the element-wise sums. The returned array must have a data type determined by Type Promotion Rules. """ return _process_c_function(self, other, backend.get().af_add) def __sub__(self, other: Union[int, float, Array], /) -> Array: """ Calculates the difference for each element of an array instance with the respective element of the array other. The result of self_i - other_i must be the same as self_i + (-other_i) and must be governed by the same floating-point rules as addition (see array.__add__()). Parameters ---------- self : Array Array instance (minuend array). Should have a numeric data type. other: Union[int, float, Array] Subtrahend array. Must be compatible with self (see Broadcasting). Should have a numeric data type. Returns ------- out : Array An array containing the element-wise differences. The returned array must have a data type determined by Type Promotion Rules. """ return _process_c_function(self, other, backend.get().af_sub) def __mul__(self, other: Union[int, float, Array], /) -> Array: """ Calculates the product for each element of an array instance with the respective element of the array other. Parameters ---------- self : Array Array instance. Should have a numeric data type. other: Union[int, float, Array] Other array. Must be compatible with self (see Broadcasting). Should have a numeric data type. Returns ------- out : Array An array containing the element-wise products. The returned array must have a data type determined by Type Promotion Rules. """ return _process_c_function(self, other, backend.get().af_mul) def __truediv__(self, other: Union[int, float, Array], /) -> Array: """ Evaluates self_i / other_i for each element of an array instance with the respective element of the array other. Parameters ---------- self : Array Array instance. Should have a numeric data type. other: Union[int, float, Array] Other array. Must be compatible with self (see Broadcasting). Should have a numeric data type. Returns ------- out : Array An array containing the element-wise results. The returned array should have a floating-point data type determined by Type Promotion Rules. Note ---- - If one or both of self and other have integer data types, the result is implementation-dependent, as type promotion between data type “kinds” (e.g., integer versus floating-point) is unspecified. Specification-compliant libraries may choose to raise an error or return an array containing the element-wise results. If an array is returned, the array must have a real-valued floating-point data type. """ return _process_c_function(self, other, backend.get().af_div) def __floordiv__(self, other: Union[int, float, Array], /) -> Array: # TODO return NotImplemented def __mod__(self, other: Union[int, float, Array], /) -> Array: """ Evaluates self_i % other_i for each element of an array instance with the respective element of the array other. Parameters ---------- self : Array Array instance. Should have a real-valued data type. other: Union[int, float, Array] Other array. Must be compatible with self (see Broadcasting). Should have a real-valued data type. Returns ------- out : Array An array containing the element-wise results. Each element-wise result must have the same sign as the respective element other_i. The returned array must have a real-valued floating-point data type determined by Type Promotion Rules. Note ---- - For input arrays which promote to an integer data type, the result of division by zero is unspecified and thus implementation-defined. """ return _process_c_function(self, other, backend.get().af_mod) def __pow__(self, other: Union[int, float, Array], /) -> Array: """ Calculates an implementation-dependent approximation of exponentiation by raising each element (the base) of an array instance to the power of other_i (the exponent), where other_i is the corresponding element of the array other. Parameters ---------- self : Array Array instance whose elements correspond to the exponentiation base. Should have a numeric data type. other: Union[int, float, Array] Other array whose elements correspond to the exponentiation exponent. Must be compatible with self (see Broadcasting). Should have a numeric data type. Returns ------- out : Array An array containing the element-wise results. The returned array must have a data type determined by Type Promotion Rules. """ return _process_c_function(self, other, backend.get().af_pow) # Array Operators def __matmul__(self, other: Array, /) -> Array: # TODO get from blas - make vanilla version and not copy af.matmul as is return NotImplemented # Bitwise Operators def __invert__(self) -> Array: """ Evaluates ~self_i for each element of an array instance. Parameters ---------- self : Array Array instance. Should have an integer or boolean data type. Returns ------- out : Array An array containing the element-wise results. The returned array must have the same data type as self. """ out = Array() safe_call(backend.get().af_bitnot(ctypes.pointer(out.arr), self.arr)) return out def __and__(self, other: Union[int, bool, Array], /) -> Array: """ Evaluates self_i & other_i for each element of an array instance with the respective element of the array other. Parameters ---------- self : Array Array instance. Should have a numeric data type. other: Union[int, bool, Array] Other array. Must be compatible with self (see Broadcasting). Should have a numeric data type. Returns ------- out : Array An array containing the element-wise results. The returned array must have a data type determined by Type Promotion Rules. """ return _process_c_function(self, other, backend.get().af_bitand) def __or__(self, other: Union[int, bool, Array], /) -> Array: """ Evaluates self_i | other_i for each element of an array instance with the respective element of the array other. Parameters ---------- self : Array Array instance. Should have a numeric data type. other: Union[int, bool, Array] Other array. Must be compatible with self (see Broadcasting). Should have a numeric data type. Returns ------- out : Array An array containing the element-wise results. The returned array must have a data type determined by Type Promotion Rules. """ return _process_c_function(self, other, backend.get().af_bitor) def __xor__(self, other: Union[int, bool, Array], /) -> Array: """ Evaluates self_i ^ other_i for each element of an array instance with the respective element of the array other. Parameters ---------- self : Array Array instance. Should have a numeric data type. other: Union[int, bool, Array] Other array. Must be compatible with self (see Broadcasting). Should have a numeric data type. Returns ------- out : Array An array containing the element-wise results. The returned array must have a data type determined by Type Promotion Rules. """ return _process_c_function(self, other, backend.get().af_bitxor) def __lshift__(self, other: Union[int, Array], /) -> Array: """ Evaluates self_i << other_i for each element of an array instance with the respective element of the array other. Parameters ---------- self : Array Array instance. Should have a numeric data type. other: Union[int, Array] Other array. Must be compatible with self (see Broadcasting). Should have a numeric data type. Each element must be greater than or equal to 0. Returns ------- out : Array An array containing the element-wise results. The returned array must have the same data type as self. """ return _process_c_function(self, other, backend.get().af_bitshiftl) def __rshift__(self, other: Union[int, Array], /) -> Array: """ Evaluates self_i >> other_i for each element of an array instance with the respective element of the array other. Parameters ---------- self : Array Array instance. Should have a numeric data type. other: Union[int, Array] Other array. Must be compatible with self (see Broadcasting). Should have a numeric data type. Each element must be greater than or equal to 0. Returns ------- out : Array An array containing the element-wise results. The returned array must have the same data type as self. """ return _process_c_function(self, other, backend.get().af_bitshiftr) # Comparison Operators def __lt__(self, other: Union[int, float, Array], /) -> Array: """ Computes the truth value of self_i < other_i for each element of an array instance with the respective element of the array other. Parameters ---------- self : Array Array instance. Should have a numeric data type. other: Union[int, float, Array] Other array. Must be compatible with self (see Broadcasting). Should have a real-valued data type. Returns ------- out : Array An array containing the element-wise results. The returned array must have a data type of bool. """ return _process_c_function(self, other, backend.get().af_lt) def __le__(self, other: Union[int, float, Array], /) -> Array: """ Computes the truth value of self_i <= other_i for each element of an array instance with the respective element of the array other. Parameters ---------- self : Array Array instance. Should have a numeric data type. other: Union[int, float, Array] Other array. Must be compatible with self (see Broadcasting). Should have a real-valued data type. Returns ------- out : Array An array containing the element-wise results. The returned array must have a data type of bool. """ return _process_c_function(self, other, backend.get().af_le) def __gt__(self, other: Union[int, float, Array], /) -> Array: """ Computes the truth value of self_i > other_i for each element of an array instance with the respective element of the array other. Parameters ---------- self : Array Array instance. Should have a numeric data type. other: Union[int, float, Array] Other array. Must be compatible with self (see Broadcasting). Should have a real-valued data type. Returns ------- out : Array An array containing the element-wise results. The returned array must have a data type of bool. """ return _process_c_function(self, other, backend.get().af_gt) def __ge__(self, other: Union[int, float, Array], /) -> Array: """ Computes the truth value of self_i >= other_i for each element of an array instance with the respective element of the array other. Parameters ---------- self : Array Array instance. Should have a numeric data type. other: Union[int, float, Array] Other array. Must be compatible with self (see Broadcasting). Should have a real-valued data type. Returns ------- out : Array An array containing the element-wise results. The returned array must have a data type of bool. """ return _process_c_function(self, other, backend.get().af_ge) def __eq__(self, other: Union[int, float, bool, Array], /) -> Array: # type: ignore[override] # FIXME """ Computes the truth value of self_i == other_i for each element of an array instance with the respective element of the array other. Parameters ---------- self : Array Array instance. Should have a numeric data type. other: Union[int, float, bool, Array] Other array. Must be compatible with self (see Broadcasting). May have any data type. Returns ------- out : Array An array containing the element-wise results. The returned array must have a data type of bool. """ return _process_c_function(self, other, backend.get().af_eq) def __ne__(self, other: Union[int, float, bool, Array], /) -> Array: # type: ignore[override] # FIXME """ Computes the truth value of self_i != other_i for each element of an array instance with the respective element of the array other. Parameters ---------- self : Array Array instance. Should have a numeric data type. other: Union[int, float, bool, Array] Other array. Must be compatible with self (see Broadcasting). May have any data type. Returns ------- out : Array An array containing the element-wise results. The returned array must have a data type of bool. """ return _process_c_function(self, other, backend.get().af_neq) # Reflected Arithmetic Operators def __radd__(self, other: Array, /) -> Array: """ Return other + self. """ return _process_c_function(other, self, backend.get().af_add) def __rsub__(self, other: Array, /) -> Array: """ Return other - self. """ return _process_c_function(other, self, backend.get().af_sub) def __rmul__(self, other: Array, /) -> Array: """ Return other * self. """ return _process_c_function(other, self, backend.get().af_mul) def __rtruediv__(self, other: Array, /) -> Array: """ Return other / self. """ return _process_c_function(other, self, backend.get().af_div) def __rfloordiv__(self, other: Array, /) -> Array: # TODO return NotImplemented def __rmod__(self, other: Array, /) -> Array: """ Return other % self. """ return _process_c_function(other, self, backend.get().af_mod) def __rpow__(self, other: Array, /) -> Array: """ Return other ** self. """ return _process_c_function(other, self, backend.get().af_pow) # Reflected Array Operators def __rmatmul__(self, other: Array, /) -> Array: # TODO return NotImplemented # Reflected Bitwise Operators def __rand__(self, other: Array, /) -> Array: """ Return other & self. """ return _process_c_function(other, self, backend.get().af_bitand) def __ror__(self, other: Array, /) -> Array: """ Return other | self. """ return _process_c_function(other, self, backend.get().af_bitor) def __rxor__(self, other: Array, /) -> Array: """ Return other ^ self. """ return _process_c_function(other, self, backend.get().af_bitxor) def __rlshift__(self, other: Array, /) -> Array: """ Return other << self. """ return _process_c_function(other, self, backend.get().af_bitshiftl) def __rrshift__(self, other: Array, /) -> Array: """ Return other >> self. """ return _process_c_function(other, self, backend.get().af_bitshiftr) # In-place Arithmetic Operators def __iadd__(self, other: Union[int, float, Array], /) -> Array: # TODO discuss either we need to support complex and bool as other input type """ Return self += other. """ return _process_c_function(self, other, backend.get().af_add) def __isub__(self, other: Union[int, float, Array], /) -> Array: """ Return self -= other. """ return _process_c_function(self, other, backend.get().af_sub) def __imul__(self, other: Union[int, float, Array], /) -> Array: """ Return self *= other. """ return _process_c_function(self, other, backend.get().af_mul) def __itruediv__(self, other: Union[int, float, Array], /) -> Array: """ Return self /= other. """ return _process_c_function(self, other, backend.get().af_div) def __ifloordiv__(self, other: Union[int, float, Array], /) -> Array: # TODO return NotImplemented def __imod__(self, other: Union[int, float, Array], /) -> Array: """ Return self %= other. """ return _process_c_function(self, other, backend.get().af_mod) def __ipow__(self, other: Union[int, float, Array], /) -> Array: """ Return self **= other. """ return _process_c_function(self, other, backend.get().af_pow) # In-place Array Operators def __imatmul__(self, other: Array, /) -> Array: # TODO return NotImplemented # In-place Bitwise Operators def __iand__(self, other: Union[int, bool, Array], /) -> Array: """ Return self &= other. """ return _process_c_function(self, other, backend.get().af_bitand) def __ior__(self, other: Union[int, bool, Array], /) -> Array: """ Return self |= other. """ return _process_c_function(self, other, backend.get().af_bitor) def __ixor__(self, other: Union[int, bool, Array], /) -> Array: """ Return self ^= other. """ return _process_c_function(self, other, backend.get().af_bitxor) def __ilshift__(self, other: Union[int, Array], /) -> Array: """ Return self <<= other. """ return _process_c_function(self, other, backend.get().af_bitshiftl) def __irshift__(self, other: Union[int, Array], /) -> Array: """ Return self >>= other. """ return _process_c_function(self, other, backend.get().af_bitshiftr) # Methods def __abs__(self) -> Array: # TODO return NotImplemented def __array_namespace__(self, *, api_version: Optional[str] = None) -> Any: # TODO return NotImplemented def __bool__(self) -> bool: # TODO consider using scalar() and is_scalar() return NotImplemented def __complex__(self) -> complex: # TODO return NotImplemented def __dlpack__(self, *, stream: Union[None, int, Any] = None): # type: ignore[no-untyped-def] # TODO implementation and expected return type -> PyCapsule return NotImplemented def __dlpack_device__(self) -> Tuple[enum.Enum, int]: # TODO return NotImplemented def __float__(self) -> float: # TODO return NotImplemented def __getitem__(self, key: Union[int, slice, Tuple[Union[int, slice, ], ...], Array], /) -> Array: """ Returns self[key]. Parameters ---------- self : Array Array instance. key : Union[int, slice, Tuple[Union[int, slice, ], ...], Array] Index key. Returns ------- out : Array An array containing the accessed value(s). The returned array must have the same data type as self. """ # TODO # API Specification - key: Union[int, slice, ellipsis, Tuple[Union[int, slice, ellipsis], ...], array]. # consider using af.span to replace ellipsis during refactoring out = Array() ndims = self.ndim if isinstance(key, Array) and key == af_bool.c_api_value: ndims = 1 if count(key) == 0: return out safe_call(backend.get().af_index_gen( ctypes.pointer(out.arr), self.arr, c_dim_t(ndims), _get_indices(key).pointer)) return out def __index__(self) -> int: # TODO return NotImplemented def __int__(self) -> int: # TODO return NotImplemented def __len__(self) -> int: # NOTE not a part of the array-api spec return self.shape[0] if self.shape else 0 def __setitem__( self, key: Union[int, slice, Tuple[Union[int, slice, ], ...], Array], value: Union[int, float, bool, Array], /) -> None: # TODO return NotImplemented # type: ignore[return-value] # FIXME def __str__(self) -> str: # NOTE not a part of the array-api spec # TODO change the look of array str. E.g., like np.array if not _in_display_dims_limit(self.shape): return _metadata_string(self.dtype, self.shape) return _metadata_string(self.dtype) + _array_as_str(self) def __repr__(self) -> str: # NOTE not a part of the array-api spec # return _metadata_string(self.dtype, self.shape) # TODO change the look of array representation. E.g., like np.array return _array_as_str(self) def to_device(self, device: Any, /, *, stream: Union[int, Any] = None) -> Array: # TODO implementation and change device type from Any to Device return NotImplemented # Attributes @property def dtype(self) -> Dtype: """ Data type of the array elements. Returns ------- out : Dtype Array data type. """ out = ctypes.c_int() safe_call(backend.get().af_get_type(ctypes.pointer(out), self.arr)) return _c_api_value_to_dtype(out.value) @property def device(self) -> Any: # TODO return NotImplemented @property def mT(self) -> Array: # TODO return NotImplemented @property def T(self) -> Array: """ Transpose of the array. Returns ------- out : Array Two-dimensional array whose first and last dimensions (axes) are permuted in reverse order relative to original array. The returned array must have the same data type as the original array. Note ---- - The array instance must be two-dimensional. If the array instance is not two-dimensional, an error should be raised. """ if self.ndim < 2: raise TypeError(f"Array should be at least 2-dimensional. Got {self.ndim}-dimensional array") # TODO add check if out.dtype == self.dtype out = Array() safe_call(backend.get().af_transpose(ctypes.pointer(out.arr), self.arr, False)) return out @property def size(self) -> int: """ Number of elements in an array. Returns ------- out : int Number of elements in an array Note ---- - This must equal the product of the array's dimensions. """ # NOTE previously - elements() out = c_dim_t(0) safe_call(backend.get().af_get_elements(ctypes.pointer(out), self.arr)) return out.value @property def ndim(self) -> int: """ Number of array dimensions (axes). out : int Number of array dimensions (axes). """ out = ctypes.c_uint(0) safe_call(backend.get().af_get_numdims(ctypes.pointer(out), self.arr)) return out.value @property def shape(self) -> ShapeType: """ Array dimensions. Returns ------- out : tuple[int, ...] Array dimensions. """ # TODO refactor d0 = c_dim_t(0) d1 = c_dim_t(0) d2 = c_dim_t(0) d3 = c_dim_t(0) safe_call(backend.get().af_get_dims( ctypes.pointer(d0), ctypes.pointer(d1), ctypes.pointer(d2), ctypes.pointer(d3), self.arr)) return (d0.value, d1.value, d2.value, d3.value)[:self.ndim] # Skip passing None values def scalar(self) -> Union[None, int, float, bool, complex]: """ Return the first element of the array """ # NOTE not a part of the array-api spec # TODO change the logic of this method if self.is_empty(): return None out = self.dtype.c_type() safe_call(backend.get().af_get_scalar(ctypes.pointer(out), self.arr)) return out.value # type: ignore[no-any-return] # FIXME def is_empty(self) -> bool: """ Check if the array is empty i.e. it has no elements. """ # NOTE not a part of the array-api spec out = ctypes.c_bool() safe_call(backend.get().af_is_empty(ctypes.pointer(out), self.arr)) return out.value def to_list(self, row_major: bool = False) -> List[Union[None, int, float, bool, complex]]: # NOTE not a part of the array-api spec if self.is_empty(): return [] array = _reorder(self) if row_major else self ctypes_array = _get_ctypes_array(array) if array.ndim == 1: return list(ctypes_array) out = [] for i in range(array.size): idx = i sub_list = [] for j in range(array.ndim): div = array.shape[j] sub_list.append(idx % div) idx //= div out.append(ctypes_array[sub_list[::-1]]) # type: ignore[call-overload] # FIXME return out def to_ctype_array(self, row_major: bool = False) -> ctypes.Array: # NOTE not a part of the array-api spec if self.is_empty(): raise RuntimeError("Can not convert an empty array to ctype.") array = _reorder(self) if row_major else self return _get_ctypes_array(array) def _get_ctypes_array(array: Array) -> ctypes.Array: c_shape = array.dtype.c_type * array.size ctypes_array = c_shape() safe_call(backend.get().af_get_data_ptr(ctypes.pointer(ctypes_array), array.arr)) return ctypes_array def _reorder(array: Array) -> Array: """ Returns a reordered array to help interoperate with row major formats. """ if array.ndim == 1: return array out = Array() c_shape = CShape(*(tuple(reversed(range(array.ndim))) + tuple(range(array.ndim, 4)))) safe_call(backend.get().af_reorder(ctypes.pointer(out.arr), array.arr, *c_shape)) return out def _array_as_str(array: Array) -> str: arr_str = ctypes.c_char_p(0) # FIXME add description to passed arguments safe_call(backend.get().af_array_to_string(ctypes.pointer(arr_str), "", array.arr, 4, True)) py_str = _to_str(arr_str) safe_call(backend.get().af_free_host(arr_str)) return py_str def _metadata_string(dtype: Dtype, dims: Optional[ShapeType] = None) -> str: return ( "arrayfire.Array()\n" f"Type: {dtype.typename}\n" f"Dims: {str(dims) if dims else ''}") def _get_cshape(shape: Optional[ShapeType], buffer_length: int) -> CShape: if shape: return CShape(*shape) |
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