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GeezerVison is showing github.com — arrayfire-python/arrayfire/array.py at master · arrayfire/arrayfire-python Expand file tree/ Copy patharray.pyMore file actions 1495 lines (1224 loc) · 42.6 KB / Copy patharray.pyFile metadata and controls1495 lines (1224 loc) · 42.6 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 ####################################################### # Copyright (c) 2015, ArrayFire # All rights reserved. # # This file is distributed under 3-clause BSD license. # The complete license agreement can be obtained at: # http://arrayfire.com/licenses/BSD-3-Clause ######################################################## """ Array class and helper functions. """ import inspect import os from .library import * from .util import * from .util import _is_number from .bcast import _bcast_var from .base import * from .index import * from .index import _Index4 _is_running_in_py_charm = "PYCHARM_HOSTED" in os.environ _display_dims_limit = None def set_display_dims_limit(*dims): """ Sets the dimension limit after which array's data won't get presented to the result of str(arr). Default is None, which means there is no limit. Parameters ---------- *dims : dimension limit args Example ------- set_display_dims_limit(10, 10, 10, 10) """ global _display_dims_limit _display_dims_limit = dims def get_display_dims_limit(): """ Gets the dimension limit after which array's data won't get presented to the result of str(arr). Default is None, which means there is no limit. Returns ----------- - tuple of the current limit - None is there is no limit Example ------- get_display_dims_limit() # None set_display_dims_limit(10, 10, 10, 10) get_display_dims_limit() # (10, 10, 10, 10) """ return _display_dims_limit def _in_display_dims_limit(dims): if _is_running_in_py_charm: return False if _display_dims_limit is not None: limit_len = len(_display_dims_limit) dim_len = len(dims) if dim_len > limit_len: return False for i in range(dim_len): if dims[i] > _display_dims_limit[i]: return False return True def _create_array(buf, numdims, idims, dtype, is_device): out_arr = c_void_ptr_t(0) c_dims = dim4(idims[0], idims[1], idims[2], idims[3]) if (not is_device): safe_call(backend.get().af_create_array(c_pointer(out_arr), c_void_ptr_t(buf), numdims, c_pointer(c_dims), dtype.value)) else: safe_call(backend.get().af_device_array(c_pointer(out_arr), c_void_ptr_t(buf), numdims, c_pointer(c_dims), dtype.value)) return out_arr def _create_strided_array(buf, numdims, idims, dtype, is_device, offset, strides): out_arr = c_void_ptr_t(0) c_dims = dim4(idims[0], idims[1], idims[2], idims[3]) if offset is None: offset = 0 offset = c_dim_t(offset) if strides is None: strides = (1, idims[0], idims[0]*idims[1], idims[0]*idims[1]*idims[2]) while len(strides) < 4: strides = strides + (strides[-1],) strides = dim4(strides[0], strides[1], strides[2], strides[3]) if is_device: location = Source.device else: location = Source.host safe_call(backend.get().af_create_strided_array(c_pointer(out_arr), c_void_ptr_t(buf), offset, numdims, c_pointer(c_dims), c_pointer(strides), dtype.value, location.value)) return out_arr def _create_empty_array(numdims, idims, dtype): out_arr = c_void_ptr_t(0) if numdims == 0: return out_arr c_dims = dim4(idims[0], idims[1], idims[2], idims[3]) safe_call(backend.get().af_create_handle(c_pointer(out_arr), numdims, c_pointer(c_dims), dtype.value)) return out_arr def constant_array(val, d0, d1=None, d2=None, d3=None, dtype=Dtype.f32): """ Internal function to create a C array. Should not be used externall. """ if not isinstance(dtype, c_int_t): if isinstance(dtype, int): dtype = c_int_t(dtype) elif isinstance(dtype, Dtype): dtype = c_int_t(dtype.value) else: raise TypeError("Invalid dtype") out = c_void_ptr_t(0) dims = dim4(d0, d1, d2, d3) if isinstance(val, complex): c_real = c_double_t(val.real) c_imag = c_double_t(val.imag) if (dtype.value != Dtype.c32.value and dtype.value != Dtype.c64.value): dtype = Dtype.c32.value safe_call(backend.get().af_constant_complex(c_pointer(out), c_real, c_imag, 4, c_pointer(dims), dtype)) elif dtype.value == Dtype.s64.value: c_val = c_longlong_t(val.real) safe_call(backend.get().af_constant_long(c_pointer(out), c_val, 4, c_pointer(dims))) elif dtype.value == Dtype.u64.value: c_val = c_ulonglong_t(val.real) safe_call(backend.get().af_constant_ulong(c_pointer(out), c_val, 4, c_pointer(dims))) else: c_val = c_double_t(val) safe_call(backend.get().af_constant(c_pointer(out), c_val, 4, c_pointer(dims), dtype)) return out def _binary_func(lhs, rhs, c_func): out = Array() other = rhs if (_is_number(rhs)): ldims = dim4_to_tuple(lhs.dims()) rty = implicit_dtype(rhs, lhs.type()) other = Array() other.arr = constant_array(rhs, ldims[0], ldims[1], ldims[2], ldims[3], rty.value) elif not isinstance(rhs, Array): raise TypeError("Invalid parameter to binary function") safe_call(c_func(c_pointer(out.arr), lhs.arr, other.arr, _bcast_var.get())) return out def _binary_funcr(lhs, rhs, c_func): out = Array() other = lhs if (_is_number(lhs)): rdims = dim4_to_tuple(rhs.dims()) lty = implicit_dtype(lhs, rhs.type()) other = Array() other.arr = constant_array(lhs, rdims[0], rdims[1], rdims[2], rdims[3], lty.value) elif not isinstance(lhs, Array): raise TypeError("Invalid parameter to binary function") c_func(c_pointer(out.arr), other.arr, rhs.arr, _bcast_var.get()) return out def _ctype_to_lists(ctype_arr, dim, shape, offset=0): if (dim == 0): return list(ctype_arr[offset : offset + shape[0]]) else: dim_len = shape[dim] res = [[]] * dim_len for n in range(dim_len): res[n] = _ctype_to_lists(ctype_arr, dim - 1, shape, offset) offset += shape[0] return res def _slice_to_length(key, dim): tkey = [key.start, key.stop, key.step] if tkey[0] is None: tkey[0] = 0 elif tkey[0] < 0: tkey[0] = dim - tkey[0] if tkey[1] is None: tkey[1] = dim elif tkey[1] < 0: tkey[1] = dim - tkey[1] if tkey[2] is None: tkey[2] = 1 return int(((tkey[1] - tkey[0] - 1) / tkey[2]) + 1) def _get_info(dims, buf_len): elements = 1 numdims = 0 if dims: numdims = len(dims) idims = [1]*4 for i in range(numdims): elements *= dims[i] idims[i] = dims[i] elif (buf_len != 0): idims = [buf_len, 1, 1, 1] numdims = 1 else: raise RuntimeError("Invalid size") return numdims, idims def _get_indices(key): inds = _Index4() if isinstance(key, tuple): n_idx = len(key) for n in range(n_idx): inds[n] = Index(key[n]) else: inds[0] = Index(key) return inds def _get_assign_dims(key, idims): dims = [1]*4 for n in range(len(idims)): dims[n] = idims[n] if _is_number(key): dims[0] = 1 return dims elif isinstance(key, slice): dims[0] = _slice_to_length(key, idims[0]) return dims elif isinstance(key, ParallelRange): dims[0] = _slice_to_length(key.S, idims[0]) return dims elif isinstance(key, BaseArray): # If the array is boolean take only the number of nonzeros if(key.dtype() is Dtype.b8): dims[0] = int(sum(key)) else: dims[0] = key.elements() return dims elif isinstance(key, tuple): n_inds = len(key) for n in range(n_inds): if (_is_number(key[n])): dims[n] = 1 elif (isinstance(key[n], BaseArray)): # If the array is boolean take only the number of nonzeros if(key[n].dtype() is Dtype.b8): dims[n] = int(sum(key[n])) else: dims[n] = key[n].elements() elif (isinstance(key[n], slice)): dims[n] = _slice_to_length(key[n], idims[n]) elif (isinstance(key[n], ParallelRange)): dims[n] = _slice_to_length(key[n].S, idims[n]) else: raise IndexError("Invalid type while assigning to arrayfire.array") return dims else: raise IndexError("Invalid type while assigning to arrayfire.array") def transpose(a, conj=False): """ Perform the transpose on an input. Parameters ----------- a : af.Array Multi dimensional arrayfire array. conj : optional: bool. default: False. Flag to specify if a complex conjugate needs to applied for complex inputs. Returns -------- out : af.Array Containing the tranpose of `a` for all batches. """ out = Array() safe_call(backend.get().af_transpose(c_pointer(out.arr), a.arr, conj)) return out def transpose_inplace(a, conj=False): """ Perform inplace transpose on an input. Parameters ----------- a : af.Array - Multi dimensional arrayfire array. - Contains transposed values on exit. conj : optional: bool. default: False. Flag to specify if a complex conjugate needs to applied for complex inputs. Note ------- Input `a` needs to be a square matrix or a batch of square matrices. """ safe_call(backend.get().af_transpose_inplace(a.arr, conj)) class Array(BaseArray): """ A multi dimensional array container. Parameters ---------- src : optional: array.array, list or C buffer. default: None. - When `src` is `array.array` or `list`, the data is copied to create the Array() - When `src` is None, an empty buffer is created. dims : optional: tuple of ints. default: (0,) - When using the default values of `dims`, the dims are caclulated as `len(src)` dtype: optional: str or arrayfire.Dtype. default: None. - if str, must be one of the following: - 'f' for float - 'd' for double - 'b' for bool - 'B' for unsigned char - 'h' for signed 16 bit integer - 'H' for unsigned 16 bit integer - 'i' for signed 32 bit integer - 'I' for unsigned 32 bit integer - 'l' for signed 64 bit integer - 'L' for unsigned 64 bit integer - 'F' for 32 bit complex number - 'D' for 64 bit complex number - if arrayfire.Dtype, must be one of the following: - Dtype.f32 for float - Dtype.f64 for double - Dtype.b8 for bool - Dtype.u8 for unsigned char - Dtype.s16 for signed 16 bit integer - Dtype.u16 for unsigned 16 bit integer - Dtype.s32 for signed 32 bit integer - Dtype.u32 for unsigned 32 bit integer - Dtype.s64 for signed 64 bit integer - Dtype.u64 for unsigned 64 bit integer - Dtype.c32 for 32 bit complex number - Dtype.c64 for 64 bit complex number - if None, Dtype.f32 is assumed Attributes ----------- arr: ctypes.c_void_p ctypes variable containing af_array from arrayfire library. Examples -------- Creating an af.Array() from array.array() >>> import arrayfire as af >>> import array >>> a = array.array('f', (1, 2, 3, 4)) >>> b = af.Array(a, (2,2)) >>> af.display(b) [2 2 1 1] 1.0000 3.0000 2.0000 4.0000 Creating an af.Array() from a list >>> import arrayfire as af >>> import array >>> a = [1, 2, 3, 4] >>> b = af.Array(a) >>> af.display(b) [4 1 1 1] 1.0000 2.0000 3.0000 4.0000 Creating an af.Array() from numpy.array() >>> import numpy as np >>> import arrayfire as af >>> a = np.random.random((2,2)) >>> a array([[ 0.33042524, 0.36135449], [ 0.86748649, 0.42199135]]) >>> b = af.Array(a.ctypes.data, a.shape, a.dtype.char) >>> af.display(b) [2 2 1 1] 0.3304 0.8675 0.3614 0.4220 Note ----- - The class is currently limited to 4 dimensions. - arrayfire.Array() uses column major format. - numpy uses row major format by default which can cause issues during conversion """ # Numpy checks this attribute to know which class handles binary builtin operations, such as __add__. # Setting to such a high value should make sure that arrayfire has priority over # other classes, ensuring that e.g. numpy.float32(1)*arrayfire.randu(3) is handled by # arrayfire's __radd__() instead of numpy's __add__() __array_priority__ = 30 def __init__(self, src=None, dims=None, dtype=None, is_device=False, offset=None, strides=None): super(Array, self).__init__() buf=None buf_len=0 if dtype is not None: if isinstance(dtype, str): type_char = dtype else: type_char = to_typecode[dtype.value] else: type_char = None _type_char='f' if src is not None: if (isinstance(src, Array)): safe_call(backend.get().af_retain_array(c_pointer(self.arr), src.arr)) return host = __import__("array") if isinstance(src, host.array): buf,buf_len = src.buffer_info() _type_char = src.typecode numdims, idims = _get_info(dims, buf_len) elif isinstance(src, list): tmp = host.array('f', src) buf,buf_len = tmp.buffer_info() _type_char = tmp.typecode numdims, idims = _get_info(dims, buf_len) elif isinstance(src, int) or isinstance(src, c_void_ptr_t): buf = src if not isinstance(src, c_void_ptr_t) else src.value numdims, idims = _get_info(dims, buf_len) elements = 1 for dim in idims: elements *= dim if (elements == 0): raise RuntimeError("Expected dims when src is data pointer") if (type_char is None): raise TypeError("Expected type_char when src is data pointer") _type_char = type_char else: raise TypeError("src is an object of unsupported class") if (type_char is not None and type_char != _type_char): raise TypeError("Can not create array of requested type from input data type") if(offset is None and strides is None): self.arr = _create_array(buf, numdims, idims, to_dtype[_type_char], is_device) else: self.arr = _create_strided_array(buf, numdims, idims, to_dtype[_type_char], is_device, offset, strides) else: if type_char is None: type_char = 'f' numdims = len(dims) if dims else 0 idims = [1] * 4 for n in range(numdims): idims[n] = dims[n] self.arr = _create_empty_array(numdims, idims, to_dtype[type_char]) def as_type(self, ty): """ Cast current array to a specified data type Parameters ---------- ty : Return data type """ return cast(self, ty) def copy(self): """ Performs a deep copy of the array. Returns ------- out: af.Array() An identical copy of self. """ out = Array() safe_call(backend.get().af_copy_array(c_pointer(out.arr), self.arr)) return out def __del__(self): """ Release the C array when going out of scope """ if self.arr.value: backend.get().af_release_array(self.arr) self.arr.value = 0 def device_ptr(self): """ Return the device pointer exclusively held by the array. Returns -------- ptr : int Contains location of the device pointer Note ---- - This can be used to integrate with custom C code and / or PyCUDA or PyOpenCL. - Implies `af.device.lock_array()`. The device pointer of `a` is not freed by memory manager until `unlock_device_ptr()` is called. - No other arrays will share the same device pointer. - A copy of the memory is done if multiple arrays share the same memory or the array is not the owner of the memory. - In case of a copy the return value points to the newly allocated memory which is now exclusively owned by the array. """ ptr = c_void_ptr_t(0) backend.get().af_get_device_ptr(c_pointer(ptr), self.arr) return ptr.value def raw_ptr(self): """ Return the device pointer held by the array. Returns -------- ptr : int Contains location of the device pointer Note ---- - This can be used to integrate with custom C code and / or PyCUDA or PyOpenCL. - No mem copy is peformed, this function returns the raw device pointer. - This pointer may be shared with other arrays. Use this function with caution. - In particular the JIT compiler will not be aware of the shared arrays. - This results in JITed operations not being immediately visible through the other array. """ ptr = c_void_ptr_t(0) backend.get().af_get_raw_ptr(c_pointer(ptr), self.arr) return ptr.value def offset(self): """ Return the offset, of the first element relative to the raw pointer. Returns -------- offset : int The offset in number of elements """ offset = c_dim_t(0) safe_call(backend.get().af_get_offset(c_pointer(offset), self.arr)) return offset.value def strides(self): """ Return the distance in bytes between consecutive elements for each dimension. Returns -------- strides : tuple The strides for each dimension """ s0 = c_dim_t(0) s1 = c_dim_t(0) s2 = c_dim_t(0) s3 = c_dim_t(0) safe_call(backend.get().af_get_strides(c_pointer(s0), c_pointer(s1), c_pointer(s2), c_pointer(s3), self.arr)) strides = (s0.value,s1.value,s2.value,s3.value) return strides[:self.numdims()] def elements(self): """ Return the number of elements in the array. """ num = c_dim_t(0) safe_call(backend.get().af_get_elements(c_pointer(num), self.arr)) return num.value def __len__(self): return(self.elements()) def allocated(self): """ Returns the number of bytes allocated by the memory manager for the array. """ num = c_size_t(0) safe_call(backend.get().af_get_allocated_bytes(c_pointer(num), self.arr)) return num.value def dtype(self): """ Return the data type as a arrayfire.Dtype enum value. """ dty = c_int_t(Dtype.f32.value) safe_call(backend.get().af_get_type(c_pointer(dty), self.arr)) return to_dtype[to_typecode[dty.value]] def type(self): """ Return the data type as an int. """ return self.dtype().value @property def T(self): """ Return the transpose of the array """ return transpose(self, False) @property def H(self): """ Return the hermitian transpose of the array """ return transpose(self, True) def dims(self): """ Return the shape of the array as a tuple. """ 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(c_pointer(d0), c_pointer(d1), c_pointer(d2), c_pointer(d3), self.arr)) dims = (d0.value,d1.value,d2.value,d3.value) return dims[:self.numdims()] @property def shape(self): """ The shape of the array """ return self.dims() def numdims(self): """ Return the number of dimensions of the array. """ nd = c_uint_t(0) safe_call(backend.get().af_get_numdims(c_pointer(nd), self.arr)) return nd.value def is_empty(self): """ Check if the array is empty i.e. it has no elements. """ res = c_bool_t(False) safe_call(backend.get().af_is_empty(c_pointer(res), self.arr)) return res.value def is_scalar(self): """ Check if the array is scalar i.e. it has only one element. """ res = c_bool_t(False) safe_call(backend.get().af_is_scalar(c_pointer(res), self.arr)) return res.value def is_row(self): """ Check if the array is a row i.e. it has a shape of (1, cols). """ res = c_bool_t(False) safe_call(backend.get().af_is_row(c_pointer(res), self.arr)) return res.value def is_column(self): """ Check if the array is a column i.e. it has a shape of (rows, 1). """ res = c_bool_t(False) safe_call(backend.get().af_is_column(c_pointer(res), self.arr)) return res.value def is_vector(self): """ Check if the array is a vector i.e. it has a shape of one of the following: - (rows, 1) - (1, cols) - (1, 1, vols) - (1, 1, 1, batch) """ res = c_bool_t(False) safe_call(backend.get().af_is_vector(c_pointer(res), self.arr)) return res.value def is_sparse(self): """ Check if the array is a sparse matrix. """ res = c_bool_t(False) safe_call(backend.get().af_is_sparse(c_pointer(res), self.arr)) return res.value def is_complex(self): """ Check if the array is of complex type. """ res = c_bool_t(False) safe_call(backend.get().af_is_complex(c_pointer(res), self.arr)) return res.value def is_real(self): """ Check if the array is not of complex type. """ res = c_bool_t(False) safe_call(backend.get().af_is_real(c_pointer(res), self.arr)) return res.value def is_double(self): """ Check if the array is of double precision floating point type. """ res = c_bool_t(False) safe_call(backend.get().af_is_double(c_pointer(res), self.arr)) return res.value def is_single(self): """ Check if the array is of single precision floating point type. """ res = c_bool_t(False) safe_call(backend.get().af_is_single(c_pointer(res), self.arr)) return res.value def is_half(self): """ Check if the array is of half floating point type (fp16). """ res = c_bool_t(False) safe_call(backend.get().af_is_half(c_pointer(res), self.arr)) return res.value def is_real_floating(self): """ Check if the array is real and of floating point type. """ res = c_bool_t(False) safe_call(backend.get().af_is_realfloating(c_pointer(res), self.arr)) return res.value def is_floating(self): """ Check if the array is of floating point type. """ res = c_bool_t(False) safe_call(backend.get().af_is_floating(c_pointer(res), self.arr)) return res.value def is_integer(self): """ Check if the array is of integer type. """ res = c_bool_t(False) safe_call(backend.get().af_is_integer(c_pointer(res), self.arr)) return res.value def is_bool(self): """ Check if the array is of type b8. """ res = c_bool_t(False) safe_call(backend.get().af_is_bool(c_pointer(res), self.arr)) return res.value def is_linear(self): """ Check if all elements of the array are contiguous. """ res = c_bool_t(False) safe_call(backend.get().af_is_linear(c_pointer(res), self.arr)) return res.value def is_owner(self): """ Check if the array owns the raw pointer or is a derived array. """ res = c_bool_t(False) safe_call(backend.get().af_is_owner(c_pointer(res), self.arr)) return res.value def __add__(self, other): """ Return self + other. """ return _binary_func(self, other, backend.get().af_add) def __iadd__(self, other): """ Perform self += other. """ self = _binary_func(self, other, backend.get().af_add) return self def __radd__(self, other): """ Return other + self. """ return _binary_funcr(other, self, backend.get().af_add) def __sub__(self, other): """ Return self - other. """ return _binary_func(self, other, backend.get().af_sub) def __isub__(self, other): """ Perform self -= other. """ self = _binary_func(self, other, backend.get().af_sub) return self def __rsub__(self, other): """ Return other - self. """ return _binary_funcr(other, self, backend.get().af_sub) def __mul__(self, other): """ Return self * other. """ return _binary_func(self, other, backend.get().af_mul) def __imul__(self, other): """ Perform self *= other. """ self = _binary_func(self, other, backend.get().af_mul) return self def __rmul__(self, other): """ Return other * self. """ return _binary_funcr(other, self, backend.get().af_mul) def __truediv__(self, other): """ Return self / other. """ return _binary_func(self, other, backend.get().af_div) def __itruediv__(self, other): """ Perform self /= other. """ self = _binary_func(self, other, backend.get().af_div) return self def __rtruediv__(self, other): """ Return other / self. """ return _binary_funcr(other, self, backend.get().af_div) def __div__(self, other): """ Return self / other. """ return _binary_func(self, other, backend.get().af_div) def __idiv__(self, other): """ Perform other / self. """ self = _binary_func(self, other, backend.get().af_div) return self def __rdiv__(self, other): """ Return other / self. """ return _binary_funcr(other, self, backend.get().af_div) def __mod__(self, other): """ Return self % other. """ return _binary_func(self, other, backend.get().af_mod) def __imod__(self, other): """ Perform self %= other. """ self = _binary_func(self, other, backend.get().af_mod) return self def __rmod__(self, other): """ Return other % self. """ return _binary_funcr(other, self, backend.get().af_mod) def __pow__(self, other): """ Return self ** other. """ return _binary_func(self, other, backend.get().af_pow) def __ipow__(self, other): """ Perform self **= other. """ self = _binary_func(self, other, backend.get().af_pow) return self def __rpow__(self, other): """ Return other ** self. """ return _binary_funcr(other, self, backend.get().af_pow) def __lt__(self, other): """ Return self < other. """ return _binary_func(self, other, backend.get().af_lt) def __gt__(self, other): """ Return self > other. """ return _binary_func(self, other, backend.get().af_gt) def __le__(self, other): """ Return self <= other. """ return _binary_func(self, other, backend.get().af_le) def __ge__(self, other): """ Return self >= other. """ return _binary_func(self, other, backend.get().af_ge) def __eq__(self, other): """ |
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