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
|
# coding=utf-8
#
# Copyright © 2016 Intel Corporation
#
# Permission is hereby granted, free of charge, to any person obtaining a
# copy of this software and associated documentation files (the "Software"),
# to deal in the Software without restriction, including without limitation
# the rights to use, copy, modify, merge, publish, distribute, sublicense,
# and/or sell copies of the Software, and to permit persons to whom the
# Software is furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice (including the next
# paragraph) shall be included in all copies or substantial portions of the
# Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL
# THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
# FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER
# DEALINGS IN THE SOFTWARE.
"""Generate fp64 and int64 types conversion tests."""
from __future__ import print_function, division, absolute_import
import abc
import argparse
import itertools
import os
import struct
import numpy as np
from templates import template_dir
from modules import utils
TEMPLATES = template_dir(os.path.basename(os.path.splitext(__file__)[0]))
# pylint: disable=bad-whitespace,line-too-long,bad-continuation
DOUBLE_INFS = ['0xfff0000000000000', # -inf
'0x7ff0000000000000'] # +inf
DOUBLE_NEG_ZERO = ['0x8000000000000000'] # Negative underflow (-0.0)
DOUBLE_POS_ZERO = ['0x0000000000000000'] # Positive underflow (+0.0)
# Double values causing an underflow to zero in any other type
DOUBLE_DENORMAL_VALUES = ['0x800fffffffffffff', # Negative maximum denormalized -- Denormalized may be flushed to 0
'0x8000000000000001', # Negative minimum denormalized -- Denormalized may be flushed to 0
'0x0000000000000001', # Positive minimum denormalized -- Denormalized may be flushed to 0
'0x000fffffffffffff'] # Positive maximum denormalized -- Denormalized may be flushed to 0
DOUBLE_NORMAL_VALUES = ['0x8010000000000000', # Negative minimum normalized
'0x0010000000000000'] # Positive minimum normalized
# Double +/-inf
DOUBLE_FLOAT_INFS = ['0xc7effffff0000000', # Negative overflow (-inf)
'0x47effffff0000000'] # Positive overflow (+inf)
DOUBLE_FLOAT_VALUES = ['0xc7efffffefffffff', # Negative maximum normalized
'0xc170000000000000', # -16777216.0
'0xc014000000000000', # -5.0
'0xbfff25ce60000000', # -1.9467300176620483
'0xb80fffffe0000000', # Negative minimum normalized
'0xb69fffffffffffff', # Negative underflow
'0x369fffffffffffff', # Positive underflow
'0x380fffffe0000000', # Positive minimum normalized
'0x3fff25ce60000000', # +1.9467300176620483
'0x4014000000000000', # +5.0
'0x4170000000000000', # +16777216.0
'0x47efffffefffffff'] # Positive maximum normalized
DOUBLE_UINT_VALUES = ['0xbfeccccccccccccd', # -0.9
#'0x8010000000000000', # Negative minimum normalized -- Already checked
#'0x800fffffffffffff', # Negative maximum denormalized -- Already checked
#'0x8000000000000001', # Negative minimum denormalized -- Already checked
#'0x8000000000000000', # Negative minimum (-0) -- Already checked
#'0x0000000000000000', # Positive minimum (+0) -- Already checked
'0x3fff25ce60000000', # +1.9467300176620483
'0x4014000000000000', # +5.0
'0x4170000000000000', # +16777216.0
'0x41dfffffffc00000', # Signed int low frontier (+2147483647)
'0x41e0000000000000', # Signed int up frontier (+2147483648)
'0x41efffffffe00000'] # Maximum (+4294967295)
DOUBLE_INT_VALUES = ['0xc1e0000000000000', # Minimum (-2147483648)
'0xc170000000000000', # -16777216.0
'0xc014000000000000', # -5.0
'0xbfff25ce60000000', # -1.9467300176620483
#'0x8000000000000000', # Negative minimum (-0) -- Already checked
#'0x0000000000000000', # Minimum (+0) -- Already checked
'0x3fff25ce60000000', # +1.9467300176620483
'0x4014000000000000', # +5.0
'0x4170000000000000', # +16777216.0
'0x41dfffffffc00000'] # Maximum (+2147483647)
DOUBLE_BOOL_VALUES = [#'0x8010000000000000', # Minimum negative True value -- Already checked
#'0x0000000000000000', # False -- Already checked
#'0x0010000000000000', # Minimum positive True value -- Already checked
]
FLOAT_INFS = ['0xff800000', # -inf
'0x7f800000'] # +inf
FLOAT_NEG_ZERO = ['0x80000000'] # Negative underflow (-0.0)
FLOAT_POS_ZERO = ['0x00000000'] # Positive underflow (+0.0)
FLOAT_VALUES = ['0xff7fffff', # Negative maximum normalized
'0xcb800000', # -16777216.0
'0xc0a00000', # -5.0
'0xbff92e73', # -1.9467300176620483
'0x80800000', # Negative minimum normalized
#'0x807fffff', # Negative maximum denormalized -- Denormalized may be flushed to 0
#'0x80000001', # Negative minimum denormalized -- Denormalized may be flushed to 0
#'0x00000001', # Positive minimum denormalized -- Denormalized may be flushed to 0
#'0x007fffff', # Positive maximum denormalized -- Denormalized may be flushed to 0
'0x00800000', # Positive minimum normalized
'0x3ff92e73', # +1.9467300176620483
'0x40a00000', # +5.0
'0x4b800000', # +16777216.0
'0x7f7fffff'] # Positive maximum normalized
FLOAT_INT64_VALUES = ['0xcf800000', # -4294967296.0
'0xcb800000', # -16777216.0
'0xc0a00000', # -5.0
'0xbff92e73', # -1.9467300176620483
'0x80800000', # Negative minimum normalized
'0x807fffff', # Negative maximum denormalized
'0x80000001', # Negative minimum denormalized
'0x00000001', # Positive minimum denormalized
'0x007fffff', # Positive maximum denormalized
'0x00800000', # Positive minimum normalized
'0x3ff92e73', # +1.9467300176620483
'0x40a00000', # +5.0
'0x4b800000', # +16777216.0
'0x4f800000'] # +4294967296.0
FLOAT_UINT64_VALUES = ['0x00000001', # Positive minimum denormalized
'0x007fffff', # Positive maximum denormalized
'0x00800000', # Positive minimum normalized
'0x3ff92e73', # +1.9467300176620483
'0x40a00000', # +5.0
'0x4b800000', # +16777216.0
'0x4f800000'] # +4294967296.0
UINT64_VALUES = ['0', # Minimum
'5',
'2147483647', # Signed int32 low frontier
'2147483648', # Signed int32 up frontier
'4294967295', # Maximum unsigned int32
'4294967296',
'9223372036854775807', # Signed int64 low frontier
'9223372036854775808', # Signed int64 up frontier
'18446744073709551615'] # Maximum
INT64_VALUES = ['-9223372036854775808', # Minimum
'-2147483649',
'-2147483648',
'-5',
'-1',
'0',
'1',
'5',
'2147483647', # Signed int32 low frontier
'2147483648', # Signed int32 up frontier
'4294967295', # Maximum unsigned int32
'4294967296',
'9223372036854775807'] # Maximum
UINT_VALUES = ['0', # Minimum
'5',
'2147483647', # Signed int low frontier
'2147483648', # Signed int up frontier
'4294967295'] # Maximum
INT_VALUES = ['-2147483648', # Minimum
'-5',
'-1',
'0',
'1',
'5',
'2147483647'] # Maximum
BOOL_VALUES = ['0', # False
'1'] # True
# pylint: enable=bad-whitespace,line-too-long,bad-continuation
def get_dir_name(ver, test_type):
"""Returns the directory name to save tests given a GLSL version and a
test type.
"""
assert isinstance(ver, str)
assert isinstance(test_type, str)
if ver.startswith('GL_'):
feature_dir = ver[3:].lower()
else:
feature_dir = 'glsl-{}.{}'.format(ver[0], ver[1:])
return os.path.join('spec', feature_dir, test_type,
'conversion')
class TestTuple(object):
"""A float64 derived and other type derived tuple to generate the
needed conversion tests.
"""
@staticmethod
def float_to_hex(fvalue):
"""Returns the hexadecimal representation from a float32 value."""
assert isinstance(fvalue, np.float32)
return hex(struct.unpack('<I', struct.pack('<f', fvalue))[0])
@staticmethod
def double_to_hex(fvalue):
"""Returns the hexadecimal representation from a float64 value."""
assert isinstance(fvalue, float)
return hex(struct.unpack('<Q', struct.pack('<d', fvalue))[0]).rstrip("L")
@staticmethod
def hex_to_float(hstr):
"""Returns a float32 value from its hexadecimal representation."""
assert isinstance(hstr, str)
return struct.unpack('<f', struct.pack('<I', int(hstr, 16)))[0]
@staticmethod
def hex_to_double(hstr):
"""Returns a float64 value from its hexadecimal representation."""
assert isinstance(hstr, str)
return struct.unpack('<d', struct.pack('<Q', int(hstr, 16)))[0]
@staticmethod
def float_hex_to_double_hex(hstr):
"""Returns the float64 hexadecimal representation from a float32
hexadecimal representation.
"""
assert isinstance(hstr, str)
double_value = TestTuple.hex_to_float(hstr)
return TestTuple.double_to_hex(double_value)
@staticmethod
def float_hex_to_inv_double_hex(hstr):
"""Returns the inverted float64 hexadecimal representation from a
float32 hexadecimal representation.
"""
assert isinstance(hstr, str)
temp = TestTuple.hex_to_float(hstr)
double_value = np.divide(1.0, temp)
return TestTuple.double_to_hex(double_value)
@staticmethod
def float_hex_to_int64_str(hstr):
"""Returns the int64 string representation from a float32
hexadecimal representation.
"""
assert isinstance(hstr, str)
x = TestTuple.hex_to_float(hstr)
if x > np.iinfo(np.dtype('int64')).max:
return str(np.iinfo(np.dtype('int64')).max)
if x < np.iinfo(np.dtype('int64')).min:
return str(np.iinfo(np.dtype('int64')).min)
return str(int(x))
@staticmethod
def float_hex_to_uint64_str(hstr):
"""Returns the uint64 string representation from a float32
hexadecimal representation.
"""
assert isinstance(hstr, str)
x = TestTuple.hex_to_float(hstr)
if x > np.iinfo(np.dtype('uint64')).max:
return str(np.iinfo(np.dtype('uint64')).max)
if x < np.iinfo(np.dtype('uint64')).min:
return str(np.iinfo(np.dtype('uint64')).min)
return str(int(x))
@staticmethod
def int_str_to_bool_str(istr):
"""Returns a bool/integer string from an (arbitrary size) integet string."""
assert isinstance(istr, str)
return str(int(bool(int(istr))))
@staticmethod
def int_str_to_float_hex(istr):
"""Returns a float32 hexadecimal representation from an (arbitrary size) integer string."""
assert isinstance(istr, str)
return TestTuple.float_to_hex(np.float32(int(istr)))
@staticmethod
def int_str_to_double_hex(istr):
"""Returns a float64 hexadecimal representation from an (arbitrary size) integer string."""
assert isinstance(istr, str)
return TestTuple.double_to_hex(float(istr))
@staticmethod
def int_str_to_double_str(istr):
"""Returns a float64 string from an (arbitrary size) integer string."""
assert isinstance(istr, str)
return str(float(istr))
@staticmethod
def int_str_to_int32_str(istr):
"""Returns an int32 string from an (arbitrary size) integer string."""
x = int(istr) & (2**32 - 1)
if x >= 2**31:
x -= 2**32
return str(x)
@staticmethod
def int_str_to_uint32_str(istr):
"""Returns an uint32 string from an (arbitrary size) integer string."""
x = int(istr) & (2**32 - 1)
return str(x)
@staticmethod
def int_str_to_int64_str(istr):
"""Returns an int64 string from an (arbitrary size) integer string."""
x = int(istr) & (2**64 - 1)
if x >= 2**63:
x -= 2**64
return str(x)
@staticmethod
def int_str_to_uint64_str(istr):
"""Returns an uint64 string from an (arbitrary size) integer string."""
x = int(istr) & (2**64 - 1)
return str(x)
@staticmethod
def int_str_to_type_str(target_type):
"""Returns a function for converting an int string to a string for the given type."""
assert target_type in ('d', 'i64', 'u64')
if target_type == 'd':
return TestTuple.int_str_to_double_str
elif target_type == 'i64':
return TestTuple.int_str_to_int64_str
elif target_type == 'u64':
return TestTuple.int_str_to_uint64_str
@staticmethod
def double_hex_to_bool_str(hstr):
"""Returns a bool string from a float64 hexadecimal representation."""
assert isinstance(hstr, str)
bool_double = TestTuple.hex_to_double(hstr)
return '1' if bool_double != 0.0 else '0'
@staticmethod
def double_hex_to_int_str(hstr):
"""Returns an int32 string from a float64 hexadecimal
representation.
"""
assert isinstance(hstr, str)
int_double = TestTuple.hex_to_double(hstr)
if int_double > np.iinfo(np.dtype('int32')).max:
return str(np.iinfo(np.dtype('int32')).max)
if int_double < np.iinfo(np.dtype('int32')).min:
return str(np.iinfo(np.dtype('int32')).min)
return str(int(int_double))
@staticmethod
def double_hex_to_uint_str(hstr):
"""Returns an uint32 string from a float64 hexadecimal
representation.
"""
assert isinstance(hstr, str)
uint_double = TestTuple.hex_to_double(hstr)
if uint_double > np.iinfo(np.dtype('uint32')).max:
return str(np.iinfo(np.dtype('uint32')).max)
if uint_double < np.iinfo(np.dtype('uint32')).min:
return str(np.iinfo(np.dtype('uint32')).min)
return str(int(uint_double))
@staticmethod
def double_hex_to_float_hex(hstr):
"""Returns the float32 hexadecimal representation from a float64
hexadecimal representation.
"""
assert isinstance(hstr, str)
float_double = np.float32(TestTuple.hex_to_double(hstr))
return TestTuple.float_to_hex(float_double)
@staticmethod
def double_hex_to_inv_float_hex(hstr):
"""Returns the inverted float32 hexadecimal representation from a
float64 hexadecimal representation.
"""
assert isinstance(hstr, str)
temp = np.divide(1.0, TestTuple.hex_to_double(hstr))
float_double = np.float32(temp)
return TestTuple.float_to_hex(float_double)
@staticmethod
def double_hex_to_int64_str(hstr):
"""Returns the int64 string representation from a float64
hexadecimal representation.
"""
assert isinstance(hstr, str)
x = TestTuple.hex_to_double(hstr)
if x > np.iinfo(np.dtype('int64')).max:
return str(np.iinfo(np.dtype('int64')).max)
if x < np.iinfo(np.dtype('int64')).min:
return str(np.iinfo(np.dtype('int64')).min)
return str(int(x))
@staticmethod
def double_hex_to_uint64_str(hstr):
"""Returns the uint64 string representation from a float64
hexadecimal representation.
"""
assert isinstance(hstr, str)
x = TestTuple.hex_to_double(hstr)
if x > np.iinfo(np.dtype('uint64')).max:
return str(np.iinfo(np.dtype('uint64')).max)
if x < np.iinfo(np.dtype('uint64')).min:
return str(np.iinfo(np.dtype('uint64')).min)
return str(int(x))
def __init__(self, ver, stage,
first_dimension, second_dimension,
basic_type, target_type, names_only):
assert stage in ('vert', 'geom', 'frag')
assert first_dimension in ('1', '2', '3', '4')
assert second_dimension in ('1', '2', '3', '4')
assert isinstance(names_only, bool)
self._ver = ver
self._stage = stage
self._basic_type = basic_type
self._target_type = target_type
self._names_only = names_only
self._target_full_type = ''
self._conversion_type = ''
self._uniform_type = ''
self._amount = int(first_dimension) * int(second_dimension)
self._filenames = []
self._extensions = []
if ver.startswith('GL_'):
if basic_type == 'd' or target_type == 'd':
self._extensions.append('GL_ARB_gpu_shader_fp64')
if basic_type in ('i64', 'u64') or target_type in ('i64', 'u64'):
self._extensions.append('GL_ARB_gpu_shader_int64')
if first_dimension != '1':
dimensional_type = 'mat' + first_dimension
if first_dimension != second_dimension:
dimensional_type += 'x' + second_dimension
elif second_dimension != '1':
dimensional_type = 'vec' + second_dimension
else:
dimensional_type = ''
if dimensional_type == '':
if basic_type == 'b':
self._conversion_type = 'bool'
self._uniform_type = 'int'
elif basic_type == 'i':
self._conversion_type = 'int'
elif basic_type == 'u':
self._conversion_type = 'uint'
elif basic_type == 'f':
self._conversion_type = 'float'
elif basic_type == 'd':
self._conversion_type = 'double'
elif basic_type == 'i64':
self._conversion_type = 'int64_t'
elif basic_type == 'u64':
self._conversion_type = 'uint64_t'
if self._uniform_type == '':
self._uniform_type = self._conversion_type
if target_type == 'd':
self._target_full_type = 'double'
elif target_type == 'i64':
self._target_full_type = 'int64_t'
elif target_type == 'u64':
self._target_full_type = 'uint64_t'
else:
self._conversion_type = (basic_type if basic_type != 'f' else '') + dimensional_type
if basic_type == 'b':
self._uniform_type = 'i' + dimensional_type
else:
self._uniform_type = self._conversion_type
self._target_full_type = target_type + dimensional_type
@abc.abstractmethod
def _gen_to_target(self):
"""Generates the test files for conversions to float64."""
@abc.abstractmethod
def _gen_from_target(self):
"""Generates the test files for conversions from float64."""
@property
def filenames(self):
"""Returns the test file names this tuple will generate."""
if self._filenames == []:
tmp = self._names_only
self._names_only = True
self.generate_test_files()
self._names_only = tmp
return self._filenames
def generate_test_files(self):
"""Generate the GLSL parser tests."""
self._filenames = []
self._gen_to_target()
self._gen_from_target()
class RegularTestTuple(TestTuple):
"""Derived class for conversion tests using regular values within the
edges of the used types.
"""
@staticmethod
def all_tests(names_only):
"""Returns all the possible contained conversion test instances."""
assert isinstance(names_only, bool)
stages = ['vert', 'geom', 'frag']
dimensions = ['1', '2', '3', '4']
basic_types = ['b', 'u', 'i', 'f', 'd', 'i64', 'u64']
target_types = ['d', 'i64', 'u64']
glsl_ver = ['GL_ARB_gpu_shader_int64', 'GL_ARB_gpu_shader_fp64', '400']
if not names_only:
test_types = ['compiler', 'execution']
for ver, test_type in itertools.product(glsl_ver, test_types):
utils.safe_makedirs(get_dir_name(ver, test_type))
for ver, stage, first_dimension, second_dimension, basic_type, target_type in itertools.product(
glsl_ver,
stages,
dimensions,
dimensions,
basic_types,
target_types):
has_int64 = basic_type in ('i64', 'u64') or target_type in ('i64', 'u64')
if (not (first_dimension != '1' and
(second_dimension == '1' or basic_type not in ('f', 'd') or target_type != 'd')) and
(basic_type not in target_types or basic_type < target_type) and
((ver == 'GL_ARB_gpu_shader_int64') == has_int64)):
yield RegularTestTuple(ver, stage,
first_dimension, second_dimension,
basic_type, target_type, names_only)
def __init__(self, ver, stage,
first_dimension, second_dimension,
basic_type, target_type, names_only):
assert ver in ('GL_ARB_gpu_shader_int64', 'GL_ARB_gpu_shader_fp64', '400')
assert basic_type in ('b', 'u', 'i', 'f', 'd', 'i64', 'u64')
assert target_type in ('d', 'i64', 'u64')
assert not (first_dimension != '1' and
(second_dimension == '1' or basic_type not in ('f', 'd') or target_type != 'd'))
super(RegularTestTuple, self).__init__(ver, stage,
first_dimension, second_dimension,
basic_type, target_type, names_only)
def _gen_comp_test(self, from_type, to_type, converted_from):
filename = os.path.join(
get_dir_name(self._ver, 'compiler'),
'{}-conversion-implicit-{}-{}-bad.{}'.format(self._stage, from_type, to_type,
self._stage))
self._filenames.append(filename)
if not self._names_only:
with open(filename, 'w') as test_file:
test_file.write(TEMPLATES.get_template(
'compiler.{}.mako'.format(self._stage)).render_unicode(
ver=self._ver,
extensions=self._extensions,
from_type=from_type,
to_type=to_type,
converted_from=converted_from))
def _gen_exec_test(self, from_type, to_type,
uniform_from_type, uniform_to_type,
explicit, converted_from, conversions):
filename = os.path.join(
get_dir_name(self._ver, 'execution'),
'{}-conversion-{}-{}-{}.shader_test'.format(self._stage, explicit,
from_type, to_type))
self._filenames.append(filename)
if not self._names_only:
with open(filename, 'w') as test_file:
test_file.write(TEMPLATES.get_template(
'execution.{}.shader_test.mako'.format(self._stage)).render_unicode(
ver=self._ver,
extensions=self._extensions,
amount=self._amount,
from_type=from_type,
to_type=to_type,
converted_from=converted_from,
uniform_from_type=uniform_from_type,
uniform_to_type=uniform_to_type,
conversions=conversions))
def _gen_to_target(self):
converted_from = 'from'
explicit = 'implicit'
if self._basic_type == 'b':
conversion_values = BOOL_VALUES
conversion_function = TestTuple.int_str_to_type_str(self._target_type)
elif self._basic_type == 'i':
conversion_values = INT_VALUES
conversion_function = TestTuple.int_str_to_type_str(self._target_type)
elif self._basic_type == 'u':
conversion_values = UINT_VALUES
conversion_function = TestTuple.int_str_to_type_str(self._target_type)
elif self._basic_type == 'f':
if self._target_type == 'd':
conversion_values = FLOAT_INFS + FLOAT_NEG_ZERO + FLOAT_POS_ZERO + FLOAT_VALUES
conversion_function = TestTuple.float_hex_to_double_hex
elif self._target_type == 'i64':
conversion_values = FLOAT_POS_ZERO + FLOAT_INT64_VALUES
conversion_function = TestTuple.float_hex_to_int64_str
elif self._target_type == 'u64':
conversion_values = FLOAT_POS_ZERO + FLOAT_UINT64_VALUES
conversion_function = TestTuple.float_hex_to_uint64_str
elif self._basic_type == 'd':
if self._target_type == 'i64':
conversion_values = DOUBLE_DENORMAL_VALUES + DOUBLE_NORMAL_VALUES + DOUBLE_INT_VALUES
conversion_function = TestTuple.double_hex_to_int64_str
elif self._target_type == 'u64':
conversion_values = DOUBLE_DENORMAL_VALUES + DOUBLE_NORMAL_VALUES + DOUBLE_UINT_VALUES
conversion_function = TestTuple.double_hex_to_uint64_str
elif self._basic_type in ('i64', 'u64'):
if self._basic_type == 'i64':
conversion_values = INT64_VALUES
else:
conversion_values = UINT64_VALUES
conversion_function = TestTuple.int_str_to_type_str(self._target_type)
if (self._basic_type == 'b' or
(self._basic_type in ('f', 'd') and self._target_type in ('i64', 'u64')) or
(self._basic_type == 'u' and self._target_type == 'i64')):
explicit = 'explicit'
self._gen_comp_test(self._conversion_type, self._target_full_type,
converted_from)
converted_from = self._target_full_type + '(from)'
conversions = []
for value in conversion_values:
to_value = conversion_function(value)
item = {'from': value, 'to': to_value}
conversions.append(item)
self._gen_exec_test(self._conversion_type, self._target_full_type,
self._uniform_type, self._target_full_type,
explicit, converted_from, conversions)
def _gen_from_target(self):
converted_from = 'from'
explicit = 'implicit'
if self._target_type == 'd':
if self._basic_type == 'b':
conversion_values = DOUBLE_INFS + DOUBLE_NORMAL_VALUES + DOUBLE_BOOL_VALUES
conversion_function = TestTuple.double_hex_to_bool_str
elif self._basic_type == 'i':
conversion_values = DOUBLE_DENORMAL_VALUES + DOUBLE_NORMAL_VALUES + DOUBLE_INT_VALUES
conversion_function = TestTuple.double_hex_to_int_str
elif self._basic_type == 'u':
conversion_values = DOUBLE_DENORMAL_VALUES + DOUBLE_NORMAL_VALUES + DOUBLE_UINT_VALUES
conversion_function = TestTuple.double_hex_to_uint_str
elif self._basic_type == 'f':
conversion_values = DOUBLE_INFS + DOUBLE_FLOAT_INFS + DOUBLE_FLOAT_VALUES
conversion_function = TestTuple.double_hex_to_float_hex
conversion_values = DOUBLE_NEG_ZERO + DOUBLE_POS_ZERO + conversion_values
elif self._target_type in ('i64', 'u64'):
if self._target_type == 'i64':
conversion_values = INT64_VALUES
elif self._target_type == 'u64':
conversion_values = UINT64_VALUES
if self._basic_type == 'b':
conversion_function = TestTuple.int_str_to_bool_str
elif self._basic_type == 'i':
conversion_function = TestTuple.int_str_to_int32_str
elif self._basic_type == 'u':
conversion_function = TestTuple.int_str_to_uint32_str
elif self._basic_type == 'f':
conversion_function = TestTuple.int_str_to_float_hex
elif self._basic_type == 'd':
conversion_function = TestTuple.int_str_to_double_hex
elif self._basic_type == 'i64':
conversion_function = TestTuple.int_str_to_int64_str
elif self._basic_type == 'i':
conversion_function = TestTuple.int_str_to_uint64_str
if self._basic_type != 'd':
self._gen_comp_test(self._target_full_type, self._conversion_type,
converted_from)
converted_from = self._conversion_type + '(from)'
explicit = 'explicit'
else:
assert self._target_type in ('i64', 'u64')
conversions = []
for value in conversion_values:
to_value = conversion_function(value)
item = {'from': value, 'to': to_value}
conversions.append(item)
self._gen_exec_test(self._target_full_type, self._conversion_type,
self._target_full_type, self._uniform_type,
explicit, converted_from, conversions)
class ZeroSignTestTuple(TestTuple):
"""Derived class for conversion tests using the float32 and float64
+/-0.0 values.
"""
@staticmethod
def all_tests(names_only):
"""Returns all the possible zero sign conversion test instances."""
assert isinstance(names_only, bool)
stages = ['vert', 'geom', 'frag']
dimensions = ['1', '2', '3', '4']
basic_types = ['f']
glsl_ver = ['410', '420']
if not names_only:
for ver in glsl_ver:
utils.safe_makedirs(get_dir_name(ver, 'execution'))
for ver, stage, first_dimension, second_dimension, basic_type in itertools.product(
glsl_ver,
stages,
dimensions,
dimensions,
basic_types):
if not (first_dimension != '1' and second_dimension == '1'):
yield ZeroSignTestTuple(ver, stage,
first_dimension, second_dimension,
basic_type, names_only)
def __init__(self, ver, stage,
first_dimension, second_dimension,
basic_type, names_only):
assert ver in ('410', '420')
assert basic_type == 'f'
assert not (first_dimension != '1' and second_dimension == '1')
super(ZeroSignTestTuple, self).__init__(ver, stage,
first_dimension, second_dimension,
basic_type, 'd', names_only)
def __gen_zero_sign_exec_test(self, from_type, to_type,
uniform_from_type, uniform_to_type,
explicit, converted_from, conversions):
filename = os.path.join(
get_dir_name(self._ver, 'execution'),
'{}-conversion-{}-{}-{}-zero-sign.shader_test'.format(self._stage, explicit,
from_type, to_type))
self._filenames.append(filename)
if not self._names_only:
with open(filename, 'w') as test_file:
test_file.write(TEMPLATES.get_template(
'execution-zero-sign.{}.shader_test.mako'.format(
self._stage)).render_unicode(
ver=self._ver,
extensions=self._extensions,
amount=self._amount,
from_type=from_type,
to_type=to_type,
converted_from=converted_from,
uniform_from_type=uniform_from_type,
uniform_to_type=uniform_to_type,
conversions=conversions))
def _gen_to_target(self):
if self._ver == '410':
conversion_values = FLOAT_POS_ZERO
elif self._ver == '420':
conversion_values = FLOAT_NEG_ZERO
conversions = []
for value in conversion_values:
to_value = TestTuple.float_hex_to_inv_double_hex(value)
item = {'from': value, 'to': to_value}
conversions.append(item)
self.__gen_zero_sign_exec_test(self._conversion_type, self._target_full_type,
self._uniform_type, self._target_full_type,
'implicit', 'from', conversions)
def _gen_from_target(self):
if self._ver == '410':
conversion_values = DOUBLE_POS_ZERO
elif self._ver == '420':
conversion_values = DOUBLE_NEG_ZERO
conversions = []
for value in conversion_values:
to_value = TestTuple.double_hex_to_inv_float_hex(value)
item = {'from': value, 'to': to_value}
conversions.append(item)
self.__gen_zero_sign_exec_test(self._target_full_type, self._conversion_type,
self._target_full_type, self._uniform_type,
'explicit', self._conversion_type + '(from)', conversions)
def main():
"""Main function."""
parser = argparse.ArgumentParser(
description="Generate shader tests that check the conversions from and "
"to fp64")
parser.add_argument(
'--names-only',
dest='names_only',
action='store_true',
default=False,
help="Don't output files, just generate a list of filenames to stdout")
args = parser.parse_args()
np.seterr(divide='ignore')
for test in (list(RegularTestTuple.all_tests(args.names_only)) +
list(ZeroSignTestTuple.all_tests(args.names_only))):
test.generate_test_files()
for filename in test.filenames:
print(filename)
if __name__ == '__main__':
main()
|