summaryrefslogtreecommitdiff
path: root/generated_tests/gen_conversion.py
blob: aa76d483a0132780ca74d69cb0e22d327bd6e1ec (plain)
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
# 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 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

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 int_str_to_double_str(istr):
        """Returns a float64 string from an int32 string."""
        assert isinstance(istr, str)
        return str(float(istr))

    @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)

    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 = []

        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'
            self._target_full_type = 'double'
            if self._uniform_type == '':
                self._uniform_type = self._conversion_type
        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 = 'd' + 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']
        target_types = ['d']
        glsl_ver = ['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):
            if (not (first_dimension != '1' and (second_dimension == '1' or basic_type != 'f')) and
                (basic_type not in target_types or basic_type < target_type)):
                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_fp64', '400')
        assert basic_type in ('b', 'u', 'i', 'f')
        assert target_type in ('d')
        assert not (first_dimension != '1' and (second_dimension == '1' or basic_type != 'f'))
        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,
                        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,
                        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':
            explicit = 'explicit'
            self._gen_comp_test(self._conversion_type, self._target_full_type,
                                converted_from)
            converted_from = self._target_full_type + '(from)'
            conversion_values = BOOL_VALUES
            conversion_function = TestTuple.int_str_to_double_str
        elif self._basic_type == 'i':
            conversion_values = INT_VALUES
            conversion_function = TestTuple.int_str_to_double_str
        elif self._basic_type == 'u':
            conversion_values = UINT_VALUES
            conversion_function = TestTuple.int_str_to_double_str
        elif self._basic_type == 'f':
            conversion_values = FLOAT_INFS + FLOAT_NEG_ZERO + FLOAT_POS_ZERO + FLOAT_VALUES
            conversion_function = TestTuple.float_hex_to_double_hex

        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'
        self._gen_comp_test(self._target_full_type, self._conversion_type,
                            converted_from)

        converted_from = self._conversion_type + '(from)'
        explicit = 'explicit'

        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

        conversions = []
        for value in DOUBLE_NEG_ZERO + DOUBLE_POS_ZERO + 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,
                            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()