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f594682627
Use range instead of xrange whenever possible. The extra list creation in Python2 is generally not a performance bottleneck. Differential Revision: https://reviews.llvm.org/D56253 llvm-svn: 350309
258 lines
9.9 KiB
Python
Executable File
258 lines
9.9 KiB
Python
Executable File
#!/usr/bin/env python
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"""A shuffle vector fuzz tester.
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This is a python program to fuzz test the LLVM shufflevector instruction. It
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generates a function with a random sequnece of shufflevectors, maintaining the
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element mapping accumulated across the function. It then generates a main
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function which calls it with a different value in each element and checks that
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the result matches the expected mapping.
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Take the output IR printed to stdout, compile it to an executable using whatever
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set of transforms you want to test, and run the program. If it crashes, it found
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a bug.
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"""
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from __future__ import print_function
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import argparse
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import itertools
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import random
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import sys
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import uuid
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def main():
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element_types=['i8', 'i16', 'i32', 'i64', 'f32', 'f64']
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parser = argparse.ArgumentParser(description=__doc__)
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parser.add_argument('-v', '--verbose', action='store_true',
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help='Show verbose output')
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parser.add_argument('--seed', default=str(uuid.uuid4()),
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help='A string used to seed the RNG')
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parser.add_argument('--max-shuffle-height', type=int, default=16,
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help='Specify a fixed height of shuffle tree to test')
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parser.add_argument('--no-blends', dest='blends', action='store_false',
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help='Include blends of two input vectors')
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parser.add_argument('--fixed-bit-width', type=int, choices=[128, 256],
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help='Specify a fixed bit width of vector to test')
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parser.add_argument('--fixed-element-type', choices=element_types,
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help='Specify a fixed element type to test')
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parser.add_argument('--triple',
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help='Specify a triple string to include in the IR')
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args = parser.parse_args()
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random.seed(args.seed)
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if args.fixed_element_type is not None:
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element_types=[args.fixed_element_type]
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if args.fixed_bit_width is not None:
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if args.fixed_bit_width == 128:
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width_map={'i64': 2, 'i32': 4, 'i16': 8, 'i8': 16, 'f64': 2, 'f32': 4}
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(width, element_type) = random.choice(
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[(width_map[t], t) for t in element_types])
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elif args.fixed_bit_width == 256:
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width_map={'i64': 4, 'i32': 8, 'i16': 16, 'i8': 32, 'f64': 4, 'f32': 8}
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(width, element_type) = random.choice(
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[(width_map[t], t) for t in element_types])
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else:
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sys.exit(1) # Checked above by argument parsing.
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else:
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width = random.choice([2, 4, 8, 16, 32, 64])
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element_type = random.choice(element_types)
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element_modulus = {
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'i8': 1 << 8, 'i16': 1 << 16, 'i32': 1 << 32, 'i64': 1 << 64,
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'f32': 1 << 32, 'f64': 1 << 64}[element_type]
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shuffle_range = (2 * width) if args.blends else width
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# Because undef (-1) saturates and is indistinguishable when testing the
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# correctness of a shuffle, we want to bias our fuzz toward having a decent
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# mixture of non-undef lanes in the end. With a deep shuffle tree, the
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# probabilies aren't good so we need to bias things. The math here is that if
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# we uniformly select between -1 and the other inputs, each element of the
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# result will have the following probability of being undef:
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#
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# 1 - (shuffle_range/(shuffle_range+1))^max_shuffle_height
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#
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# More generally, for any probability P of selecting a defined element in
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# a single shuffle, the end result is:
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#
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# 1 - P^max_shuffle_height
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#
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# The power of the shuffle height is the real problem, as we want:
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#
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# 1 - shuffle_range/(shuffle_range+1)
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#
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# So we bias the selection of undef at any given node based on the tree
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# height. Below, let 'A' be 'len(shuffle_range)', 'C' be 'max_shuffle_height',
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# and 'B' be the bias we use to compensate for
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# C '((A+1)*A^(1/C))/(A*(A+1)^(1/C))':
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#
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# 1 - (B * A)/(A + 1)^C = 1 - A/(A + 1)
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#
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# So at each node we use:
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#
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# 1 - (B * A)/(A + 1)
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# = 1 - ((A + 1) * A * A^(1/C))/(A * (A + 1) * (A + 1)^(1/C))
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# = 1 - ((A + 1) * A^((C + 1)/C))/(A * (A + 1)^((C + 1)/C))
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#
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# This is the formula we use to select undef lanes in the shuffle.
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A = float(shuffle_range)
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C = float(args.max_shuffle_height)
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undef_prob = 1.0 - (((A + 1.0) * pow(A, (C + 1.0)/C)) /
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(A * pow(A + 1.0, (C + 1.0)/C)))
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shuffle_tree = [[[-1 if random.random() <= undef_prob
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else random.choice(range(shuffle_range))
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for _ in itertools.repeat(None, width)]
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for _ in itertools.repeat(None, args.max_shuffle_height - i)]
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for i in range(args.max_shuffle_height)]
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if args.verbose:
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# Print out the shuffle sequence in a compact form.
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print(('Testing shuffle sequence "%s" (v%d%s):' %
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(args.seed, width, element_type)), file=sys.stderr)
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for i, shuffles in enumerate(shuffle_tree):
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print(' tree level %d:' % (i,), file=sys.stderr)
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for j, s in enumerate(shuffles):
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print(' shuffle %d: %s' % (j, s), file=sys.stderr)
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print('', file=sys.stderr)
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# Symbolically evaluate the shuffle tree.
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inputs = [[int(j % element_modulus)
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for j in range(i * width + 1, (i + 1) * width + 1)]
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for i in range(args.max_shuffle_height + 1)]
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results = inputs
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for shuffles in shuffle_tree:
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results = [[((results[i] if j < width else results[i + 1])[j % width]
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if j != -1 else -1)
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for j in s]
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for i, s in enumerate(shuffles)]
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if len(results) != 1:
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print('ERROR: Bad results: %s' % (results,), file=sys.stderr)
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sys.exit(1)
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result = results[0]
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if args.verbose:
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print('Which transforms:', file=sys.stderr)
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print(' from: %s' % (inputs,), file=sys.stderr)
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print(' into: %s' % (result,), file=sys.stderr)
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print('', file=sys.stderr)
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# The IR uses silly names for floating point types. We also need a same-size
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# integer type.
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integral_element_type = element_type
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if element_type == 'f32':
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integral_element_type = 'i32'
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element_type = 'float'
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elif element_type == 'f64':
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integral_element_type = 'i64'
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element_type = 'double'
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# Now we need to generate IR for the shuffle function.
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subst = {'N': width, 'T': element_type, 'IT': integral_element_type}
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print("""
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define internal fastcc <%(N)d x %(T)s> @test(%(arguments)s) noinline nounwind {
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entry:""" % dict(subst,
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arguments=', '.join(
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['<%(N)d x %(T)s> %%s.0.%(i)d' % dict(subst, i=i)
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for i in range(args.max_shuffle_height + 1)])))
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for i, shuffles in enumerate(shuffle_tree):
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for j, s in enumerate(shuffles):
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print("""
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%%s.%(next_i)d.%(j)d = shufflevector <%(N)d x %(T)s> %%s.%(i)d.%(j)d, <%(N)d x %(T)s> %%s.%(i)d.%(next_j)d, <%(N)d x i32> <%(S)s>
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""".strip('\n') % dict(subst, i=i, next_i=i + 1, j=j, next_j=j + 1,
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S=', '.join(['i32 ' + (str(si) if si != -1 else 'undef')
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for si in s])))
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print("""
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ret <%(N)d x %(T)s> %%s.%(i)d.0
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}
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""" % dict(subst, i=len(shuffle_tree)))
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# Generate some string constants that we can use to report errors.
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for i, r in enumerate(result):
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if r != -1:
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s = ('FAIL(%(seed)s): lane %(lane)d, expected %(result)d, found %%d\n\\0A' %
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{'seed': args.seed, 'lane': i, 'result': r})
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s += ''.join(['\\00' for _ in itertools.repeat(None, 128 - len(s) + 2)])
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print("""
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@error.%(i)d = private unnamed_addr global [128 x i8] c"%(s)s"
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""".strip() % {'i': i, 's': s})
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# Define a wrapper function which is marked 'optnone' to prevent
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# interprocedural optimizations from deleting the test.
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print("""
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define internal fastcc <%(N)d x %(T)s> @test_wrapper(%(arguments)s) optnone noinline {
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%%result = call fastcc <%(N)d x %(T)s> @test(%(arguments)s)
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ret <%(N)d x %(T)s> %%result
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}
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""" % dict(subst,
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arguments=', '.join(['<%(N)d x %(T)s> %%s.%(i)d' % dict(subst, i=i)
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for i in range(args.max_shuffle_height + 1)])))
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# Finally, generate a main function which will trap if any lanes are mapped
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# incorrectly (in an observable way).
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print("""
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define i32 @main() {
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entry:
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; Create a scratch space to print error messages.
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%%str = alloca [128 x i8]
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%%str.ptr = getelementptr inbounds [128 x i8], [128 x i8]* %%str, i32 0, i32 0
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; Build the input vector and call the test function.
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%%v = call fastcc <%(N)d x %(T)s> @test_wrapper(%(inputs)s)
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; We need to cast this back to an integer type vector to easily check the
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; result.
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%%v.cast = bitcast <%(N)d x %(T)s> %%v to <%(N)d x %(IT)s>
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br label %%test.0
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""" % dict(subst,
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inputs=', '.join(
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[('<%(N)d x %(T)s> bitcast '
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'(<%(N)d x %(IT)s> <%(input)s> to <%(N)d x %(T)s>)' %
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dict(subst, input=', '.join(['%(IT)s %(i)d' % dict(subst, i=i)
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for i in input])))
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for input in inputs])))
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# Test that each non-undef result lane contains the expected value.
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for i, r in enumerate(result):
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if r == -1:
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print("""
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test.%(i)d:
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; Skip this lane, its value is undef.
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br label %%test.%(next_i)d
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""" % dict(subst, i=i, next_i=i + 1))
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else:
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print("""
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test.%(i)d:
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%%v.%(i)d = extractelement <%(N)d x %(IT)s> %%v.cast, i32 %(i)d
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%%cmp.%(i)d = icmp ne %(IT)s %%v.%(i)d, %(r)d
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br i1 %%cmp.%(i)d, label %%die.%(i)d, label %%test.%(next_i)d
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die.%(i)d:
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; Capture the actual value and print an error message.
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%%tmp.%(i)d = zext %(IT)s %%v.%(i)d to i2048
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%%bad.%(i)d = trunc i2048 %%tmp.%(i)d to i32
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call i32 (i8*, i8*, ...) @sprintf(i8* %%str.ptr, i8* getelementptr inbounds ([128 x i8], [128 x i8]* @error.%(i)d, i32 0, i32 0), i32 %%bad.%(i)d)
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%%length.%(i)d = call i32 @strlen(i8* %%str.ptr)
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call i32 @write(i32 2, i8* %%str.ptr, i32 %%length.%(i)d)
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call void @llvm.trap()
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unreachable
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""" % dict(subst, i=i, next_i=i + 1, r=r))
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print("""
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test.%d:
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ret i32 0
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}
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declare i32 @strlen(i8*)
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declare i32 @write(i32, i8*, i32)
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declare i32 @sprintf(i8*, i8*, ...)
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declare void @llvm.trap() noreturn nounwind
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""" % (len(result),))
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if __name__ == '__main__':
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main()
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