3 """A shuffle vector fuzz tester.
5 This is a python program to fuzz test the LLVM shufflevector instruction. It
6 generates a function with a random sequnece of shufflevectors, maintaining the
7 element mapping accumulated across the function. It then generates a main
8 function which calls it with a different value in each element and checks that
9 the result matches the expected mapping.
11 Take the output IR printed to stdout, compile it to an executable using whatever
12 set of transforms you want to test, and run the program. If it crashes, it found
23 element_types
=['i8', 'i16', 'i32', 'i64', 'f32', 'f64']
24 parser
= argparse
.ArgumentParser(description
=__doc__
)
25 parser
.add_argument('-v', '--verbose', action
='store_true',
26 help='Show verbose output')
27 parser
.add_argument('--seed', default
=str(uuid
.uuid4()),
28 help='A string used to seed the RNG')
29 parser
.add_argument('--max-shuffle-height', type=int, default
=16,
30 help='Specify a fixed height of shuffle tree to test')
31 parser
.add_argument('--no-blends', dest
='blends', action
='store_false',
32 help='Include blends of two input vectors')
33 parser
.add_argument('--fixed-bit-width', type=int, choices
=[128, 256],
34 help='Specify a fixed bit width of vector to test')
35 parser
.add_argument('--fixed-element-type', choices
=element_types
,
36 help='Specify a fixed element type to test')
37 parser
.add_argument('--triple',
38 help='Specify a triple string to include in the IR')
39 args
= parser
.parse_args()
41 random
.seed(args
.seed
)
43 if args
.fixed_element_type
is not None:
44 element_types
=[args
.fixed_element_type
]
46 if args
.fixed_bit_width
is not None:
47 if args
.fixed_bit_width
== 128:
48 width_map
={'i64': 2, 'i32': 4, 'i16': 8, 'i8': 16, 'f64': 2, 'f32': 4}
49 (width
, element_type
) = random
.choice(
50 [(width_map
[t
], t
) for t
in element_types
])
51 elif args
.fixed_bit_width
== 256:
52 width_map
={'i64': 4, 'i32': 8, 'i16': 16, 'i8': 32, 'f64': 4, 'f32': 8}
53 (width
, element_type
) = random
.choice(
54 [(width_map
[t
], t
) for t
in element_types
])
56 sys
.exit(1) # Checked above by argument parsing.
58 width
= random
.choice([2, 4, 8, 16, 32, 64])
59 element_type
= random
.choice(element_types
)
62 'i8': 1 << 8, 'i16': 1 << 16, 'i32': 1 << 32, 'i64': 1 << 64,
63 'f32': 1 << 32, 'f64': 1 << 64}[element_type
]
65 shuffle_range
= (2 * width
) if args
.blends
else width
67 # Because undef (-1) saturates and is indistinguishable when testing the
68 # correctness of a shuffle, we want to bias our fuzz toward having a decent
69 # mixture of non-undef lanes in the end. With a deep shuffle tree, the
70 # probabilies aren't good so we need to bias things. The math here is that if
71 # we uniformly select between -1 and the other inputs, each element of the
72 # result will have the following probability of being undef:
74 # 1 - (shuffle_range/(shuffle_range+1))^max_shuffle_height
76 # More generally, for any probability P of selecting a defined element in
77 # a single shuffle, the end result is:
79 # 1 - P^max_shuffle_height
81 # The power of the shuffle height is the real problem, as we want:
83 # 1 - shuffle_range/(shuffle_range+1)
85 # So we bias the selection of undef at any given node based on the tree
86 # height. Below, let 'A' be 'len(shuffle_range)', 'C' be 'max_shuffle_height',
87 # and 'B' be the bias we use to compensate for
88 # C '((A+1)*A^(1/C))/(A*(A+1)^(1/C))':
90 # 1 - (B * A)/(A + 1)^C = 1 - A/(A + 1)
92 # So at each node we use:
95 # = 1 - ((A + 1) * A * A^(1/C))/(A * (A + 1) * (A + 1)^(1/C))
96 # = 1 - ((A + 1) * A^((C + 1)/C))/(A * (A + 1)^((C + 1)/C))
98 # This is the formula we use to select undef lanes in the shuffle.
99 A
= float(shuffle_range
)
100 C
= float(args
.max_shuffle_height
)
101 undef_prob
= 1.0 - (((A
+ 1.0) * pow(A
, (C
+ 1.0)/C
)) /
102 (A
* pow(A
+ 1.0, (C
+ 1.0)/C
)))
104 shuffle_tree
= [[[-1 if random
.random() <= undef_prob
105 else random
.choice(range(shuffle_range
))
106 for _
in itertools
.repeat(None, width
)]
107 for _
in itertools
.repeat(None, args
.max_shuffle_height
- i
)]
108 for i
in xrange(args
.max_shuffle_height
)]
111 # Print out the shuffle sequence in a compact form.
112 print >>sys
.stderr
, ('Testing shuffle sequence "%s" (v%d%s):' %
113 (args
.seed
, width
, element_type
))
114 for i
, shuffles
in enumerate(shuffle_tree
):
115 print >>sys
.stderr
, ' tree level %d:' % (i
,)
116 for j
, s
in enumerate(shuffles
):
117 print >>sys
.stderr
, ' shuffle %d: %s' % (j
, s
)
118 print >>sys
.stderr
, ''
120 # Symbolically evaluate the shuffle tree.
121 inputs
= [[int(j
% element_modulus
)
122 for j
in xrange(i
* width
+ 1, (i
+ 1) * width
+ 1)]
123 for i
in xrange(args
.max_shuffle_height
+ 1)]
125 for shuffles
in shuffle_tree
:
126 results
= [[((results
[i
] if j
< width
else results
[i
+ 1])[j
% width
]
129 for i
, s
in enumerate(shuffles
)]
130 if len(results
) != 1:
131 print >>sys
.stderr
, 'ERROR: Bad results: %s' % (results
,)
136 print >>sys
.stderr
, 'Which transforms:'
137 print >>sys
.stderr
, ' from: %s' % (inputs
,)
138 print >>sys
.stderr
, ' into: %s' % (result
,)
139 print >>sys
.stderr
, ''
141 # The IR uses silly names for floating point types. We also need a same-size
143 integral_element_type
= element_type
144 if element_type
== 'f32':
145 integral_element_type
= 'i32'
146 element_type
= 'float'
147 elif element_type
== 'f64':
148 integral_element_type
= 'i64'
149 element_type
= 'double'
151 # Now we need to generate IR for the shuffle function.
152 subst
= {'N': width
, 'T': element_type
, 'IT': integral_element_type
}
154 define internal fastcc <%(N)d x %(T)s> @test(%(arguments)s) noinline nounwind {
155 entry:""" % dict(subst
,
157 ['<%(N)d x %(T)s> %%s.0.%(i)d' % dict(subst
, i
=i
)
158 for i
in xrange(args
.max_shuffle_height
+ 1)]))
160 for i
, shuffles
in enumerate(shuffle_tree
):
161 for j
, s
in enumerate(shuffles
):
163 %%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>
164 """.strip('\n') % dict(subst
, i
=i
, next_i
=i
+ 1, j
=j
, next_j
=j
+ 1,
165 S
=', '.join(['i32 ' + (str(si
) if si
!= -1 else 'undef')
169 ret <%(N)d x %(T)s> %%s.%(i)d.0
171 """ % dict(subst
, i
=len(shuffle_tree
))
173 # Generate some string constants that we can use to report errors.
174 for i
, r
in enumerate(result
):
176 s
= ('FAIL(%(seed)s): lane %(lane)d, expected %(result)d, found %%d\n\\0A' %
177 {'seed': args
.seed
, 'lane': i
, 'result': r
})
178 s
+= ''.join(['\\00' for _
in itertools
.repeat(None, 128 - len(s
) + 2)])
180 @error.%(i)d = private unnamed_addr global [128 x i8] c"%(s)s"
181 """.strip() % {'i': i
, 's': s
}
183 # Define a wrapper function which is marked 'optnone' to prevent
184 # interprocedural optimizations from deleting the test.
186 define internal fastcc <%(N)d x %(T)s> @test_wrapper(%(arguments)s) optnone noinline {
187 %%result = call fastcc <%(N)d x %(T)s> @test(%(arguments)s)
188 ret <%(N)d x %(T)s> %%result
191 arguments
=', '.join(['<%(N)d x %(T)s> %%s.%(i)d' % dict(subst
, i
=i
)
192 for i
in xrange(args
.max_shuffle_height
+ 1)]))
194 # Finally, generate a main function which will trap if any lanes are mapped
195 # incorrectly (in an observable way).
199 ; Create a scratch space to print error messages.
200 %%str = alloca [128 x i8]
201 %%str.ptr = getelementptr inbounds [128 x i8], [128 x i8]* %%str, i32 0, i32 0
203 ; Build the input vector and call the test function.
204 %%v = call fastcc <%(N)d x %(T)s> @test_wrapper(%(inputs)s)
205 ; We need to cast this back to an integer type vector to easily check the
207 %%v.cast = bitcast <%(N)d x %(T)s> %%v to <%(N)d x %(IT)s>
211 [('<%(N)d x %(T)s> bitcast '
212 '(<%(N)d x %(IT)s> <%(input)s> to <%(N)d x %(T)s>)' %
213 dict(subst
, input=', '.join(['%(IT)s %(i)d' % dict(subst
, i
=i
)
215 for input in inputs
]))
217 # Test that each non-undef result lane contains the expected value.
218 for i
, r
in enumerate(result
):
222 ; Skip this lane, its value is undef.
223 br label %%test.%(next_i)d
224 """ % dict(subst
, i
=i
, next_i
=i
+ 1)
228 %%v.%(i)d = extractelement <%(N)d x %(IT)s> %%v.cast, i32 %(i)d
229 %%cmp.%(i)d = icmp ne %(IT)s %%v.%(i)d, %(r)d
230 br i1 %%cmp.%(i)d, label %%die.%(i)d, label %%test.%(next_i)d
233 ; Capture the actual value and print an error message.
234 %%tmp.%(i)d = zext %(IT)s %%v.%(i)d to i2048
235 %%bad.%(i)d = trunc i2048 %%tmp.%(i)d to i32
236 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)
237 %%length.%(i)d = call i32 @strlen(i8* %%str.ptr)
238 call i32 @write(i32 2, i8* %%str.ptr, i32 %%length.%(i)d)
239 call void @llvm.trap()
241 """ % dict(subst
, i
=i
, next_i
=i
+ 1, r
=r
)
248 declare i32 @strlen(i8*)
249 declare i32 @write(i32, i8*, i32)
250 declare i32 @sprintf(i8*, i8*, ...)
251 declare void @llvm.trap() noreturn nounwind
254 if __name__
== '__main__':