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from __future__ import division
import numpy as np
import loopy as lp
import pyopencl as cl
from pyopencl.tools import pytest_generate_tests_for_pyopencl \
as pytest_generate_tests
__all__ = ["pytest_generate_tests",
"cl" # 'cl.create_some_context'
]
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def test_simple_side_effect(ctx_factory):
ctx = ctx_factory()
knl = lp.make_kernel(ctx.devices[0],
"{[i,j]: 0<=i,j<100}",
"""
a[i] = a[i] + 1
""",
[lp.GlobalArg("a", np.float32, shape=(100,))]
)
kernel_gen = lp.generate_loop_schedules(knl)
kernel_gen = lp.check_kernels(kernel_gen)
for gen_knl in kernel_gen:
print gen_knl
compiled = lp.CompiledKernel(ctx, gen_knl)
print compiled.code
def test_nonsense_reduction(ctx_factory):
ctx = ctx_factory()
knl = lp.make_kernel(ctx.devices[0],
"{[i]: 0<=i<100}",
"""
a[i] = sum(i, 2)
""",
[lp.GlobalArg("a", np.float32, shape=(100,))]
)
import pytest
with pytest.raises(RuntimeError):
list(lp.generate_loop_schedules(knl))
def test_owed_barriers(ctx_factory):
ctx = ctx_factory()
knl = lp.make_kernel(ctx.devices[0],
"{[i]: 0<=i<100}",
[
"[i:l.0] <float32> z[i] = a[i]"
],
[lp.GlobalArg("a", np.float32, shape=(100,))]
kernel_gen = lp.generate_loop_schedules(knl)
kernel_gen = lp.check_kernels(kernel_gen)
for gen_knl in kernel_gen:
compiled = lp.CompiledKernel(ctx, gen_knl)
print compiled.code
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def test_wg_too_small(ctx_factory):
ctx = ctx_factory()
knl = lp.make_kernel(ctx.devices[0],
"{[i]: 0<=i<100}",
[
"[i:l.0] <float32> z[i] = a[i] {id=copy}"
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],
[lp.GlobalArg("a", np.float32, shape=(100,))],
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local_sizes={0: 16})
kernel_gen = lp.generate_loop_schedules(knl)
kernel_gen = lp.check_kernels(kernel_gen)
for gen_knl in kernel_gen:
try:
lp.CompiledKernel(ctx, gen_knl)
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except RuntimeError, e:
assert "implemented and desired" in str(e)
pass # expected!
else:
assert False # expecting an error
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def test_join_inames(ctx_factory):
ctx = ctx_factory()
knl = lp.make_kernel(ctx.devices[0],
"{[i,j]: 0<=i,j<16}",
[
"b[i,j] = 2*a[i,j]"
],
[
lp.GlobalArg("a", np.float32, shape=(16, 16,)),
lp.GlobalArg("b", np.float32, shape=(16, 16,))
],
)
ref_knl = knl
knl = lp.add_prefetch(knl, "a", sweep_inames=["i", "j"])
knl = lp.join_inames(knl, ["a_dim_0", "a_dim_1"])
kernel_gen = lp.generate_loop_schedules(knl)
kernel_gen = lp.check_kernels(kernel_gen)
lp.auto_test_vs_ref(ref_knl, ctx, kernel_gen)
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def test_divisibility_assumption(ctx_factory):
ctx = ctx_factory()
knl = lp.make_kernel(ctx.devices[0],
"[n] -> {[i]: 0<=i<n}",
[
"b[i] = 2*a[i]"
],
[
lp.GlobalArg("a", np.float32, shape=("n",)),
lp.GlobalArg("b", np.float32, shape=("n",)),
lp.ValueArg("n", np.int32),
],
assumptions="n>=1 and (exists zz: n = 16*zz)")
ref_knl = knl
knl = lp.split_iname(knl, "i", 16)
for k in lp.generate_loop_schedules(knl):
code = lp.generate_code(k)
assert "if" not in code
kernel_gen = lp.generate_loop_schedules(knl)
kernel_gen = lp.check_kernels(kernel_gen)
lp.auto_test_vs_ref(ref_knl, ctx, kernel_gen,
parameters={"n": 16**3})
def test_multi_cse(ctx_factory):
ctx = ctx_factory()
knl = lp.make_kernel(ctx.devices[0],
"{[i]: 0<=i<100}",
[
"[i] <float32> z[i] = a[i] + a[i]**2"
],
[lp.GlobalArg("a", np.float32, shape=(100,))],
local_sizes={0: 16})
knl = lp.split_iname(knl, "i", 16, inner_tag="l.0")
knl = lp.add_prefetch(knl, "a", [])
kernel_gen = lp.generate_loop_schedules(knl)
kernel_gen = lp.check_kernels(kernel_gen)
for gen_knl in kernel_gen:
compiled = lp.CompiledKernel(ctx, gen_knl)
print compiled.code
def test_stencil(ctx_factory):
ctx = ctx_factory()
# n=32 causes corner case behavior in size calculations for temprorary (a
# non-unifiable, two-constant-segments PwAff as the base index)
n = 256
knl = lp.make_kernel(ctx.devices[0],
"{[i,j]: 0<= i,j < %d}" % n,
"a_offset(ii, jj) := a[ii+1, jj+1]",
"z[i,j] = -2*a_offset(i,j)"
" + a_offset(i,j-1)"
" + a_offset(i,j+1)"
" + a_offset(i-1,j)"
" + a_offset(i+1,j)"
lp.GlobalArg("a", np.float32, shape=(n+2,n+2,)),
lp.GlobalArg("z", np.float32, shape=(n+2,n+2,))
def variant_1(knl):
knl = lp.split_iname(knl, "i", 16, outer_tag="g.1", inner_tag="l.1")
knl = lp.split_iname(knl, "j", 16, outer_tag="g.0", inner_tag="l.0")
knl = lp.add_prefetch(knl, "a", ["i_inner", "j_inner"])
for variant in [variant_1]:
kernel_gen = lp.generate_loop_schedules(variant(knl),
loop_priority=["i_outer", "i_inner_0", "j_0"])
kernel_gen = lp.check_kernels(kernel_gen)
lp.auto_test_vs_ref(ref_knl, ctx, kernel_gen,
fills_entire_output=False, print_ref_code=True,
op_count=[n*n], op_label=["cells"])
def test_eq_constraint(ctx_factory):
ctx = ctx_factory()
knl = lp.make_kernel(ctx.devices[0],
"{[i,j]: 0<= i,j < 32}",
[
"a[i] = b[i]"
],
[
lp.GlobalArg("a", np.float32, shape=(1000,)),
lp.GlobalArg("b", np.float32, shape=(1000,))
knl = lp.split_iname(knl, "i", 16, outer_tag="g.0")
knl = lp.split_iname(knl, "i_inner", 16, outer_tag=None, inner_tag="l.0")
kernel_gen = lp.generate_loop_schedules(knl)
kernel_gen = lp.check_kernels(kernel_gen)
for knl in kernel_gen:
print lp.generate_code(knl)
def test_argmax(ctx_factory):
dtype = np.dtype(np.float32)
ctx = ctx_factory()
order = "C"
n = 10000
knl = lp.make_kernel(ctx.devices[0],
"{[i]: 0<=i<%d}" % n,
[
"<> result = argmax(i, fabs(a[i]))",
"max_idx = result.index",
"max_val = result.value",
],
[
lp.GlobalArg("a", dtype, shape=(n,), order=order),
lp.GlobalArg("max_idx", np.int32, shape=(), order=order),
lp.GlobalArg("max_val", dtype, shape=(), order=order),
])
a = np.random.randn(10000).astype(dtype)
cknl = lp.CompiledKernel(ctx, knl)
evt, (max_idx, max_val) = cknl(queue, a=a, out_host=True)
assert max_val == np.max(np.abs(a))
assert max_idx == np.where(np.abs(a)==max_val)[-1]
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def make_random_value():
from random import randrange, uniform
v = randrange(3)
if v == 0:
while True:
z = randrange(-1000, 1000)
if z:
return z
elif v == 1:
return uniform(-10, 10)
else:
return uniform(-10, 10) + 1j*uniform(-10, 10)
def make_random_expression(var_values, size):
from random import randrange
import pymbolic.primitives as p
v = randrange(1500)
size[0] += 1
if v < 500 and size[0] < 40:
term_count = randrange(2, 5)
if randrange(2) < 1:
cls = p.Sum
else:
cls = p.Product
return cls(tuple(
make_random_expression(var_values, size)
for i in range(term_count)))
elif v < 750:
return make_random_value()
elif v < 1000:
var_name = "var_%d" % len(var_values)
assert var_name not in var_values
var_values[var_name] = make_random_value()
return p.Variable(var_name)
elif v < 1250:
return make_random_expression(var_values, size) - make_random_expression(var_values, size)
elif v < 1500:
return make_random_expression(var_values, size) / make_random_expression(var_values, size)
def generate_random_fuzz_examples(count):
for i in xrange(count):
size = [0]
var_values = {}
expr = make_random_expression(var_values, size)
yield expr, var_values
def test_fuzz_code_generator(ctx_factory):
ctx = ctx_factory()
queue = cl.CommandQueue(ctx)
#from expr_fuzz import get_fuzz_examples
for expr, var_values in generate_random_fuzz_examples(20):
#for expr, var_values in get_fuzz_examples():
from pymbolic import evaluate
true_value = evaluate(expr, var_values)
def get_dtype(x):
if isinstance(x, complex):
return np.complex128
else:
return np.float64
knl = lp.make_kernel(ctx.devices[0], "{ : }",
[lp.Instruction(None, "value", expr)],
[lp.GlobalArg("value", np.complex128, shape=())]
+ [
for name, val in var_values.iteritems()
])
ck = lp.CompiledKernel(ctx, knl)
evt, (lp_value,) = ck(queue, out_host=True, **var_values)
err = abs(true_value-lp_value)/abs(true_value)
if abs(err) > 1e-10:
print "---------------------------------------------------------------------"
print "WRONG: rel error=%g" % err
print "true=%r" % true_value
print "loopy=%r" % lp_value
print "---------------------------------------------------------------------"
print ck.code
print "---------------------------------------------------------------------"
print var_values
print "---------------------------------------------------------------------"
print repr(expr)
print "---------------------------------------------------------------------"
print expr
print "---------------------------------------------------------------------"
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def test_empty_reduction(ctx_factory):
dtype = np.dtype(np.float32)
ctx = ctx_factory()
queue = cl.CommandQueue(ctx)
knl = lp.make_kernel(ctx.devices[0],
[
"{[i]: 0<=i<20}",
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],
[
"a[i] = sum(j, j)",
],
[
lp.GlobalArg("a", dtype, (20,)),
])
cknl = lp.CompiledKernel(ctx, knl)
evt, (a,) = cknl(queue)
assert (a.get() == 0).all()
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def test_nested_dependent_reduction(ctx_factory):
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ctx = ctx_factory()
queue = cl.CommandQueue(ctx)
knl = lp.make_kernel(ctx.devices[0],
[
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"{[j]: 0<=j<i+sumlen}"
],
[
"<> sumlen = l[i]",
"a[i] = sum(j, j)",
],
[
lp.GlobalArg("a", dtype, ("n",)),
lp.GlobalArg("l", np.int32, ("n",)),
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])
cknl = lp.CompiledKernel(ctx, knl)
n = 330
l = np.arange(n, dtype=np.int32)
evt, (a,) = cknl(queue, l=l, n=n, out_host=True)
tgt_result = (2*l-1)*2*l/2
assert (a == tgt_result).all()
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def test_dependent_loop_bounds(ctx_factory):
dtype = np.dtype(np.float32)
ctx = ctx_factory()
knl = lp.make_kernel(ctx.devices[0],
[
"{[i]: 0<=i<n}",
"{[jj]: 0<=jj<row_len}",
],
[
"<> row_len = a_rowstarts[i+1] - a_rowstarts[i]",
"ax[i] = sum(jj, a_values[a_rowstarts[i]+jj])",
],
[
lp.GlobalArg("a_rowstarts", np.int32),
lp.GlobalArg("a_indices", np.int32),
lp.GlobalArg("a_values", dtype),
lp.GlobalArg("x", dtype),
lp.GlobalArg("ax", dtype),
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],
assumptions="n>=1 and row_len>=1")
cknl = lp.CompiledKernel(ctx, knl)
print "---------------------------------------------------"
cknl.print_code()
print "---------------------------------------------------"
def test_dependent_loop_bounds_2(ctx_factory):
dtype = np.dtype(np.float32)
ctx = ctx_factory()
knl = lp.make_kernel(ctx.devices[0],
[
"{[i]: 0<=i<n}",
"{[jj]: 0<=jj<row_len}",
],
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[
"<> row_start = a_rowstarts[i]",
"<> row_len = a_rowstarts[i+1] - row_start",
"ax[i] = sum(jj, a_values[row_start+jj])",
],
[
lp.GlobalArg("a_rowstarts", np.int32),
lp.GlobalArg("a_indices", np.int32),
lp.GlobalArg("a_values", dtype),
lp.GlobalArg("x", dtype),
lp.GlobalArg("ax", dtype),
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],
assumptions="n>=1 and row_len>=1")
knl = lp.split_iname(knl, "i", 128, outer_tag="g.0",
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inner_tag="l.0")
cknl = lp.CompiledKernel(ctx, knl)
print "---------------------------------------------------"
cknl.print_code()
print "---------------------------------------------------"
def test_dependent_loop_bounds_3(ctx_factory):
# The point of this test is that it shows a dependency between
# domains that is exclusively mediated by the row_len temporary.
# It also makes sure that row_len gets read before any
# conditionals use it.
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dtype = np.dtype(np.float32)
ctx = ctx_factory()
knl = lp.make_kernel(ctx.devices[0],
[
"{[i]: 0<=i<n}",
"{[jj]: 0<=jj<row_len}",
],
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[
"<> row_len = a_row_lengths[i]",
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],
[
lp.GlobalArg("a_row_lengths", np.int32),
lp.GlobalArg("a", dtype, shape=("n,n"), order="C"),
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])
assert knl.parents_per_domain()[1] == 0
knl = lp.split_iname(knl, "i", 128, outer_tag="g.0",
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inner_tag="l.0")
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cknl = lp.CompiledKernel(ctx, knl)
print "---------------------------------------------------"
cknl.print_code()
print "---------------------------------------------------"
knl_bad = lp.split_iname(knl, "jj", 128, outer_tag="g.1",
inner_tag="l.1")
import pytest
with pytest.raises(RuntimeError):
list(lp.generate_loop_schedules(knl_bad))
def test_independent_multi_domain(ctx_factory):
dtype = np.dtype(np.float32)
ctx = ctx_factory()
queue = cl.CommandQueue(ctx)
knl = lp.make_kernel(ctx.devices[0],
[
"{[i]: 0<=i<n}",
"{[j]: 0<=j<n}",
],
[
lp.GlobalArg("a", dtype, shape=("n"), order="C"),
lp.GlobalArg("b", dtype, shape=("n"), order="C"),
knl = lp.split_iname(knl, "i", 16, outer_tag="g.0",
knl = lp.split_iname(knl, "j", 16, outer_tag="g.0",
assert knl.parents_per_domain() == 2*[None]
n = 50
cknl = lp.CompiledKernel(ctx, knl)
evt, (a, b) = cknl(queue, n=n, out_host=True)
assert a.shape == (50,)
assert b.shape == (50,)
def test_bare_data_dependency(ctx_factory):
dtype = np.dtype(np.float32)
ctx = ctx_factory()
queue = cl.CommandQueue(ctx)
knl = lp.make_kernel(ctx.devices[0],
[
"[znirp] -> {[i]: 0<=i<znirp}",
],
[
"<> znirp = n",
"a[i] = 1",
],
[
lp.GlobalArg("a", dtype, shape=("n"), order="C"),
])
cknl = lp.CompiledKernel(ctx, knl)
n = 20000
evt, (a,) = cknl(queue, n=n, out_host=True)
assert a.shape == (n,)
assert (a == 1).all()
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def test_equality_constraints(ctx_factory):
dtype = np.float32
ctx = ctx_factory()
order = "C"
knl = lp.make_kernel(ctx.devices[0], [
"[n] -> {[i,j]: 0<=i,j<n }",
"{[k]: k =i+5 and k < n}",
],
"a[i,j] = 5 {id=set_all}",
"a[i,k] = 22 {dep=set_all}",
lp.GlobalArg("a", dtype, shape="n, n", order=order),
lp.ValueArg("n", np.int32, approximately=1000),
name="equality_constraints", assumptions="n>=1")
seq_knl = knl
knl = lp.split_iname(knl, "i", 16, outer_tag="g.0", inner_tag="l.0")
knl = lp.split_iname(knl, "j", 16, outer_tag="g.1", inner_tag="l.1")
#print knl
#print knl.domains[0].detect_equalities()
kernel_gen = lp.generate_loop_schedules(knl)
kernel_gen = lp.check_kernels(kernel_gen, dict(n=n))
lp.auto_test_vs_ref(seq_knl, ctx, kernel_gen,
parameters=dict(n=n), print_ref_code=True)
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def test_stride(ctx_factory):
dtype = np.float32
ctx = ctx_factory()
order = "C"
n = 10
knl = lp.make_kernel(ctx.devices[0], [
"{[i]: 0<=i<n and (exists l: i = 2*l)}",
],
[
"a[i] = 5",
],
[
lp.GlobalArg("a", dtype, shape="n", order=order),
lp.ValueArg("n", np.int32, approximately=1000),
],
assumptions="n>=1")
seq_knl = knl
kernel_gen = lp.generate_loop_schedules(knl)
kernel_gen = lp.check_kernels(kernel_gen, dict(n=n))
lp.auto_test_vs_ref(seq_knl, ctx, kernel_gen,
parameters=dict(n=n), fills_entire_output=False)
def test_domain_dependency_via_existentially_quantified_variable(ctx_factory):
dtype = np.float32
ctx = ctx_factory()
order = "C"
n = 10
knl = lp.make_kernel(ctx.devices[0], [
"{[i]: 0<=i<n }",
"{[k]: k=i and (exists l: k = 2*l) }",
],
[
"a[i] = 5 {id=set}",
"a[k] = 6 {dep=set}",
],
[
lp.GlobalArg("a", dtype, shape="n", order=order),
lp.ValueArg("n", np.int32, approximately=1000),
],
assumptions="n>=1")
seq_knl = knl
kernel_gen = lp.generate_loop_schedules(knl)
kernel_gen = lp.check_kernels(kernel_gen, dict(n=n))
lp.auto_test_vs_ref(seq_knl, ctx, kernel_gen,
parameters=dict(n=n), )
# {{{ test race detection
def test_ilp_write_race_detection_global(ctx_factory):
ctx = ctx_factory()
knl = lp.make_kernel(ctx.devices[0], [
"[n] -> {[i,j]: 0<=i,j<n }",
],
[
"[j:ilp] a[i] = 5+i+j",
],
[
lp.GlobalArg("a", np.float32),
lp.ValueArg("n", np.int32, approximately=1000),
],
assumptions="n>=1")
from loopy.check import WriteRaceConditionError
import pytest
with pytest.raises(WriteRaceConditionError):
list(lp.generate_loop_schedules(knl))
def test_ilp_write_race_avoidance_local(ctx_factory):
ctx = ctx_factory()
knl = lp.make_kernel(ctx.devices[0],
[
"[i:l.0, j:ilp] <> a[i] = 5+i+j",
],
[])
for k in lp.generate_loop_schedules(knl):
assert k.temporary_variables["a"].shape == (16,17)
def test_ilp_write_race_avoidance_private(ctx_factory):
ctx = ctx_factory()
knl = lp.make_kernel(ctx.devices[0],
"{[j]: 0<=j<16 }",
[
"[j:ilp] <> a = 5+j",
],
[])
for k in lp.generate_loop_schedules(knl):
assert k.temporary_variables["a"].shape == (16,)
# }}}
if __name__ == "__main__":
import sys
if len(sys.argv) > 1:
exec(sys.argv[1])
else:
from py.test.cmdline import main
main([__file__])
# vim: foldmethod=marker