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knl = lp.tag_inames(knl, dict(j="ilp"))
for k in lp.generate_loop_schedules(knl):
assert k.temporary_variables["a"].shape == (16,)
# }}}
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def test_write_parameter(ctx_factory):
dtype = np.float32
ctx = ctx_factory()
knl = lp.make_kernel(ctx.devices[0], [
"{[i,j]: 0<=i,j<n }",
],
"""
a = sum((i,j), i*j)
b = sum(i, sum(j, i*j))
n = 15
""",
[
lp.GlobalArg("a", dtype, shape=()),
lp.GlobalArg("b", dtype, shape=()),
lp.ValueArg("n", np.int32, approximately=1000),
],
assumptions="n>=1")
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import pytest
with pytest.raises(RuntimeError):
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lp.CompiledKernel(ctx, knl).get_code()
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def test_arg_shape_guessing(ctx_factory):
ctx = ctx_factory()
knl = lp.make_kernel(ctx.devices[0], [
"{[i,j]: 0<=i,j<n }",
],
"""
a = 1.5 + sum((i,j), i*j)
b[i, j] = i*j
c[i+j, j] = b[j,i]
""",
[
lp.GlobalArg("a", shape=lp.auto_shape),
lp.GlobalArg("b", shape=lp.auto_shape),
lp.GlobalArg("c", shape=lp.auto_shape),
lp.ValueArg("n"),
],
assumptions="n>=1")
print knl
print lp.CompiledKernel(ctx, knl).get_highlighted_code()
def test_arg_guessing(ctx_factory):
ctx = ctx_factory()
knl = lp.make_kernel(ctx.devices[0], [
"{[i,j]: 0<=i,j<n }",
],
"""
a = 1.5 + sum((i,j), i*j)
b[i, j] = i*j
c[i+j, j] = b[j,i]
""",
assumptions="n>=1")
print knl
print lp.CompiledKernel(ctx, knl).get_highlighted_code()
def test_nonlinear_index(ctx_factory):
ctx = ctx_factory()
knl = lp.make_kernel(ctx.devices[0], [
"{[i,j]: 0<=i,j<n }",
],
"""
a[i*i] = 17
""",
[
lp.GlobalArg("a", shape="n"),
lp.ValueArg("n"),
],
assumptions="n>=1")
print knl
print lp.CompiledKernel(ctx, knl).get_highlighted_code()
def test_triangle_domain(ctx_factory):
ctx = ctx_factory()
knl = lp.make_kernel(ctx.devices[0], [
"{[i,j]: 0<=i,j<n and i <= j}",
],
"a[i,j] = 17",
assumptions="n>=1")
print knl
print lp.CompiledKernel(ctx, knl).get_highlighted_code()
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