77 lines
2.4 KiB
Python
77 lines
2.4 KiB
Python
"""Test: run each approach in a separate process to survive LLVM ERROR."""
|
|
import torch
|
|
import cutlass.cute as cute
|
|
import cutlass.torch as cutlass_torch
|
|
import sys
|
|
|
|
approach = sys.argv[1] if len(sys.argv) > 1 else "arith"
|
|
|
|
if approach == "arith":
|
|
from cutlass.cutlass_dsl import dsl_user_op, T
|
|
from cutlass._mlir.dialects import arith
|
|
from cutlass.cute.typing import Float32, Int32
|
|
|
|
@dsl_user_op
|
|
def f32_to_i32(x: Float32, *, loc=None, ip=None) -> Int32:
|
|
return Int32(
|
|
arith.fptosi(T.i32(), Float32(x).ir_value(loc=loc, ip=ip), loc=loc, ip=ip)
|
|
)
|
|
|
|
elif approach == "nvvm_ptx":
|
|
from cutlass.cutlass_dsl import dsl_user_op, T
|
|
from cutlass._mlir.dialects import nvvm
|
|
from cutlass.cute.typing import Float32, Int32
|
|
|
|
@dsl_user_op
|
|
def f32_to_i32(x: Float32, *, loc=None, ip=None) -> Int32:
|
|
result = nvvm.inline_ptx(
|
|
write_only_args=[T.i32()],
|
|
read_only_args=[Float32(x).ir_value(loc=loc, ip=ip)],
|
|
ptx_code="cvt.rni.s32.f32 $0, $1;",
|
|
loc=loc,
|
|
ip=ip,
|
|
)
|
|
return Int32(result)
|
|
|
|
elif approach == "nvvm_multiline":
|
|
from cutlass.cutlass_dsl import dsl_user_op, T
|
|
from cutlass._mlir.dialects import nvvm
|
|
from cutlass.cute.typing import Float32, Int32
|
|
|
|
@dsl_user_op
|
|
def f32_to_i32(x: Float32, *, loc=None, ip=None) -> Int32:
|
|
result = nvvm.inline_ptx(
|
|
write_only_args=[T.i32()],
|
|
read_only_args=[Float32(x).ir_value(loc=loc, ip=ip)],
|
|
ptx_code="{\n\tcvt.rni.s32.f32 $0, $1;\n\t}",
|
|
loc=loc,
|
|
ip=ip,
|
|
)
|
|
return Int32(result)
|
|
|
|
else:
|
|
print(f"Unknown approach: {approach}")
|
|
sys.exit(1)
|
|
|
|
|
|
@cute.kernel
|
|
def test_k(inp: cute.Tensor, out: cute.Tensor):
|
|
tidx, _, _ = cute.arch.thread_idx()
|
|
if tidx == Int32(0):
|
|
x = cute.arch.load(inp.iterator, Float32)
|
|
r = f32_to_i32(x)
|
|
cute.arch.store(out.iterator, r)
|
|
|
|
|
|
if __name__ == "__main__":
|
|
x = torch.tensor([3.7], dtype=torch.float32, device='cuda')
|
|
o = torch.zeros(1, dtype=torch.int32, device='cuda')
|
|
xc = cutlass_torch.from_dlpack(x).mark_layout_dynamic(leading_dim=0)
|
|
oc = cutlass_torch.from_dlpack(o).mark_layout_dynamic(leading_dim=0)
|
|
print(f"Approach: {approach}")
|
|
print("Compiling...")
|
|
compiled = cute.compile(test_k, xc, oc)
|
|
print("Running...")
|
|
compiled(xc, oc)
|
|
print(f"Result: {o.item()} (expected 4)")
|