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[LLVM][Codegen] Cast NaN to bool gives true #18772

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Merged
tqchen merged 1 commit into from
Feb 13, 2026
+25 −1
Merged

[LLVM][Codegen] Cast NaN to bool gives true #18772

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2 changes: 1 addition & 1 deletion src/target/llvm/codegen_llvm.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -928,7 +928,7 @@ llvm::Value* CodeGenLLVM::CreateCast(DataType from, DataType to, llvm::Value* va
} else if (to.is_bool()) {
if (from.is_float()) {
llvm::Constant* zero = llvm::ConstantFP::get(DTypeToLLVMType(from), 0.);
return builder_->CreateFCmpONE(value, zero);
return builder_->CreateFCmpUNE(value, zero);
} else {
llvm::Constant* zero = llvm::ConstantInt::get(DTypeToLLVMType(from), 0);
return builder_->CreateICmpNE(value, zero);
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24 changes: 24 additions & 0 deletions tests/python/codegen/test_target_codegen_llvm.py
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Original file line number Diff line number Diff line change
Expand Up @@ -370,6 +370,30 @@ def main(A: T.Buffer((64,), "int32"), C: T.Buffer((64,), "float32")):
tvm.testing.assert_allclose(c.numpy(), c_np)


@tvm.testing.requires_llvm
def test_llvm_cast_float_to_bool():
@I.ir_module
class Module:
@T.prim_func
def main(A: T.Buffer((4,), "float32"), C: T.Buffer((4,), "bool")):
T.func_attr({"tir.noalias": True})
for i in range(4):
with T.sblock("C"):
v_i = T.axis.spatial(4, i)
T.reads(A[v_i])
T.writes(C[v_i])
C[v_i] = T.Cast("bool", A[v_i])

n = 4
f = tvm.compile(Module, target="llvm")
dev = tvm.cpu(0)
a = tvm.runtime.tensor(np.array([0.0, 1.0, np.nan, np.inf], dtype="float32"), dev)
c = tvm.runtime.empty((n,), dtype="bool", device=dev)
f(a, c)
c_np = np.array([False, True, True, True], dtype="bool")
tvm.testing.assert_allclose(c.numpy(), c_np)
Comment on lines +373 to +394
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@gemini-code-assist gemini-code-assist bot Feb 13, 2026

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medium

This is a great test for verifying the new behavior. To improve test coverage, consider parameterizing it to run against different float types (float16, float32, float64), since the change in codegen_llvm.cc affects all float types.

@tvm.testing.requires_llvm
@pytest.mark.parametrize("dtype", ["float16", "float32", "float64"])
def test_llvm_cast_float_to_bool(dtype):
    @I.ir_module
    class Module:
        @T.prim_func
        def main(A: T.Buffer((4,), dtype), C: T.Buffer((4,), "bool")):
            T.func_attr({"tir.noalias": True})
            for i in range(4):
                with T.sblock("C"):
                    v_i = T.axis.spatial(4, i)
                    T.reads(A[v_i])
                    T.writes(C[v_i])
                    C[v_i] = T.Cast("bool", A[v_i])

    n = 4
    f = tvm.compile(Module, target="llvm")
    dev = tvm.cpu(0)
    a = tvm.runtime.tensor(np.array([0.0, 1.0, np.nan, np.inf], dtype=dtype), dev)
    c = tvm.runtime.empty((n,), dtype="bool", device=dev)
    f(a, c)
    c_np = np.array([False, True, True, True], dtype="bool")
    tvm.testing.assert_allclose(c.numpy(), c_np)



@tvm.testing.requires_llvm
def test_rank_zero():
@I.ir_module
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