import torch import tilelang.testing import tilelang.language as T @tilelang.jit def get_select_kernel_1(): @T.prim_func def main( A: T.Tensor[(128, 8), T.float32], B: T.Tensor[(128, 8), T.float32], ): with T.Kernel(1, threads=128): tx = T.get_thread_binding(0) tmp = T.alloc_var(T.bfloat16) tmp = A[tx, 3] B[tx, 0] = T.Select(True, A[tx, 0], 0.0) B[tx, 1] = T.Select(False, 1.0, A[tx, 1]) B[tx, 2] = T.Select(T.Cast(T.bfloat16, A[tx, 3]) == tmp, A[tx, 2], T.Cast(T.float32, tmp)) B[tx, 3] = T.Select(B[tx, 0] != 0.0, T.if_then_else(B[tx, 1] != 0.0, A[tx, 3], 0.0), 0.0) for i in T.serial(4): B[tx, i + 4] = T.Select( A[tx, 0] == 0, T.if_then_else(T.Select(True, False, True), 1.0, 2.0), T.Select(True, A[tx, i + 4], 3.0) ) return main def test_select_correctness(): A = torch.randn((128, 8), dtype=torch.float32, device="cuda") B = torch.empty((128, 8), dtype=torch.float32, device="cuda") kernel = get_select_kernel_1() A = torch.clamp(A, min=1e-4) kernel(A, B) assert torch.allclose(A, B) @tilelang.jit def get_select_kernel_2(): @T.prim_func def main( A: T.Tensor[(128, 8), T.float32], B: T.Tensor[(128, 8), T.float32], ): with T.Kernel(1, threads=128): tx = T.get_thread_binding(0) tmp = T.alloc_var(T.bfloat16) tmp = A[tx, 3] B[tx, 0] = T.Select(True, A[tx, 0], 0.0) B[tx, 1] = T.Select(False, 1.0, A[tx, 1]) B[tx, 2] = T.Select(T.Cast(T.bfloat16, A[tx, 3]) == tmp, A[tx, 2], T.Cast(T.float32, tmp)) B[tx, 3] = T.Select(B[tx, 0] != 0.0, T.Select(B[tx, 1] != 0.0, A[tx, 3], 0.0), 0.0) for i in T.serial(4): B[tx, i + 4] = T.Select( A[tx, 0] == 0, T.Select(T.Select(True, False, True), 1.0, 2.0), T.Select(T.sin(A[tx, 2]) == 1.0, T.sin(A[tx, 0]), T.cos(A[tx, 1])), ) return main def test_select_codegen_no_if(): kernel = get_select_kernel_2() source = kernel.get_kernel_source() assert "if (" not in source if __name__ == "__main__": tilelang.testing.main()