[DSL] Support python tenary if then else expression (#822)

* support python tenary if then else expression

* lint fix

tvm @ b56420b3

-Subproject commit 87b845fa0e14c2029bbf5799fbbbb9d490db4f20
+Subproject commit b56420b34277b6e257b0426eb78ecec1f1fb45fb

testing/python/language/test_tilelang_language_ternary.py

+import tilelang
+import tilelang.language as T
+import torch
+import tilelang.testing
+
+
+@tilelang.jit(out_idx=[1],)
+def tilelang_ternary(M, N, block_M, block_N, dtype="float16"):
+
+    @T.prim_func
+    def main(
+            A: T.Tensor((M, N), dtype),
+            B: T.Tensor((M, N), dtype),
+    ):
+        # Initialize Kernel Context
+        with T.Kernel(T.ceildiv(N, block_N), T.ceildiv(M, block_M), threads=128) as (bx, by):
+            for i, j in T.Parallel(block_M, block_N):
+                B[by * block_M + i, bx * block_N + j] = (
+                    A[by * block_M + i, bx * block_N + j] if (by * block_M + i) < (M // 2) else 0)
+
+    return main
+
+
+def run_tilelang_ternary(M=128, N=128, block_M=32, block_N=32, dtype="float16"):
+    kernel = tilelang_ternary(M, N, block_M, block_N, dtype)
+    a = torch.randn(M, N, device="cuda", dtype=getattr(torch, dtype))
+    b = kernel(a)
+    ref_b = torch.zeros_like(b)
+    for i in range(M):
+        for j in range(N):
+            if i < M // 2:
+                ref_b[i, j] = a[i, j]
+            else:
+                ref_b[i, j] = 0
+
+    torch.testing.assert_close(b, ref_b, rtol=1e-2, atol=1e-2)
+
+
+def test_tilelang_ternary():
+    run_tilelang_ternary(M=128, N=128, block_M=32, block_N=32)
+
+
+if __name__ == "__main__":
+    tilelang.testing.main()