[Bugfix] Fix a bug for simplifier (#425)

* Update submodule 'tvm' to latest commit f4a8f9b

* lint fix

tvm @ b16c9f29

-Subproject commit b2945254932cffa89922ec7f6e868d726aed0f6a
+Subproject commit b16c9f298bc37fa502ffdb2ea809c2793e2a0bd6

testing/python/language/test_tilelang_language_copy.py

+import tilelang
+import tilelang.language as T
+import torch
+
+
+def tilelang_copy(M, N, block_M, block_N, dtype="float16"):
+    # add decorator @tilelang.jit if you want to return a torch function
+    @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]
+
+    return main
+
+
+def run_tilelang_copy(M=1024, N=1024, block_M=128, block_N=128, dtype="float16"):
+    program = tilelang_copy(M, N, block_M, block_N, dtype)
+    kernel = tilelang.compile(
+        program,
+        out_idx=[1],
+        target="cuda",
+        pass_configs={
+            "tl.disable_warp_specialized": True,
+            "tl.disable_tma_lower": True
+        })
+    a = torch.randn(M, N, device="cuda", dtype=getattr(torch, dtype))
+    b = kernel(a)
+    torch.testing.assert_close(b, a, rtol=1e-2, atol=1e-2)
+
+
+def test_tilelang_copy():
+    run_tilelang_copy(M=1024, N=1024, block_M=128, block_N=128)
+    run_tilelang_copy(M=1024, N=576, block_M=32, block_N=576)
+    run_tilelang_copy(M=1024, N=576, block_M=32, block_N=576, dtype="float")
+
+
+if __name__ == "__main__":
+    tilelang.testing.main()