import tvm def test_verify_compute(): n = tvm.var("n") m = tvm.var("m") A = tvm.placeholder((n, m), name='A') k = tvm.reduce_axis((0, m), "k") k_ = tvm.reduce_axis((0, m-1), "k_") f1 = lambda i: tvm.sum(A[i, k], axis=k) f2 = lambda i: A[i,0] + 1 f3 = lambda i: tvm.sum(A[i, k], axis=k) + 1 f4 = lambda i: A[i,0] * (tvm.sum(A[i, k], axis=k) + 1) f5 = lambda i: (tvm.sum(A[i, k], axis=k), A[i,0] + 1) f6 = lambda i: (tvm.sum(A[i, k], axis=k), tvm.sum(A[i, k_], axis=k_)) # # Valid compute try: B = tvm.compute((n,), f1, name="B") except tvm._ffi.base.TVMError as ex: assert False # # Valid compute try: B = tvm.compute((n,), f2, name="B") except tvm._ffi.base.TVMError as ex: assert False # # Invalid compute with non top level reduction try: B = tvm.compute((n,), f3, name="B") assert False except tvm._ffi.base.TVMError as ex: pass # # Invalid compute with non top level reduction try: B = tvm.compute((n,), f4, name="B") assert False except tvm._ffi.base.TVMError as ex: pass # # Invalid compute with reduction and non-reduction batch ops try: B0, B1 = tvm.compute((n,), f5, name="B") assert False except tvm._ffi.base.TVMError as ex: pass # # Invalid compute with unequal batch reduction ops try: B0, B1 = tvm.compute((n,), f6, name="B") assert False except tvm._ffi.base.TVMError as ex: pass if __name__ == "__main__": test_verify_compute()