class_docstr: 2-d buffers are flattened to 1-d
class_docstr_tok: ["2-d","buffers","are","flattened","to","1-d"]
code: def expected(
      input_A: T.Buffer((16, 16), "float32"),
      input_C: T.Buffer((16, 16), "float32"),
  ):
      A = T.Buffer(256, dtype="float32", data=input_A.data)
      C = T.Buffer(256, dtype="float32", data=input_C.data)
      for i in T.serial(0, 16):
          B_new_data = T.allocate([16], "float32", scope="global")
          B_new = T.Buffer(
              [16], "float32", scope="global", data=B_new_data
          )
          for j in T.serial(0, 16):
              B_new[j] = A[((i * 16) + j)] + 1.0
          for j in T.serial(0, 16):
              C[((i * 16) + j)] = B_new[j] * 2.0
  
imports: import tvm
  import tvm.testing
  from tvm import te
  from tvm.script import tir
label_desc: Use image node_id 2 for calling the TestElementwise obj's underlying member method code with example usage: obj.expected(input_A, input_C) without return types