code: def test_tensor():
      m = te.size_var("m")
      n = te.size_var("n")
      l = te.size_var("l")
      A = te.placeholder((m, l), name="A")
      B = te.placeholder((n, l), name="B")
      T = te.compute((m, n, l), lambda i, j, k: A[i, k] * B[j, k])
      print(T)
      print(T.op.body)
      assert tuple(T.shape) == (m, n, l)
      assert isinstance(A.op, tvm.te.PlaceholderOp)
      assert A == A
      assert T.op.output(0) == T
      assert T.op.output(0).__hash__() == T.__hash__()
      d = {T.op.output(0): 1}
      assert d[T] == 1
      assert T[0][0][0].astype("float16").dtype == "float16"
  
imports: import numpy
  import tvm
  import tvm.testing
  from tvm import te
  from tvm.topi.nn.pooling import pool2d
label_desc: Use image node_id 1 for calling a global function with example usage: test_tensor() without return types