class_docstr: Test template inputs and pre-processing (ensure the correct exceptions are thrown for the inputs)
class_docstr_tok: ["Test","template","inputs","and","pre-processing","(","ensure","the","correct","exceptions","are","thrown","for","the","inputs",")"]
docstr: Verifies that a warning is raised if n_wires doesn't correspond to n_block_wires.
docstr_tok: ["Verifies","that","a","warning","is","raised","if","n_wires","does","n't","correspond","to","n_block_wires","."]
code: def test_warning_many_wires(self):
      """Verifies that a warning is raised if n_wires doesn't correspond to n_block_wires."""
  
      n_block_wires = 4
      wires = [1, 2, 3, 4, 5]
      n_wires = len(wires)
      n_params_block = 1
      with pytest.warns(
          Warning,
          match=f"The number of wires should be n_block_wires times 2\\^n; "
          f"got n_wires/n_block_wires = {n_wires/n_block_wires}",
      ):
          TTN(
              wires,
              n_block_wires,
              block=None,
              n_params_block=n_params_block,
          )
  
imports: import pytest
  import numpy
  import pennylane
  from pennylane.templates.tensornetworks.ttn import compute_indices, TTN
label_desc: Use image node_id 2 for calling the TestTemplateInputs obj's underlying member method code with example usage: obj.test_warning_many_wires() without return types