code: def _general_transpose_helper(draw):
      dims = draw(st.integers(1, 3))
      padding = (
          st.sampled_from(["SAME", "VALID"]) if dims != 2 else None
      )
      x_f_d_df = draw(
          _x_and_filters(
              dim=dims,
              general=True,
              transpose=True,
              bias=True,
              padding=padding,
          )
      )
      return dims, x_f_d_df
  
imports: from hypothesis import strategies, assume
  import ivy
  import numpy
  import ivy_tests.test_ivy.helpers
  from ivy_tests.test_ivy.helpers import handle_test
  from ivy.functional.ivy.layers import _deconv_length, _pack_padded_sequence
label_desc: Use image node_id 3 for calling a global function with example usage: _general_transpose_helper(draw) and returns: dims,  x_f_d_df