code: def h2oassembly_download_mojo_inplace_pipeline():
      values = [
          [11, 12.5, "13", 14],
          [21, 22.2, "23", 24],
          [31, 32.3, "33", 34],
      ]
      frame1 = h2o.H2OFrame(
          python_obj=values,
          destination_frame="first",
          column_names=["a", "b", "c", "d"],
          column_types=["numeric", "numeric", "string", "numeric"],
      )
      frame2 = h2o.H2OFrame(
          python_obj=values,
          destination_frame="second",
          column_names=["a", "b", "c", "d"],
          column_types=["numeric", "numeric", "string", "numeric"],
      )
      assembly = H2OAssembly(
          steps=[
              ("sqrt", H2OColOp(op=H2OFrame.sqrt, col="b")),
              (
                  "minus",
                  H2OBinaryOp(
                      op=H2OFrame.__sub__, col="b", right=H2OCol("d")
                  ),
              ),
              ("abs", H2OColOp(op=H2OFrame.abs, col="b")),
              ("log", H2OColOp(op=H2OFrame.log, col="b")),
              ("select", H2OColSelect(cols="b")),
          ]
      )
  
      expected = assembly.fit(frame1)
      assert_is_type(expected, H2OFrame)
  
      results_dir = os.path.join(os.getcwd(), "results")
      file_name = "h2oassembly_download_mojo_inplace_pipeline"
      path = os.path.join(results_dir, file_name + ".mojo")
  
      mojo_file = assembly.download_mojo(file_name=file_name, path=path)
      assert os.path.exists(mojo_file)
  
      pipeline = H2OMojoPipeline(mojo_path=mojo_file)
      result = pipeline.transform(frame2)
      assert_is_type(result, H2OFrame)
  
      pyunit_utils.compare_frames(
          expected, result, expected.nrows, tol_numeric=1e-5
      )
  
imports: import sys
  from tests import pyunit_utils
  from h2o.assembly import *
  from h2o.transforms.preprocessing import *
  from h2o.pipeline import H2OMojoPipeline
label_desc: Use image node_id 1 for calling a global function with example usage: h2oassembly_download_mojo_inplace_pipeline() without return types