code: def pandas_input(request):
      dtype = request.param
      rng = np.random.default_rng()
      size = 100
  
      def random_ints(dtype, size):
          dtype_min = np.iinfo(dtype).min
          dtype_max = np.iinfo(dtype).max
          return rng.integers(
              dtype_min, dtype_max, size=size, dtype=dtype
          )
  
      try:
          dtype = np.dtype(dtype)
      except TypeError:
          if dtype == "category":
              data = random_ints(np.int64, size)
          else:
              raise
      else:
          if dtype.kind == "b":
              data = rng.choice([False, True], size=size)
          elif dtype.kind in ("m", "M"):
              # datetime or timedelta
              data = random_ints(np.int64, size)
          elif dtype.kind == "U":
              # Unicode strings of integers like "12345"
              data = random_ints(np.int64, size).astype(dtype.str)
          elif dtype.kind == "f":
              # floats in [0.0, 1.0)
              data = rng.random(size=size, dtype=dtype)
          else:
              data = random_ints(dtype, size)
      return pd.Series(data, dtype=dtype)
  
imports: import cupy
  import numpy
  import pandas
  import pyarrow
  import pytest
  import cudf
  from cudf._lib.transform import mask_to_bools
  from cudf.core.column.column import as_column
  from cudf.testing._utils import assert_eq, assert_exceptions_equal
  from cudf.utils import dtypes
label_desc: Use image node_id 1 for calling a global function with example usage: pandas_input(request) and returns: pd, rng