[BUG] - cuML LabelEncoder is 200x slower with cuDF-Pandas vs cuDF

[cdeotte]

Describe the bug
When Label Encoding a column of strings, if we input a cuDF-Pandas dataframe then cuML Label Encoder is 200x slower than inputting a pure cuDF dataframe

Steps/Code to reproduce bug

%load_ext cudf.pandas

from time import time
import random, string
import pandas as pd, numpy as np, cudf
from cuml.preprocessing import LabelEncoder

def generate_unique_strings(count, length):
    chars = string.ascii_letters + string.digits
    unique_strings = set()

    while len(unique_strings) < count:
        new_string = ''.join(random.choices(chars, k=length))
        unique_strings.add(new_string)

    return list(unique_strings)

unique_strings = generate_unique_strings(1000, 13)
strings = np.random.choice(unique_strings,1_000_000,replace=True)

df_cudf_pandas = pd.DataFrame(strings)
LE = LabelEncoder()
start = time()
df_cudf_pandas[0] = LE.fit_transform(df_cudf_pandas[0])
elapsed_cudf_pandas = time()-start
print(f"cuML Label Encoder with cuDF-Pandas took {elapsed_cudf_pandas:.5f} seconds")

df_cudf = cudf.DataFrame(strings)
LE = LabelEncoder()
start = time()
df_cudf[0] = LE.fit_transform(df_cudf[0])
elapsed_cudf = time()-start
print(f"cuML Label Encoder with pure cuDF took {elapsed_cudf:.5f} seconds")

slowdown = elapsed_cudf_pandas / elapsed_cudf
print(f"cuML Label Encoder is slowdowned by a factor of {slowdown:.0f}x using cuDF-Pandas")

Expected behavior
We would expect cuDF-Pandas to have same speed as pure cuDF. Not 200x slower.

Environment details (please complete the following information):
RAPIDS 24.12