code: def test_text_embedding(embedding_method):
      """Assert that text columns are embedded."""
      data = pycaret.datasets.get_data("spx")
      pc = pycaret.regression.setup(
          data=data.iloc[:50, :],  # Less rows for faster processing
          text_features=["text"],
          text_features_method=embedding_method,
      )
      X, _ = pc.pipeline.transform(pc.X, pc.y)
      assert X.shape[1] > 50
  
imports: import io
  import numpy
  import pandas
  import pytest
  from imblearn.over_sampling import ADASYN
  from scipy.sparse import csr_matrix
  from sklearn.decomposition import PCA
  from sklearn.ensemble import RandomForestClassifier
  from sklearn.pipeline import Pipeline
  from sklearn.preprocessing import StandardScaler
  import pycaret.classification
  import pycaret.datasets
  import pycaret.regression
label_desc: Use image node_id 23 for calling a global function with example usage: test_text_embedding(embedding_method) without return types