class_docstr: An abstact base class for sklearn classifier adapters for fasttext.
  
  Parameters
  ----------
  **kwargs
      Keyword arguments will be redirected to fasttext.train_supervised.
class_docstr_tok: ["An","abstact","base","class","for","sklearn","classifier","adapters","for","fasttext",".","Parameters","--","--","--","--","--","*","*","kwargs","Keyword","arguments","will","be","redirected","to","fasttext.train_supervised","."]
code: def _validate_x(X):
      try:
          if len(X.shape) != 2:
              raise ValueError(
                  "FastTextClassifier methods must get a two-dimensional "
                  "numpy array (or castable) as the X parameter."
              )
          return X
      except AttributeError:
          return FtClassifierABC._validate_x(np.array(X))
  
imports: import os
  import abc
  import numpy
  from fasttext import train_supervised
  from sklearn.base import BaseEstimator, ClassifierMixin
  from sklearn.utils.multiclass import unique_labels
  from sklearn.exceptions import NotFittedError
  from .util import temp_dataset_fpath, dump_xy_to_fasttext_format, python_fasttext_model_to_bytes, bytes_to_python_fasttext_model
label_desc: Use image node_id 5 for calling the FtClassifierABC obj's underlying member method code with example usage: obj._validate_x(X) and returns: X, FtClassifierABC