class_docstr: An abstact base class for sklearn classifier adapters for fasttext.
  
  Parameters
  ----------
  **kwargs
      Keyword arguments will be redirected to fasttext.train_supervised.
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docstr: Predict class probabilities for X.
  
  Parameters
  ----------
  X : array-like of shape = [n_samples, n_features]
      The input samples.
  
  Returns
  -------
  p : array of shape = [n_samples, n_classes]
      The class probabilities of the input samples. The order of the
      classes corresponds to that in the attribute classes_.
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code: def predict_proba(self, X):
      """Predict class probabilities for X.
  
      Parameters
      ----------
      X : array-like of shape = [n_samples, n_features]
          The input samples.
  
      Returns
      -------
      p : array of shape = [n_samples, n_classes]
          The class probabilities of the input samples. The order of the
          classes corresponds to that in the attribute classes_.
      """
      return np.array(
          [
              self._format_probas(res)
              for res in self._predict(X, self.num_classes_)
          ],
          dtype=np.float_,
      )
  
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 15 for calling the FtClassifierABC obj's underlying member method code with example usage: obj.predict_proba(X) and returns: np