class_docstr: An sklearn classifier adapter for fasttext using the a pandas Series.
  
  Parameters
  ----------
  **kwargs
      Additional keyword arguments will be redirected to
      fasttext.train_supervised.
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docstr: Fits the classifier
  
  Parameters
  ----------
  X : pd.Series
      The training input samples.
  y : array-like, shape = [n_samples]
      The target values. An array of int.
  X_validation : pd.Series
      The validation input samples.
  y_validation : array-like, shape = [n_samples]
      The validation target values. An array of int.
  
  Returns
  -------
  self : object
      Returns self.
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code: def fit(self, X, y, X_validation=None, y_validation=None):
      """Fits the classifier
  
      Parameters
      ----------
      X : pd.Series
          The training input samples.
      y : array-like, shape = [n_samples]
          The target values. An array of int.
      X_validation : pd.Series
          The validation input samples.
      y_validation : array-like, shape = [n_samples]
          The validation target values. An array of int.
  
      Returns
      -------
      self : object
          Returns self.
      """
      # Check that X and y have correct shape
      try:
          input_col = X.values
      except AttributeError:
          input_col = X
      y = self._validate_y(y)
      if X_validation is not None:
          try:
              input_col_validation = X_validation.values
          except AttributeError:
              input_col_validation = X_validation
          y_validation = self._validate_y(y_validation)
      else:
          input_col_validation = None
      return self._fit_input_col(
          input_col, y, input_col_validation, y_validation
      )
  
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 3 for calling the SeriesFtClassifier obj's underlying member method code with example usage: obj.fit(X, y, X_validation, y_validation) and returns: self