class_docstr: An sklearn adapter for fasttext using the first object column as input.
  
  This classifier assume the X parameter for fit, predict and predict_proba
  is in all cases a pandas.DataFrame object.
  
  Parameters
  ----------
  **kwargs
      Keyword arguments will be redirected to fasttext.train_supervised.
class_docstr_tok: ["An","sklearn","adapter","for","fasttext","using","the","first","object","column","as","input",".","This","classifier","assume","the","X","parameter","for","fit",",","predict","and","predict_proba","is","in","all","cases","a","pandas.DataFrame","object",".","Parameters","--","--","--","--","--","*","*","kwargs","Keyword","arguments","will","be","redirected","to","fasttext.train_supervised","."]
code: def _input_col(self, X):
      input_col_name = None
      for col_name, dtype in X.dtypes.items():
          if dtype == object:
              input_col_name = col_name
              break
      if input_col_name is not None:
          return X[input_col_name]
      raise ValueError("No object dtype column in input param 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 1 for calling the FirstObjFtClassifier obj's underlying member method code with example usage: obj._input_col(X) and returns: X