class_docstr: Wrapper for fastText embeddings.
class_docstr_tok: ["Wrapper","for","fastText","embeddings","."]
docstr: Look at combination of parameters give to class
  and determine if any invalid combination or missing
  models.
code: def _check_input_params(self):
      """Look at combination of parameters give to class
      and determine if any invalid combination or missing
      models.
      """
  
      # 1. check if lang valid
      get_lang(self.iso_code)  # check if iso_code valid
  
      # 2. check if any fasttext embeddings for this lang
      if not self._is_fasttext_lang_available():
          available_embeddings_str = "', '".join(
              MAP_LANGS_CLTK_FASTTEXT.keys()
          )
          raise UnimplementedAlgorithmError(
              f"No embedding available for language '{self.iso_code}'. FastTextEmbeddings available for: '{available_embeddings_str}'."
          )
  
      # 3. check if requested model type is available for fasttext
      valid_model_types = ["bin", "vec"]
      if self.model_type not in valid_model_types:
          valid_model_types_str = "', '"
          raise CLTKException(
              f"Invalid model type '{self.model_type}'. Choose: '{valid_model_types_str}'."
          )
  
      # 4. check if requested training set is available for language for fasttext
      training_sets = ["common_crawl", "wiki"]
      if self.training_set not in training_sets:
          training_sets_str = "', '".join(training_sets)
          raise CLTKException(
              f"Invalid ``training_set`` '{self.training_set}'. Available: '{training_sets_str}'."
          )
      available_vectors = list()
      if self.training_set == "wiki":
          available_vectors = [
              "ang",
              "arb",
              "arc",
              "got",
              "lat",
              "pli",
              "san",
          ]
      elif self.training_set == "common_crawl":
          available_vectors = ["arb", "lat", "san"]
      else:
          CLTKException("Unanticipated exception.")
      if self.iso_code in available_vectors:
          pass
      else:
          available_vectors_str = "', '".join(available_vectors)
          raise CLTKException(
              f"Training set '{self.training_set}' not available for language '{self.iso_code}'. Languages available for this training set: '{available_vectors_str}'."
          )
  
imports: import os
  from typing import List
  from zipfile import ZipFile
  from gensim import models
  from cltk.core.cltk_logger import logger
  from cltk.core.exceptions import CLTKException, UnimplementedAlgorithmError
  from cltk.data.fetch import FetchCorpus
  from cltk.languages.utils import get_lang
  from cltk.utils import CLTK_DATA_DIR, get_file_with_progress_bar, query_yes_no
  from cltk.utils.file_operations import make_cltk_path
label_desc: Use image node_id 7 for calling the FastTextEmbeddings obj's underlying member method code with example usage: obj._check_input_params() without return types