class_docstr: Wrapper for Word2Vec embeddings. Note: For models
  provided by fastText, use class ``FastTextEmbeddings``.
class_docstr_tok: ["Wrapper","for","Word2Vec","embeddings",".","Note",":","For","models","provided","by","fastText",",","use","class","``","FastTextEmbeddings","``","."]
docstr: Confirm that input parameters are valid and in a
  valid configuration.
code: def _check_input_params(self) -> None:
      """Confirm that input parameters are valid and in a
      valid configuration.
      """
      # 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 self.iso_code not in MAP_NLPL_LANG_TO_URL:
          available_embeddings_str = "', '".join(
              MAP_NLPL_LANG_TO_URL.keys()
          )
          raise UnimplementedAlgorithmError(
              f"No embedding available for language '{self.iso_code}'. "
              f"Word2Vec models available for: '{available_embeddings_str}'."
          )
  
      # 3. assert that model type is valid
      valid_types = ["bin", "txt"]
      if self.model_type not in valid_types:
          unavailable_types_str = "', '".join(valid_types)
          raise ValueError(
              f"Invalid ``model_type`` {self.model_type}. Valid model types: {unavailable_types_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 5 for calling the Word2VecEmbeddings obj's underlying member method code with example usage: obj._check_input_params() without return types