docstr: Class doesn't support fit operation
  
  :param train_data: data with features, target and ids to process
docstr_tok: ["Class","does","n't","support","fit","operation",":","param","train_data",":","data","with","features",",","target","and","ids","to","process"]
code: def fit(self, train_data: InputData):
      """Class doesn't support fit operation
  
      :param train_data: data with features, target and ids to process
      """
      with ImplementationRandomStateHandler(
          implementation=self.vectorizer
      ):
          self.vectorizer.fit(train_data)
      return self.vectorizer
  
imports: import warnings
  from typing import Optional
  import numpy
  from sklearn.feature_extraction.text import CountVectorizer, TfidfVectorizer
  from fedot.core.data.data import InputData, OutputData
  from fedot.core.operations.evaluation.evaluation_interfaces import EvaluationStrategy
  from fedot.core.operations.evaluation.operation_implementations.data_operations.text_preprocessing import TextCleanImplementation
  from fedot.core.operations.evaluation.operation_implementations.data_operations.text_pretrained import PretrainedEmbeddingsImplementation
  from fedot.core.operations.operation_parameters import OperationParameters
  from fedot.utilities.random import ImplementationRandomStateHandler
label_desc: Use image node_id 2 for calling the GensimTextVectorizeStrategy obj's underlying member method code with example usage: obj.fit(train_data) and returns: self