class_docstr: Class for text vectorization by pretrained embeddings
  model_name can be selected from https://github.com/RaRe-Technologies/gensim-data
docstr: Method converts text to an average of token vectors
  
  :param text: str with text data
  :param embeddings: gensim pretrained embeddings
  :return features: one-dimensional np.array with numbers
docstr_tok: ["Method","converts","text","to","an","average","of","token","vectors",":","param","text",":","str","with","text","data",":","param","embeddings",":","gensim","pretrained","embeddings",":","return","features",":","one-dimensional","np.array","with","numbers"]
code: def vectorize_avg(text: str, embeddings):
      """Method converts text to an average of token vectors
  
      :param text: str with text data
      :param embeddings: gensim pretrained embeddings
      :return features: one-dimensional np.array with numbers
      """
      embedding_dim = embeddings.vectors.shape[1]
      features = np.zeros([embedding_dim], dtype="float32")
      num_words = 0
  
      for word in text.split():
          if word in embeddings:
              features += embeddings[f"{word}"]
              num_words += 1
  
      if num_words > 0:
          return features / num_words
      return features
  
file_path: FEDOT/fedot/core/operations/evaluation/operation_implementations/data_operations/text_pretrained.py
imports: import os
  from typing import Optional
  import numpy
  from golem.core.log import default_log
  from golem.utilities.requirements_notificator import warn_requirement
  from fedot.core.data.data import InputData, OutputData
  from fedot.core.operations.evaluation.operation_implementations.implementation_interfaces import DataOperationImplementation
  from fedot.core.operations.operation_parameters import OperationParameters
  from fedot.core.repository.dataset_types import DataTypesEnum
label_desc: Use image node_id 4 for calling the PretrainedEmbeddingsImplementation obj's underlying member method code with example usage: obj.vectorize_avg(text, embeddings) and returns: features, unknown