class_docstr: Class for text vectorization by pretrained embeddings
  model_name can be selected from https://github.com/RaRe-Technologies/gensim-data
code: def __init__(self, params: Optional[OperationParameters]):
      super().__init__(params)
      self.logger = default_log(prefix="FEDOT logger")
      self._download_model_resources()
  
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 1 to create a new PretrainedEmbeddingsImplementation object from inherited base classes: DataOperationImplementation with example: obj = PretrainedEmbeddingsImplementation(params)