class_docstr: The ``TextEmbedder`` is a :class:`~flash.Task` for generating sentence embeddings, training and validation. For
  more details, see `embeddings`.
  
  You can change the backbone to any question answering model from `UKPLab/sentence-transformers
  <https://github.com/UKPLab/sentence-transformers>`_ using the ``backbone``
  argument.
  
  Args:
      backbone: backbone model to use for the task.
      enable_ort: Enable Torch ONNX Runtime Optimization: https://onnxruntime.ai/docs/#onnx-runtime-for-training
code: def validation_step(self, batch: Any, batch_idx: int) -> Any:
      raise NotImplementedError(
          "Validating a `TextEmbedder` is not supported. Use a different text task instead."
      )
  
imports: import logging
  import os
  import warnings
  from typing import Any, Dict, List, Optional
  import torch
  from pytorch_lightning import Callback
  from torch import Tensor
  from flash.core.model import Task
  from flash.core.registry import FlashRegistry, print_provider_info
  from flash.core.utilities.imports import _TOPIC_TEXT_AVAILABLE
  from flash.core.utilities.providers import _SENTENCE_TRANSFORMERS
  from flash.text.classification.collate import TextClassificationCollate
  from flash.text.embedding.backbones import HUGGINGFACE_BACKBONES
  from flash.text.ort_callback import ORTCallback
label_desc: Use image node_id 3 for calling the TextEmbedder obj's underlying member method code with example usage: obj.validation_step(batch, batch_idx) without return types