docstr: Returns the input ids for the text feature input.
docstr_tok: ["Returns","the","input","ids","for","the","text","feature","input","."]
code: def get_input_ids(
      self,
      inputs: Union[
          Dict[str, torch.Tensor],
          Dict[str, np.ndarray],
          Tuple[Dict[str, torch.Tensor], Dict[str, torch.Tensor]],
      ],
  ) -> torch.Tensor:
      """Returns the input ids for the text feature input."""
      return inputs[self.config_obj.input_features[0].name].type(
          torch.int32
      )
  
imports: import contextlib
  import logging
  import os
  from typing import Any, Dict, List, Optional, Tuple, Union
  import numpy
  import torch
  from transformers import AutoConfig, GenerationConfig
  from ludwig.accounting.used_tokens import get_used_tokens_for_llm
  from ludwig.constants import IGNORE_INDEX_TOKEN_ID, LOGITS, MODEL_LLM, PREDICTIONS, TEXT, USED_TOKENS
  from ludwig.features.base_feature import ModuleWrapper, OutputFeature
  from ludwig.features.feature_utils import LudwigFeatureDict
  from ludwig.features.text_feature import TextOutputFeature
  from ludwig.globals import MODEL_WEIGHTS_FILE_NAME
  from ludwig.models.base import BaseModel
  from ludwig.modules.training_hooks import NEFTuneHook
  from ludwig.schema.features.base import BaseOutputFeatureConfig, FeatureCollection
  from ludwig.schema.model_types.llm import LLMModelConfig
  from ludwig.utils.augmentation_utils import AugmentationPipelines
  from ludwig.utils.data_utils import clear_data_cache
  from ludwig.utils.llm_quantization_utils import convert_quantized_linear_to_linear
  from ludwig.utils.llm_utils import add_left_padding, generate_merged_ids, get_context_len, get_realigned_target_and_prediction_tensors_for_inference, initialize_adapter, load_pretrained_from_config, pad_target_tensor_for_fine_tuning, remove_left_padding, to_device
  from ludwig.utils.logging_utils import log_once
  from ludwig.utils.output_feature_utils import set_output_feature_tensor
  from ludwig.utils.tokenizers import HFTokenizer
  from ludwig.utils.torch_utils import reg_loss
label_desc: Use image node_id 17 for calling the LLM obj's underlying member method code with example usage: obj.get_input_ids(inputs) and returns: inputs