class_docstr: A nn.Module subclass that wraps the inference preprocessor, predictor, and postprocessor.
class_docstr_tok: ["A","nn.Module","subclass","that","wraps","the","inference","preprocessor",",","predictor",",","and","postprocessor","."]
code: def forward(
      self, inputs: Dict[str, TorchscriptPreprocessingInput]
  ) -> Dict[str, Dict[str, Any]]:
      preproc_inputs: Dict[
          str, torch.Tensor
      ] = self.preprocessor_forward(inputs)
      predictions_flattened: Dict[
          str, torch.Tensor
      ] = self.predictor_forward(preproc_inputs)
      postproc_outputs: Dict[
          str, Dict[str, Any]
      ] = self.postprocessor_forward(predictions_flattened)
      return postproc_outputs
  
imports: import logging
  import os
  from typing import Any, Dict, Optional, TYPE_CHECKING, Union
  import pandas
  import torch
  from torch import nn
  from ludwig.constants import NAME, POSTPROCESSOR, PREDICTOR, PREPROCESSOR, TYPE
  from ludwig.data.postprocessing import convert_dict_to_df
  from ludwig.data.preprocessing import load_metadata
  from ludwig.features.feature_registries import get_input_type_registry
  from ludwig.features.feature_utils import get_module_dict_key_from_name, get_name_from_module_dict_key
  from ludwig.globals import MODEL_HYPERPARAMETERS_FILE_NAME, TRAIN_SET_METADATA_FILE_NAME
  from ludwig.types import ModelConfigDict, TrainingSetMetadataDict
  from ludwig.utils import output_feature_utils
  from ludwig.utils.data_utils import load_json, save_json
  from ludwig.utils.inference_utils import get_filename_from_stage, to_inference_module_input_from_dataframe
  from ludwig.utils.misc_utils import get_from_registry
  from ludwig.utils.output_feature_utils import get_feature_name_from_concat_name, get_tensor_name_from_concat_name
  from ludwig.utils.torch_utils import DEVICE
  from ludwig.utils.types import TorchDevice, TorchscriptPreprocessingInput
label_desc: Use image node_id 5 for calling the InferenceModule obj's underlying member method code with example usage: obj.forward(inputs) and returns: postproc_outputs