class_docstr: Dataset class for loading in-memory data.
  
  :param inputs: (numpy array)
  
  :param targets: (numpy array)
  
  :param input_transform: (transform):
      transform to apply to input sample individually
  
  :param target_transform: (transform):
      transform to apply to target sample individually
  
  :param co_transform: (transform):
      transform to apply to both input and target sample simultaneously
class_docstr_tok: ["Dataset","class","for","loading","in-memory","data",".",":","param","inputs",":","(","numpy","array",")",":","param","targets",":","(","numpy","array",")",":","param","input_transform",":","(","transform",")",":","transform","to","apply","to","input","sample","individually",":","param","target_transform",":","(","transform",")",":","transform","to","apply","to","target","sample","individually",":","param","co_transform",":","(","transform",")",":","transform","to","apply","to","both","input","and","target","sample","simultaneously"]
docstr: Index the dataset and return the input + target
docstr_tok: ["Index","the","dataset","and","return","the","input","+","target"]
code: def __getitem__(self, index):
      """
      Index the dataset and return the input + target
      """
      input_sample = [
          self.input_transform[i](self.inputs[i][index])
          for i in range(self.num_inputs)
      ]
  
      if self.has_target:
          target_sample = [
              self.target_transform[i](self.targets[i][index])
              for i in range(self.num_targets)
          ]
          # for i in range(self.min_inputs_or_targets):
          #    input_sample[i], target_sample[i] = self.co_transform[i](input_sample[i], target_sample[i])
  
          return self.input_return_processor(
              input_sample
          ), self.target_return_processor(target_sample)
      else:
          return self.input_return_processor(input_sample)
  
imports: from .BaseDataset import BaseDataset
  from .data_utils import _process_array_argument, _return_first_element_of_list, _process_transform_argument, _process_co_transform_argument, _pass_through
label_desc: Use image node_id 2 for calling the TensorDataset obj's underlying member method code with example usage: obj.__getitem__(index) and returns: self,  self, self