code: def test_lstm_forecaster_xshard_input(self):
      from bigdl.orca import init_orca_context, stop_orca_context
  
      train_data, val_data, test_data = create_data()
      print("original", train_data[0].dtype)
      init_orca_context(cores=4, memory="2g")
      from bigdl.orca.data import XShards
  
      def transform_to_dict(data):
          return {"x": data[0], "y": data[1]}
  
      def transform_to_dict_x(data):
          return {"x": data[0]}
  
      train_data = XShards.partition(train_data).transform_shard(
          transform_to_dict
      )
      val_data = XShards.partition(val_data).transform_shard(
          transform_to_dict
      )
      test_data = XShards.partition(test_data).transform_shard(
          transform_to_dict_x
      )
      for distributed in [True, False]:
          forecaster = LSTMForecaster(
              past_seq_len=24,
              input_feature_num=2,
              output_feature_num=2,
              loss="mae",
              lr=0.01,
              distributed=distributed,
          )
          forecaster.fit(train_data, epochs=2)
          distributed_pred = forecaster.predict(
              test_data, acceleration=False
          )
          distributed_eval = forecaster.evaluate(
              val_data, acceleration=False
          )
      stop_orca_context()
  
imports: import numpy
  import tempfile
  import os
  from bigdl.chronos.utils import LazyImport
  from unittest import TestCase
  import pytest
  from ..None import op_torch, op_distributed, op_inference, op_automl
label_desc: Use image node_id 16 for calling the TestChronosModelLSTMForecaster obj's underlying member method code with example usage: obj.test_lstm_forecaster_xshard_input() and returns: dict, dict