code: def create_overlapping_windows(batch_x):
      batch_size = tf.shape(input=batch_x)[0]
      window_width = 2 * Config.n_context + 1
      num_channels = Config.n_input
  
      # Create a constant convolution filter using an identity matrix, so that the
      # convolution returns patches of the input tensor as is, and we can create
      # overlapping windows over the MFCCs.
      eye_filter = tf.constant(
          np.eye(window_width * num_channels).reshape(
              window_width, num_channels, window_width * num_channels
          ),
          tf.float32,
      )  # pylint: disable=bad-continuation
  
      # Create overlapping windows
      batch_x = tf.nn.conv1d(
          input=batch_x, filters=eye_filter, stride=1, padding="SAME"
      )
  
      # Remove dummy depth dimension and reshape into [batch_size, n_windows, window_width, n_input]
      batch_x = tf.reshape(
          batch_x, [batch_size, -1, window_width, num_channels]
      )
  
      return batch_x
  
imports: from __future__ import absolute_import, division, print_function
  import os
  import sys
  import absl.app
  import numpy
  import progressbar
  import shutil
  import tensorflow
  import tensorflow.compat.v1
  import time
  from datetime import datetime
  from ds_ctcdecoder import ctc_beam_search_decoder, Scorer
  from .evaluate import evaluate
  from six.moves import zip, range
  from .util.config import Config, initialize_globals
  from .util.checkpoints import load_or_init_graph_for_training, load_graph_for_evaluation, reload_best_checkpoint
  from .util.evaluate_tools import save_samples_json
  from .util.feeding import create_dataset, audio_to_features, audiofile_to_features
  from .util.flags import create_flags, FLAGS
  from .util.helpers import check_ctcdecoder_version, ExceptionBox
  from .util.logging import create_progressbar, log_debug, log_error, log_info, log_progress, log_warn
  from .util.io import open_remote, remove_remote, listdir_remote, is_remote_path, isdir_remote
label_desc: Use image node_id 2 for calling a global function with example usage: create_overlapping_windows(batch_x) and returns: batch_x