code: def split_view(tensor, split_size: int, dim: int = 0):
      if dim < 0:  # Support negative indexing
          dim = len(tensor.shape) + dim
      # If not divisible by split_size, we need to pad with 0
      if tensor.shape[dim] % split_size != 0:
          to_pad = split_size - (tensor.shape[dim] % split_size)
          padding = [0] * len(tensor.shape) * 2
          padding[dim * 2 + 1] = to_pad
          padding.reverse()
          tensor = torch.nn.functional.pad(tensor, padding)
      cur_shape = tensor.shape
      new_shape = (
          cur_shape[:dim]
          + (tensor.shape[dim] // split_size, split_size)
          + cur_shape[dim + 1 :]
      )
      return tensor.reshape(*new_shape)
  
imports: from enum import Enum
  from typing import Optional, Tuple
  import librosa
  import matplotlib.pylab
  import numpy
  import torch
  from einops import rearrange
  from numba import jit, prange
  from nemo.collections.tts.torch.tts_data_types import DATA_STR2DATA_CLASS, MAIN_DATA_TYPES, WithLens
  from nemo.utils import logging
  from nemo.utils.decorators import deprecated
label_desc: Use image node_id 25 for calling a global function with example usage: split_view(tensor, split_size, dim) and returns: tensor