code: def tensors_to_df(tensors, head=None, keys=None, ax_names=None):
      dfs = [
          tensor_to_df(tensor, ax_names=ax_names) for tensor in tensors
      ]
      df = pd.concat(
          dfs, keys=(np.arange(len(tensors)) if keys is None else keys)
      )
      df.reset_index(level=0, inplace=True)
      if head is not None:
          df.rename(columns={"level_0": head}, inplace=True)
      return df
  
file_path: mmvae/src/vis.py
imports: import matplotlib.colors
  import matplotlib.pyplot
  import numpy
  import pandas
  import seaborn
  import torch
  from matplotlib.lines import Line2D
  from umap import UMAP
label_desc: Use image node_id 5 for calling a global function with example usage: tensors_to_df(tensors, head, keys, ax_names) and returns: df