code: def visualize_qualitative_analysis(
      inputs, model, samples=1, batch_size=3, length=8
  ):
      """Visualizes a qualitative analysis of a given model.
  
      Args:
        inputs: A tensor of the original inputs, of shape [batch, timesteps,
          h, w, c].
        model: A DisentangledSequentialVAE model.
        samples: Number of samples to draw from the latent distributions.
        batch_size: Number of sequences to generate.
        length: Number of timesteps to generate for each sequence.
      """
      average = lambda dist: tf1.reduce_mean(
          input_tensor=dist.mean(), axis=0
      )  # avg over samples
      with tf1.name_scope("val_reconstruction"):
          reconstruct = functools.partial(
              model.reconstruct, inputs=inputs, samples=samples
          )
          visualize_reconstruction(inputs, average(reconstruct()))
          visualize_reconstruction(
              inputs,
              average(reconstruct(sample_static=True)),
              name="static_prior",
          )
          visualize_reconstruction(
              inputs,
              average(reconstruct(sample_dynamic=True)),
              name="dynamic_prior",
          )
          visualize_reconstruction(
              inputs,
              average(reconstruct(swap_static=True)),
              name="swap_static",
          )
          visualize_reconstruction(
              inputs,
              average(reconstruct(swap_dynamic=True)),
              name="swap_dynamic",
          )
  
      with tf1.name_scope("generation"):
          generate = functools.partial(
              model.generate,
              batch_size=batch_size,
              length=length,
              samples=samples,
          )
          image_summary(
              average(generate(fix_static=True)), "fix_static"
          )
          image_summary(
              average(generate(fix_dynamic=True)), "fix_dynamic"
          )
  
imports: from datetime import datetime
  import functools
  from absl import app
  from absl import flags
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  import tensorflow_probability
  from tensorflow_probability.examples import sprites_dataset
  from tensorflow_probability.python.internal import tf_keras
label_desc: Use image node_id 3 for calling a global function with example usage: visualize_qualitative_analysis(inputs, model, samples, batch_size, length) without return types