code: def plot_sequence_filters(dnn):
      fig = plt.figure(figsize=(15, 8))
      fig.subplots_adjust(hspace=0.1, wspace=0.1)
      conv_filters = dnn.get_sequence_filters()
      num_plots_per_axis = int(len(conv_filters) ** 0.5) + 1
      for i, conv_filter in enumerate(conv_filters):
          ax = fig.add_subplot(
              num_plots_per_axis, num_plots_per_axis, i + 1
          )
          add_letters_to_axis(ax, conv_filter.T)
          ax.axis("off")
          ax.set_title("Filter %s" % (str(i + 1)))
  
file_path: deepchem/contrib/dragonn/tutorial_utils.py
imports: from __future__ import division
  import random
  import inspect
  from collections import namedtuple, defaultdict, OrderedDict
  import numpy
  from sklearn.model_selection import train_test_split
  import simulations
  from simdna.synthetic import StringEmbeddable
  from utils import get_motif_scores, one_hot_encode
  from models import SequenceDNN
  from dragonn.plot import add_letters_to_axis, plot_motif
  import matplotlib.pyplot
  from matplotlib.lines import Line2D
label_desc: Use image node_id 4 for calling a global function with example usage: plot_sequence_filters(dnn) without return types