class_docstr: Tests that genomic metrics work as expected.
code: def create_model_for_mutagenesis(self):
      keras_model = tf.keras.Sequential(
          [
              tf.keras.layers.Conv2D(
                  1, 15, activation="relu", padding="same"
              ),
              tf.keras.layers.Conv2D(
                  1, 15, activation="relu", padding="same"
              ),
              tf.keras.layers.Flatten(),
              tf.keras.layers.Dense(1, activation="relu"),
          ]
      )
      return dc.models.KerasModel(
          keras_model, dc.models.losses.BinaryCrossEntropy()
      )
  
file_path: deepchem/deepchem/metrics/tests/test_genomics.py
imports: import unittest
  import numpy
  import deepchem
  import pytest
  from deepchem.metrics.genomic_metrics import get_motif_scores
  from deepchem.metrics.genomic_metrics import get_pssm_scores
  from deepchem.metrics.genomic_metrics import in_silico_mutagenesis
label_desc: Use image node_id 3 for calling the TestGenomicMetrics obj's underlying member method code with example usage: obj.create_model_for_mutagenesis() and returns: dc