Fix binarize. (Reported in ⁠#286)

PiperOrigin-RevId: 303875906

deepvariant/modeling.py

@@ -117,18 +117,19 @@ class UnsupportedImageDimensionsError(Exception):
 def binarize(labels, target_class):
   """Binarize labels and predictions.
 
-  The labels that are not equal to target_class parameter are set to zero.
+  The labels that are equal to target_class parameter are set to 0, else
+  set to 1.
 
   Args:
     labels: the ground-truth labels for the examples.
-    target_class: index of the class that is left as non-zero.
+    target_class: index of the class that is left as zero.
 
   Returns:
     Tensor of the same shape as labels.
   """
   labels_binary = tf.compat.v1.where(
       tf.equal(labels, tf.constant(target_class, dtype=tf.int64)),
-      tf.zeros_like(labels), labels)
+      tf.zeros_like(labels), tf.ones_like(labels))
   return labels_binary
 
 

deepvariant/modeling_test.py

@@ -98,6 +98,17 @@ def _run(tensor_to_run):
             modeling.is_encoded_variant_type(
                 tensor, tf_utils.EncodedVariantType.INDEL)), [False, True] * 4)
 
+  @parameterized.parameters(
+      dict(labels=[0, 2, 1, 0], target_class=0, expected=[0, 1, 1, 0]),
+      dict(labels=[0, 2, 1, 0], target_class=1, expected=[1, 1, 0, 1]),
+      dict(labels=[0, 2, 1, 0], target_class=2, expected=[1, 0, 1, 1]),
+  )
+  def test_binarize(self, labels, target_class, expected):
+    with self.test_session() as sess:
+      result = sess.run(
+          modeling.binarize(np.array(labels), np.array(target_class)))
+      self.assertListEqual(result.tolist(), expected)
+
   @parameterized.parameters([True, False])
   def test_eval_metric_fn(self, include_variant_types):
     labels = tf.constant([1, 0], dtype=tf.int64)