Swaps order of input/label arguments for weighted_cross_entropy_with_logits

Change: 141569831

tensorflow/python/ops/nn_impl.py

@@ -164,7 +164,7 @@ def sigmoid_cross_entropy_with_logits(logits, targets, name=None):
                         name=name)
 
 
-def weighted_cross_entropy_with_logits(logits, targets, pos_weight, name=None):
+def weighted_cross_entropy_with_logits(targets, logits, pos_weight, name=None):
   """Computes a weighted cross entropy.
 
   This is like `sigmoid_cross_entropy_with_logits()` except that `pos_weight`,
@@ -198,8 +198,8 @@ def weighted_cross_entropy_with_logits(logits, targets, pos_weight, name=None):
   `logits` and `targets` must have the same type and shape.
 
   Args:
-    logits: A `Tensor` of type `float32` or `float64`.
     targets: A `Tensor` of the same type and shape as `logits`.
+    logits: A `Tensor` of type `float32` or `float64`.
     pos_weight: A coefficient to use on the positive examples.
     name: A name for the operation (optional).
 

tensorflow/python/ops/nn_xent_test.py

@@ -119,7 +119,7 @@ class WeightedCrossEntropyTest(tf.test.TestCase):
   def testConstructionNamed(self):
     with self.test_session():
       logits, targets, pos_weight, _ = self._Inputs()
-      loss = tf.nn.weighted_cross_entropy_with_logits(logits, targets,
+      loss = tf.nn.weighted_cross_entropy_with_logits(targets, logits,
                                                       pos_weight, name="mybce")
     self.assertEqual("mybce", loss.op.name)
 
@@ -127,7 +127,7 @@ class WeightedCrossEntropyTest(tf.test.TestCase):
     for use_gpu in [True, False]:
       with self.test_session(use_gpu=use_gpu):
         logits, targets, pos_weight, losses = self._Inputs(dtype=tf.float32)
-        loss = tf.nn.weighted_cross_entropy_with_logits(logits, targets,
+        loss = tf.nn.weighted_cross_entropy_with_logits(targets, logits,
                                                         pos_weight)
         np_loss = np.array(losses).astype(np.float32)
         tf_loss = loss.eval()
@@ -138,7 +138,7 @@ class WeightedCrossEntropyTest(tf.test.TestCase):
       with self.test_session(use_gpu=use_gpu):
         logits, targets, pos_weight, losses = self._Inputs(dtype=tf.float32,
                                                            sizes=[2, 2, 2])
-        loss = tf.nn.weighted_cross_entropy_with_logits(logits, targets,
+        loss = tf.nn.weighted_cross_entropy_with_logits(targets, logits,
                                                         pos_weight)
         np_loss = np.array(losses).astype(np.float32)
         tf_loss = loss.eval()
@@ -148,7 +148,7 @@ class WeightedCrossEntropyTest(tf.test.TestCase):
     sizes = [4, 2]
     with self.test_session():
       logits, targets, pos_weight, _ = self._Inputs(sizes=sizes)
-      loss = tf.nn.weighted_cross_entropy_with_logits(logits, targets,
+      loss = tf.nn.weighted_cross_entropy_with_logits(targets, logits,
                                                       pos_weight)
       err = tf.test.compute_gradient_error(logits, sizes, loss, sizes)
     print("logistic loss gradient err = ", err)
@@ -156,7 +156,7 @@ class WeightedCrossEntropyTest(tf.test.TestCase):
 
   def testShapeError(self):
     with self.assertRaisesRegexp(ValueError, "must have the same shape"):
-      tf.nn.weighted_cross_entropy_with_logits([[2, 1]], [1, 2, 3], 2.0)
+      tf.nn.weighted_cross_entropy_with_logits([1, 2, 3], [[2, 1]], 2.0)
 
 
 if __name__ == "__main__":