Use a division directly instead of multiplying by the inverse. Also use the rsqrt operation instead of taking the inverse of the square root.

Change: 128859647

4 files changed, 5 insertions, 6 deletions

diff --git a/tensorflow/contrib/layers/python/layers/layers_test.py b/tensorflow/contrib/layers/python/layers/layers_test.py
index 9c9cfe4c99..4d84989405 100644
--- a/tensorflow/contrib/layers/python/layers/layers_test.py
+++ b/tensorflow/contrib/layers/python/layers/layers_test.py
@@ -818,7 +818,7 @@ class DropoutTest(tf.test.TestCase):
     with self.test_session():
       images = np.random.uniform(size=(5, height, width, 3))
       output = tf.contrib.layers.dropout(images)
-      self.assertEquals(output.op.name, 'Dropout/dropout/mul_1')
+      self.assertEquals(output.op.name, 'Dropout/dropout/mul')
       output.get_shape().assert_is_compatible_with(
           tf.convert_to_tensor(images).get_shape())
 
@@ -828,7 +828,7 @@ class DropoutTest(tf.test.TestCase):
       is_training = tf.constant(True)
       images = tf.random_uniform((5, height, width, 3), seed=1)
       output = tf.contrib.layers.dropout(images, is_training=is_training)
-      self.assertEquals(output.op.name, 'Dropout/dropout/mul_1')
+      self.assertEquals(output.op.name, 'Dropout/dropout/mul')
       output.get_shape().assert_is_compatible_with(images.get_shape())
 
   def testCreateDropoutWithConstantFalse(self):
diff --git a/tensorflow/python/ops/image_ops.py b/tensorflow/python/ops/image_ops.py
index f63cf81247..abed6b5777 100644
--- a/tensorflow/python/ops/image_ops.py
+++ b/tensorflow/python/ops/image_ops.py
@@ -846,8 +846,7 @@ def per_image_whitening(image):
   stddev = math_ops.sqrt(variance)
 
   # Apply a minimum normalization that protects us against uniform images.
-  min_stddev = math_ops.inv(
-      math_ops.sqrt(math_ops.cast(num_pixels, dtypes.float32)))
+  min_stddev = math_ops.rsqrt(math_ops.cast(num_pixels, dtypes.float32))
   pixel_value_scale = math_ops.maximum(stddev, min_stddev)
   pixel_value_offset = image_mean
 
diff --git a/tensorflow/python/ops/math_grad.py b/tensorflow/python/ops/math_grad.py
index 0620a3da2c..2331f21d47 100644
--- a/tensorflow/python/ops/math_grad.py
+++ b/tensorflow/python/ops/math_grad.py
@@ -161,7 +161,7 @@ def _SegmentMeanGrad(op, grad):
           array_ops.fill(array_ops.expand_dims(input_rank - 1, 0), 1)])
   ones = array_ops.fill(ones_shape,
                         constant_op.constant(1, dtype=grad.dtype))
-  scaled_grad = grad * math_ops.inv(math_ops.segment_sum(ones, op.inputs[1]))
+  scaled_grad = math_ops.div(grad, math_ops.segment_sum(ones, op.inputs[1]))
   return array_ops.gather(scaled_grad, op.inputs[1]), None
 
 
diff --git a/tensorflow/python/ops/nn_ops.py b/tensorflow/python/ops/nn_ops.py
index 73e51aab7d..562c0408b9 100644
--- a/tensorflow/python/ops/nn_ops.py
+++ b/tensorflow/python/ops/nn_ops.py
@@ -1125,7 +1125,7 @@ def dropout(x, keep_prob, noise_shape=None, seed=None, name=None):
                                                dtype=x.dtype)
     # 0. if [keep_prob, 1.0) and 1. if [1.0, 1.0 + keep_prob)
     binary_tensor = math_ops.floor(random_tensor)
-    ret = x * math_ops.inv(keep_prob) * binary_tensor
+    ret = math_ops.div(x, keep_prob) * binary_tensor
     ret.set_shape(x.get_shape())
     return ret