From 50b999a8336d19400ab75aea66fe46eca2f5fe0b Mon Sep 17 00:00:00 2001
From: "A. Unique TensorFlower" <gardener@tensorflow.org>
Date: Tue, 27 Jun 2017 16:33:00 -0700
Subject: Merge changes from github.

PiperOrigin-RevId: 160344052
---
 tensorflow/contrib/keras/python/keras/backend.py          | 6 +++---
 tensorflow/contrib/keras/python/keras/layers/core.py      | 2 +-
 tensorflow/contrib/keras/python/keras/layers/recurrent.py | 2 +-
 tensorflow/contrib/keras/python/keras/models_test.py      | 2 +-
 4 files changed, 6 insertions(+), 6 deletions(-)

(limited to 'tensorflow/contrib/keras')

diff --git a/tensorflow/contrib/keras/python/keras/backend.py b/tensorflow/contrib/keras/python/keras/backend.py
index 9f02fc0958..324f510301 100644
--- a/tensorflow/contrib/keras/python/keras/backend.py
+++ b/tensorflow/contrib/keras/python/keras/backend.py
@@ -3261,7 +3261,7 @@ def conv2d(x,
       padding: string, `"same"` or `"valid"`.
       data_format: `"channels_last"` or `"channels_first"`.
           Whether to use Theano or TensorFlow data format
-          for inputs/kernels/ouputs.
+          for inputs/kernels/outputs.
       dilation_rate: tuple of 2 integers.
 
   Returns:
@@ -3309,7 +3309,7 @@ def conv2d_transpose(x,
       padding: string, `"same"` or `"valid"`.
       data_format: `"channels_last"` or `"channels_first"`.
           Whether to use Theano or TensorFlow data format
-          for inputs/kernels/ouputs.
+          for inputs/kernels/outputs.
 
   Returns:
       A tensor, result of transposed 2D convolution.
@@ -3395,7 +3395,7 @@ def conv3d(x,
       padding: string, `"same"` or `"valid"`.
       data_format: `"channels_last"` or `"channels_first"`.
           Whether to use Theano or TensorFlow data format
-          for inputs/kernels/ouputs.
+          for inputs/kernels/outputs.
       dilation_rate: tuple of 3 integers.
 
   Returns:
diff --git a/tensorflow/contrib/keras/python/keras/layers/core.py b/tensorflow/contrib/keras/python/keras/layers/core.py
index d287fa56d9..34548c83c5 100644
--- a/tensorflow/contrib/keras/python/keras/layers/core.py
+++ b/tensorflow/contrib/keras/python/keras/layers/core.py
@@ -107,7 +107,7 @@ class Dropout(tf_core_layers.Dropout, Layer):
     self.supports_masking = True
     # Inheritance call order:
     # 1) tf.layers.Dropout, 2) keras.layers.Layer, 3) tf.layers.Layer
-    super(Dropout, self).__init__(**kwargs)
+    super(Dropout, self).__init__(rate=rate, noise_shape=noise_shape, seed=seed, **kwargs)
 
   def call(self, inputs, training=None):
     if training is None:
diff --git a/tensorflow/contrib/keras/python/keras/layers/recurrent.py b/tensorflow/contrib/keras/python/keras/layers/recurrent.py
index 5e8c23ed3e..cdef55f599 100644
--- a/tensorflow/contrib/keras/python/keras/layers/recurrent.py
+++ b/tensorflow/contrib/keras/python/keras/layers/recurrent.py
@@ -985,7 +985,7 @@ class LSTM(Recurrent):
 
   References:
       - [Long short-term
-        memory](http://deeplearning.cs.cmu.edu/pdfs/Hochreiter97_lstm.pdf)
+        memory](http://www.bioinf.jku.at/publications/older/2604.pdf)
         (original 1997 paper)
       - [Supervised sequence labeling with recurrent neural
         networks](http://www.cs.toronto.edu/~graves/preprint.pdf)
diff --git a/tensorflow/contrib/keras/python/keras/models_test.py b/tensorflow/contrib/keras/python/keras/models_test.py
index 50aba43c24..99fd6e1cbe 100644
--- a/tensorflow/contrib/keras/python/keras/models_test.py
+++ b/tensorflow/contrib/keras/python/keras/models_test.py
@@ -105,7 +105,7 @@ class TestModelSaving(test.TestCase):
       out2 = model.predict(x)
       self.assertAllClose(out, out2, atol=1e-05)
 
-  def test_fuctional_model_saving(self):
+  def test_functional_model_saving(self):
     if h5py is None:
       return  # Skip test if models cannot be saved.
 
-- 
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