From ec8010077cc678c3614be5f7e316f0e3db7b9c68 Mon Sep 17 00:00:00 2001
From: Ben <bstriner@users.noreply.github.com>
Date: Wed, 7 Jun 2017 23:47:39 -0400
Subject: [PATCH] Move DSSIMObjective to submodule (#93)

* Move DSSIMObjective to submodule

* fix losses/dssim_test.py
---
 keras_contrib/losses/__init__.py                           | 1 +
 keras_contrib/{losses.py => losses/dssim.py}               | 0
 .../keras_contrib/{losses_test.py => losses/dssim_test.py} | 7 +++----
 3 files changed, 4 insertions(+), 4 deletions(-)
 create mode 100644 keras_contrib/losses/__init__.py
 rename keras_contrib/{losses.py => losses/dssim.py} (100%)
 rename tests/keras_contrib/{losses_test.py => losses/dssim_test.py} (94%)

diff --git a/keras_contrib/losses/__init__.py b/keras_contrib/losses/__init__.py
new file mode 100644
index 0000000..35e8e76
--- /dev/null
+++ b/keras_contrib/losses/__init__.py
@@ -0,0 +1 @@
+from .dssim import DSSIMObjective
diff --git a/keras_contrib/losses.py b/keras_contrib/losses/dssim.py
similarity index 100%
rename from keras_contrib/losses.py
rename to keras_contrib/losses/dssim.py
diff --git a/tests/keras_contrib/losses_test.py b/tests/keras_contrib/losses/dssim_test.py
similarity index 94%
rename from tests/keras_contrib/losses_test.py
rename to tests/keras_contrib/losses/dssim_test.py
index 225317f..ae47b62 100644
--- a/tests/keras_contrib/losses_test.py
+++ b/tests/keras_contrib/losses/dssim_test.py
@@ -5,9 +5,8 @@ from keras.layers import Conv2D
 from keras.models import Sequential
 from keras.optimizers import Adam
 
-from keras_contrib import losses
+from keras.losses import sparse_categorical_crossentropy
 from keras import backend as K
-from keras_contrib import backend as KC
 from keras_contrib.losses import DSSIMObjective
 
 allobj = []
@@ -32,12 +31,12 @@ def test_objective_shapes_2d():
 def test_cce_one_hot():
     y_a = K.variable(np.random.randint(0, 7, (5, 6)))
     y_b = K.variable(np.random.random((5, 6, 7)))
-    objective_output = losses.sparse_categorical_crossentropy(y_a, y_b)
+    objective_output = sparse_categorical_crossentropy(y_a, y_b)
     assert K.eval(objective_output).shape == (5, 6)
 
     y_a = K.variable(np.random.randint(0, 7, (6,)))
     y_b = K.variable(np.random.random((6, 7)))
-    assert K.eval(losses.sparse_categorical_crossentropy(y_a, y_b)).shape == (6,)
+    assert K.eval(sparse_categorical_crossentropy(y_a, y_b)).shape == (6,)
 
 
 def test_DSSIM_channels_last():