From 7610c55bdc046ff0b0d6300af5ea9dcfd0a427cb Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Fr=C3=A9d=C3=A9ric=20Branchaud-Charron?=
 <frederic.branchaud-charron@usherbrooke.ca>
Date: Mon, 16 Oct 2017 18:09:35 -0400
Subject: [PATCH] Add dilation to SeparableConv2D (#8152)

* Add dilation to SeparableConv2D

* pep8
---
 keras/layers/convolutional.py            | 22 ++--------------------
 tests/keras/layers/convolutional_test.py | 24 ++++++++++++++----------
 2 files changed, 16 insertions(+), 30 deletions(-)

diff --git a/keras/layers/convolutional.py b/keras/layers/convolutional.py
index 70f0a4dc911..6719eac9848 100644
--- a/keras/layers/convolutional.py
+++ b/keras/layers/convolutional.py
@@ -1217,7 +1217,8 @@ def call(self, inputs):
             self.pointwise_kernel,
             data_format=self.data_format,
             strides=self.strides,
-            padding=self.padding)
+            padding=self.padding,
+            dilation_rate=self.dilation_rate)
 
         if self.bias:
             outputs = K.bias_add(
@@ -1229,25 +1230,6 @@ def call(self, inputs):
             return self.activation(outputs)
         return outputs
 
-    def compute_output_shape(self, input_shape):
-        if self.data_format == 'channels_first':
-            rows = input_shape[2]
-            cols = input_shape[3]
-        elif self.data_format == 'channels_last':
-            rows = input_shape[1]
-            cols = input_shape[2]
-
-        rows = conv_utils.conv_output_length(rows, self.kernel_size[0],
-                                             self.padding,
-                                             self.strides[0])
-        cols = conv_utils.conv_output_length(cols, self.kernel_size[1],
-                                             self.padding,
-                                             self.strides[1])
-        if self.data_format == 'channels_first':
-            return (input_shape[0], self.filters, rows, cols)
-        elif self.data_format == 'channels_last':
-            return (input_shape[0], rows, cols, self.filters)
-
     def get_config(self):
         config = super(SeparableConv2D, self).get_config()
         config.pop('kernel_initializer')
diff --git a/tests/keras/layers/convolutional_test.py b/tests/keras/layers/convolutional_test.py
index dc4868b30af..66e48f306a4 100644
--- a/tests/keras/layers/convolutional_test.py
+++ b/tests/keras/layers/convolutional_test.py
@@ -241,16 +241,20 @@ def test_separable_conv_2d():
     for padding in _convolution_paddings:
         for strides in [(1, 1), (2, 2)]:
             for multiplier in [1, 2]:
-                if padding == 'same' and strides != (1, 1):
-                    continue
-
-                layer_test(convolutional.SeparableConv2D,
-                           kwargs={'filters': filters,
-                                   'kernel_size': (3, 3),
-                                   'padding': padding,
-                                   'strides': strides,
-                                   'depth_multiplier': multiplier},
-                           input_shape=(num_samples, num_row, num_col, stack_size))
+                for dilation_rate in [(1, 1), (2, 2), (2, 1), (1, 2)]:
+                    if padding == 'same' and strides != (1, 1):
+                        continue
+                    if dilation_rate != (1, 1) and strides != (1, 1):
+                        continue
+
+                    layer_test(convolutional.SeparableConv2D,
+                               kwargs={'filters': filters,
+                                       'kernel_size': (3, 3),
+                                       'padding': padding,
+                                       'strides': strides,
+                                       'depth_multiplier': multiplier,
+                                       'dilation_rate': dilation_rate},
+                               input_shape=(num_samples, num_row, num_col, stack_size))
 
     layer_test(convolutional.SeparableConv2D,
                kwargs={'filters': filters,