[WIP] Fix Issue #561 - Convolution Support NCHW

tensorlayer/layers/convolution.py

@@ -76,15 +76,19 @@ def __init__(
             act=None,
             shape=(5, 1, 5),
             stride=1,
-            dilation_rate=1,
             padding='SAME',
-            data_format='NWC',
+            dilation_rate=1,
+            data_format=None,
             W_init=tf.truncated_normal_initializer(stddev=0.02),
             b_init=tf.constant_initializer(value=0.0),
             W_init_args=None,
             b_init_args=None,
             name='cnn1d',
     ):
+
+        if data_format not in [None, 'NWC', 'channels_last', 'NCW', 'channels_first']:
+            raise ValueError("`data_format` should be among 'NWC', 'channels_last', 'NCW', 'channels_first'")
+
         super(Conv1dLayer, self
              ).__init__(prev_layer=prev_layer, act=act, W_init_args=W_init_args, b_init_args=b_init_args, name=name)
 
@@ -207,6 +211,11 @@ def __init__(
             data_format=None,
             name='cnn_layer',
     ):
+
+        # dic = {'channels_last': 'NHWC', 'channels_first': 'NCHW'}
+        if data_format not in [None, 'NHWC', 'channels_last', 'NCHW', 'channels_first']:
+            raise ValueError("'data_format' must be among 'NHWC', 'channels_last', 'NCHW', 'channels_first'.")
+
         super(Conv2dLayer, self
              ).__init__(prev_layer=prev_layer, act=act, W_init_args=W_init_args, b_init_args=b_init_args, name=name)
 
@@ -418,12 +427,16 @@ def __init__(
             shape=(2, 2, 2, 3, 32),
             strides=(1, 2, 2, 2, 1),
             padding='SAME',
+            data_format=None,
             W_init=tf.truncated_normal_initializer(stddev=0.02),
             b_init=tf.constant_initializer(value=0.0),
             W_init_args=None,
             b_init_args=None,
             name='cnn3d_layer',
     ):
+        if data_format not in [None, 'NDHWC', 'channels_last', 'NCDHW', 'channels_first']:
+            raise ValueError("'data_format' must be one of 'channels_last', 'channels_first'.")
+
         super(Conv3dLayer, self
              ).__init__(prev_layer=prev_layer, act=act, W_init_args=W_init_args, b_init_args=b_init_args, name=name)
 
@@ -440,7 +453,7 @@ def __init__(
                 name='W_conv3d', shape=shape, initializer=W_init, dtype=LayersConfig.tf_dtype, **self.W_init_args
             )
 
-            self.outputs = tf.nn.conv3d(self.inputs, W, strides=strides, padding=padding, name=None)
+            self.outputs = tf.nn.conv3d(self.inputs, W, strides=strides, padding=padding, data_format=data_format, name=None)
 
             if b_init:
                 b = tf.get_variable(
@@ -1448,6 +1461,7 @@ def __init__(
                 if self.act is not None else '- No Activation'
             )
         )
+
         # with tf.variable_scope(name) as vs:
         conv2d = tf.layers.Conv2D(
             # inputs=self.inputs,

tests/test_layers_convolution_channel_first.py

@@ -0,0 +1,63 @@
+import unittest
+
+try:
+    from tests.unittests_helper import CustomTestCase
+except ImportError:
+    from unittests_helper import CustomTestCase
+
+# To be removed later
+import sys
+sys.path.insert(0, './')
+
+import tensorflow as tf
+import tensorlayer as tl
+
+
+class Layer_Data_Format_Test(CustomTestCase):
+
+    @classmethod
+    def setUpClass(cls):
+        x_1d = tf.placeholder(tf.float32, [None, 1, 5])
+        cls.input_1d = tl.layers.InputLayer(x_1d)
+
+        x_2d = tf.placeholder(tf.float32, [None, 1, 5, 5])
+        cls.input_2d = tl.layers.InputLayer(x_2d)
+
+        x_3d = tf.placeholder(tf.float32, [None, 3, 5, 6, 7])
+        cls.input_3d = tl.layers.InputLayer(x_3d)
+
+    @classmethod
+    def tearDownClass(cls):
+        tf.reset_default_graph()
+
+    def test_Conv1dLayer_NCW(self):
+        with self.assertRaises(Exception):
+            with tf.variable_scope('test_Conv1dLayer_NCW', reuse=False):
+                tl.layers.Conv1dLayer(self.input_1d, data_format="channels_first")
+
+    def test_Conv1d_NCW(self):
+        with self.assertNotRaises(Exception):
+            with tf.variable_scope('test_Conv1d_NCW', reuse=False):
+                tl.layers.Conv1d(self.input_1d, data_format="channels_first")
+
+    def test_Conv2dLayer_NCHW(self):
+        with self.assertRaises(Exception):
+            with tf.variable_scope('test_Conv2dLayer_NCHW', reuse=False):
+                tl.layers.Conv2dLayer(self.input_2d, data_format="NCHW")
+
+    def test_Conv2d_NCHW(self):
+        with self.assertNotRaises(Exception):
+            with tf.variable_scope('test_Conv2d_NCHW', reuse=False):
+                tl.layers.Conv2d(self.input_2d, data_format="NCHW")
+
+    def test_Conv3dLayer_NCDHW(self):
+        with self.assertRaises(Exception):
+            with tf.variable_scope('test_Conv3dLayer_NCDHW', reuse=False):
+                tl.layers.Conv3dLayer(self.input_3d, data_format="NCDHW")
+
+
+if __name__ == '__main__':
+    # tf.logging.set_verbosity(tf.logging.INFO)
+    tf.logging.set_verbosity(tf.logging.DEBUG)
+
+    unittest.main()

tests/test_layers_convolution_channel_last.py

@@ -0,0 +1,63 @@
+import unittest
+
+try:
+    from tests.unittests_helper import CustomTestCase
+except ImportError:
+    from unittests_helper import CustomTestCase
+
+# To be removed later
+import sys
+sys.path.insert(0, './')
+
+import tensorflow as tf
+import tensorlayer as tl
+
+
+class Layer_Data_Format_Test(CustomTestCase):
+
+    @classmethod
+    def setUpClass(cls):
+        x_1d = tf.placeholder(tf.float32, [None, 5, 1])
+        cls.input_1d = tl.layers.InputLayer(x_1d)
+
+        x_2d = tf.placeholder(tf.float32, [None, 5, 5, 1])
+        cls.input_2d = tl.layers.InputLayer(x_2d)
+
+        x_3d = tf.placeholder(tf.float32, [None, 5, 6, 7, 3])
+        cls.input_3d = tl.layers.InputLayer(x_3d)
+
+    @classmethod
+    def tearDownClass(cls):
+        tf.reset_default_graph()
+
+    def test_Conv1dLayer_NWC(self):
+        with self.assertNotRaises(Exception):
+            with tf.variable_scope('test_Conv1dLayer_NWC', reuse=False):
+                tl.layers.Conv1dLayer(self.input_1d, data_format="channels_last")
+
+    def test_Conv1d_NWC(self):
+        with self.assertNotRaises(Exception):
+            with tf.variable_scope('test_Conv1d_NWC', reuse=False):
+                tl.layers.Conv1d(self.input_1d, data_format="channels_last")
+
+    def test_Conv2dLayer_NHWC(self):
+        with self.assertNotRaises(Exception):
+            with tf.variable_scope('test_Conv2dLayer_NHWC', reuse=False):
+                tl.layers.Conv2dLayer(self.input_2d, data_format="NHWC")
+
+    def test_Conv2d_NHWC(self):
+        with self.assertNotRaises(Exception):
+            with tf.variable_scope('test_Conv2d_NHWC', reuse=False):
+                tl.layers.Conv2d(self.input_2d, data_format="channels_last")
+
+    def test_Conv3dLayer_NDHWC(self):
+        with self.assertNotRaises(Exception):
+            with tf.variable_scope('test_Conv3dLayer_1', reuse=False):
+                tl.layers.Conv3dLayer(self.input_3d, data_format="NDHWC")
+
+
+if __name__ == '__main__':
+    # tf.logging.set_verbosity(tf.logging.INFO)
+    tf.logging.set_verbosity(tf.logging.DEBUG)
+
+    unittest.main()