import tensorflow as tf

            self.x_preprocessed = (self.x_preprocessed - self.resnet_mean) #/ self.resnet_std
#            red, green, blue = tf.split(self.x_preprocessed, num_or_size_splits=3, axis=3)
#            self.x_preprocessed = tf.concat([blue,green,red], 3)

        # These variables to keep track of what i do
        # filters = [64, 64, 128, 256, 512]
        # kernels = [7, 3, 3, 3, 3]
        # strides = [2, 0, 2, 2, 2]
        tf.add_to_collection('debug_layers', self.x_preprocessed)

        with tf.variable_scope('conv1_x'):
            print('Building unit: conv1')
            self.conv1 = self._conv('conv1', self.x_preprocessed, padding= [[0,0],[3,3],[3,3],[0,0]],
                                    num_filters=64, kernel_size=(7, 7), stride=(2, 2), l2_strength=self.wd,
                                    bias=self.bias)

            self.conv1 = self._bn('bn1', self.conv1)

            self.conv1 = self._relu('relu1', self.conv1)
            _debug(self.conv1)
