ffd5f4f328155460dc9adeb91ddf28782e96c0dd,hypergan/ops/tensorflow/ops.py,TensorflowOps,deconv2d,#TensorflowOps#Any#Any#Any#Any#Any#Any#,91

Before Change

        init_bias = 0.
        with tf.variable_scope(self.generate_name()):
            // filter : [height, width, output_channels, in_channels]
            w = tf.get_variable("w", [filter_h, filter_w, output_shape[-1], net.get_shape()[-1]], dtype=self.dtype, initializer=initializer)

            try:
                deconv = tf.nn.conv2d_transpose(net, w, output_shape=output_shape,
                                    strides=[1, stride_h, stride_w, 1])

            // Support for versions of TensorFlow before 0.7.0
            except AttributeError:
                deconv = tf.nn.deconv2d(net, w, output_shape=output_shape,
                                    strides=[1, stride_h, stride_w, 1])

            biases = tf.get_variable("biases", [output_shape[-1]], dtype=self.dtype,initializer=tf.constant_initializer(init_bias, dtype=self.dtype))
            deconv = tf.reshape(tf.nn.bias_add(deconv, biases), deconv.get_shape())

            return deconv

After Change

            conv = tf.nn.bias_add(conv, biases)
            return conv

    def deconv2d(self, net, filter_w, filter_h, stride_w, stride_h, output_dim):
        self.assert_tensor(net)
        initializer = self.initializer()
        shape = self.shape(net)
        output_shape = [shape[0], shape[1]*stride_h, shape[2]*stride_w, output_dim]
        init_bias = 0.
        with tf.variable_scope(self.generate_name()):
            // filter : [height, width, output_channels, in_channels]
            w = self.get_weight([filter_h, filter_w, output_dim, output_dim])

            deconv = tf.nn.conv2d_transpose(net, w, output_shape=output_shape,
                                    strides=[1, stride_h, stride_w, 1])

            biases = self.get_bias([output_shape[-1]])
            deconv = tf.reshape(tf.nn.bias_add(deconv, biases), deconv.get_shape())

            return deconv

Instances