bc4a0ecb1c146647632c3add2de814a64ab9d44a,pixel_cnn_pp/nn.py,,deconv2d,#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#,219

Before Change

            m_init, v_init = tf.nn.moments(x, [0,1,2])
            scale_init = init_scale / tf.sqrt(v_init + 1e-10)
            with tf.control_dependencies([g.assign(g * scale_init), b.assign_add(-m_init * scale_init)]):
                x = tf.identity(x)

        // apply nonlinearity
        if nonlinearity is not None:

After Change

            scale_init = init_scale / tf.sqrt(v_init + 1e-10)
            with tf.control_dependencies([g.assign(g * scale_init), b.assign_add(-m_init * scale_init)]):
                // x = tf.identity(x)
                W = tf.reshape(g, [1, 1, num_filters, 1]) * tf.nn.l2_normalize(V, [0, 1, 3])
                x = tf.nn.conv2d_transpose(x_, W, target_shape, [1] + stride + [1], padding=pad)
                x = tf.nn.bias_add(x, b)

        // apply nonlinearity
        if nonlinearity is not None:

Instances