gan.py 文件源码

def generator(self, opts, noise, reuse=False):
        """Generator function, suitable for simple toy experiments.

        Args:
            noise: [num_points, dim] array, where dim is dimensionality of the
                latent noise space.
        Returns:
            [num_points, dim1, dim2, dim3] array, where the first coordinate
            indexes the points, which all are of the shape (dim1, dim2, dim3).
        """
        output_shape = self._data.data_shape
        num_filters = opts['g_num_filters']

        with tf.variable_scope("GENERATOR", reuse=reuse):
            h0 = ops.linear(opts, noise, num_filters, 'h0_lin')
            h0 = tf.nn.relu(h0)
            h1 = ops.linear(opts, h0, num_filters, 'h1_lin')
            h1 = tf.nn.relu(h1)
            h2 = ops.linear(opts, h1, np.prod(output_shape), 'h2_lin')
            h2 = tf.reshape(h2, [-1] + list(output_shape))

        if opts['input_normalize_sym']:
            return tf.nn.tanh(h2)
        else:
            return h2