def fc_layer(input, size_in, size_out, name='fc'):
    with tf.name_scope(name):
        w = tf.Variable(tf.truncated_normal([window_size, size_in, size_out], stddev=0.1), name='W')
        b = tf.Variable(tf.constant(0.1, shape=[size_out]), name='B')
        act = (conv1d(input, w) + b)
        tf.summary.histogram('weights', w)
        tf.summary.histogram('biases', b)
        tf.summary.histogram('activations', act)
        return (act, w)
def fc_layer(input, size_in, size_out, name='fc'):
    with tf.name_scope(name):
        w = tf.Variable(tf.truncated_normal([window_size, size_in, size_out], stddev=0.1), name='W')
        b = tf.Variable(tf.constant(0.1, shape=[size_out]), name='B')
        act = (conv1d(input, w) + b)
        tf.summary.histogram('weights', w)
        tf.summary.histogram('biases', b)
        tf.summary.histogram('activations', act)
        return (act, w)