Hi, I am trying to reproduce your exponential moving average example but I get the error "TypeError: Can not convert a float32 into a Tensor. " I modified the lines ``` summary_str, curr_value = sess.run([merged, update_avg], feed_dict={curr_value: raw_data[i]}) sess.run(tf.assign(prev_avg, curr_value)) print(raw_data[i], curr_value) ``` for ``` summary_str, curr_value_float = sess.run([merged, update_avg], feed_dict={curr_value: raw_data[i]}) sess.run(tf.assign(prev_avg, curr_value_float)) print(raw_data[i], curr_value_float) ``` to make things work, but I was wondering is this way the best solution or can we do better? Thanks