in
4 sess.run(init)
5 for i in range(len(raw_data)):
----> 6 summary_str, curr_value_float = sess.run([**merged**, update_avg], feed_dict={curr_value: raw_data[i]})
7 sess.run(tf.assign(prev_avg, curr_value_float ))
8 print(raw_data[i], curr_value_float )
**InvalidArgumentError** (see above for traceback): You must feed a value for placeholder tensor 'Placeholder' with dtype float
[[node Placeholder (defined at :2) = Placeholder[dtype=DT_FLOAT, shape=, _device="/job:localhost/replica:0/task:0/device:CPU:0"]()]]
Hi,
I am trying to reproduce your exponential moving average example but I get the error:
InvalidArgumentError Traceback (most recent call last)