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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
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