## Description
In BaseModule.fit function, <code>forward_backward</code> only needs 0.00055s,
<code>update</code> only needs 0.079953s, <code>next(data_iter)</code> only
needs 0.000265s. However, we run <code>forward_backward</code> and
<code>next(data_iter)</code> together and spend 2.919867s. Could you please
tell me what is the reason of this time bottleneck?
## Environment info (Required)
Platform: MacOS
Language: Python 2.7
Platform Version: MXNet 1.2.0
Device: 2.9 GHz Intel Core i5 (The test runs using single CPU)
Memory: 8 GB 1867 MHz DDR3
Install Tool: pip
## Steps to reproduce (In BaseModule.fit function)
* Run <code>forward_backward</code> only:
```
while True:
data_batch = next_data_batch
calc_start = time.time()
self.forward_backward(data_batch)
calc_end = time.time()
self.logger.info("[CALC TIME] %f", calc_end - calc_start)
```
result: [CALC TIME] 0.000551
* Run <code>next(data_iter)</code> only:
```
while True:
data_iter_start = time.time()
next(data_iter)
data_iter_end = time.time()
self.logger.info("[DATAITER TIME] %f", data_iter_end - data_iter_start)
```
result: [DATAITER TIME] 0.000265
* Run <code>forward_backward</code> and <code>next(data_iter)</code> together:
```
while True:
data_batch = next_data_batch
calc_iter_start = time.time()
self.forward_backward(data_batch)
next_data_batch = next(data_iter)
calc_iter_end = time.time()
self.logger.info("[CALC AND DATAITER TIME] %f", calc_iter_end -
calc_iter_start)
```
result: [CALC AND DATAITER TIME] 2.919867
## What have you tried to solve it?
1. I read the source code of <code>forward_backward</code> and
<code>ImageRecordIter</code> but have no idea.
2. I found little modify in <code>data_batch</code> variable would also cause
the time bottleneck in the loop of <code>forward_backward</code>.
Thanks a lot for your kind !
[ Full content available at:
https://github.com/apache/incubator-mxnet/issues/12640 ]
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