[GitHub] [incubator-mxnet] wkcn edited a comment on pull request #18707: [MXNET-1453] Support the intput whose dimension is greater than 6 for Transpose and Rollaxis

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wkcn edited a comment on pull request #18707:
URL: https://github.com/apache/incubator-mxnet/pull/18707#issuecomment-659304799


   Performance Benchmark:
   transpose operator on CPU, axes is generated randomly
   
   ndim | max use (kb) | avg time (ms)
   ---|---|--
   1|12582.9121|1.0786
   2|12582.9121|1.0851
   3|12582.9121|0.6763
   4|12582.9121|1.2172
   5|12582.9121|6.4305
   6|12582.9121|11.7841
   7|12583.3604|65.7184
   8|12583.4238|65.2171
   9|12583.4883|82.4930
   
   The increase of memory footprint is slight, but the time is intolerable when `axes.ndim() > 6`. I will try to optimize it.
   
   If axes is monotonically increasing (namely [0, 1, 2, 3, ..., ndim - 1]),
   ndim | max use (kb) | avg time (ms)
   ---|---|--
   1|12582.9121|1.1492
   2|12582.9121|1.1732
   3|12582.9121|1.3264
   4|12582.9121|1.3896
   5|12582.9121|0.9107
   6|12582.9121|0.8965
   7|12583.3604|0.9028
   8|12583.4238|0.9105
   9|12583.4883|0.8981
   
   Test Code:
   ```python
   import mxnet as mx
   from mxnet import profiler
   print(mx)
   import numpy as np
   from numpy.testing import assert_allclose
   import time
   import random
   seed = 42
   np.random.seed(seed)
   mx.random.seed(seed)
   
   #configure the profiler
   profiler.set_config(profile_all=True, aggregate_stats=True, filename='trace_profile.json')
   #start the profiler collecting data
   
   def test_transpose(ndim):
       for t in range(20):
           dims = [4 for _ in range(ndim)]
           dims[-1] *= 4 ** (10 - ndim) 
           axes = list(range(ndim))
           random.shuffle(axes)
           axes = tuple(axes)
           x = mx.nd.array(np.random.normal(size=dims))
           y = mx.nd.transpose(x, axes=axes)
           assert_allclose(np.transpose(x.asnumpy(), axes=axes), y.asnumpy())
   
   for ndim in range(1, 10):
       profiler.set_state('run')
       tic = time.time()
       test_transpose(ndim)
       print(ndim, "====", time.time() - tic)
       #stop the profiler
       profiler.set_state('stop')
       #dump the profiling data as a string
       print(profiler.dumps(reset=True))
   print("Over")
   ```


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