[GitHub] [incubator-mxnet] wuxun-zhang commented on issue #17884: [MKL-DNN] Integrate Conv3d and Pool3d/1d

2020-04-20 Thread GitBox 


wuxun-zhang commented on issue #17884:
URL: https://github.com/apache/incubator-mxnet/pull/17884#issuecomment-616912500


   **Performance numbers for Conv3d op:**
   
   shape | w/o mkldnn | w/mkldnn |
   -- | -- | -- |
   (3, 3, 16, 224, 224) | 3.696679 sec |  0.046571 sec|
   (3, 3, 128, 128, 128) | 11.716535 sec |  0.165749 sec| 
   
   **Test script:**
   ```
   import mxnet as mx
   from mxnet import nd, gluon
   import time
   
   data_shape = [(3, 3, 16, 224, 224), (3, 3, 128, 128, 128)]
   
   for shape in data_shape:
data = mx.random.uniform(shape=shape)
weight_shape = (32, shape[1], 3, 3, 3)
weight = mx.nd.ones(shape=weight_shape)
   
num_iter = 10
dry_run = 5
for i in range(num_iter):
if i == dry_run:
tic = time.time()
out = mx.nd.Convolution(data, weight, kernel=(3,3,3), 
stride=(1,1,1), num_filter=weight_shape[0], pad=(0,0,0), dilate=(2,2,2), 
no_bias=True, cudnn_off=True, name='conv3d')
out.asnumpy()
print("For shape : {}".format(shape))
print("Average time cost is %f sec" % ((time.time() - 
tic)/(num_iter-dry_run))
   ```



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[GitHub] [incubator-mxnet] wuxun-zhang commented on issue #17884: [MKL-DNN] Integrate Conv3d and Pool3d/1d

2020-04-07 Thread GitBox 
wuxun-zhang commented on issue #17884: [MKL-DNN] Integrate Conv3d and Pool3d/1d
URL: https://github.com/apache/incubator-mxnet/pull/17884#issuecomment-610747504
 
 
   Now CI has finally passed. @pengzhao-intel @TaoLv please help review again. 
   @ChaiBapchya please also double check if this PR fixes 
https://github.com/apache/incubator-mxnet/issues/17915.


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[GitHub] [incubator-mxnet] wuxun-zhang commented on issue #17884: [MKL-DNN] Integrate Conv3d and Pool3d/1d

2020-04-06 Thread GitBox 
wuxun-zhang commented on issue #17884: [MKL-DNN] Integrate Conv3d and Pool3d/1d
URL: https://github.com/apache/incubator-mxnet/pull/17884#issuecomment-610103164
 
 
   Thank you @ChaiBapchya for investigating this. 8e96ef should be OneDNN 
v1.2.2. Actually we are working on confirming with the PR author of #17084 if 
such downgrade is intended or a mistake.  


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[GitHub] [incubator-mxnet] wuxun-zhang commented on issue #17884: [MKL-DNN] Integrate Conv3d and Pool3d/1d

2020-04-05 Thread GitBox 
wuxun-zhang commented on issue #17884: [MKL-DNN] Integrate Conv3d and Pool3d/1d
URL: https://github.com/apache/incubator-mxnet/pull/17884#issuecomment-609364511
 
 
   Now DNNL version in master branch has been wrongly changed (from v1.2.2 to 
v1.1.2). This PR is now waiting for DNNL v1.2 or higher version coming back.


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[GitHub] [incubator-mxnet] wuxun-zhang commented on issue #17884: [MKL-DNN] Integrate Conv3d and Pool3d/1d

2020-03-29 Thread GitBox 
wuxun-zhang commented on issue #17884: [MKL-DNN] Integrate Conv3d and Pool3d/1d
URL: https://github.com/apache/incubator-mxnet/pull/17884#issuecomment-605753245
 
 
   Seems CI system is now experiencing failures. The errors are unrelated to 
this PR.


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[GitHub] [incubator-mxnet] wuxun-zhang commented on issue #17884: [MKL-DNN] Integrate Conv3d and Pool3d/1d

2020-03-25 Thread GitBox 
wuxun-zhang commented on issue #17884: [MKL-DNN] Integrate Conv3d and Pool3d/1d
URL: https://github.com/apache/incubator-mxnet/pull/17884#issuecomment-604172727
 
 
   @mxnet-bot run ci [centos-cpu, unix-gpu, windows-gpu]


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