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Posted to commits@mxnet.apache.org by GitBox <gi...@apache.org> on 2020/05/17 01:33:25 UTC
[GitHub] [incubator-mxnet] moveforever opened a new issue #18344: Failed to train model trained by mxnet 1.0 in mxnet 2.0
moveforever opened a new issue #18344:
URL: https://github.com/apache/incubator-mxnet/issues/18344
i upgrade mxnet version from 1.0 to 2.0. I load the model which is trained at 1.0 in mxnet 2.0, and when i train the model, it came across the situation that it stops after 30 epochs, which seems to be hanged.
can somebody help me?
Any help make me appreciate it.
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[GitHub] [incubator-mxnet] moveforever edited a comment on issue #18344: Failed to train model trained by mxnet 1.0 in mxnet 2.0
Posted by GitBox <gi...@apache.org>.
moveforever edited a comment on issue #18344:
URL: https://github.com/apache/incubator-mxnet/issues/18344#issuecomment-629734656
## Description
i upgrade mxnet version from 1.0 to 2.0. I load the model which is trained at 1.0 in mxnet 2.0, and when i train the model, it came across the situation that it stops after 30 batches, which seems to be hanged.
### Error Message
(Paste the complete error message. Please also include stack trace by setting environment variable `DMLC_LOG_STACK_TRACE_DEPTH=10` before running your script.)
There is no error information, and it seems to be hanged!
```
+ export DMLC_LOG_STACK_TRACE_DEPTH=10
+ DMLC_LOG_STACK_TRACE_DEPTH=10
+ curl --retry 10 -s https://raw.githubusercontent.com/dmlc/gluon-nlp/master/tools/diagnose.py
+ /thirdparty/bin/python3 src/train.py
INFO:root:current path is: /cephfs/group/omg-omgmobile-app-tencent-sports/qomozheng/project/mult
i_obj_opt
20
INFO:root:['dense', 'cate', 'sparse', 'field_0', 'field_1', 'field_2', 'field_3', 'field_4', 'fi
eld_5', 'field_6']
INFO:root:only use embedding model
[10:37:49] src/base.cc:51: Upgrade advisory: this mxnet has been built against cuda library vers
ion 9010, which is older than the oldest version tested by CI (10000). Set MXNET_CUDA_LIB_CHECK
ING=0 to quiet this warning.
INFO:root:Training started ...
INFO:root:Epoch[0] Batch [0-10] Speed: 1817.71 samples/sec auc=0.500820 multi_log
loss=10.058306 multi_mse=0.000000
INFO:root:batch=10, forward_backward=21ms, update=174ms, update_metric=6679ms, data=15703ms, tot
al=22579ms
INFO:root:Epoch[0] Batch [10-20] Speed: 3873.38 samples/sec auc=0.513181 multi_log
loss=7.157333 multi_mse=0.974069
INFO:root:batch=20, forward_backward=17ms, update=185ms, update_metric=4430ms, data=5941ms, tota
l=10574ms
INFO:root:Epoch[0] Batch [20-30] Speed: 4769.79 samples/sec auc=0.539163 multi_log
loss=4.971608 multi_mse=0.000000
INFO:root:batch=30, forward_backward=13ms, update=121ms, update_metric=3803ms, data=4648ms, tota
l=8586ms
```
## To Reproduce
(If you developed your own code, please provide a short script that reproduces the error. For existing examples, please provide link.)
it may be diffult to reproduce my problem
I implement a DataIter through c++ mxnet source code to support multi-storage and multi-label sample as followed, and it runs well at mxnet.
The row is splited by ^A(\001) as folowed. The first column is label, and the second column is dense feature, and the third column is categorical feature, and the the fourth column is multi-hot categorical feature which can be splited by comma , and the fifth column is sparse feature which is support wide input for google wide and deep model.
### Steps to reproduce
(Paste the commands you ran that produced the error.)
1.
2.
## What have you tried to solve it?
1.
2.
## Environment
cuda-9.0
gcc 8.4
centos 7.2
python 3.7
We recommend using our script for collecting the diagnositc information. Run the following command and paste the outputs below:
`curl --retry 10 -s https://raw.githubusercontent.com/dmlc/gluon-nlp/master/tools/diagnose.py | python`
There is no information, and it seems to be hanged.
----------------------------------------------------------------
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[GitHub] [incubator-mxnet] moveforever commented on issue #18344: Failed to train model trained by mxnet 1.0 in mxnet 2.0
Posted by GitBox <gi...@apache.org>.
moveforever commented on issue #18344:
URL: https://github.com/apache/incubator-mxnet/issues/18344#issuecomment-629734656
## Description
i upgrade mxnet version from 1.0 to 2.0. I load the model which is trained at 1.0 in mxnet 2.0, and when i train the model, it came across the situation that it stops after 30 batches, which seems to be hanged.
### Error Message
(Paste the complete error message. Please also include stack trace by setting environment variable `DMLC_LOG_STACK_TRACE_DEPTH=10` before running your script.)
There is no error information, and it seems to be hanged!
```
+ export DMLC_LOG_STACK_TRACE_DEPTH=10
+ DMLC_LOG_STACK_TRACE_DEPTH=10
+ curl --retry 10 -s https://raw.githubusercontent.com/dmlc/gluon-nlp/master/tools/diagnose.py
+ /thirdparty/bin/python3 src/train.py
INFO:root:current path is: /cephfs/group/omg-omgmobile-app-tencent-sports/qomozheng/project/mult
i_obj_opt
20
INFO:root:['dense', 'cate', 'sparse', 'field_0', 'field_1', 'field_2', 'field_3', 'field_4', 'fi
eld_5', 'field_6']
INFO:root:only use embedding model
[10:37:49] src/base.cc:51: Upgrade advisory: this mxnet has been built against cuda library vers
ion 9010, which is older than the oldest version tested by CI (10000). Set MXNET_CUDA_LIB_CHECK
ING=0 to quiet this warning.
INFO:root:Training started ...
INFO:root:Epoch[0] Batch [0-10] Speed: 1817.71 samples/sec auc=0.500820 multi_log
loss=10.058306 multi_mse=0.000000
INFO:root:batch=10, forward_backward=21ms, update=174ms, update_metric=6679ms, data=15703ms, tot
al=22579ms
INFO:root:Epoch[0] Batch [10-20] Speed: 3873.38 samples/sec auc=0.513181 multi_log
loss=7.157333 multi_mse=0.974069
INFO:root:batch=20, forward_backward=17ms, update=185ms, update_metric=4430ms, data=5941ms, tota
l=10574ms
INFO:root:Epoch[0] Batch [20-30] Speed: 4769.79 samples/sec auc=0.539163 multi_log
loss=4.971608 multi_mse=0.000000
INFO:root:batch=30, forward_backward=13ms, update=121ms, update_metric=3803ms, data=4648ms, tota
l=8586ms
```
## To Reproduce
(If you developed your own code, please provide a short script that reproduces the error. For existing examples, please provide link.)
### Steps to reproduce
(Paste the commands you ran that produced the error.)
1.
2.
## What have you tried to solve it?
1.
2.
## Environment
cuda-9.0
gcc 8.4
centos 7.2
python 3.7
We recommend using our script for collecting the diagnositc information. Run the following command and paste the outputs below:
`curl --retry 10 -s https://raw.githubusercontent.com/dmlc/gluon-nlp/master/tools/diagnose.py | python`
There is no information, and it seems to be hanged.
# paste outputs here
----------------------------------------------------------------
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[GitHub] [incubator-mxnet] zhreshold commented on issue #18344: Failed to train model trained by mxnet 1.0 in mxnet 2.0
Posted by GitBox <gi...@apache.org>.
zhreshold commented on issue #18344:
URL: https://github.com/apache/incubator-mxnet/issues/18344#issuecomment-630469519
@moveforever Can you provide the implementation of the DataIter?
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[GitHub] [incubator-mxnet] moveforever edited a comment on issue #18344: Failed to train model trained by mxnet 1.0 in mxnet 2.0
Posted by GitBox <gi...@apache.org>.
moveforever edited a comment on issue #18344:
URL: https://github.com/apache/incubator-mxnet/issues/18344#issuecomment-629734656
## Description
i upgrade mxnet version from 1.0 to 2.0. I load the model which is trained at 1.0 in mxnet 2.0, and when i train the model, it came across the situation that it stops after 30 batches, which seems to be hanged.
### Error Message
(Paste the complete error message. Please also include stack trace by setting environment variable `DMLC_LOG_STACK_TRACE_DEPTH=10` before running your script.)
There is no error information, and it seems to be hanged!
```
+ export DMLC_LOG_STACK_TRACE_DEPTH=10
+ DMLC_LOG_STACK_TRACE_DEPTH=10
+ curl --retry 10 -s https://raw.githubusercontent.com/dmlc/gluon-nlp/master/tools/diagnose.py
+ /thirdparty/bin/python3 src/train.py
20
INFO:root:['dense', 'cate', 'sparse', 'field_0', 'field_1', 'field_2', 'field_3', 'field_4', 'fi
eld_5', 'field_6']
INFO:root:only use embedding model
[10:37:49] src/base.cc:51: Upgrade advisory: this mxnet has been built against cuda library vers
ion 9010, which is older than the oldest version tested by CI (10000). Set MXNET_CUDA_LIB_CHECK
ING=0 to quiet this warning.
INFO:root:Training started ...
INFO:root:Epoch[0] Batch [0-10] Speed: 1817.71 samples/sec auc=0.500820 multi_log
loss=10.058306 multi_mse=0.000000
INFO:root:batch=10, forward_backward=21ms, update=174ms, update_metric=6679ms, data=15703ms, tot
al=22579ms
INFO:root:Epoch[0] Batch [10-20] Speed: 3873.38 samples/sec auc=0.513181 multi_log
loss=7.157333 multi_mse=0.974069
INFO:root:batch=20, forward_backward=17ms, update=185ms, update_metric=4430ms, data=5941ms, tota
l=10574ms
INFO:root:Epoch[0] Batch [20-30] Speed: 4769.79 samples/sec auc=0.539163 multi_log
loss=4.971608 multi_mse=0.000000
INFO:root:batch=30, forward_backward=13ms, update=121ms, update_metric=3803ms, data=4648ms, tota
l=8586ms
```
## To Reproduce
(If you developed your own code, please provide a short script that reproduces the error. For existing examples, please provide link.)
it may be diffult to reproduce my problem
I implement a DataIter through c++ mxnet source code to support multi-storage and multi-label sample as followed, and it runs well at mxnet.
The row is splited by ^A(\001) as folowed. The first column is label, and the second column is dense feature, and the third column is categorical feature, and the the fourth column is multi-hot categorical feature which can be splited by comma , and the fifth column is sparse feature which is support wide input for google wide and deep model.
### Steps to reproduce
(Paste the commands you ran that produced the error.)
1.
2.
## What have you tried to solve it?
1.
2.
## Environment
cuda-9.0
gcc 8.4
centos 7.2
python 3.7
We recommend using our script for collecting the diagnositc information. Run the following command and paste the outputs below:
`curl --retry 10 -s https://raw.githubusercontent.com/dmlc/gluon-nlp/master/tools/diagnose.py | python`
There is no information, and it seems to be hanged.
----------------------------------------------------------------
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
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[GitHub] [incubator-mxnet] leezu commented on issue #18344: Failed to train model trained by mxnet 1.0 in mxnet 2.0
Posted by GitBox <gi...@apache.org>.
leezu commented on issue #18344:
URL: https://github.com/apache/incubator-mxnet/issues/18344#issuecomment-630459136
@zhreshold
> I implement a DataIter through c++ mxnet source code to support multi-storage and multi-label sample as followed, and it runs well at mxnet.
----------------------------------------------------------------
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[GitHub] [incubator-mxnet] moveforever commented on issue #18344: Failed to train model trained by mxnet 1.0 in mxnet 2.0
Posted by GitBox <gi...@apache.org>.
moveforever commented on issue #18344:
URL: https://github.com/apache/incubator-mxnet/issues/18344#issuecomment-634310331
The related code is listed in https://github.com/apache/incubator-mxnet/issues/18346.
The dataiter can be iterated. however, it appear that only iterates 20-30 batch then stops when i upgradded to mxnet2.0.
----------------------------------------------------------------
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[GitHub] [incubator-mxnet] moveforever edited a comment on issue #18344: Failed to train model trained by mxnet 1.0 in mxnet 2.0
Posted by GitBox <gi...@apache.org>.
moveforever edited a comment on issue #18344:
URL: https://github.com/apache/incubator-mxnet/issues/18344#issuecomment-629734656
## Description
i upgrade mxnet version from 1.0 to 2.0. I load the model which is trained at 1.0 in mxnet 2.0, and when i train the model, it came across the situation that it stops after 30 batches, which seems to be hanged.
### Error Message
(Paste the complete error message. Please also include stack trace by setting environment variable `DMLC_LOG_STACK_TRACE_DEPTH=10` before running your script.)
There is no error information, and it seems to be hanged!
```
+ export DMLC_LOG_STACK_TRACE_DEPTH=10
+ DMLC_LOG_STACK_TRACE_DEPTH=10
+ curl --retry 10 -s https://raw.githubusercontent.com/dmlc/gluon-nlp/master/tools/diagnose.py
+ /thirdparty/bin/python3 src/train.py
INFO:root:current path is: /cephfs/group/omg-omgmobile-app-tencent-sports/qomozheng/project/mult
i_obj_opt
20
INFO:root:['dense', 'cate', 'sparse', 'field_0', 'field_1', 'field_2', 'field_3', 'field_4', 'fi
eld_5', 'field_6']
INFO:root:only use embedding model
[10:37:49] src/base.cc:51: Upgrade advisory: this mxnet has been built against cuda library vers
ion 9010, which is older than the oldest version tested by CI (10000). Set MXNET_CUDA_LIB_CHECK
ING=0 to quiet this warning.
INFO:root:Training started ...
INFO:root:Epoch[0] Batch [0-10] Speed: 1817.71 samples/sec auc=0.500820 multi_log
loss=10.058306 multi_mse=0.000000
INFO:root:batch=10, forward_backward=21ms, update=174ms, update_metric=6679ms, data=15703ms, tot
al=22579ms
INFO:root:Epoch[0] Batch [10-20] Speed: 3873.38 samples/sec auc=0.513181 multi_log
loss=7.157333 multi_mse=0.974069
INFO:root:batch=20, forward_backward=17ms, update=185ms, update_metric=4430ms, data=5941ms, tota
l=10574ms
INFO:root:Epoch[0] Batch [20-30] Speed: 4769.79 samples/sec auc=0.539163 multi_log
loss=4.971608 multi_mse=0.000000
INFO:root:batch=30, forward_backward=13ms, update=121ms, update_metric=3803ms, data=4648ms, tota
l=8586ms
```
## To Reproduce
(If you developed your own code, please provide a short script that reproduces the error. For existing examples, please provide link.)
### Steps to reproduce
(Paste the commands you ran that produced the error.)
it may be diffult to reproduce my problem
I implement a DataIter through c++ mxnet source code to support multi-storage and multi-label sample as followed, and it runs well at mxnet.
The row is splited by ^A(\001) as folowed. The first column is label, and the second column is dense feature, and the third column is categorical feature, and the the fourth column is multi-hot categorical feature which can be splited by comma , and the fifth column is sparse feature which is support wide input for google wide and deep model.
1.
2.
## What have you tried to solve it?
1.
2.
## Environment
cuda-9.0
gcc 8.4
centos 7.2
python 3.7
We recommend using our script for collecting the diagnositc information. Run the following command and paste the outputs below:
`curl --retry 10 -s https://raw.githubusercontent.com/dmlc/gluon-nlp/master/tools/diagnose.py | python`
There is no information, and it seems to be hanged.
----------------------------------------------------------------
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
[GitHub] [incubator-mxnet] moveforever edited a comment on issue #18344: Failed to train model trained by mxnet 1.0 in mxnet 2.0
Posted by GitBox <gi...@apache.org>.
moveforever edited a comment on issue #18344:
URL: https://github.com/apache/incubator-mxnet/issues/18344#issuecomment-629734656
## Description
i upgrade mxnet version from 1.0 to 2.0. I load the model which is trained at 1.0 in mxnet 2.0, and when i train the model, it came across the situation that it stops after 30 batches, which seems to be hanged.
### Error Message
(Paste the complete error message. Please also include stack trace by setting environment variable `DMLC_LOG_STACK_TRACE_DEPTH=10` before running your script.)
There is no error information, and it seems to be hanged!
```
+ export DMLC_LOG_STACK_TRACE_DEPTH=10
+ DMLC_LOG_STACK_TRACE_DEPTH=10
+ curl --retry 10 -s https://raw.githubusercontent.com/dmlc/gluon-nlp/master/tools/diagnose.py
+ /thirdparty/bin/python3 src/train.py
INFO:root:current path is: /cephfs/group/omg-omgmobile-app-tencent-sports/qomozheng/project/mult
i_obj_opt
20
INFO:root:['dense', 'cate', 'sparse', 'field_0', 'field_1', 'field_2', 'field_3', 'field_4', 'fi
eld_5', 'field_6']
INFO:root:only use embedding model
[10:37:49] src/base.cc:51: Upgrade advisory: this mxnet has been built against cuda library vers
ion 9010, which is older than the oldest version tested by CI (10000). Set MXNET_CUDA_LIB_CHECK
ING=0 to quiet this warning.
INFO:root:Training started ...
INFO:root:Epoch[0] Batch [0-10] Speed: 1817.71 samples/sec auc=0.500820 multi_log
loss=10.058306 multi_mse=0.000000
INFO:root:batch=10, forward_backward=21ms, update=174ms, update_metric=6679ms, data=15703ms, tot
al=22579ms
INFO:root:Epoch[0] Batch [10-20] Speed: 3873.38 samples/sec auc=0.513181 multi_log
loss=7.157333 multi_mse=0.974069
INFO:root:batch=20, forward_backward=17ms, update=185ms, update_metric=4430ms, data=5941ms, tota
l=10574ms
INFO:root:Epoch[0] Batch [20-30] Speed: 4769.79 samples/sec auc=0.539163 multi_log
loss=4.971608 multi_mse=0.000000
INFO:root:batch=30, forward_backward=13ms, update=121ms, update_metric=3803ms, data=4648ms, tota
l=8586ms
```
## To Reproduce
(If you developed your own code, please provide a short script that reproduces the error. For existing examples, please provide link.)
### Steps to reproduce
(Paste the commands you ran that produced the error.)
I implement a DataIter through c++ mxnet source code to support multi-storage sample as followed, and it runs well at mxnet.
The row is splited by ^A(\001) as folowed.
1.
2.
## What have you tried to solve it?
1.
2.
## Environment
cuda-9.0
gcc 8.4
centos 7.2
python 3.7
We recommend using our script for collecting the diagnositc information. Run the following command and paste the outputs below:
`curl --retry 10 -s https://raw.githubusercontent.com/dmlc/gluon-nlp/master/tools/diagnose.py | python`
There is no information, and it seems to be hanged.
----------------------------------------------------------------
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
For queries about this service, please contact Infrastructure at:
users@infra.apache.org
[GitHub] [incubator-mxnet] moveforever edited a comment on issue #18344: Failed to train model trained by mxnet 1.0 in mxnet 2.0
Posted by GitBox <gi...@apache.org>.
moveforever edited a comment on issue #18344:
URL: https://github.com/apache/incubator-mxnet/issues/18344#issuecomment-629734656
## Description
i upgrade mxnet version from 1.0 to 2.0. I load the model which is trained at 1.0 in mxnet 2.0, and when i train the model, it came across the situation that it stops after 30 batches, which seems to be hanged.
### Error Message
(Paste the complete error message. Please also include stack trace by setting environment variable `DMLC_LOG_STACK_TRACE_DEPTH=10` before running your script.)
There is no error information, and it seems to be hanged!
```
+ export DMLC_LOG_STACK_TRACE_DEPTH=10
+ DMLC_LOG_STACK_TRACE_DEPTH=10
+ curl --retry 10 -s https://raw.githubusercontent.com/dmlc/gluon-nlp/master/tools/diagnose.py
+ /thirdparty/bin/python3 src/train.py
INFO:root:current path is: /cephfs/group/omg-omgmobile-app-tencent-sports/qomozheng/project/mult
i_obj_opt
20
INFO:root:['dense', 'cate', 'sparse', 'field_0', 'field_1', 'field_2', 'field_3', 'field_4', 'fi
eld_5', 'field_6']
INFO:root:only use embedding model
[10:37:49] src/base.cc:51: Upgrade advisory: this mxnet has been built against cuda library vers
ion 9010, which is older than the oldest version tested by CI (10000). Set MXNET_CUDA_LIB_CHECK
ING=0 to quiet this warning.
INFO:root:Training started ...
INFO:root:Epoch[0] Batch [0-10] Speed: 1817.71 samples/sec auc=0.500820 multi_log
loss=10.058306 multi_mse=0.000000
INFO:root:batch=10, forward_backward=21ms, update=174ms, update_metric=6679ms, data=15703ms, tot
al=22579ms
INFO:root:Epoch[0] Batch [10-20] Speed: 3873.38 samples/sec auc=0.513181 multi_log
loss=7.157333 multi_mse=0.974069
INFO:root:batch=20, forward_backward=17ms, update=185ms, update_metric=4430ms, data=5941ms, tota
l=10574ms
INFO:root:Epoch[0] Batch [20-30] Speed: 4769.79 samples/sec auc=0.539163 multi_log
loss=4.971608 multi_mse=0.000000
INFO:root:batch=30, forward_backward=13ms, update=121ms, update_metric=3803ms, data=4648ms, tota
l=8586ms
```
## To Reproduce
(If you developed your own code, please provide a short script that reproduces the error. For existing examples, please provide link.)
### Steps to reproduce
(Paste the commands you ran that produced the error.)
1.
2.
## What have you tried to solve it?
1.
2.
## Environment
cuda-9.0
gcc 8.4
centos 7.2
python 3.7
We recommend using our script for collecting the diagnositc information. Run the following command and paste the outputs below:
`curl --retry 10 -s https://raw.githubusercontent.com/dmlc/gluon-nlp/master/tools/diagnose.py | python`
There is no information, and it seems to be hanged.
----------------------------------------------------------------
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
For queries about this service, please contact Infrastructure at:
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[GitHub] [incubator-mxnet] szha commented on issue #18344: Failed to train model trained by mxnet 1.0 in mxnet 2.0
Posted by GitBox <gi...@apache.org>.
szha commented on issue #18344:
URL: https://github.com/apache/incubator-mxnet/issues/18344#issuecomment-629731015
@moveforever in order to others to help, you will need to provide the information for others to reproduce the problem you see. Consider using the following template.
```
## Description
(A clear and concise description of what the bug is.)
### Error Message
(Paste the complete error message. Please also include stack trace by setting environment variable `DMLC_LOG_STACK_TRACE_DEPTH=10` before running your script.)
## To Reproduce
(If you developed your own code, please provide a short script that reproduces the error. For existing examples, please provide link.)
### Steps to reproduce
(Paste the commands you ran that produced the error.)
1.
2.
## What have you tried to solve it?
1.
2.
## Environment
We recommend using our script for collecting the diagnositc information. Run the following command and paste the outputs below:
`curl --retry 10 -s https://raw.githubusercontent.com/dmlc/gluon-nlp/master/tools/diagnose.py | python`
# paste outputs here
```
----------------------------------------------------------------
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