[jira] [Created] (SINGA-493) Updata news and website
YEUNG SAI HO created SINGA-493: -- Summary: Updata news and website Key: SINGA-493 URL: https://issues.apache.org/jira/browse/SINGA-493 Project: Singa Issue Type: Improvement Components: Documentation Reporter: YEUNG SAI HO I add a JIRA ticket to update news of SINGA. There are two steps: 1. PR to update the doc/en/index.rst (may modify or add related files) 2. Follow the steps in http://singa.apache.org/en/develop/contribute-docs.html to submit PR for updating the website -- This message was sent by Atlassian Jira (v8.3.4#803005)
[jira] [Updated] (SINGA-493) Update news and website
[ https://issues.apache.org/jira/browse/SINGA-493?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] YEUNG SAI HO updated SINGA-493: --- Description: I add a JIRA ticket to update news of SINGA. There are two steps: 1. PR to update the doc/en/index.rst (may modify or add related files) 2. After the above mentioned PR in is merged, follow the steps in http://singa.apache.org/en/develop/contribute-docs.html to submit PR for updating the website was: I add a JIRA ticket to update news of SINGA. There are two steps: 1. PR to update the doc/en/index.rst (may modify or add related files) 2. Follow the steps in http://singa.apache.org/en/develop/contribute-docs.html to submit PR for updating the website > Update news and website > --- > > Key: SINGA-493 > URL: https://issues.apache.org/jira/browse/SINGA-493 > Project: Singa > Issue Type: Improvement > Components: Documentation >Reporter: YEUNG SAI HO >Priority: Major > > I add a JIRA ticket to update news of SINGA. There are two steps: > 1. PR to update the doc/en/index.rst (may modify or add related files) > 2. After the above mentioned PR in is merged, follow the steps in > http://singa.apache.org/en/develop/contribute-docs.html to submit PR for > updating the website -- This message was sent by Atlassian Jira (v8.3.4#803005)
[jira] [Updated] (SINGA-493) Update news and website
[ https://issues.apache.org/jira/browse/SINGA-493?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] YEUNG SAI HO updated SINGA-493: --- Summary: Update news and website (was: Updata news and website) > Update news and website > --- > > Key: SINGA-493 > URL: https://issues.apache.org/jira/browse/SINGA-493 > Project: Singa > Issue Type: Improvement > Components: Documentation >Reporter: YEUNG SAI HO >Priority: Major > > I add a JIRA ticket to update news of SINGA. There are two steps: > 1. PR to update the doc/en/index.rst (may modify or add related files) > 2. Follow the steps in > http://singa.apache.org/en/develop/contribute-docs.html to submit PR for > updating the website -- This message was sent by Atlassian Jira (v8.3.4#803005)
[GitHub] [incubator-singa] joddiy commented on issue #541: added 4d test on batchnorm
joddiy commented on issue #541: added 4d test on batchnorm URL: https://github.com/apache/incubator-singa/pull/541#issuecomment-538211845 the return of _CpuBatchNormForwardInference_ should be y, var, mean, not just y. could you fix it? 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: us...@infra.apache.org With regards, Apache Git Services
[GitHub] [incubator-singa] joddiy commented on issue #540: added softmax with axis
joddiy commented on issue #540: added softmax with axis URL: https://github.com/apache/incubator-singa/pull/540#issuecomment-538211628 still has some problems, the output of multiple dimension inputs is not correct. please check: ``` x_0 = np.array([[0, 1, 2, 3], [1, 10001, 10002, 10003]]).astype(np.float32) # axis is 1 # expected output [[0.0320586, 0.08714432, 0.23688284, 0.64391428], # [0.0320586, 0.08714432, 0.23688284, 0.64391428]] ``` 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: us...@infra.apache.org With regards, Apache Git Services
[jira] [Commented] (SINGA-491) Code Cleaning with the Reference of LGTM Analysis Result
[ https://issues.apache.org/jira/browse/SINGA-491?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16944187#comment-16944187 ] ASF subversion and git services commented on SINGA-491: --- Commit acabafbfbec42a597037b245e194ce7d5167f10d in incubator-singa's branch refs/heads/master from Wei Wang [ https://gitbox.apache.org/repos/asf?p=incubator-singa.git;h=acabafb ] Merge pull request #543 from chrishkchris/SINGA-491_3 SINGA-491 Use const reference for CopyData and ResetLike from Tensor Input > Code Cleaning with the Reference of LGTM Analysis Result > > > Key: SINGA-491 > URL: https://issues.apache.org/jira/browse/SINGA-491 > Project: Singa > Issue Type: Improvement > Components: Core >Reporter: YEUNG SAI HO >Priority: Major > Time Spent: 1h 20m > Remaining Estimate: 0h > > Code Cleaning with the Reference of LGTM Analysis Result > Since LGTM has been applied for our code analysis (see SINGA-484), I added > this JIRA ticket so I can also help cleaning the code. > At my first glance, the code cleaning according to many issues alerted by > LGTM seems to be not difficult for me. -- This message was sent by Atlassian Jira (v8.3.4#803005)
[jira] [Commented] (SINGA-491) Code Cleaning with the Reference of LGTM Analysis Result
[ https://issues.apache.org/jira/browse/SINGA-491?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16944188#comment-16944188 ] ASF subversion and git services commented on SINGA-491: --- Commit acabafbfbec42a597037b245e194ce7d5167f10d in incubator-singa's branch refs/heads/master from Wei Wang [ https://gitbox.apache.org/repos/asf?p=incubator-singa.git;h=acabafb ] Merge pull request #543 from chrishkchris/SINGA-491_3 SINGA-491 Use const reference for CopyData and ResetLike from Tensor Input > Code Cleaning with the Reference of LGTM Analysis Result > > > Key: SINGA-491 > URL: https://issues.apache.org/jira/browse/SINGA-491 > Project: Singa > Issue Type: Improvement > Components: Core >Reporter: YEUNG SAI HO >Priority: Major > Time Spent: 1h 20m > Remaining Estimate: 0h > > Code Cleaning with the Reference of LGTM Analysis Result > Since LGTM has been applied for our code analysis (see SINGA-484), I added > this JIRA ticket so I can also help cleaning the code. > At my first glance, the code cleaning according to many issues alerted by > LGTM seems to be not difficult for me. -- This message was sent by Atlassian Jira (v8.3.4#803005)
[GitHub] [incubator-singa] nudles merged pull request #543: SINGA-491 Use const reference for CopyData and ResetLike from Tensor Input
nudles merged pull request #543: SINGA-491 Use const reference for CopyData and ResetLike from Tensor Input URL: https://github.com/apache/incubator-singa/pull/543 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: us...@infra.apache.org With regards, Apache Git Services
[jira] [Commented] (SINGA-492) add Food(lg) news in the documentation
[ https://issues.apache.org/jira/browse/SINGA-492?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16944185#comment-16944185 ] ASF subversion and git services commented on SINGA-492: --- Commit 663789148380c52147363b9aec7eaaaeaaf4665a in incubator-singa's branch refs/heads/master from Wei Wang [ https://gitbox.apache.org/repos/asf?p=incubator-singa.git;h=6637891 ] Merge pull request #542 from lzjpaul/19-10-3-foodlg SINGA-492 add Food(lg) news in the documentation > add Food(lg) news in the documentation > -- > > Key: SINGA-492 > URL: https://issues.apache.org/jira/browse/SINGA-492 > Project: Singa > Issue Type: New Feature >Reporter: Luo Zhaojing >Priority: Minor > Time Spent: 20m > Remaining Estimate: 0h > -- This message was sent by Atlassian Jira (v8.3.4#803005)
[jira] [Commented] (SINGA-492) add Food(lg) news in the documentation
[ https://issues.apache.org/jira/browse/SINGA-492?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16944184#comment-16944184 ] ASF subversion and git services commented on SINGA-492: --- Commit aa83319df00476a576bd3c8602f11eb63dbf52e4 in incubator-singa's branch refs/heads/master from zhaojing [ https://gitbox.apache.org/repos/asf?p=incubator-singa.git;h=aa83319 ] SINGA-492 add Food(lg) news in the documentation -add Food(lg) news in the SINGA homepage > add Food(lg) news in the documentation > -- > > Key: SINGA-492 > URL: https://issues.apache.org/jira/browse/SINGA-492 > Project: Singa > Issue Type: New Feature >Reporter: Luo Zhaojing >Priority: Minor > Time Spent: 20m > Remaining Estimate: 0h > -- This message was sent by Atlassian Jira (v8.3.4#803005)
[GitHub] [incubator-singa] chrishkchris opened a new pull request #543: SINGA-491 Use const reference when we use CopyData and ResetLike from Tensor Input
chrishkchris opened a new pull request #543: SINGA-491 Use const reference when
we use CopyData and ResetLike from Tensor Input
URL: https://github.com/apache/incubator-singa/pull/543
This is to fix the remaining C language alert from LGTM:
There are some functions using ResetLike and CopyData to copy the data from
the tensor input. This PR changes the input type from "Tensor" to "const
Tensor&"
However, it seems that the src/model/layer is used by the old
optimizer/model, it does not have effect on the autograd.py based model.
If I am correct, this avoid the system copying the input tensor with the
tensor copy constructor, instead it uses the address of the input pointer as
reference.
For a verification, the batchnorm in src/model/layer is used by the old
optimizer (not the autograd one), and hence we use the old resnet example to
verify the training loss reduction progress.
```
ubuntu@ip-172-31-42-250:~/incubator-singa/examples/cifar10$ python3 train.py
resnet cifar-10-batches-py
Loading data ..
Loading data file cifar-10-batches-py/data_batch_1
Loading data file cifar-10-batches-py/data_batch_2
Loading data file cifar-10-batches-py/data_batch_3
Loading data file cifar-10-batches-py/data_batch_4
Loading data file cifar-10-batches-py/data_batch_5
Loading data file cifar-10-batches-py/test_batch
('conv1', (16, 32, 32))
('bn1', (16, 32, 32))
('relu1', (16, 32, 32))
('2a-split', [(16, 32, 32), (16, 32, 32)])
('2a-br1-conv1', (16, 32, 32))
('2a-br1-bn1', (16, 32, 32))
('2a-br1-relu', (16, 32, 32))
('2a-br1-conv2', (16, 32, 32))
('2a-br1-bn2', (16, 32, 32))
('2a-merge', [(16, 32, 32), (16, 32, 32)])
('2b-split', [(16, 32, 32), (16, 32, 32)])
('2b-br1-conv1', (16, 32, 32))
('2b-br1-bn1', (16, 32, 32))
('2b-br1-relu', (16, 32, 32))
('2b-br1-conv2', (16, 32, 32))
('2b-br1-bn2', (16, 32, 32))
('2b-merge', [(16, 32, 32), (16, 32, 32)])
('2c-split', [(16, 32, 32), (16, 32, 32)])
('2c-br1-conv1', (16, 32, 32))
('2c-br1-bn1', (16, 32, 32))
('2c-br1-relu', (16, 32, 32))
('2c-br1-conv2', (16, 32, 32))
('2c-br1-bn2', (16, 32, 32))
('2c-merge', [(16, 32, 32), (16, 32, 32)])
('3a-split', [(16, 32, 32), (16, 32, 32)])
('3a-br2-conv', (32, 16, 16))
('3a-br2-bn', (32, 16, 16))
('3a-br1-conv1', (32, 16, 16))
('3a-br1-bn1', (32, 16, 16))
('3a-br1-relu', (32, 16, 16))
('3a-br1-conv2', (32, 16, 16))
('3a-br1-bn2', (32, 16, 16))
('3a-merge', [(32, 16, 16), (32, 16, 16)])
('3b-split', [(32, 16, 16), (32, 16, 16)])
('3b-br1-conv1', (32, 16, 16))
('3b-br1-bn1', (32, 16, 16))
('3b-br1-relu', (32, 16, 16))
('3b-br1-conv2', (32, 16, 16))
('3b-br1-bn2', (32, 16, 16))
('3b-merge', [(32, 16, 16), (32, 16, 16)])
('3c-split', [(32, 16, 16), (32, 16, 16)])
('3c-br1-conv1', (32, 16, 16))
('3c-br1-bn1', (32, 16, 16))
('3c-br1-relu', (32, 16, 16))
('3c-br1-conv2', (32, 16, 16))
('3c-br1-bn2', (32, 16, 16))
('3c-merge', [(32, 16, 16), (32, 16, 16)])
('4a-split', [(32, 16, 16), (32, 16, 16)])
('4a-br2-conv', (64, 8, 8))
('4a-br2-bn', (64, 8, 8))
('4a-br1-conv1', (64, 8, 8))
('4a-br1-bn1', (64, 8, 8))
('4a-br1-relu', (64, 8, 8))
('4a-br1-conv2', (64, 8, 8))
('4a-br1-bn2', (64, 8, 8))
('4a-merge', [(64, 8, 8), (64, 8, 8)])
('4b-split', [(64, 8, 8), (64, 8, 8)])
('4b-br1-conv1', (64, 8, 8))
('4b-br1-bn1', (64, 8, 8))
('4b-br1-relu', (64, 8, 8))
('4b-br1-conv2', (64, 8, 8))
('4b-br1-bn2', (64, 8, 8))
('4b-merge', [(64, 8, 8), (64, 8, 8)])
('4c-split', [(64, 8, 8), (64, 8, 8)])
('4c-br1-conv1', (64, 8, 8))
('4c-br1-bn1', (64, 8, 8))
('4c-br1-relu', (64, 8, 8))
('4c-br1-conv2', (64, 8, 8))
('4c-br1-bn2', (64, 8, 8))
('4c-merge', [(64, 8, 8), (64, 8, 8)])
('pool4', (64, 1, 1))
('flat', (64,))
('ip5', (10,))
Start intialization
Start intialization
Using GPU
Epoch=0:
100%|██|
500/500 [00:17<00:00, 28.18it/s, accuracy=0.59, loss=1.13]
Training loss = 1.418575, training accuracy = 0.481940, lr = 0.10
Test loss = 1.145096, test accuracy = 0.586800
Epoch=1:
100%|█|
500/500 [00:17<00:00, 29.34it/s, accuracy=0.76, loss=0.784]
Training loss = 0.996122, training accuracy = 0.645940, lr = 0.10
Test loss = 0.947394, test accuracy = 0.665900
Epoch=2:
100%|█|
500/500 [00:17<00:00, 28.81it/s, accuracy=0.81, loss=0.696]
Training loss = 0.812576, training accuracy = 0.713660, lr = 0.10
Test loss = 0.830808, test accuracy = 0.713700
Epoch=3:
100%|█|
500/500 [00:17<00:00, 27.96it/s, accuracy=0.81, loss=0.617]
[GitHub] [incubator-singa] lzjpaul opened a new pull request #542: SINGA-492 add Food(lg) news in the documentation
lzjpaul opened a new pull request #542: SINGA-492 add Food(lg) news in the documentation URL: https://github.com/apache/incubator-singa/pull/542 -add Food(lg) news in the SINGA homepage 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: us...@infra.apache.org With regards, Apache Git Services
[jira] [Created] (SINGA-492) add Food(lg) news in the documentation
Luo Zhaojing created SINGA-492: -- Summary: add Food(lg) news in the documentation Key: SINGA-492 URL: https://issues.apache.org/jira/browse/SINGA-492 Project: Singa Issue Type: New Feature Reporter: Luo Zhaojing -- This message was sent by Atlassian Jira (v8.3.4#803005)
[GitHub] [incubator-singa] dcslin opened a new pull request #541: added 4d test on batchnorm
dcslin opened a new pull request #541: added 4d test on batchnorm URL: https://github.com/apache/incubator-singa/pull/541 added batchnorm test adapted from `/test/python/test_onnx_backend.py` and test passed. Hi @joddiy , If current Batchnorm API could fulfil ONNX batchnorm requirement, shall we keep the current API unchanged? Kindly advise. Thanks. 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: us...@infra.apache.org With regards, Apache Git Services
