solin319 commented on a change in pull request #8373: distribute training in
fp16
URL: https://github.com/apache/incubator-mxnet/pull/8373#discussion_r168089512
##
File path: src/kvstore/kvstore_dist.h
##
@@ -272,16 +282,35 @@ class KVStoreDist : public KVStoreLocal {
gaosanyuan commented on issue #9764: Large batch size does not improve predict
speed
URL:
https://github.com/apache/incubator-mxnet/issues/9764#issuecomment-365511819
@anirudh2290
This is an automated message from the
gaosanyuan commented on issue #9764: Large batch size does not improve predict
speed
URL:
https://github.com/apache/incubator-mxnet/issues/9764#issuecomment-365484738
I use mxnet 0.12.0 to do image semantic segmentation, and the input data
size is (Batch, C, H, W). When I set Batch is 1,
gaosanyuan commented on issue #9764: Large batch size does not improve predict
speed
URL:
https://github.com/apache/incubator-mxnet/issues/9764#issuecomment-365484667
I use mxnet 0.12.0 to do image semantic segmentation, and the input data
size is (Batch, C, H, W). When I set Batch is 1,
gaosanyuan commented on issue #9764: Large batch size does not improve predict
speed
URL:
https://github.com/apache/incubator-mxnet/issues/9764#issuecomment-365484667
I use mxnet 0.12.0 to do image semantic segmentation, and the input data
size is (Batch, C, H, W). When I set Batch is 1,
ptrendx commented on issue #9774: mx.io.ImageRecordIter does not respect dtype
argument
URL:
https://github.com/apache/incubator-mxnet/issues/9774#issuecomment-365484238
Engine does not seem to differentiate between first layer and subsequent
layers on that it considers data going into
ptrendx commented on issue #9774: mx.io.ImageRecordIter does not respect dtype
argument
URL:
https://github.com/apache/incubator-mxnet/issues/9774#issuecomment-365483069
I don't think it will perform better than producing fp32 and then casting to
fp16 at the beginning of the training.
cccorn commented on issue #9758: unknown output shape before inference
URL:
https://github.com/apache/incubator-mxnet/issues/9758#issuecomment-365481468
@ZiyueHuang Thank you for your response.
There is a maximum shape of my operator's output. Did you mean the output
and actual size
safrooze commented on issue #9213: Crash when MXNet API called before spawning
multiprocess
URL:
https://github.com/apache/incubator-mxnet/issues/9213#issuecomment-365481034
This issue appears to be fixed by the change in
[#8995](https://github.com/apache/incubator-mxnet/pull/8995) which
sxjscience commented on a change in pull request #9747: Add
contrib.rand_log_uniform
URL: https://github.com/apache/incubator-mxnet/pull/9747#discussion_r168065613
##
File path: python/mxnet/ndarray/contrib.py
##
@@ -18,9 +18,76 @@
# coding: utf-8
# pylint:
eric-haibin-lin commented on issue #9675: Add contrib.compute_accidental_hits
operator for candidate sampling
URL: https://github.com/apache/incubator-mxnet/pull/9675#issuecomment-365476686
Closing it for now until the hash issue is fixed.
eric-haibin-lin closed pull request #9675: Add contrib.compute_accidental_hits
operator for candidate sampling
URL: https://github.com/apache/incubator-mxnet/pull/9675
This is a PR merged from a forked repository.
As GitHub hides the original diff on merge, it is displayed below for
the
eric-haibin-lin commented on a change in pull request #9747: Add
contrib.rand_log_uniform
URL: https://github.com/apache/incubator-mxnet/pull/9747#discussion_r168063477
##
File path: python/mxnet/ndarray/contrib.py
##
@@ -18,9 +18,76 @@
# coding: utf-8
# pylint:
feevos commented on issue #9288: Get HybridBlock layer shape on runtime
URL:
https://github.com/apache/incubator-mxnet/issues/9288#issuecomment-365475030
Dear all, do we have any progress on this?
Thank you very much for your time.
eric-haibin-lin commented on issue #9625: sparse regression operators
URL: https://github.com/apache/incubator-mxnet/pull/9625#issuecomment-365471224
@marcoabreu any idea on the error msg
```
c:\jenkins_slave\workspace\build-cpu@3\src\operator\mxnet_op.h(456): fatal
error C1002:
rahul003 commented on a change in pull request #8373: distribute training in
fp16
URL: https://github.com/apache/incubator-mxnet/pull/8373#discussion_r168058685
##
File path: src/kvstore/kvstore_dist.h
##
@@ -272,16 +282,35 @@ class KVStoreDist : public KVStoreLocal {
DickJC123 opened a new pull request #9791: CI test randomness 3
URL: https://github.com/apache/incubator-mxnet/pull/9791
## Description ##
This is a rebasing and partial squashing of the stale "ci test randomness2"
PR #8526 . It's based on the premise that the CI should test the
solin319 commented on issue #9782: problem in local kvstore
URL:
https://github.com/apache/incubator-mxnet/issues/9782#issuecomment-365464602
We train resnet50 in imageclassification with kvstore=local.
solin319 commented on a change in pull request #8373: distribute training in
fp16
URL: https://github.com/apache/incubator-mxnet/pull/8373#discussion_r168054096
##
File path: src/kvstore/kvstore_dist_server.h
##
@@ -378,25 +379,46 @@ class KVStoreDistServer {
if
solin319 commented on a change in pull request #8373: distribute training in
fp16
URL: https://github.com/apache/incubator-mxnet/pull/8373#discussion_r168054096
##
File path: src/kvstore/kvstore_dist_server.h
##
@@ -378,25 +379,46 @@ class KVStoreDistServer {
if
dwSun commented on a change in pull request #9614: MobileNetV2
URL: https://github.com/apache/incubator-mxnet/pull/9614#discussion_r168051072
##
File path: python/mxnet/gluon/model_zoo/vision/mobilenet.py
##
@@ -74,13 +123,69 @@ def hybrid_forward(self, F, x):
x =
parallelgithub closed issue #9781: Where to find argument definition with
String type
URL: https://github.com/apache/incubator-mxnet/issues/9781
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parallelgithub commented on a change in pull request #9771: Modify NDArrayIter
constructor to receive tuple (i.e. dict in Python)?
URL: https://github.com/apache/incubator-mxnet/pull/9771#discussion_r168052820
##
File path:
mbaijal commented on issue #8913: MXNet 1.0.0 Release Feedback: Source Headers
and License Files
URL:
https://github.com/apache/incubator-mxnet/issues/8913#issuecomment-365458977
@lupesko yes, I am tracking these and other issues in [this
mbaijal commented on issue #8913: MXNet 1.0.0 Release Feedback: Source Headers
and License Files
URL:
https://github.com/apache/incubator-mxnet/issues/8913#issuecomment-365458977
@lupesko yes, I am tracking these and other issues in [this
dwSun commented on a change in pull request #9614: MobileNetV2
URL: https://github.com/apache/incubator-mxnet/pull/9614#discussion_r168051072
##
File path: python/mxnet/gluon/model_zoo/vision/mobilenet.py
##
@@ -74,13 +123,69 @@ def hybrid_forward(self, F, x):
x =
lupesko commented on issue #8913: MXNet 1.0.0 Release Feedback: Source Headers
and License Files
URL:
https://github.com/apache/incubator-mxnet/issues/8913#issuecomment-365458375
@mbaijal are you or anyone else following up on this? 1.1.0 is going out
soon...
stonedl3 commented on issue #9766: DeepLearning on Imagenet with mxnet issues
translating .lst to .rec files
URL:
https://github.com/apache/incubator-mxnet/issues/9766#issuecomment-365457452
I am traveling for the next couple of days. I will post the script when I
return. I have not
lupesko commented on issue #9781: Where to find argument definition with String
type
URL:
https://github.com/apache/incubator-mxnet/issues/9781#issuecomment-365454884
For MXNet questions, please use [discuss.mxnet.io](https://discuss.mxnet.io/)
Thanks!
@sandeep-krishnamurthy can
szha commented on issue #6872: HDF5 DataIter Python
URL:
https://github.com/apache/incubator-mxnet/issues/6872#issuecomment-365452982
@apache/mxnet-committers: This issue has been inactive for the past 90 days.
It has no label and needs triage.
For general "how-to" questions, our
zhreshold commented on a change in pull request #9614: MobileNetV2
URL: https://github.com/apache/incubator-mxnet/pull/9614#discussion_r168043288
##
File path: python/mxnet/gluon/model_zoo/vision/mobilenet.py
##
@@ -74,13 +123,69 @@ def hybrid_forward(self, F, x):
rahul003 commented on a change in pull request #8373: distribute training in
fp16
URL: https://github.com/apache/incubator-mxnet/pull/8373#discussion_r168042933
##
File path: src/kvstore/kvstore_dist_server.h
##
@@ -378,25 +379,46 @@ class KVStoreDistServer {
if
rahul003 commented on a change in pull request #8373: distribute training in
fp16
URL: https://github.com/apache/incubator-mxnet/pull/8373#discussion_r168042933
##
File path: src/kvstore/kvstore_dist_server.h
##
@@ -378,25 +379,46 @@ class KVStoreDistServer {
if
zhreshold commented on a change in pull request #9614: MobileNetV2
URL: https://github.com/apache/incubator-mxnet/pull/9614#discussion_r168042820
##
File path: python/mxnet/gluon/model_zoo/vision/mobilenet.py
##
@@ -74,13 +123,69 @@ def hybrid_forward(self, F, x):
szha opened a new pull request #9790: make array.reshape compatible with numpy
URL: https://github.com/apache/incubator-mxnet/pull/9790
## Description ##
Allow n ints as input to array.reshape.
## Checklist ##
### Essentials ###
- [x] Passed code style checking (`make lint`)
rf987 closed issue #9787: net.collect_params() omits Dropout layers
URL: https://github.com/apache/incubator-mxnet/issues/9787
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marcoabreu commented on a change in pull request #9777: [MX-9588] Add micro
averaging strategy for F1 metric
URL: https://github.com/apache/incubator-mxnet/pull/9777#discussion_r168025671
##
File path: tests/python/unittest/test_metric.py
##
@@ -56,18 +55,51 @@ def
sxjscience commented on issue #9586: mx.metric F1 is using numpy logic
URL:
https://github.com/apache/incubator-mxnet/issues/9586#issuecomment-365429204
OK, I'll PR after it's merged.
This is an automated message from the
szha commented on issue #9586: mx.metric F1 is using numpy logic
URL:
https://github.com/apache/incubator-mxnet/issues/9586#issuecomment-365429078
@sxjscience awesome. Would you propose a PR after #9777 is merged? If/when
you do, remember to report the benchmark test results from #9705
sxjscience commented on issue #9586: mx.metric F1 is using numpy logic
URL:
https://github.com/apache/incubator-mxnet/issues/9586#issuecomment-365427676
Bring discussion to the correct place. I've implemented an ndarray version
of F1 score when doing the experiments and I've included my
marcoabreu commented on issue #9616: Removing a broken tutorial from the
nightly tests
URL: https://github.com/apache/incubator-mxnet/pull/9616#issuecomment-365428986
Thanks Aaron,
since @eric-haibin-lin is on vacation, I'd like @mbaijal opinion on this.
Have you reviewed this case and
marcoabreu commented on issue #9763: Too many header files need to be included
when using C++ api
URL:
https://github.com/apache/incubator-mxnet/issues/9763#issuecomment-365428085
Good idea, please mention me in the other ones so I can label them
accordingly
sxjscience commented on issue #9586: mx.metric F1 is using numpy logic
URL:
https://github.com/apache/incubator-mxnet/issues/9586#issuecomment-365427676
Bring discussion to the correct place. I've implemented an ndarray version
of F1 score when doing the experiments and this is my code
sxjscience commented on issue #9589: mx.metric should support top-K version of
TP FP TN FN Precision Recall F1
URL:
https://github.com/apache/incubator-mxnet/issues/9589#issuecomment-365426968
Also, we need to add F1 score for multi-label classification.
szha commented on issue #9777: [MX-9588] Add micro averaging strategy for F1
metric
URL: https://github.com/apache/incubator-mxnet/pull/9777#issuecomment-365426202
@sethah do you mind running the related test from #9705 and report the
before/after change results here?
szha commented on issue #9777: [MX-9588] Add micro averaging strategy for F1
metric
URL: https://github.com/apache/incubator-mxnet/pull/9777#issuecomment-365425756
@sxjscience let's track the multi-label case in #9589
This
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new 45e8555 Some small typo fixes.
szha closed pull request #9788: Some small typo fixes.
URL: https://github.com/apache/incubator-mxnet/pull/9788
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sxjscience commented on issue #9787: net.collect_params() omits Dropout layers
URL:
https://github.com/apache/incubator-mxnet/issues/9787#issuecomment-365417024
@rf987 You can directly use `print(net)` or `logging.info(str(net))`
sxjscience commented on issue #9787: net.collect_params() omits Dropout layers
URL:
https://github.com/apache/incubator-mxnet/issues/9787#issuecomment-365417024
@rf987 You may directly try `print(net)`
This is an automated
rf987 commented on issue #9787: net.collect_params() omits Dropout layers
URL:
https://github.com/apache/incubator-mxnet/issues/9787#issuecomment-365416037
When I open old models, I use the string output of net.collect_params() to
remind me of what the network architecture was.
szha commented on issue #9787: net.collect_params() omits Dropout layers
URL:
https://github.com/apache/incubator-mxnet/issues/9787#issuecomment-365413675
That's because Dropout layer doesn't have a parameter right now.
szha commented on issue #9789: add activations doc
URL: https://github.com/apache/incubator-mxnet/pull/9789#issuecomment-365412551
Updated doc can be found at
http://mxnet-doc.s3-accelerate.dualstack.amazonaws.com/api/python/gluon/nn.html#activation-layers
szha opened a new pull request #9789: add activations doc
URL: https://github.com/apache/incubator-mxnet/pull/9789
## Description ##
add doc section for gluon activations.
## Checklist ##
### Essentials ###
- [x] To the my best knowledge, examples are either not affected by
anirudh2290 commented on issue #9772: ndarray indexing issues
URL:
https://github.com/apache/incubator-mxnet/issues/9772#issuecomment-365348247
Issue is that isinstance is not working as expected by the code and returns
false in python3. Workaround is to force the type of i to be int
rahul003 commented on issue #8373: distribute training in fp16
URL: https://github.com/apache/incubator-mxnet/pull/8373#issuecomment-365386805
@solin319 Which machines did you run the above numbers on? Let us try to
come up with an easier interface for this so we can use this on the latest
sxjscience commented on a change in pull request #9777: [MX-9588] Add micro
averaging strategy for F1 metric
URL: https://github.com/apache/incubator-mxnet/pull/9777#discussion_r16759
##
File path: python/mxnet/metric.py
##
@@ -475,8 +475,84 @@ def update(self,
sethah commented on a change in pull request #9777: [MX-9588] Add micro
averaging strategy for F1 metric
URL: https://github.com/apache/incubator-mxnet/pull/9777#discussion_r167998887
##
File path: python/mxnet/metric.py
##
@@ -475,8 +475,84 @@ def update(self, labels,
KellenSunderland opened a new pull request #9788: Some small typo fixes.
URL: https://github.com/apache/incubator-mxnet/pull/9788
Some small typo fixes.
This is an automated message from the Apache Git Service.
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sxjscience commented on issue #9777: [MX-9588] Add micro averaging strategy for
F1 metric
URL: https://github.com/apache/incubator-mxnet/pull/9777#issuecomment-365397351
Also, one thing to note is that when the output has only one-label, the
micro F1 is equivalent to accuracy
aaronmarkham opened a new pull request #9616: Removing a broken tutorial from
the nightly tests
URL: https://github.com/apache/incubator-mxnet/pull/9616
## Description ##
The predict image tutorial is broken:
https://github.com/apache/incubator-mxnet/issues/9532
It is causing the
sxjscience commented on issue #9777: [MX-9588] Add micro averaging strategy for
F1 metric
URL: https://github.com/apache/incubator-mxnet/pull/9777#issuecomment-365397351
Also, one thing to note is that when the output has only one-label, the
micro F1 is equivalent to accuracy
sxjscience commented on issue #9777: [MX-9588] Add micro averaging strategy for
F1 metric
URL: https://github.com/apache/incubator-mxnet/pull/9777#issuecomment-365397351
Also, one thing to note is that when the output has only one-label, the
micro F1 is equivalent to accuracy
sxjscience commented on a change in pull request #9777: [MX-9588] Add micro
averaging strategy for F1 metric
URL: https://github.com/apache/incubator-mxnet/pull/9777#discussion_r167993481
##
File path: python/mxnet/metric.py
##
@@ -475,8 +475,84 @@ def update(self,
sxjscience commented on a change in pull request #9777: [MX-9588] Add micro
averaging strategy for F1 metric
URL: https://github.com/apache/incubator-mxnet/pull/9777#discussion_r167992849
##
File path: python/mxnet/metric.py
##
@@ -475,8 +475,84 @@ def update(self,
sethah commented on a change in pull request #9777: [MX-9588] Add micro
averaging strategy for F1 metric
URL: https://github.com/apache/incubator-mxnet/pull/9777#discussion_r167989462
##
File path: python/mxnet/metric.py
##
@@ -475,8 +475,84 @@ def update(self, labels,
sethah commented on a change in pull request #9777: [MX-9588] Add micro
averaging strategy for F1 metric
URL: https://github.com/apache/incubator-mxnet/pull/9777#discussion_r167989350
##
File path: python/mxnet/metric.py
##
@@ -475,8 +475,84 @@ def update(self, labels,
rf987 opened a new issue #9787: net.collect_params() optims Dropout layers
URL: https://github.com/apache/incubator-mxnet/issues/9787
Why does net.collect_params() not make mention of Dropout layers ?
This is an automated
szha commented on a change in pull request #9777: [MX-9588] Add micro averaging
strategy for F1 metric
URL: https://github.com/apache/incubator-mxnet/pull/9777#discussion_r167986170
##
File path: python/mxnet/metric.py
##
@@ -475,8 +475,84 @@ def update(self, labels,
rahul003 commented on issue #8373: distribute training in fp16
URL: https://github.com/apache/incubator-mxnet/pull/8373#issuecomment-365386805
@solin319 Which machines did you run the above numbers on? Let us try to
come up with an easier interface for this so we can use this on the latest
Bestehorn commented on issue #2860: NDArray header in SAVE and LOAD function:
URL:
https://github.com/apache/incubator-mxnet/issues/2860#issuecomment-365384590
I have seen this error when I saved a model on a Linux machine and then
loaded the model in Windows (or vice versa).
piiswrong commented on issue #7938: instance norm and reflection padding
URL: https://github.com/apache/incubator-mxnet/pull/7938#issuecomment-365378948
@zhanghang1989 @szha
The instance norm operator needs an axis argument to be consistent with
batchnorm
reflectionpad2d's
piiswrong commented on a change in pull request #9738: Add Support for int64
URL: https://github.com/apache/incubator-mxnet/pull/9738#discussion_r167975658
##
File path: src/operator/mxnet_op.h
##
@@ -204,6 +204,15 @@ inline int get_num_threads(const int N) {
}
piiswrong commented on a change in pull request #9738: Add Support for int64
URL: https://github.com/apache/incubator-mxnet/pull/9738#discussion_r167975658
##
File path: src/operator/mxnet_op.h
##
@@ -204,6 +204,15 @@ inline int get_num_threads(const int N) {
}
piiswrong commented on a change in pull request #9777: [MX-9588] Add micro
averaging strategy for F1 metric
URL: https://github.com/apache/incubator-mxnet/pull/9777#discussion_r167971594
##
File path: python/mxnet/metric.py
##
@@ -475,8 +475,84 @@ def update(self, labels,
piiswrong commented on a change in pull request #9777: [MX-9588] Add micro
averaging strategy for F1 metric
URL: https://github.com/apache/incubator-mxnet/pull/9777#discussion_r167971498
##
File path: python/mxnet/metric.py
##
@@ -475,8 +475,84 @@ def update(self, labels,
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The following commit(s) were added to refs/heads/master by this push:
new 7b24137 Better Exception Handling for
piiswrong closed issue #8835: Python crashes (core-dump) instead of a graceful
error message when GPU context is used on a CPU-only instance (EC2 x1.32xlarge)
URL: https://github.com/apache/incubator-mxnet/issues/8835
This
piiswrong closed issue #9567: nd.argmax cause "Kernel Died" error in Jupyter
Notebook
URL: https://github.com/apache/incubator-mxnet/issues/9567
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piiswrong closed pull request #9681: Better Exception Handling for Operators
URL: https://github.com/apache/incubator-mxnet/pull/9681
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piiswrong closed issue #9131: random_uniform causes VM to crash
URL: https://github.com/apache/incubator-mxnet/issues/9131
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piiswrong closed issue #7335: Exception in threads kills entire process
URL: https://github.com/apache/incubator-mxnet/issues/7335
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piiswrong closed issue #9380: nd.stack causes abort for differently sized arrays
URL: https://github.com/apache/incubator-mxnet/issues/9380
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jxie pushed a commit to branch master
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The following commit(s) were added to refs/heads/master by this push:
new f57073e Using the "global_pool" option
piiswrong closed pull request #9783: Fixing a symbol file for
image-classification example
URL: https://github.com/apache/incubator-mxnet/pull/9783
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anirudh2290 commented on issue #9750: Any ideas how to implement Z-Buffer
algorithm?
URL:
https://github.com/apache/incubator-mxnet/issues/9750#issuecomment-365364303
This seems more like Q/discussion topic. Please ask on discuss.mxnet.io
anirudh2290 commented on issue #9750: Any ideas how to implement Z-Buffer
algorithm?
URL:
https://github.com/apache/incubator-mxnet/issues/9750#issuecomment-365364303
This seems more like Q/discussion topic. Please ask on discuss.mxnet.io.
rahul003 commented on issue #9782: problem in local kvstore
URL:
https://github.com/apache/incubator-mxnet/issues/9782#issuecomment-365363075
Do you have some profiling output regarding this? What kind of network are
you using?
anirudh2290 commented on issue #9764: Large batch size does not improve predict
speed
URL:
https://github.com/apache/incubator-mxnet/issues/9764#issuecomment-365359799
Can you provide some more information: Do you have a minimum reproducible
example ? Do you have any benchmark numbers ?
cjolivier01 closed pull request #9785: remove superfluous cmake error output
URL: https://github.com/apache/incubator-mxnet/pull/9785
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cjolivier01 pushed a commit to branch master
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The following commit(s) were added to refs/heads/master by this push:
new 9b7058d remove error output
anirudh2290 commented on issue #9766: DeepLearning on Imagenet with mxnet
issues translating .lst to .rec files
URL:
https://github.com/apache/incubator-mxnet/issues/9766#issuecomment-365358116
Can you please also provide the script that you ran to reproduce the issue ?
I see that you
pishen commented on a change in pull request #9771: Modify NDArrayIter
constructor to receive tuple (i.e. dict in Python)?
URL: https://github.com/apache/incubator-mxnet/pull/9771#discussion_r167953138
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File path:
cjolivier01 closed pull request #9786: Add C++ modules to CODEOWNERS
URL: https://github.com/apache/incubator-mxnet/pull/9786
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cjolivier01 pushed a commit to branch master
in repository https://gitbox.apache.org/repos/asf/incubator-mxnet.git
The following commit(s) were added to refs/heads/master by this push:
new 8a7b18f Add C++ modules to
sxjscience commented on a change in pull request #9688: Adapt operators from
PyTorch, will keep adding
URL: https://github.com/apache/incubator-mxnet/pull/9688#discussion_r167952142
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File path: src/operator/bilinear_upsample.cc
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@@ -0,0 +1,185 @@
+/*
+ * Licensed to
zhreshold commented on a change in pull request #9784: Fix for the case where
there are no detections
URL: https://github.com/apache/incubator-mxnet/pull/9784#discussion_r167951825
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File path: example/ssd/detect/detector.py
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@@ -136,31 +133,52 @@ class names
zhreshold commented on a change in pull request #9784: Fix for the case where
there are no detections
URL: https://github.com/apache/incubator-mxnet/pull/9784#discussion_r167951698
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File path: example/ssd/detect/detector.py
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@@ -136,31 +133,52 @@ class names
zhreshold commented on a change in pull request #9784: Fix for the case where
there are no detections
URL: https://github.com/apache/incubator-mxnet/pull/9784#discussion_r167951600
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File path: example/ssd/detect/detector.py
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@@ -43,6 +43,7 @@ class Detector(object):
cjolivier01 commented on issue #8972: Profiling enhancements, python API, vtune
and chrome tracing objects, etc.
URL: https://github.com/apache/incubator-mxnet/pull/8972#issuecomment-360906975
CI broken can't build
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