[GitHub] wentingj commented on a change in pull request #10433: [MXNET-290] MKLDNN support for model quantization

[GitBox]

wentingj commented on a change in pull request #10433: [MXNET-290] MKLDNN 
support for model quantization
URL: https://github.com/apache/incubator-mxnet/pull/10433#discussion_r182639741
 
 

 ##
 File path: src/operator/quantization/quantize_graph_pass.cc
 ##
 @@ -198,7 +198,7 @@ Graph QuantizeGraph(Graph &) {
 NodePtr mirror_node = mirror_map.at(e.node.get());
 NodeEntry mirror_entry = NodeEntry{
   mirror_node, e.index, e.version};
-size_t num_outputs = e.node->num_outputs();
+size_t num_outputs = mirror_node->num_outputs() - 2;
 
 Review comment:
   Yes, I will fix it back for QuantizeGraph pass. Besides, we have added 
QuantizeGraphUnsigned pass for mkldnn since mkldnn support u8 input data type. 
So output data type for quantize op will be set u8 in QuantizeGraphUnsigned 
pass.


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[GitHub] li-haoran opened a new issue #10610: memory increase when use adam and rmsprop.

[GitBox]

li-haoran opened a new issue #10610: memory increase when use adam and rmsprop.
URL: https://github.com/apache/incubator-mxnet/issues/10610
 
 
   recently, i implement an hourglass like model for pose estimation. during 
training, the memory increases. and i use the memory_profile to diagnose 
separately for data loader and module.  the data loader can not increase the 
memory using.   and i profile the training process, i find if i use the adam 
and rmsprop optimizer, the memory will increase . if i use sgd, the memory do 
not increase.
   
   i also test adam for other tasks, the memory do not increase.  i also use 
output.wait_to_read() to synchronization， the memory also increases by using 
adam.
   
   the host information:
   --Python Info--
   ('Version  :', '2.7.12')
   ('Compiler :', 'GCC 5.4.0 20160609')
   ('Build:', ('default', 'Nov 20 2017 18:23:56'))
   ('Arch :', ('64bit', 'ELF'))
   Pip Info---
   ('Version  :', '8.1.1')
   ('Directory:', '/usr/lib/python2.7/dist-packages/pip')
   --MXNet Info---
   ('Version  :', '1.0.0')
   ('Directory:', '/home/hrli/incubator-mxnet/python/mxnet')
   Hashtag not found. Not installed from pre-built package.
   --System Info--
   ('Platform :', 'Linux-4.13.0-38-generic-x86_64-with-Ubuntu-16.04-xenial')
   ('system   :', 'Linux')
   ('node :', 'VILab-620-Server')
   ('release  :', '4.13.0-38-generic')
   ('version  :', '#43~16.04.1-Ubuntu SMP Wed Mar 14 17:48:43 UTC 2018')
   --Hardware Info--
   ('machine  :', 'x86_64')
   ('processor:', 'x86_64')
   Architecture:  x86_64
   CPU op-mode(s):32-bit, 64-bit
   Byte Order:Little Endian
   CPU(s):16
   On-line CPU(s) list:   0-15
   Thread(s) per core:2
   Core(s) per socket:8
   Socket(s): 1
   NUMA node(s):  1
   Vendor ID: GenuineIntel
   CPU family:6
   Model: 79
   Model name:Intel(R) Xeon(R) CPU E5-2620 v4 @ 2.10GHz
   Stepping:  1
   CPU MHz:   1300.873
   CPU max MHz:   3000.
   CPU min MHz:   1200.
   BogoMIPS:  4197.79
   Virtualization:VT-x
   L1d cache: 32K
   L1i cache: 32K
   L2 cache:  256K
   L3 cache:  20480K
   NUMA node0 CPU(s): 0-15
   Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge 
mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx 
pdpe1gb rdtscp lm constant_tsc arch_perfmon pebs bts rep_good nopl xtopology 
nonstop_tsc cpuid aperfmperf pni pclmulqdq dtes64 monitor ds_cpl vmx smx est 
tm2 ssse3 sdbg fma cx16 xtpr pdcm pcid dca sse4_1 sse4_2 x2apic movbe popcnt 
aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch cpuid_fault epb cat_l3 
cdp_l3 invpcid_single pti retpoline intel_ppin intel_pt tpr_shadow vnmi 
flexpriority ept vpid fsgsbase tsc_adjust bmi1 hle avx2 smep bmi2 erms invpcid 
rtm cqm rdt_a rdseed adx smap xsaveopt cqm_llc cqm_occup_llc cqm_mbm_total 
cqm_mbm_local dtherm ida arat pln pts
   --Network Test--
   Setting timeout: 10
   Timing for MXNet: https://github.com/apache/incubator-mxnet, DNS: 0.0861 
sec, LOAD: 1.6811 sec.
   Timing for PYPI: https://pypi.python.org/pypi/pip, DNS: 0.0030 sec, LOAD: 
2.9404 sec.
   Error open FashionMNIST: 
https://apache-mxnet.s3-accelerate.dualstack.amazonaws.com/gluon/dataset/fashion-mnist/train-labels-idx1-ubyte.gz,
 , DNS 
finished in 0.00298500061035 sec.
   Timing for Conda: https://repo.continuum.io/pkgs/free/, DNS: 0.1720 sec, 
LOAD: 1.1443 sec.
   Timing for Gluon Tutorial(en): http://gluon.mxnet.io, DNS: 0.1269 sec, LOAD: 
0.5243 sec.
   Error open Gluon Tutorial(cn): https://zh.gluon.ai, , DNS finished in 
0.24963092804 sec.
   
   
   


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[GitHub] zheng-da opened a new issue #10609: Gluon code fails in the normal mode but succeeds in the hybrid mode.

[GitBox]

zheng-da opened a new issue #10609: Gluon code fails in the normal mode but 
succeeds in the hybrid mode.
URL: https://github.com/apache/incubator-mxnet/issues/10609
 
 
   ## Description
   ```python
   from mxnet import gluon
   import mxnet as mx
   gru = gluon.rnn.GRUCell(5)
   gru.initialize(ctx=mx.cpu(0))
   data =  mx.nd.random.uniform(shape=(2, 3))
   state = mx.nd.random.uniform(shape=(2, 5))
   out = gru(data, state)
   ```
   the code above fails with the following error:
   ```
   MXNetErrorTraceback (most recent call last)
in ()
 5 data =  mx.nd.random.uniform(shape=(2, 3))
 6 state = mx.nd.random.uniform(shape=(2, 5))
   > 7 out = gru(data, state)
   
   /home/ubuntu/incubator-mxnet/python/mxnet/gluon/block.pyc in __call__(self, 
*args)
   411 def __call__(self, *args):
   412 """Calls forward. Only accepts positional arguments."""
   --> 413 return self.forward(*args)
   414 
   415 def forward(self, *args):
   
   /home/ubuntu/incubator-mxnet/python/mxnet/gluon/rnn/rnn_cell.pyc in 
forward(self, inputs, states)
   287 # pylint: disable= arguments-differ
   288 self._counter += 1
   --> 289 return super(RecurrentCell, self).forward(inputs, states)
   290 
   291 
   
   /home/ubuntu/incubator-mxnet/python/mxnet/gluon/block.pyc in forward(self, 
x, *args)
   627 return self._call_cached_op(x, *args)
   628 params = {i: j.data(ctx) for i, j in 
self._reg_params.items()}
   --> 629 return self.hybrid_forward(ndarray, x, *args, 
**params)
   630 
   631 assert isinstance(x, Symbol), \
   
   /home/ubuntu/incubator-mxnet/python/mxnet/gluon/rnn/rnn_cell.pyc in 
hybrid_forward(self, F, inputs, states, i2h_weight, h2h_weight, i2h_bias, 
h2h_bias)
   610bias=h2h_bias,
   611num_hidden=self._hidden_size * 3,
   --> 612name=prefix+'h2h')
   613 
   614 i2h_r, i2h_z, i2h = F.SliceChannel(i2h, num_outputs=3,
   
   /home/ubuntu/incubator-mxnet/python/mxnet/ndarray/register.pyc in 
FullyConnected(data, weight, bias, num_hidden, no_bias, flatten, out, name, 
**kwargs)
   
   /home/ubuntu/incubator-mxnet/python/mxnet/_ctypes/ndarray.pyc in 
_imperative_invoke(handle, ndargs, keys, vals, out)
90 c_str_array(keys),
91 c_str_array([str(s) for s in vals]),
   ---> 92 ctypes.byref(out_stypes)))
93 
94 if original_output is not None:
   
   /home/ubuntu/incubator-mxnet/python/mxnet/base.pyc in check_call(ret)
   147 """
   148 if ret != 0:
   --> 149 raise MXNetError(py_str(_LIB.MXGetLastError()))
   150 
   151 
   
   MXNetError: Shape inconsistent, Provided = [15,5], inferred shape=(15,1)
   ```
   
   If I call hybridize the block and pass the data again to the block. It works.
   
   ```python
   gru.hybridize()
   out = gru(data, state)
   ```
   
   Is this a bug?
   


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[GitHub] ariwaranosai commented on issue #10604: fix strip prefix in HybridBlock with parameter to control it.

[GitBox]

ariwaranosai commented on issue #10604: fix strip prefix in HybridBlock with 
parameter to control it.
URL: https://github.com/apache/incubator-mxnet/pull/10604#issuecomment-382591897
 
 
   change strip_prefix be False by default.


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[GitHub] ZiyueHuang commented on issue #10509: [Improvement] Distinguish Sparse/Dense operator for temp resource request

[GitBox]

ZiyueHuang commented on issue #10509: [Improvement] Distinguish Sparse/Dense 
operator for temp resource request
URL: 
https://github.com/apache/incubator-mxnet/issues/10509#issuecomment-382590971
 
 
   Sounds good. I will have a try. Thanks.


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svn commit: r26411 - in /dev/incubator/mxnet/1.2.0.rc0: apache-mxnet-src-1.2.0.rc0-incubating.tar.gz apache-mxnet-src-1.2.0.rc0-incubating.tar.gz.asc apache-mxnet-src-1.2.0.rc0-incubating.tar.gz.md5 a

[haibin]

Author: haibin
Date: Thu Apr 19 01:46:44 2018
New Revision: 26411

Log:
add mxnet 1.2.0.rc0

Added:
dev/incubator/mxnet/1.2.0.rc0/apache-mxnet-src-1.2.0.rc0-incubating.tar.gz  
 (with props)

dev/incubator/mxnet/1.2.0.rc0/apache-mxnet-src-1.2.0.rc0-incubating.tar.gz.asc

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Thu Apr 19 01:46:44 2018
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e27cc980870590b4158e3695658da322

Added: 
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svn commit: r26410 - in /dev/incubator/mxnet/1.2.0.rc0: apache-mxnet-src-1.2.0.rc0-incubating.tar.gz apache-mxnet-src-1.2.0.rc0-incubating.tar.gz.asc apache-mxnet-src-1.2.0.rc0-incubating.tar.gz.md5 a

[haibin]

Author: haibin
Date: Thu Apr 19 01:46:02 2018
New Revision: 26410

Log:
remove

Removed:
dev/incubator/mxnet/1.2.0.rc0/apache-mxnet-src-1.2.0.rc0-incubating.tar.gz

dev/incubator/mxnet/1.2.0.rc0/apache-mxnet-src-1.2.0.rc0-incubating.tar.gz.asc

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[GitHub] xinyu-intel commented on a change in pull request #10433: [MXNET-290] MKLDNN support for model quantization

[GitBox]

xinyu-intel commented on a change in pull request #10433: [MXNET-290] MKLDNN 
support for model quantization
URL: https://github.com/apache/incubator-mxnet/pull/10433#discussion_r182614674
 
 

 ##
 File path: ci/docker/runtime_functions.sh
 ##
 @@ -371,7 +371,6 @@ unittest_ubuntu_python2_cpu() {
 export MXNET_STORAGE_FALLBACK_LOG_VERBOSE=0
 nosetests-2.7 --verbose tests/python/unittest
 nosetests-2.7 --verbose tests/python/train
-nosetests-2.7 --verbose tests/python/quantization
 
 Review comment:
   @marcoabreu We cannot pass the `test_quantization_mkldnn.py` when building 
without mkldnn. So I skip this line or we can put the test file in a separate 
dictionary?


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[GitHub] ThomasDelteil opened a new pull request #10608: [MX-292] Add tutorial tests to the CI

[GitBox]

ThomasDelteil opened a new pull request #10608: [MX-292] Add tutorial tests to 
the CI
URL: https://github.com/apache/incubator-mxnet/pull/10608
 
 
   ## Description ##
   
   - Adding the tutorials to the CI
   - Adding a sanity check to tutorials:
   - Every tutorial needs to be downloadable (except whitelist)
   - Every tutorial needs to be tested (except whitelist)
   - Sequential run (multiprocessing run is flaky and can leave orphan 
processes running)
   
   @marcoabreu 
   
   ## Checklist ##
   ### Essentials ###
   Please feel free to remove inapplicable items for your PR.
   - [ ] The PR title starts with [MXNET-$JIRA_ID], where $JIRA_ID refers to 
the relevant [JIRA issue](https://issues.apache.org/jira/projects/MXNET/issues) 
created (except PRs with tiny changes)
   - [ ] Changes are complete (i.e. I finished coding on this PR)
   - [ ] All changes have test coverage:
   - Unit tests are added for small changes to verify correctness (e.g. adding 
a new operator)
   - Nightly tests are added for complicated/long-running ones (e.g. changing 
distributed kvstore)
   - Build tests will be added for build configuration changes (e.g. adding a 
new build option with NCCL)
   - [ ] Code is well-documented: 
   - For user-facing API changes, API doc string has been updated. 
   - For new C++ functions in header files, their functionalities and arguments 
are documented. 
   - For new examples, README.md is added to explain the what the example does, 
the source of the dataset, expected performance on test set and reference to 
the original paper if applicable
   - Check the API doc at 
http://mxnet-ci-doc.s3-accelerate.dualstack.amazonaws.com/PR-$PR_ID/$BUILD_ID/index.html
   - [ ] To the my best knowledge, examples are either not affected by this 
change, or have been fixed to be compatible with this change
   
   ## Comments ##
   - If this change is a backward incompatible change, why must this change be 
made.
   - Interesting edge cases to note here


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svn commit: r26409 - in /dev/incubator/mxnet/1.2.0.rc0: ./ apache-mxnet-src-1.2.0.rc0-incubating.tar.gz apache-mxnet-src-1.2.0.rc0-incubating.tar.gz.asc apache-mxnet-src-1.2.0.rc0-incubating.tar.gz.md

[haibin]

Author: haibin
Date: Thu Apr 19 01:20:42 2018
New Revision: 26409

Log:
Add mxnet-1.2.0.rc0

Added:
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+++ 
dev/incubator/mxnet/1.2.0.rc0/apache-mxnet-src-1.2.0.rc0-incubating.tar.gz.md5 
Thu Apr 19 01:20:42 2018
@@ -0,0 +1 @@
+MD5 (apache-mxnet-src-1.2.0.rc0-incubating.tar.gz) = 
4eca6d5a04328f8aa35acb43870f7981

Added: 
dev/incubator/mxnet/1.2.0.rc0/apache-mxnet-src-1.2.0.rc0-incubating.tar.gz.sha512
==
--- 
dev/incubator/mxnet/1.2.0.rc0/apache-mxnet-src-1.2.0.rc0-incubating.tar.gz.sha512
 (added)
+++ 
dev/incubator/mxnet/1.2.0.rc0/apache-mxnet-src-1.2.0.rc0-incubating.tar.gz.sha512
 Thu Apr 19 01:20:42 2018
@@ -0,0 +1 @@
+d7edf783efc319bd112f088f4292b203d80333d439c3d62f756ada12802224376e55c226ae28db4f660a51afad824bedb0cd4234556f0e10ea76471dd79b1117
  apache-mxnet-src-1.2.0.rc0-incubating.tar.gz

svn commit: r26408 - /dev/incubator/mxnet/1.2.0.rc0/

[haibin]

Author: haibin
Date: Thu Apr 19 01:16:11 2018
New Revision: 26408

Log:
remove

Removed:
dev/incubator/mxnet/1.2.0.rc0/

svn commit: r26407 - in /dev/incubator/mxnet/1.2.0.rc0: ./ apache-mxnet-src-1.2.0.rc0-incubating.tar.gz apache-mxnet-src-1.2.0.rc0-incubating.tar.gz.asc apache-mxnet-src-1.2.0.rc0-incubating.tar.gz.md

[haibin]

Author: haibin
Date: Thu Apr 19 01:14:31 2018
New Revision: 26407

Log:
Add mxnet-1.2.0.rc0

Added:
dev/incubator/mxnet/1.2.0.rc0/
dev/incubator/mxnet/1.2.0.rc0/apache-mxnet-src-1.2.0.rc0-incubating.tar.gz  
 (with props)

dev/incubator/mxnet/1.2.0.rc0/apache-mxnet-src-1.2.0.rc0-incubating.tar.gz.asc

dev/incubator/mxnet/1.2.0.rc0/apache-mxnet-src-1.2.0.rc0-incubating.tar.gz.md5

dev/incubator/mxnet/1.2.0.rc0/apache-mxnet-src-1.2.0.rc0-incubating.tar.gz.sha512

Added: 
dev/incubator/mxnet/1.2.0.rc0/apache-mxnet-src-1.2.0.rc0-incubating.tar.gz
==
Binary file - no diff available.

Propchange: 
dev/incubator/mxnet/1.2.0.rc0/apache-mxnet-src-1.2.0.rc0-incubating.tar.gz
--
svn:mime-type = application/octet-stream

Added: 
dev/incubator/mxnet/1.2.0.rc0/apache-mxnet-src-1.2.0.rc0-incubating.tar.gz.asc
==
--- 
dev/incubator/mxnet/1.2.0.rc0/apache-mxnet-src-1.2.0.rc0-incubating.tar.gz.asc 
(added)
+++ 
dev/incubator/mxnet/1.2.0.rc0/apache-mxnet-src-1.2.0.rc0-incubating.tar.gz.asc 
Thu Apr 19 01:14:31 2018
@@ -0,0 +1,16 @@
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Added: 
dev/incubator/mxnet/1.2.0.rc0/apache-mxnet-src-1.2.0.rc0-incubating.tar.gz.md5
==
--- 
dev/incubator/mxnet/1.2.0.rc0/apache-mxnet-src-1.2.0.rc0-incubating.tar.gz.md5 
(added)
+++ 
dev/incubator/mxnet/1.2.0.rc0/apache-mxnet-src-1.2.0.rc0-incubating.tar.gz.md5 
Thu Apr 19 01:14:31 2018
@@ -0,0 +1 @@
+MD5 (apache-mxnet-src-1.2.0.rc0-incubating.tar.gz) = 
a172611d85806c002e4ca498534f5aa7

Added: 
dev/incubator/mxnet/1.2.0.rc0/apache-mxnet-src-1.2.0.rc0-incubating.tar.gz.sha512
==
--- 
dev/incubator/mxnet/1.2.0.rc0/apache-mxnet-src-1.2.0.rc0-incubating.tar.gz.sha512
 (added)
+++ 
dev/incubator/mxnet/1.2.0.rc0/apache-mxnet-src-1.2.0.rc0-incubating.tar.gz.sha512
 Thu Apr 19 01:14:31 2018
@@ -0,0 +1 @@
+acf2ab9929aa2c8dba06ab5bca8312e53ef260624e47bd38c24a26c2049d7f1ebba864b01db6dfbe164de59043df4f89966a74bd51fa392b52e79eed09af511b
  apache-mxnet-src-1.2.0.rc0-incubating.tar.gz

[GitHub] rahul003 commented on a change in pull request #10530: Jetson build with cmake and CUDA

[GitBox]

rahul003 commented on a change in pull request #10530: Jetson build with cmake 
and CUDA
URL: https://github.com/apache/incubator-mxnet/pull/10530#discussion_r182611722
 
 

 ##
 File path: ci/docker/runtime_functions.sh
 ##
 @@ -38,9 +38,30 @@ clean_repo() {
 build_jetson() {
 set -ex
 pushd .
-mv make/crosscompile.jetson.mk make/config.mk
-make -j$(nproc)
 
+# Needed for FindCUDA.cmake module
+export CUDA_TOOLKIT_ROOT=${CUDA_PATH}
+
+cd /work/build
+cmake \
+   -DCMAKE_TOOLCHAIN_FILE=${CMAKE_TOOLCHAIN_FILE} \
+-DCMAKE_CROSSCOMPILING=ON \
+-DUSE_CUDA=ON \
+-DUSE_CUDNN=ON \
+-DUSE_OPENCV=OFF \
+-DUSE_OPENMP=ON \
+-DUSE_SSE=OFF \
+-DCMAKE_C_FLAGS=-DMSHADOW_USE_SSE=0 \
 
 Review comment:
   You probably also want to set -DMSHADOW_USE_F16C=0 similar to SSE, because 
Jetson would not support F16C as well


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[GitHub] rahul003 commented on issue #10558: NNVM build failed in the newst mxnet version

[GitBox]

rahul003 commented on issue #10558: NNVM build failed in the newst mxnet version
URL: 
https://github.com/apache/incubator-mxnet/issues/10558#issuecomment-382576446
 
 
   For the CMake build I checked both that the CPU supports f16c and compiler 
supports f16c and then set the flag on. For Make I couldn't figure out how to 
identify if the compiler supports the flag, so I only checked that the CPU 
supports it. I'll try to see if I can figure out compiler support automatically 
and then set USE_F16C=0


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[GitHub] ThomasDelteil commented on issue #10607: New tutorial on how to create a new custom layer in Gluon

[GitBox]

ThomasDelteil commented on issue #10607: New tutorial on how to create a new 
custom layer in Gluon
URL: https://github.com/apache/incubator-mxnet/pull/10607#issuecomment-382571821
 
 
   @Ishitori you are missing the download placeholder at the end of your 
tutorial and you haven't updated the tutorials/index.md file


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[GitHub] Roshrini commented on issue #10504: Can MXNet operator profiling work well using gluon model?

[GitBox]

Roshrini commented on issue #10504: Can MXNet operator profiling work well 
using gluon model?
URL: 
https://github.com/apache/incubator-mxnet/issues/10504#issuecomment-382570070
 
 
   @eric-haibin-lin  Can you please add labels-
   Python, Gluon, Profiler


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[GitHub] Roshrini commented on issue #10505: profiler shoudl collect call durations not just timestamps

[GitBox]

Roshrini commented on issue #10505: profiler shoudl collect call durations not 
just timestamps
URL: 
https://github.com/apache/incubator-mxnet/issues/10505#issuecomment-382569557
 
 
   @eric-haibin-lin could you please add label-
   Profiler


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[GitHub] Ishitori opened a new pull request #10607: New tutorial on how to create a new custom layer in Gluon

[GitBox]

Ishitori opened a new pull request #10607: New tutorial on how to create a new 
custom layer in Gluon
URL: https://github.com/apache/incubator-mxnet/pull/10607
 
 
   ## Description ##
   This pull request adds a new tutorial explaining how to create a new custom 
layer using Gluon API. It doesn't introduce any changes to the code base.
   
   ## Checklist ##
   ### Essentials ###
   Please feel free to remove inapplicable items for your PR.
   - [X] Changes are complete (i.e. I finished coding on this PR)
   - [X] Code is well-documented
   
   ### Changes ###
   - New tutorial for Python/Gluon


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[GitHub] eric-haibin-lin commented on issue #60: Site refresh

[GitBox]

eric-haibin-lin commented on issue #60: Site refresh
URL: 
https://github.com/apache/incubator-mxnet-site/pull/60#issuecomment-382567814
 
 
   Wow.. big change.. How are ppl supposed to review this..?


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[GitHub] Roshrini commented on issue #10494: stop_gradient fails under adam and wd

[GitBox]

Roshrini commented on issue #10494: stop_gradient fails under adam and wd
URL: 
https://github.com/apache/incubator-mxnet/issues/10494#issuecomment-382567521
 
 
   @eric-haibin-lin could you please add labels-
   Python, Optimizer


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[GitHub] Roshrini commented on issue #10492: Logging level for C++ lib

[GitBox]

Roshrini commented on issue #10492: Logging level for C++ lib
URL: 
https://github.com/apache/incubator-mxnet/issues/10492#issuecomment-382567329
 
 
   @cjolivier01 Any idea how to set the logging level?
   Also could you please add labels-
   C++, Question


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[GitHub] Roshrini commented on issue #10549: scala-package 1.1.0 build instruction Windows VS2015

[GitBox]

Roshrini commented on issue #10549: scala-package 1.1.0 build instruction 
Windows VS2015
URL: 
https://github.com/apache/incubator-mxnet/issues/10549#issuecomment-382565462
 
 
   @nswamy Could you please add labels-
   Scala, Windows, Installation


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[GitHub] Roshrini commented on issue #10532: NDArray failed to allocate CPU memory

[GitBox]

Roshrini commented on issue #10532: NDArray failed to allocate CPU memory
URL: 
https://github.com/apache/incubator-mxnet/issues/10532#issuecomment-382565304
 
 
   @nswamy Could you please add labels-
   Python, NDarray


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[GitHub] marcoabreu commented on a change in pull request #10354: Expose the number of GPUs.

[GitBox]

marcoabreu commented on a change in pull request #10354: Expose the number of 
GPUs.
URL: https://github.com/apache/incubator-mxnet/pull/10354#discussion_r182601933
 
 

 ##
 File path: include/mxnet/base.h
 ##
 @@ -307,6 +312,21 @@ inline Context Context::GPU(int32_t dev_id) {
   return Create(kGPU, dev_id);
 }
 
+inline int32_t Context::GetGPUCount() {
+#if MXNET_USE_CUDA
+  int32_t count;
+  cudaError_t e = cudaGetDeviceCount();
+  if (e == cudaErrorNoDevice) {
+return 0;
+  }
+  CHECK_EQ(e, cudaSuccess) << " CUDA: " << cudaGetErrorString(e);
+  return count;
+#else
+  LOG(FATAL) << "Please compile with CUDA support to query the number of 
GPUs.";
 
 Review comment:
   I think it is valid to do this call since the frontend apis do not know 
whether the underlying library was compiled with or without CUDA support. 
Instead, we should also have a second API which provides that information. 


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[GitHub] marcoabreu commented on issue #10354: Expose the number of GPUs.

[GitBox]

marcoabreu commented on issue #10354: Expose the number of GPUs.
URL: https://github.com/apache/incubator-mxnet/pull/10354#issuecomment-382564700
 
 
   Exactly


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[GitHub] marcoabreu commented on a change in pull request #60: Site refresh

[GitBox]

marcoabreu commented on a change in pull request #60: Site refresh
URL: 
https://github.com/apache/incubator-mxnet-site/pull/60#discussion_r182601395
 
 

 ##
 File path: .htaccess
 ##
 @@ -1,5 +0,0 @@
-RewriteEngine on
 
 Review comment:
   Is it intended to remove this?


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[GitHub] Roshrini commented on issue #10432: [scala-infer]move test files for scala infer API to s3

[GitBox]

Roshrini commented on issue #10432: [scala-infer]move test files for scala 
infer API to s3
URL: 
https://github.com/apache/incubator-mxnet/issues/10432#issuecomment-382564261
 
 
   @lanking520 Can you upload models files for imageclassification and SSD 
examples in S3 and change the links?


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[GitHub] marcoabreu commented on a change in pull request #10605: [MXNET-310] [ONNX-MXNet] API to import ONNX models into Gluon.

[GitBox]

marcoabreu commented on a change in pull request #10605: [MXNET-310] 
[ONNX-MXNet] API to import ONNX models into Gluon.
URL: https://github.com/apache/incubator-mxnet/pull/10605#discussion_r182600988
 
 

 ##
 File path: tests/python-pytest/onnx/gluon_backend.py
 ##
 @@ -0,0 +1,148 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License.  You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied.  See the License for the
+# specific language governing permissions and limitations
+# under the License.
+
+# coding: utf-8
+"""Gluon backend wrapper for onnx test infrastructure"""
+import mxnet as mx
+from mxnet import nd
+from mxnet.contrib.onnx._import.import_onnx import GraphProto
+import numpy as np
+try:
+from onnx import helper, TensorProto
+from onnx.backend.base import Backend
+except ImportError:
+raise ImportError("Onnx and protobuf need to be installed. Instructions to"
+  + " install - https://github.com/onnx/onnx#installation;)
+from gluon_backend_rep import GluonBackendRep
+
+# GluonBackend class will take an ONNX model with inputs, perform a 
computation,
+# and then return the output.
+# Implemented by following onnx docs guide:
+# https://github.com/onnx/onnx/blob/master/docs/ImplementingAnOnnxBackend.md
+
+class GluonBackend(Backend):
+"""Gluon backend for ONNX"""
+
+@staticmethod
+def make_graph(node, inputs):
+""" Created ONNX GraphProto from node"""
+initializer = []
+tensor_input_info = []
+tensor_output_info = []
+
+# Adding input tensor info.
+for index in range(len(node.input)):
+tensor_input_info.append(
+helper.make_tensor_value_info(str(node.input[index]), 
TensorProto.FLOAT, [1]))
+
+# Creating an initializer for Weight params.
+# Assumes that weight params is named as 'W'.
+if node.input[index] == 'W':
+dim = inputs[index].shape
+param_tensor = helper.make_tensor(
+name=node.input[index],
+data_type=TensorProto.FLOAT,
+dims=dim,
+vals=inputs[index].flatten())
+
+initializer.append(param_tensor)
+
+# Adding output tensor info.
+for index in range(len(node.output)):
+tensor_output_info.append(
+helper.make_tensor_value_info(str(node.output[index]), 
TensorProto.FLOAT, [1]))
+
+# creating graph proto object.
+graph_proto = helper.make_graph(
+[node],
+"test",
+tensor_input_info,
+tensor_output_info,
+initializer=initializer)
+
+return graph_proto
+
+@classmethod
+def run_node(cls, node, inputs, device='CPU'):
+"""Running individual node inference on gluon backend and
+return the result to onnx test infrastructure.
+
+Parameters
+--
+node   : onnx node object
+loaded onnx node (individual layer)
+inputs : numpy array
+input to run a node on
+device : 'CPU'
+device to run a node on
+
+Returns
+---
+params : numpy array
+result obtained after running the operator
+"""
+graph = GraphProto()
+net = graph.graph_to_gluon(GluonBackend.make_graph(node, inputs))
+
+# create module, passing cpu context
+if device == 'CPU':
+ctx = mx.cpu()
+else:
+raise NotImplementedError("Only CPU context is supported for now")
 
 Review comment:
   Shouldn't ONNX be implementation independent and thus not care about the 
used device type?


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[GitHub] Roshrini commented on issue #10480: Could you help build windows pypi package with cuda9.0

[GitBox]

Roshrini commented on issue #10480: Could you help build windows pypi package 
with cuda9.0
URL: 
https://github.com/apache/incubator-mxnet/issues/10480#issuecomment-382562152
 
 
   @nswamy Could you please add label-
   installation, windows


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[GitHub] aaronmarkham opened a new pull request #60: Site refresh

[GitBox]

aaronmarkham opened a new pull request #60: Site refresh
URL: https://github.com/apache/incubator-mxnet-site/pull/60
 
 
   ## Description ##
   Manual site refresh for 1.2.0 RC0
   


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[GitHub] haojin2 commented on issue #10585: [MXNET-329] support SparseEmbedding with dense weight

[GitBox]

haojin2 commented on issue #10585: [MXNET-329] support SparseEmbedding with 
dense weight
URL: https://github.com/apache/incubator-mxnet/pull/10585#issuecomment-382557084
 
 
   LGTM


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[GitHub] eric-haibin-lin commented on a change in pull request #10585: [MXNET-329] support SparseEmbedding with dense weight

[GitBox]

eric-haibin-lin commented on a change in pull request #10585: [MXNET-329] 
support SparseEmbedding with dense weight
URL: https://github.com/apache/incubator-mxnet/pull/10585#discussion_r182593627
 
 

 ##
 File path: tests/python/unittest/test_sparse_operator.py
 ##
 @@ -1638,10 +1638,10 @@ def check_sparse_elementwise_sum_with_shape(stype, 
shape, n):
 @with_seed()
 def test_sparse_embedding():
 ''' test sparse embedding operator '''
-def check_sparse_embedding(in_dim, out_dim, batch, densities, 
deterministic):
+def check_sparse_embedding(in_dim, out_dim, batch, densities, 
deterministic, weight_stype):
 
 Review comment:
   deterministic is the param passed to mx.sym.contrib.SparseEmbedding. See 
line 1645


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[GitHub] anirudh2290 commented on issue #10606: Additional v1.2.0 changes - install docs changes, website changes

[GitBox]

anirudh2290 commented on issue #10606: Additional v1.2.0 changes - install docs 
changes, website changes
URL: https://github.com/apache/incubator-mxnet/pull/10606#issuecomment-382553520
 
 
   The CI running on the branch was successful: 
http://jenkins.mxnet-ci.amazon-ml.com/blue/organizations/jenkins/incubator-mxnet/detail/v1.2.0/6/pipeline


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[GitHub] zhreshold commented on a change in pull request #10595: Update mobilenetv2 symbol definition

[GitBox]

zhreshold commented on a change in pull request #10595: Update mobilenetv2 
symbol definition
URL: https://github.com/apache/incubator-mxnet/pull/10595#discussion_r182583557
 
 

 ##
 File path: example/image-classification/symbols/mobilenetv2.py
 ##
 @@ -17,60 +17,239 @@
 
 # -*- coding:utf-8 -*-
 '''
-MobileNetV2, implemented in Gluon.
+MobileNetV2, implemented in built-in symbols.
 
 Reference:
 Inverted Residuals and Linear Bottlenecks:
 Mobile Networks for Classification, Detection and Segmentation
 https://arxiv.org/abs/1801.04381
 '''
-__author__ = 'dwSun'
-__date__ = '18/1/31'
+__author__ = 'liangfu'
+__date__ = '18/4/3'
 
 import mxnet as mx
 
-from mxnet.gluon.model_zoo.vision.mobilenet import MobileNetV2
+def relu6(data, prefix):
+return mx.sym.clip(data,0,6,name='%s-relu6'%prefix)
 
+def shortcut(data_in, data_residual, prefix):
+out=mx.sym.elemwise_add(data_in, data_residual, name='%s-shortcut'%prefix)
+return out
 
-__all__ = ['MobileNetV2', 'get_symbol']
+def mobilenet_unit(data, num_filter=1, kernel=(1, 1), stride=(1, 1), pad=(0, 
0), num_group=1, if_act=True, prefix=''):
+conv = mx.sym.Convolution(
+data=data,
+num_filter=num_filter,
+kernel=kernel,
+num_group=num_group,
+stride=stride,
+pad=pad,
+no_bias=True,
+name='%s-conv2d'%prefix)
+bn = mx.sym.BatchNorm(data=conv, name='%s-batchnorm'%prefix, 
fix_gamma=False, use_global_stats=False, eps=1e-5)
+if if_act:
+act = relu6(bn, prefix)
+return act
+else:
+return bn
 
+def inverted_residual_unit(data, num_in_filter, num_filter, ifshortcut, 
stride, kernel, pad, expansion_factor, prefix):
+num_expfilter = int(round(num_in_filter*expansion_factor))
 
-def get_symbol(num_classes=1000, multiplier=1.0, ctx=mx.cpu(), **kwargs):
-r"""MobileNetV2 model from the
-`"Inverted Residuals and Linear Bottlenecks:
-  Mobile Networks for  Classification, Detection and Segmentation"
-`_ paper.
+channel_expand = mobilenet_unit(
+data=data,
+num_filter=num_expfilter,
+kernel=(1,1),
+stride=(1,1),
+pad=(0,0),
+num_group=1,
+if_act=True,
+prefix='%s-exp'%prefix,
+)
+bottleneck_conv = mobilenet_unit(
+data= channel_expand,
+num_filter=num_expfilter,
+stride=stride,
+kernel=kernel,
+pad=pad,
+num_group=num_expfilter,
+if_act=True,
+prefix='%s-depthwise'%prefix,
+)
+linear_out = mobilenet_unit(
+data=bottleneck_conv,
+num_filter=num_filter,
+kernel=(1, 1),
+stride=(1, 1),
+pad=(0, 0),
+num_group=1,
+if_act=False,
+prefix='%s-linear'%prefix
+)
+if ifshortcut:
+out = shortcut(
+data_in=data,
+data_residual=linear_out,
+prefix=prefix,
+) 
+return out
+else:
+return linear_out
 
-Parameters
---
-num_classes : int, default 1000
-Number of classes for the output layer.
-multiplier : float, default 1.0
-The width multiplier for controling the model size. The actual number 
of channels
-is equal to the original channel size multiplied by this multiplier.
-ctx : Context, default CPU
-The context in which to initialize the model weights.
-"""
-net = MobileNetV2(multiplier=multiplier, classes=num_classes, **kwargs)
-net.initialize(ctx=ctx, init=mx.init.Xavier())
-net.hybridize()
+def invresi_blocks(data, in_c, t, c, n, s, prefix):
+first_block = inverted_residual_unit(
+data=data,
+num_in_filter=in_c,
+num_filter=c,
+ifshortcut=False,
+stride=(s,s),
+kernel=(3,3),
+pad=(1,1),
+expansion_factor=t,
+prefix='%s-block0'%prefix
+)
 
-data = mx.sym.var('data')
-out = net(data)
-sym = mx.sym.SoftmaxOutput(out, name='softmax')
-return sym
+last_residual_block = first_block
+last_c = c
 
+for i in range(1,n):
+last_residual_block = inverted_residual_unit(
+data=last_residual_block,
+num_in_filter=last_c,
+num_filter=c,
+ifshortcut=True,
+stride=(1,1),
+kernel=(3,3),
+pad=(1,1),
+expansion_factor=t,
+prefix='%s-block%d'%(prefix, i)
+)
+return last_residual_block
 
-def plot_net():
-"""
-Visualize the network.
-"""
-sym = get_symbol(1000, prefix='mob_')
+MNETV2_CONFIGS_MAP = {
+(224,224):{
+'firstconv_filter_num': 32, # 3*224*224 -> 32*112*112
+# t, c, n, s
+'bottleneck_params_list':[
+(1, 16, 1, 1), # 32x112x112 -> 16x112x112
+(6, 24, 2, 2), # 16x112x112 -> 24x56x56
+(6, 32, 3, 2), # 24x56x56 -> 32x28x28
+(6, 64, 4, 1), 

[GitHub] zhreshold commented on a change in pull request #10595: Update mobilenetv2 symbol definition

[GitBox]

zhreshold commented on a change in pull request #10595: Update mobilenetv2 
symbol definition
URL: https://github.com/apache/incubator-mxnet/pull/10595#discussion_r182583210
 
 

 ##
 File path: example/image-classification/symbols/mobilenetv2.py
 ##
 @@ -17,60 +17,239 @@
 
 # -*- coding:utf-8 -*-
 '''
-MobileNetV2, implemented in Gluon.
+MobileNetV2, implemented in built-in symbols.
 
 Reference:
 Inverted Residuals and Linear Bottlenecks:
 Mobile Networks for Classification, Detection and Segmentation
 https://arxiv.org/abs/1801.04381
 '''
-__author__ = 'dwSun'
-__date__ = '18/1/31'
+__author__ = 'liangfu'
+__date__ = '18/4/3'
 
 import mxnet as mx
 
-from mxnet.gluon.model_zoo.vision.mobilenet import MobileNetV2
+def relu6(data, prefix):
+return mx.sym.clip(data,0,6,name='%s-relu6'%prefix)
 
+def shortcut(data_in, data_residual, prefix):
+out=mx.sym.elemwise_add(data_in, data_residual, name='%s-shortcut'%prefix)
+return out
 
-__all__ = ['MobileNetV2', 'get_symbol']
+def mobilenet_unit(data, num_filter=1, kernel=(1, 1), stride=(1, 1), pad=(0, 
0), num_group=1, if_act=True, prefix=''):
+conv = mx.sym.Convolution(
+data=data,
+num_filter=num_filter,
+kernel=kernel,
+num_group=num_group,
+stride=stride,
+pad=pad,
+no_bias=True,
+name='%s-conv2d'%prefix)
+bn = mx.sym.BatchNorm(data=conv, name='%s-batchnorm'%prefix, 
fix_gamma=False, use_global_stats=False, eps=1e-5)
+if if_act:
+act = relu6(bn, prefix)
+return act
+else:
+return bn
 
+def inverted_residual_unit(data, num_in_filter, num_filter, ifshortcut, 
stride, kernel, pad, expansion_factor, prefix):
+num_expfilter = int(round(num_in_filter*expansion_factor))
 
-def get_symbol(num_classes=1000, multiplier=1.0, ctx=mx.cpu(), **kwargs):
-r"""MobileNetV2 model from the
-`"Inverted Residuals and Linear Bottlenecks:
-  Mobile Networks for  Classification, Detection and Segmentation"
-`_ paper.
+channel_expand = mobilenet_unit(
+data=data,
+num_filter=num_expfilter,
+kernel=(1,1),
+stride=(1,1),
+pad=(0,0),
+num_group=1,
+if_act=True,
+prefix='%s-exp'%prefix,
+)
+bottleneck_conv = mobilenet_unit(
+data= channel_expand,
+num_filter=num_expfilter,
+stride=stride,
+kernel=kernel,
+pad=pad,
+num_group=num_expfilter,
+if_act=True,
+prefix='%s-depthwise'%prefix,
+)
+linear_out = mobilenet_unit(
+data=bottleneck_conv,
+num_filter=num_filter,
+kernel=(1, 1),
+stride=(1, 1),
+pad=(0, 0),
+num_group=1,
+if_act=False,
+prefix='%s-linear'%prefix
+)
+if ifshortcut:
+out = shortcut(
+data_in=data,
+data_residual=linear_out,
+prefix=prefix,
+) 
+return out
+else:
+return linear_out
 
-Parameters
---
-num_classes : int, default 1000
-Number of classes for the output layer.
-multiplier : float, default 1.0
-The width multiplier for controling the model size. The actual number 
of channels
-is equal to the original channel size multiplied by this multiplier.
-ctx : Context, default CPU
-The context in which to initialize the model weights.
-"""
-net = MobileNetV2(multiplier=multiplier, classes=num_classes, **kwargs)
-net.initialize(ctx=ctx, init=mx.init.Xavier())
-net.hybridize()
+def invresi_blocks(data, in_c, t, c, n, s, prefix):
 
 Review comment:
   function name? 


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[GitHub] eric-haibin-lin commented on issue #10606: Additional v1.2.0 changes - install docs changes, website changes

[GitBox]

eric-haibin-lin commented on issue #10606: Additional v1.2.0 changes - install 
docs changes, website changes
URL: https://github.com/apache/incubator-mxnet/pull/10606#issuecomment-382532583
 
 
   I'll merge these now since they're just cherrypicked commits. 


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[GitHub] eric-haibin-lin closed pull request #10606: Additional v1.2.0 changes - install docs changes, website changes

[GitBox]

eric-haibin-lin closed pull request #10606: Additional v1.2.0 changes - install 
docs changes, website changes
URL: https://github.com/apache/incubator-mxnet/pull/10606
 
 
   

This is a PR merged from a forked repository.
As GitHub hides the original diff on merge, it is displayed below for
the sake of provenance:

As this is a foreign pull request (from a fork), the diff is supplied
below (as it won't show otherwise due to GitHub magic):

diff --git a/docs/_static/js/navbar.js b/docs/_static/js/navbar.js
index d7635af888a..27191723f82 100644
--- a/docs/_static/js/navbar.js
+++ b/docs/_static/js/navbar.js
@@ -1,5 +1,5 @@
 var searchBox = $("#search-input-wrap");
-var TITLE = ['/install/', '/gluon/' , '/api/', '/docs/', '/github/', 
'/community/', ];
+var TITLE = ['/install/', '/gluon/', '/api/', '/docs/', '/community/' ];
 var DOC_TITLE = ['/faq/', '/tutorials/', '/architecture/', '/model_zoo/'];
 var APISubmenu, versionSubmenu, docSubmenu;
 $("#burgerMenu").children().each(function () {
@@ -87,4 +87,4 @@ $(document).ready(function () {
 if($("body").prop("clientWidth") < 1000 || 
$('div.sphinxsidebar').css('visibility') == 'hidden') 
$('div.content').css('width', '100%');
 else $('div.content').css('width', 'calc(100% - 300px)');
 });
-});
\ No newline at end of file
+});
diff --git a/docs/_static/mxnet-theme/navbar.html 
b/docs/_static/mxnet-theme/navbar.html
index bcc89896e40..218454aea77 100644
--- a/docs/_static/mxnet-theme/navbar.html
+++ b/docs/_static/mxnet-theme/navbar.html
@@ -14,40 +14,39 @@ 
 http://gluon.mxnet.io;>Tutorials
   
 
-
- 
+ 
+
   API 
   
 Python
+C++
 Scala
-R
 Julia
-C++
 Perl
+R
   
 
 
- 
+
   Docs 
   
-Tutorials
 FAQ
-Architecture
+Tutorials
 https://github.com/apache/incubator-mxnet/tree/master/example;>Examples
-Gluon Model Zoo
+Architecture
+Model Zoo
+ONNX
   
 
 
-
-https://github.com/dmlc/mxnet;>Github
-
 
   Community 
   
+http://discuss.mxnet.io;>Forum
+https://github.com/apache/incubator-mxnet;>Github
 Community
 Contribute
 Powered By
-http://discuss.mxnet.io;>Discuss
   
 
   
diff --git a/docs/install/index.md b/docs/install/index.md
index 2fe8dbf5c51..e36ed23bb87 100644
--- a/docs/install/index.md
+++ b/docs/install/index.md
@@ -253,7 +253,6 @@ $ sudo apt-get install -y python-dev python-setuptools 
python-pip libgfortran3
 
 ```bash
 $ cd python
-$ pip install --upgrade pip
 $ pip install -e .
 ```
 
@@ -476,7 +475,6 @@ $ sudo apt-get install -y python-dev python-setuptools 
python-pip libgfortran3
 
 ```bash
 $ cd python
-$ pip install --upgrade pip
 $ pip install -e .
 ```
 


 


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[GitHub] anirudh2290 commented on issue #10606: Additional v1.2.0 changes - install docs changes, website changes

[GitBox]

anirudh2290 commented on issue #10606: Additional v1.2.0 changes - install docs 
changes, website changes
URL: https://github.com/apache/incubator-mxnet/pull/10606#issuecomment-382529735
 
 
   @eric-haibin-lin can this be merged without squashing. We don't have to wait 
for CI to pass since the CI checks already passed in the corresponding PRs and 
the changes are disjoint: #10587 and #10449 . Plus, we will make sure that the 
branch passes all CI tests, including nightlies.


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[GitHub] eric-haibin-lin closed pull request #10449: [MXNET-293] Navigation updates

[GitBox]

eric-haibin-lin closed pull request #10449: [MXNET-293] Navigation updates
URL: https://github.com/apache/incubator-mxnet/pull/10449
 
 
   

This is a PR merged from a forked repository.
As GitHub hides the original diff on merge, it is displayed below for
the sake of provenance:

As this is a foreign pull request (from a fork), the diff is supplied
below (as it won't show otherwise due to GitHub magic):

diff --git a/docs/_static/js/navbar.js b/docs/_static/js/navbar.js
index d7635af888a..27191723f82 100644
--- a/docs/_static/js/navbar.js
+++ b/docs/_static/js/navbar.js
@@ -1,5 +1,5 @@
 var searchBox = $("#search-input-wrap");
-var TITLE = ['/install/', '/gluon/' , '/api/', '/docs/', '/github/', 
'/community/', ];
+var TITLE = ['/install/', '/gluon/', '/api/', '/docs/', '/community/' ];
 var DOC_TITLE = ['/faq/', '/tutorials/', '/architecture/', '/model_zoo/'];
 var APISubmenu, versionSubmenu, docSubmenu;
 $("#burgerMenu").children().each(function () {
@@ -87,4 +87,4 @@ $(document).ready(function () {
 if($("body").prop("clientWidth") < 1000 || 
$('div.sphinxsidebar').css('visibility') == 'hidden') 
$('div.content').css('width', '100%');
 else $('div.content').css('width', 'calc(100% - 300px)');
 });
-});
\ No newline at end of file
+});
diff --git a/docs/_static/mxnet-theme/navbar.html 
b/docs/_static/mxnet-theme/navbar.html
index bcc89896e40..218454aea77 100644
--- a/docs/_static/mxnet-theme/navbar.html
+++ b/docs/_static/mxnet-theme/navbar.html
@@ -14,40 +14,39 @@ 
 http://gluon.mxnet.io;>Tutorials
   
 
-
- 
+ 
+
   API 
   
 Python
+C++
 Scala
-R
 Julia
-C++
 Perl
+R
   
 
 
- 
+
   Docs 
   
-Tutorials
 FAQ
-Architecture
+Tutorials
 https://github.com/apache/incubator-mxnet/tree/master/example;>Examples
-Gluon Model Zoo
+Architecture
+Model Zoo
+ONNX
   
 
 
-
-https://github.com/dmlc/mxnet;>Github
-
 
   Community 
   
+http://discuss.mxnet.io;>Forum
+https://github.com/apache/incubator-mxnet;>Github
 Community
 Contribute
 Powered By
-http://discuss.mxnet.io;>Discuss
   
 
   


 


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[incubator-mxnet] branch master updated: [MXNET-293] Navigation updates (#10449)

[haibin]

This is an automated email from the ASF dual-hosted git repository.

haibin 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 19c5212  [MXNET-293] Navigation updates (#10449)
19c5212 is described below

commit 19c52129229349456f033cd4e2a89755b3c0709d
Author: kpmurali <37911926+kpmur...@users.noreply.github.com>
AuthorDate: Wed Apr 18 14:01:21 2018 -0700

[MXNET-293] Navigation updates (#10449)

* Changes for SIM AWSDBUX-19875
1. Add ONNX to Docs
2. Move Github to Community
3. ename Gluon Model Zoo to Model Zoo

* Removing Gluon from the Navbar and correcting the link for ONNX

* Re-ordering the elements in the Navbar for SIM AWSDBUX-19875

* In the navbar, changing the Github URL to to apache/incubator-mxnet

* Removing gluon and github from navbar.js

* Adding Gluon back to the Navbar
---
 docs/_static/js/navbar.js|  4 ++--
 docs/_static/mxnet-theme/navbar.html | 23 +++
 2 files changed, 13 insertions(+), 14 deletions(-)

diff --git a/docs/_static/js/navbar.js b/docs/_static/js/navbar.js
index d7635af..2719172 100644
--- a/docs/_static/js/navbar.js
+++ b/docs/_static/js/navbar.js
@@ -1,5 +1,5 @@
 var searchBox = $("#search-input-wrap");
-var TITLE = ['/install/', '/gluon/' , '/api/', '/docs/', '/github/', 
'/community/', ];
+var TITLE = ['/install/', '/gluon/', '/api/', '/docs/', '/community/' ];
 var DOC_TITLE = ['/faq/', '/tutorials/', '/architecture/', '/model_zoo/'];
 var APISubmenu, versionSubmenu, docSubmenu;
 $("#burgerMenu").children().each(function () {
@@ -87,4 +87,4 @@ $(document).ready(function () {
 if($("body").prop("clientWidth") < 1000 || 
$('div.sphinxsidebar').css('visibility') == 'hidden') 
$('div.content').css('width', '100%');
 else $('div.content').css('width', 'calc(100% - 300px)');
 });
-});
\ No newline at end of file
+});
diff --git a/docs/_static/mxnet-theme/navbar.html 
b/docs/_static/mxnet-theme/navbar.html
index bcc8989..218454a 100644
--- a/docs/_static/mxnet-theme/navbar.html
+++ b/docs/_static/mxnet-theme/navbar.html
@@ -14,40 +14,39 @@
 http://gluon.mxnet.io;>Tutorials
   
 
-
- 
+ 
+
   API 
   
 Python
+C++
 Scala
-R
 Julia
-C++
 Perl
+R
   
 
 
- 
+
   Docs 
   
-Tutorials
 FAQ
-Architecture
+Tutorials
 https://github.com/apache/incubator-mxnet/tree/master/example;>Examples
-Gluon Model Zoo
+Architecture
+Model Zoo
+ONNX
   
 
 
-
-https://github.com/dmlc/mxnet;>Github
-
 
   Community 
   
+http://discuss.mxnet.io;>Forum
+https://github.com/apache/incubator-mxnet;>Github
 Community
 Contribute
 Powered By
-http://discuss.mxnet.io;>Discuss
   
 
   

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[GitHub] haojin2 commented on a change in pull request #10585: [MXNET-329] support SparseEmbedding with dense weight

[GitBox]

haojin2 commented on a change in pull request #10585: [MXNET-329] support 
SparseEmbedding with dense weight
URL: https://github.com/apache/incubator-mxnet/pull/10585#discussion_r182565612
 
 

 ##
 File path: tests/python/unittest/test_sparse_operator.py
 ##
 @@ -1638,10 +1638,10 @@ def check_sparse_elementwise_sum_with_shape(stype, 
shape, n):
 @with_seed()
 def test_sparse_embedding():
 ''' test sparse embedding operator '''
-def check_sparse_embedding(in_dim, out_dim, batch, densities, 
deterministic):
+def check_sparse_embedding(in_dim, out_dim, batch, densities, 
deterministic, weight_stype):
 
 Review comment:
   What about change the name to "check_deterministic"? "deterministic" does 
not sound really straightforward.


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[GitHub] ThomasDelteil commented on issue #10485: [MXNET-304][RFC] Jenkins docs build

[GitBox]

ThomasDelteil commented on issue #10485: [MXNET-304][RFC] Jenkins docs build
URL: https://github.com/apache/incubator-mxnet/pull/10485#issuecomment-382522569
 
 
   @aaronmarkham re the "fixing scala issue" commit, we don't need to install 
the java sdk to run scala compile docs? Or does it come as a dependency of 
scala itself?


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[GitHub] anirudh2290 commented on issue #10449: [MXNET-293] Navigation updates

[GitBox]

anirudh2290 commented on issue #10449: [MXNET-293] Navigation updates
URL: https://github.com/apache/incubator-mxnet/pull/10449#issuecomment-382521646
 
 
   @piiswrong @mli gluon has been added back. Is this good to merge ?


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[GitHub] anirudh2290 opened a new pull request #10606: [WIP] Additional v1.2.0 changes - install docs changes, website changes

[GitBox]

anirudh2290 opened a new pull request #10606: [WIP] Additional v1.2.0 changes - 
install docs changes, website changes
URL: https://github.com/apache/incubator-mxnet/pull/10606
 
 
   ## Description ##
   PR to the release branch to add : #10587 and #10449 
   
   ## Checklist ##
   ### Essentials ###
   Please feel free to remove inapplicable items for your PR.
   - [ ] The PR title starts with [MXNET-$JIRA_ID], where $JIRA_ID refers to 
the relevant [JIRA issue](https://issues.apache.org/jira/projects/MXNET/issues) 
created (except PRs with tiny changes)
   - [ ] Changes are complete (i.e. I finished coding on this PR)
   - [ ] All changes have test coverage:
   - Unit tests are added for small changes to verify correctness (e.g. adding 
a new operator)
   - Nightly tests are added for complicated/long-running ones (e.g. changing 
distributed kvstore)
   - Build tests will be added for build configuration changes (e.g. adding a 
new build option with NCCL)
   - [ ] Code is well-documented: 
   - For user-facing API changes, API doc string has been updated. 
   - For new C++ functions in header files, their functionalities and arguments 
are documented. 
   - For new examples, README.md is added to explain the what the example does, 
the source of the dataset, expected performance on test set and reference to 
the original paper if applicable
   - Check the API doc at 
http://mxnet-ci-doc.s3-accelerate.dualstack.amazonaws.com/PR-$PR_ID/$BUILD_ID/index.html
   - [ ] To the my best knowledge, examples are either not affected by this 
change, or have been fixed to be compatible with this change
   
   ### Changes ###
   - [ ] Feature1, tests, (and when applicable, API doc)
   - [ ] Feature2, tests, (and when applicable, API doc)
   
   ## Comments ##
   - If this change is a backward incompatible change, why must this change be 
made.
   - Interesting edge cases to note here
   


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[GitHub] eric-haibin-lin commented on issue #10585: [MXNET-329] support SparseEmbedding with dense weight

[GitBox]

eric-haibin-lin commented on issue #10585: [MXNET-329] support SparseEmbedding 
with dense weight
URL: https://github.com/apache/incubator-mxnet/pull/10585#issuecomment-382514788
 
 
   @ZiyueHuang @haojin2 could you review?


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[incubator-mxnet] branch master updated: Remove pip upgrade step from install docs (#10587)

[cjolivier01]

This is an automated email from the ASF dual-hosted git repository.

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 869b156  Remove pip upgrade step from install docs (#10587)
869b156 is described below

commit 869b156f2f2acfca0012f3e1f720120f9ee9dd8d
Author: Anirudh Subramanian 
AuthorDate: Wed Apr 18 12:58:23 2018 -0700

Remove pip upgrade step from install docs (#10587)

* Remove pip upgrade step

* Trigger CI

* Fix for GPU too

* Trigger CI
---
 docs/install/index.md | 2 --
 1 file changed, 2 deletions(-)

diff --git a/docs/install/index.md b/docs/install/index.md
index 2fe8dbf..e36ed23 100644
--- a/docs/install/index.md
+++ b/docs/install/index.md
@@ -253,7 +253,6 @@ $ sudo apt-get install -y python-dev python-setuptools 
python-pip libgfortran3
 
 ```bash
 $ cd python
-$ pip install --upgrade pip
 $ pip install -e .
 ```
 
@@ -476,7 +475,6 @@ $ sudo apt-get install -y python-dev python-setuptools 
python-pip libgfortran3
 
 ```bash
 $ cd python
-$ pip install --upgrade pip
 $ pip install -e .
 ```
 

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[GitHub] cjolivier01 closed pull request #10587: Remove pip upgrade step from install docs

[GitBox]

cjolivier01 closed pull request #10587: Remove pip upgrade step from install 
docs
URL: https://github.com/apache/incubator-mxnet/pull/10587
 
 
   

This is a PR merged from a forked repository.
As GitHub hides the original diff on merge, it is displayed below for
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below (as it won't show otherwise due to GitHub magic):

diff --git a/docs/install/index.md b/docs/install/index.md
index 2fe8dbf5c51..e36ed23bb87 100644
--- a/docs/install/index.md
+++ b/docs/install/index.md
@@ -253,7 +253,6 @@ $ sudo apt-get install -y python-dev python-setuptools 
python-pip libgfortran3
 
 ```bash
 $ cd python
-$ pip install --upgrade pip
 $ pip install -e .
 ```
 
@@ -476,7 +475,6 @@ $ sudo apt-get install -y python-dev python-setuptools 
python-pip libgfortran3
 
 ```bash
 $ cd python
-$ pip install --upgrade pip
 $ pip install -e .
 ```
 


 


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[GitHub] eric-haibin-lin commented on issue #10509: [Improvement] Distinguish Sparse/Dense operator for temp resource request

[GitBox]

eric-haibin-lin commented on issue #10509: [Improvement] Distinguish 
Sparse/Dense operator for temp resource request
URL: 
https://github.com/apache/incubator-mxnet/issues/10509#issuecomment-382503640
 
 
   After some discussion with @piiswrong and @zheng-da I think the following 
additional interface will be sufficient to distinguish most of the ops:
   ```
   using FResourceRequestEx = std::function<
 std::vector (const NodeAttrs& n, const DispatchMode 
dispatch_mode, const int dev_mask)>;
   ```
   We need to replace FResourceRequest with FResourceRequestEx for the ops we 
want to change.


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[GitHub] tdomhan commented on issue #10354: Expose the number of GPUs.

[GitBox]

tdomhan commented on issue #10354: Expose the number of GPUs.
URL: https://github.com/apache/incubator-mxnet/pull/10354#issuecomment-382502963
 
 
   so for CPU tests we run MXNet without CUDA built in, meaning that we compile 
once for CPU tests and then also for GPU tests with different flags?


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[GitHub] rahul003 commented on issue #10531: Float16 Support for dot

[GitBox]

rahul003 commented on issue #10531: Float16 Support for dot
URL: 
https://github.com/apache/incubator-mxnet/issues/10531#issuecomment-382488353
 
 
   Can we close this now?


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[GitHub] rahul003 commented on issue #9629: do not save gpu memory during fp16 training

[GitBox]

rahul003 commented on issue #9629: do not save gpu memory during fp16 training
URL: 
https://github.com/apache/incubator-mxnet/issues/9629#issuecomment-382485782
 
 
   @tornadomeet / @315386775 Were you both using such low batch sizes? I 
imagine in such cases, the CUDA overhead might dominate network GPU costs and 
does not provide a fair picture. I've tried using larger batch sizes for the 
same model and did notice decrease in memory used.


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[GitHub] zhreshold closed pull request #10603: fix MobileNetV2 structure according to 1801.04381 v3

[GitBox]

zhreshold closed pull request #10603: fix MobileNetV2 structure according to 
1801.04381 v3
URL: https://github.com/apache/incubator-mxnet/pull/10603
 
 
   

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diff --git a/python/mxnet/gluon/model_zoo/vision/mobilenet.py 
b/python/mxnet/gluon/model_zoo/vision/mobilenet.py
index 7c3b7d643eb..5b4c9a8e615 100644
--- a/python/mxnet/gluon/model_zoo/vision/mobilenet.py
+++ b/python/mxnet/gluon/model_zoo/vision/mobilenet.py
@@ -23,7 +23,7 @@
'mobilenet_v2_0_25', 'get_mobilenet', 'get_mobilenet_v2']
 
 __modify__ = 'dwSun'
-__modified_date__ = '18/01/31'
+__modified_date__ = '18/04/18'
 
 import os
 
@@ -33,17 +33,29 @@
 
 
 # Helpers
+class RELU6(nn.HybridBlock):
+"""Relu6 used in MobileNetV2."""
+
+def __init__(self, **kwargs):
+super(RELU6, self).__init__(**kwargs)
+
+def hybrid_forward(self, F, x):
+return F.clip(x, 0, 6, name="relu6")
+
+
 # pylint: disable= too-many-arguments
-def _add_conv(out, channels=1, kernel=1, stride=1, pad=0, num_group=1, 
active=True):
+def _add_conv(out, channels=1, kernel=1, stride=1, pad=0,
+  num_group=1, active=True, relu6=False):
 out.add(nn.Conv2D(channels, kernel, stride, pad, groups=num_group, 
use_bias=False))
 out.add(nn.BatchNorm(scale=True))
 if active:
-out.add(nn.Activation('relu'))
+out.add(RELU6() if relu6 else nn.Activation('relu'))
 
 
-def _add_conv_dw(out, dw_channels, channels, stride):
-_add_conv(out, channels=dw_channels, kernel=3, stride=stride, pad=1, 
num_group=dw_channels)
-_add_conv(out, channels=channels)
+def _add_conv_dw(out, dw_channels, channels, stride, relu6=False):
+_add_conv(out, channels=dw_channels, kernel=3, stride=stride,
+  pad=1, num_group=dw_channels, relu6=relu6)
+_add_conv(out, channels=channels, relu6=relu6)
 
 
 class LinearBottleneck(nn.HybridBlock):
@@ -70,10 +82,10 @@ def __init__(self, in_channels, channels, t, stride, 
**kwargs):
 with self.name_scope():
 self.out = nn.HybridSequential()
 
-_add_conv(self.out, in_channels * t)
+_add_conv(self.out, in_channels * t, relu6=True)
 _add_conv(self.out, in_channels * t, kernel=3, stride=stride,
-  pad=1, num_group=in_channels * t)
-_add_conv(self.out, channels, active=False)
+  pad=1, num_group=in_channels * t, relu6=True)
+_add_conv(self.out, channels, active=False, relu6=True)
 
 def hybrid_forward(self, F, x):
 out = self.out(x)
@@ -143,21 +155,21 @@ def __init__(self, multiplier=1.0, classes=1000, 
**kwargs):
 self.features = nn.HybridSequential(prefix='features_')
 with self.features.name_scope():
 _add_conv(self.features, int(32 * multiplier), kernel=3,
-  stride=2, pad=1)
+  stride=2, pad=1, relu6=True)
 
 in_channels_group = [int(x * multiplier) for x in [32] + [16] 
+ [24] * 2
  + [32] * 3 + [64] * 4 + [96] * 3 + [160] 
* 3]
 channels_group = [int(x * multiplier) for x in [16] + [24] * 2 
+ [32] * 3
   + [64] * 4 + [96] * 3 + [160] * 3 + [320]]
 ts = [1] + [6] * 16
-strides = [1, 2] * 2 + [1] * 6 + [2, 1, 1] * 2 + [1]
+strides = [1, 2] * 2 + [1, 1, 2] + [1] * 6 + [2] + [1] * 3
 
 for in_c, c, t, s in zip(in_channels_group, channels_group, 
ts, strides):
 self.features.add(LinearBottleneck(in_channels=in_c, 
channels=c,
t=t, stride=s))
 
 last_channels = int(1280 * multiplier) if multiplier > 1.0 
else 1280
-_add_conv(self.features, last_channels)
+_add_conv(self.features, last_channels, relu6=True)
 
 self.features.add(nn.GlobalAvgPool2D())
 


 


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[incubator-mxnet] branch master updated: fix MobileNetV2 structure according to 1801.04381 v3 (#10603)

[zhreshold]

This is an automated email from the ASF dual-hosted git repository.

zhreshold 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 7661fee  fix MobileNetV2 structure according to 1801.04381 v3 (#10603)
7661fee is described below

commit 7661fee7b2818504abd58f5ca52323f888d85a7a
Author: dwSun <5899962+dw...@users.noreply.github.com>
AuthorDate: Thu Apr 19 02:30:31 2018 +0800

fix MobileNetV2 structure according to 1801.04381 v3 (#10603)

* fix net structure according to 1801.04381 v3. the struct is:
input shape stride  output shape
224x224x3   2   112x112x32

112x112x32  1   112x112x16

112x112x16  2   56x56x24
56x56x241   56x56x24

56x56x242   28x28x32
28x28x321   28x28x32
28x28x321   28x28x32

28x28x322   28x28x64
14x14x641   14x14x64
14x14x641   14x14x64
14x14x641   14x14x64

14x14x641   14x14x96
14x14x961   14x14x96
14x14x961   14x14x96

14x14x962   7x7x160
7x7x160 1   7x7x160
7x7x160 1   7x7x160

7x7x160 1   7x7x320

7x7x320 1   7x7x1280

7x7x1280_   1x1x1280

1x1x1280_   1x1xk

* relu -> relu6 in MobileNetV2
---
 python/mxnet/gluon/model_zoo/vision/mobilenet.py | 36 
 1 file changed, 24 insertions(+), 12 deletions(-)

diff --git a/python/mxnet/gluon/model_zoo/vision/mobilenet.py 
b/python/mxnet/gluon/model_zoo/vision/mobilenet.py
index 7c3b7d6..5b4c9a8 100644
--- a/python/mxnet/gluon/model_zoo/vision/mobilenet.py
+++ b/python/mxnet/gluon/model_zoo/vision/mobilenet.py
@@ -23,7 +23,7 @@ __all__ = ['MobileNet', 'MobileNetV2', 'mobilenet1_0', 
'mobilenet_v2_1_0', 'mobi
'mobilenet_v2_0_25', 'get_mobilenet', 'get_mobilenet_v2']
 
 __modify__ = 'dwSun'
-__modified_date__ = '18/01/31'
+__modified_date__ = '18/04/18'
 
 import os
 
@@ -33,17 +33,29 @@ from ...block import HybridBlock
 
 
 # Helpers
+class RELU6(nn.HybridBlock):
+"""Relu6 used in MobileNetV2."""
+
+def __init__(self, **kwargs):
+super(RELU6, self).__init__(**kwargs)
+
+def hybrid_forward(self, F, x):
+return F.clip(x, 0, 6, name="relu6")
+
+
 # pylint: disable= too-many-arguments
-def _add_conv(out, channels=1, kernel=1, stride=1, pad=0, num_group=1, 
active=True):
+def _add_conv(out, channels=1, kernel=1, stride=1, pad=0,
+  num_group=1, active=True, relu6=False):
 out.add(nn.Conv2D(channels, kernel, stride, pad, groups=num_group, 
use_bias=False))
 out.add(nn.BatchNorm(scale=True))
 if active:
-out.add(nn.Activation('relu'))
+out.add(RELU6() if relu6 else nn.Activation('relu'))
 
 
-def _add_conv_dw(out, dw_channels, channels, stride):
-_add_conv(out, channels=dw_channels, kernel=3, stride=stride, pad=1, 
num_group=dw_channels)
-_add_conv(out, channels=channels)
+def _add_conv_dw(out, dw_channels, channels, stride, relu6=False):
+_add_conv(out, channels=dw_channels, kernel=3, stride=stride,
+  pad=1, num_group=dw_channels, relu6=relu6)
+_add_conv(out, channels=channels, relu6=relu6)
 
 
 class LinearBottleneck(nn.HybridBlock):
@@ -70,10 +82,10 @@ class LinearBottleneck(nn.HybridBlock):
 with self.name_scope():
 self.out = nn.HybridSequential()
 
-_add_conv(self.out, in_channels * t)
+_add_conv(self.out, in_channels * t, relu6=True)
 _add_conv(self.out, in_channels * t, kernel=3, stride=stride,
-  pad=1, num_group=in_channels * t)
-_add_conv(self.out, channels, active=False)
+  pad=1, num_group=in_channels * t, relu6=True)
+_add_conv(self.out, channels, active=False, relu6=True)
 
 def hybrid_forward(self, F, x):
 out = self.out(x)
@@ -143,21 +155,21 @@ class MobileNetV2(nn.HybridBlock):
 self.features = nn.HybridSequential(prefix='features_')
 with self.features.name_scope():
 _add_conv(self.features, int(32 * multiplier), kernel=3,
-  stride=2, pad=1)
+  stride=2, pad=1, relu6=True)
 
 in_channels_group = [int(x * multiplier) for x in [32] + [16] 
+ [24] * 2
  + [32] * 3 + [64] * 4 + [96] * 3 + [160] 
* 3]
 channels_group = [int(x * multiplier) for x in [16] + [24] * 2 
+ [32] * 3
   + [64] * 4 + [96] * 3 + [160] * 3 + [320]]
 ts = [1] + [6] * 16
-strides = [1, 2] * 2 + [1] * 6 + [2, 1, 1] * 2 + [1]
+strides = [1, 2] * 2 + [1, 1, 2] + 

[GitHub] kpmurali commented on issue #10449: [MXNET-293] Navigation updates

[GitBox]

kpmurali commented on issue #10449: [MXNET-293] Navigation updates
URL: https://github.com/apache/incubator-mxnet/pull/10449#issuecomment-382482818
 
 
   I have added Gluon back to the navbar. Please review @aaronmarkham @mli 
@piiswrong @srochel


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[GitHub] aaronmarkham commented on issue #10449: [MXNET-293] Navigation updates

[GitBox]

aaronmarkham commented on issue #10449: [MXNET-293] Navigation updates
URL: https://github.com/apache/incubator-mxnet/pull/10449#issuecomment-382482209
 
 
   @srochel - this was intended to go out after 1.2 RC, but when ONNX was 
removed from the home page to make room for the 60-min crash course, we lost 
the only way to find ONNX info. It wouldn't even be in the nav, so that's why I 
asked for the overall nav update to be included as well.


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[GitHub] anirudh2290 commented on issue #10587: Remove pip upgrade step from install docs

[GitBox]

anirudh2290 commented on issue #10587: Remove pip upgrade step from install docs
URL: https://github.com/apache/incubator-mxnet/pull/10587#issuecomment-382450910
 
 
   @gsemet Thanks for your inputs. Even with the `--user` flag the system pip 
breaks on Ubuntu 16.04:
   ```
   $ pip install --upgrade pip --user
   $ pip -v
   Traceback (most recent call last):
 File "/usr/bin/pip", line 9, in 
   from pip import main
   ImportError: cannot import name main
   $ /usr/bin/pip -v
   Traceback (most recent call last):
 File "/usr/bin/pip", line 9, in 
   from pip import main
   ImportError: cannot import name main
   $ echo $PATH
   
/home/ubuntu/bin:/home/ubuntu/.local/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/games:/usr/local/games:/snap/bin
   ```

   Since, the upgrade to pip doesn't seem to be required (unless there is a 
counter use case that i am not aware of), we can just omit the upgrade step 
here.
   


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[GitHub] piiswrong closed pull request #10572: Make frontpage nav fonts bolder

[GitBox]

piiswrong closed pull request #10572: Make frontpage nav fonts bolder
URL: https://github.com/apache/incubator-mxnet/pull/10572
 
 
   

This is a PR merged from a forked repository.
As GitHub hides the original diff on merge, it is displayed below for
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below (as it won't show otherwise due to GitHub magic):

diff --git a/docs/_static/mxnet.css b/docs/_static/mxnet.css
index a62ceb59890..d949f7fd5ba 100644
--- a/docs/_static/mxnet.css
+++ b/docs/_static/mxnet.css
@@ -209,7 +209,7 @@ img {
 font-family: AmazonEmber;
 display: inline-block;
 padding: 0 15px;
-font-weight: 300;
+font-weight: 500; 
 }
 
 .main-nav-link:hover {
@@ -548,7 +548,7 @@ li.dropdown-submenu ul.dropdown-menu a {
 padding: 60px 0 10px 0;
 font-size: 40px;
 line-height: 55px;
-font-weight: 300;
+font-weight: 500;
 font-family: AmazonEmber;
 color: #fff;
 max-width: 600px;


 


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[incubator-mxnet] branch master updated: Make frontpage nav fonts bolder (#10572)

[jxie]

This is an automated email from the ASF dual-hosted git repository.

jxie 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 1b0afc0  Make frontpage nav fonts bolder (#10572)
1b0afc0 is described below

commit 1b0afc0fd6135000160e69f2d77e3a52476d9540
Author: Mu Li 
AuthorDate: Wed Apr 18 10:56:14 2018 -0700

Make frontpage nav fonts bolder (#10572)

* Make frontpage nav fonts bolder

* re-run the build
---
 docs/_static/mxnet.css | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/docs/_static/mxnet.css b/docs/_static/mxnet.css
index a62ceb5..d949f7f 100644
--- a/docs/_static/mxnet.css
+++ b/docs/_static/mxnet.css
@@ -209,7 +209,7 @@ img {
 font-family: AmazonEmber;
 display: inline-block;
 padding: 0 15px;
-font-weight: 300;
+font-weight: 500; 
 }
 
 .main-nav-link:hover {
@@ -548,7 +548,7 @@ li.dropdown-submenu ul.dropdown-menu a {
 padding: 60px 0 10px 0;
 font-size: 40px;
 line-height: 55px;
-font-weight: 300;
+font-weight: 500;
 font-family: AmazonEmber;
 color: #fff;
 max-width: 600px;

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[GitHub] piiswrong commented on issue #10604: fix strip prefix in HybridBlock with parameter to control it.

[GitBox]

piiswrong commented on issue #10604: fix strip prefix in HybridBlock with 
parameter to control it.
URL: https://github.com/apache/incubator-mxnet/pull/10604#issuecomment-382474076
 
 
   You can use net.collect_params().load to load the exported network.
   strip_prefix should be False by default.
   


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[GitHub] indhub commented on issue #10568: [WIP] [MXNET-325] Model parallelism tutorial.

[GitBox]

indhub commented on issue #10568: [WIP] [MXNET-325] Model parallelism tutorial.
URL: https://github.com/apache/incubator-mxnet/pull/10568#issuecomment-382472168
 
 
   @ThomasDelteil When I run it on two GPUs, I see 100% utilization of both 
GPUs. There are no blocking operations in the code.


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[GitHub] spidyDev commented on a change in pull request #10605: [MXNET-310] [ONNX-MXNet] API to import ONNX models into Gluon.

[GitBox]

spidyDev commented on a change in pull request #10605: [MXNET-310] [ONNX-MXNet] 
API to import ONNX models into Gluon.
URL: https://github.com/apache/incubator-mxnet/pull/10605#discussion_r182505547
 
 

 ##
 File path: python/mxnet/contrib/onnx/_import/import_onnx.py
 ##
 @@ -132,13 +133,71 @@ def from_onnx(self, graph):
 out = out[0]
 return out, argDict, auxDict
 
+def get_graph_metadata(self, graph):
+"""
+Get metadata from a given onnx graph.
+"""
+_params = set()
+for tensor_vals in graph.initializer:
+_params.add(tensor_vals.name)
+
+input_data = []
+for graph_input in graph.input:
+shape = []
+if graph_input.name not in _params:
+for val in graph_input.type.tensor_type.shape.dim:
+shape.append(val.dim_value)
+input_data.append((graph_input.name, tuple(shape)))
+
+output_data = []
+for graph_out in graph.output:
+shape = []
+for val in graph_out.type.tensor_type.shape.dim:
+shape.append(val.dim_value)
+output_data.append((graph_out.name, tuple(shape)))
+metadata = {'input_tensor_data' : input_data,
+'output_tensor_data' : output_data
+   }
+return metadata
+
+def graph_to_gluon(self, graph):
+"""Construct SymbolBlock from onnx graph.
+
+Parameters
+--
+graph : onnx protobuf object
+The loaded onnx graph
+
+Returns
+---
+sym_block :gluon.nn.SymbolBlock
+The returned gluon SymbolBlock
+"""
+sym, arg_params, aux_params = self.from_onnx(graph)
+metadata = self.get_graph_metadata(graph)
+data_names = [input_tensor[0] for input_tensor in 
metadata['input_tensor_data']]
+data_inputs = [symbol.var(data_name) for data_name in data_names]
+
+from gluon import SymbolBlock
 
 Review comment:
   do we need this here ? can we move it to top ?


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[GitHub] spidyDev commented on a change in pull request #10605: [MXNET-310] [ONNX-MXNet] API to import ONNX models into Gluon.

[GitBox]

spidyDev commented on a change in pull request #10605: [MXNET-310] [ONNX-MXNet] 
API to import ONNX models into Gluon.
URL: https://github.com/apache/incubator-mxnet/pull/10605#discussion_r182510986
 
 

 ##
 File path: python/mxnet/contrib/onnx/_import/import_onnx.py
 ##
 @@ -132,13 +133,71 @@ def from_onnx(self, graph):
 out = out[0]
 return out, argDict, auxDict
 
+def get_graph_metadata(self, graph):
+"""
+Get metadata from a given onnx graph.
+"""
+_params = set()
+for tensor_vals in graph.initializer:
+_params.add(tensor_vals.name)
+
+input_data = []
+for graph_input in graph.input:
+shape = []
+if graph_input.name not in _params:
+for val in graph_input.type.tensor_type.shape.dim:
+shape.append(val.dim_value)
+input_data.append((graph_input.name, tuple(shape)))
+
+output_data = []
+for graph_out in graph.output:
+shape = []
+for val in graph_out.type.tensor_type.shape.dim:
+shape.append(val.dim_value)
+output_data.append((graph_out.name, tuple(shape)))
+metadata = {'input_tensor_data' : input_data,
+'output_tensor_data' : output_data
+   }
+return metadata
+
+def graph_to_gluon(self, graph):
+"""Construct SymbolBlock from onnx graph.
+
+Parameters
+--
+graph : onnx protobuf object
+The loaded onnx graph
+
+Returns
+---
+sym_block :gluon.nn.SymbolBlock
+The returned gluon SymbolBlock
+"""
+sym, arg_params, aux_params = self.from_onnx(graph)
+metadata = self.get_graph_metadata(graph)
+data_names = [input_tensor[0] for input_tensor in 
metadata['input_tensor_data']]
+data_inputs = [symbol.var(data_name) for data_name in data_names]
+
+from gluon import SymbolBlock
+net = SymbolBlock(outputs=sym, inputs=data_inputs)
 
 Review comment:
   Add few comments to explain what is the logic here 


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[GitHub] spidyDev commented on a change in pull request #10605: [MXNET-310] [ONNX-MXNet] API to import ONNX models into Gluon.

[GitBox]

spidyDev commented on a change in pull request #10605: [MXNET-310] [ONNX-MXNet] 
API to import ONNX models into Gluon.
URL: https://github.com/apache/incubator-mxnet/pull/10605#discussion_r182511252
 
 

 ##
 File path: python/mxnet/contrib/onnx/_import/import_to_gluon.py
 ##
 @@ -0,0 +1,45 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License.  You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied.  See the License for the
+# specific language governing permissions and limitations
+# under the License.
+
+# coding: utf-8
+"""Import ONNX model to gluon interface"""
+from .import_onnx import GraphProto
+
+def import_to_gluon(model_file):
+"""
+Imports the ONNX model files, passed as a parameter, into Gluon 
SymbolBlock object.
+
+Parameters
+--
+model_file : str
+ONNX model file name
+
+Returns
+---
+sym_block : :class:`~mxnet.gluon.SymbolBlock`
+A SymbolBlock object representing the given model file.
+"""
+graph = GraphProto()
+try:
+import onnx
+except ImportError:
+raise ImportError("Onnx and protobuf need to be installed. 
Instructions to"
+  + " install - 
https://github.com/onnx/onnx#installation;)
+model_proto = onnx.load(model_file)
 
 Review comment:
   file exists check 


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[GitHub] spidyDev commented on a change in pull request #10605: [MXNET-310] [ONNX-MXNet] API to import ONNX models into Gluon.

[GitBox]

spidyDev commented on a change in pull request #10605: [MXNET-310] [ONNX-MXNet] 
API to import ONNX models into Gluon.
URL: https://github.com/apache/incubator-mxnet/pull/10605#discussion_r182510350
 
 

 ##
 File path: python/mxnet/contrib/onnx/_import/import_model.py
 ##
 @@ -52,3 +52,28 @@ def import_model(model_file):
 model_proto = onnx.load(model_file)
 sym, arg_params, aux_params = graph.from_onnx(model_proto.graph)
 return sym, arg_params, aux_params
+
+def get_model_metadata(model_file):
+"""
+Returns the name and shape information of input and output tensors of the 
given ONNX model file.
+
+Parameters
+--
+model_file : str
+ONNX model file name
+
+Returns
+---
+model_metadata : dict
+A dictionary object mapping various metadata to its corresponding 
value.
+"""
+graph = GraphProto()
+try:
+import onnx
+except ImportError:
+raise ImportError("Onnx and protobuf need to be installed. "
+  + "Instructions to install - 
https://github.com/onnx/onnx;)
+model_proto = onnx.load(model_file)
 
 Review comment:
   add check for if file exists and throw appropriate error message


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[GitHub] spidyDev commented on a change in pull request #10605: [MXNET-310] [ONNX-MXNet] API to import ONNX models into Gluon.

[GitBox]

spidyDev commented on a change in pull request #10605: [MXNET-310] [ONNX-MXNet] 
API to import ONNX models into Gluon.
URL: https://github.com/apache/incubator-mxnet/pull/10605#discussion_r182512877
 
 

 ##
 File path: tests/python-pytest/onnx/gluon_backend.py
 ##
 @@ -0,0 +1,148 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License.  You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied.  See the License for the
+# specific language governing permissions and limitations
+# under the License.
+
+# coding: utf-8
+"""Gluon backend wrapper for onnx test infrastructure"""
+import mxnet as mx
+from mxnet import nd
+from mxnet.contrib.onnx._import.import_onnx import GraphProto
+import numpy as np
+try:
+from onnx import helper, TensorProto
+from onnx.backend.base import Backend
+except ImportError:
+raise ImportError("Onnx and protobuf need to be installed. Instructions to"
+  + " install - https://github.com/onnx/onnx#installation;)
+from gluon_backend_rep import GluonBackendRep
+
+# GluonBackend class will take an ONNX model with inputs, perform a 
computation,
+# and then return the output.
+# Implemented by following onnx docs guide:
+# https://github.com/onnx/onnx/blob/master/docs/ImplementingAnOnnxBackend.md
+
+class GluonBackend(Backend):
+"""Gluon backend for ONNX"""
+
+@staticmethod
+def make_graph(node, inputs):
+""" Created ONNX GraphProto from node"""
+initializer = []
+tensor_input_info = []
+tensor_output_info = []
+
+# Adding input tensor info.
+for index in range(len(node.input)):
+tensor_input_info.append(
+helper.make_tensor_value_info(str(node.input[index]), 
TensorProto.FLOAT, [1]))
+
+# Creating an initializer for Weight params.
+# Assumes that weight params is named as 'W'.
+if node.input[index] == 'W':
+dim = inputs[index].shape
+param_tensor = helper.make_tensor(
+name=node.input[index],
+data_type=TensorProto.FLOAT,
+dims=dim,
+vals=inputs[index].flatten())
+
+initializer.append(param_tensor)
+
+# Adding output tensor info.
+for index in range(len(node.output)):
+tensor_output_info.append(
+helper.make_tensor_value_info(str(node.output[index]), 
TensorProto.FLOAT, [1]))
+
+# creating graph proto object.
+graph_proto = helper.make_graph(
+[node],
+"test",
+tensor_input_info,
+tensor_output_info,
+initializer=initializer)
+
+return graph_proto
+
+@classmethod
+def run_node(cls, node, inputs, device='CPU'):
+"""Running individual node inference on gluon backend and
+return the result to onnx test infrastructure.
+
+Parameters
+--
+node   : onnx node object
+loaded onnx node (individual layer)
+inputs : numpy array
+input to run a node on
+device : 'CPU'
+device to run a node on
+
+Returns
+---
+params : numpy array
+result obtained after running the operator
+"""
+graph = GraphProto()
+net = graph.graph_to_gluon(GluonBackend.make_graph(node, inputs))
+
+# create module, passing cpu context
+if device == 'CPU':
+ctx = mx.cpu()
+else:
+raise NotImplementedError("Only CPU context is supported for now")
+
+if node.op_type in ['Conv']:
 
 Review comment:
   Add comment why we are doing this for 'conv'?


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[GitHub] spidyDev commented on a change in pull request #10605: [MXNET-310] [ONNX-MXNet] API to import ONNX models into Gluon.

[GitBox]

spidyDev commented on a change in pull request #10605: [MXNET-310] [ONNX-MXNet] 
API to import ONNX models into Gluon.
URL: https://github.com/apache/incubator-mxnet/pull/10605#discussion_r182507348
 
 

 ##
 File path: tests/python-pytest/onnx/gluon_backend_test.py
 ##
 @@ -0,0 +1,57 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License.  You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied.  See the License for the
+# specific language governing permissions and limitations
+# under the License.
+
+"""ONNX test backend wrapper"""
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+from __future__ import unicode_literals
+
+import unittest
+try:
+import onnx.backend.test
+except ImportError:
+raise ImportError("Onnx and protobuf need to be installed. Instructions to"
+  + " install - https://github.com/onnx/onnx#installation;)
+
+import gluon_backend
+import test_cases
+
+# This is a pytest magic variable to load extra plugins
+pytest_plugins = "onnx.backend.test.report",
+
+BACKEND_TESTS = onnx.backend.test.BackendTest(gluon_backend, __name__)
+
+for op_test in test_cases.IMPLEMENTED_OPERATORS_TEST:
+BACKEND_TESTS.include(op_test)
+
+for std_model_test in test_cases.STANDARD_MODEL:
+BACKEND_TESTS.include(std_model_test)
+
+for basic_model_test in test_cases.BASIC_MODEL_TESTS:
+BACKEND_TESTS.include(basic_model_test)
+
+#test_elu_example
+#test_leakyrelu_example
+
+#GLUON_TEST.include('test_elu_example')
 
 Review comment:
   remove lines


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[GitHub] piiswrong commented on issue #10605: [MXNET-310] [ONNX-MXNet] API to import ONNX models into Gluon.

[GitBox]

piiswrong commented on issue #10605: [MXNET-310] [ONNX-MXNet] API to import 
ONNX models into Gluon.
URL: https://github.com/apache/incubator-mxnet/pull/10605#issuecomment-382470853
 
 
   This is unnecessary. You can use gluon's SymbolBlock to directly load symbol 
models.


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[GitHub] haojin2 commented on a change in pull request #10557: [MXNET-322] Elemwise_mul(row_sparse, dense) = row_sparse on CPU

[GitBox]

haojin2 commented on a change in pull request #10557: [MXNET-322] 
Elemwise_mul(row_sparse, dense) = row_sparse on CPU
URL: https://github.com/apache/incubator-mxnet/pull/10557#discussion_r182510261
 
 

 ##
 File path: tests/python/unittest/test_sparse_operator.py
 ##
 @@ -322,17 +322,15 @@ def lt(l, r):
 def le(l, r):
 return check_all(l, r, lambda a, b: a <= b)
 
-def least_sparse(lstype, rstype):
-if lstype == 'default' and rstype == 'default':
+def elemwise_mul_stype(lstype, rstype):
+if lstype == rstype:
+return lstype
+elif lstype == 'default' and rstype == 'row_sparse':
+return 'row_sparse'
+elif rstype == 'default' and lstype == 'row_sparse':
 
 Review comment:
   just a nit, will "elif lstype == 'row_sparse' and rstype == 'default'" 
easier to read?


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[GitHub] kpmurali commented on issue #10449: [MXNET-293] Navigation updates

[GitBox]

kpmurali commented on issue #10449: [MXNET-293] Navigation updates
URL: https://github.com/apache/incubator-mxnet/pull/10449#issuecomment-382468370
 
 
   Ok, I will add Gluon and its links back to the Navbar unless anyone has any 
objections.


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[GitHub] indhub commented on issue #10568: [WIP] [MXNET-325] Model parallelism tutorial.

[GitBox]

indhub commented on issue #10568: [WIP] [MXNET-325] Model parallelism tutorial.
URL: https://github.com/apache/incubator-mxnet/pull/10568#issuecomment-382466399
 
 
   @mli 


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[GitHub] anirudh2290 commented on issue #10587: Remove pip upgrade step from install docs

[GitBox]

anirudh2290 commented on issue #10587: Remove pip upgrade step from install docs
URL: https://github.com/apache/incubator-mxnet/pull/10587#issuecomment-382461854
 
 
   Yes it's in the path. You can see that I have outputted path. which pip
   returns ~/.local/bin/pip. It's weird because when I try with
   ~/.local/bin/pip it works fine.
   
   On Wed, Apr 18, 2018, 9:54 AM Gaetan Semet  wrote:
   
   > what does which pip returns? You need to ensure you have ~/.local/bin in
   > your PATH
   >
   > —
   > You are receiving this because you were mentioned.
   > Reply to this email directly, view it on GitHub
   > 
,
   > or mute the thread
   > 

   > .
   >
   


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[GitHub] anirudhacharya opened a new pull request #10605: [MXNET-310] [ONNX-MXNet] API to import ONNX models into Gluon.

[GitBox]

anirudhacharya opened a new pull request #10605: [MXNET-310] [ONNX-MXNet] API 
to import ONNX models into Gluon.
URL: https://github.com/apache/incubator-mxnet/pull/10605
 
 
   ## Description ##
   API and corresponding tests to import ONNX models into Gluon
   
   ## Checklist ##
   ### Essentials ###
   Please feel free to remove inapplicable items for your PR.
   - [ ] The PR title starts with [MXNET-$JIRA_ID], where $JIRA_ID refers to 
the relevant [JIRA issue](https://issues.apache.org/jira/projects/MXNET/issues) 
created (except PRs with tiny changes)
   - [ ] Changes are complete (i.e. I finished coding on this PR)
   - [ ] All changes have test coverage:
   - Unit tests are added for small changes to verify correctness (e.g. adding 
a new operator)
   - Build tests will be added for build configuration changes (e.g. adding a 
new build option with NCCL)
   - [ ] Code is well-documented: 
   - For user-facing API changes, API doc string has been updated. 
   - Check the API doc at 
http://mxnet-ci-doc.s3-accelerate.dualstack.amazonaws.com/PR-$PR_ID/$BUILD_ID/index.html
   - [ ] To the my best knowledge, examples are either not affected by this 
change, or have been fixed to be compatible with this change
   
   ### Changes ###
   - [ ] New import to gluon API
   
   ## Comments ##
   - Currently two tests are failing due to this - 
https://github.com/apache/incubator-mxnet/issues/10588
   @spidyDev @Roshrini 


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[GitHub] gsemet commented on issue #10587: Remove pip upgrade step from install docs

[GitBox]

gsemet commented on issue #10587: Remove pip upgrade step from install docs
URL: https://github.com/apache/incubator-mxnet/pull/10587#issuecomment-382455740
 
 
   what does `which pip` returns? You need to ensure you have ~/.local/bin in 
your PATH


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[GitHub] anirudh2290 commented on issue #10587: Remove pip upgrade step from install docs

[GitBox]

anirudh2290 commented on issue #10587: Remove pip upgrade step from install docs
URL: https://github.com/apache/incubator-mxnet/pull/10587#issuecomment-382450910
 
 
   @gsemet Thanks for your inputs. Even with the `--user` flag the system pip 
breaks on Ubuntu 16.04:
   ```
   $ pip install --upgrade pip --user
   $ pip -v
   Traceback (most recent call last):
 File "/usr/bin/pip", line 9, in 
   from pip import main
   ImportError: cannot import name main
   $ /usr/bin/pip -v
   Traceback (most recent call last):
 File "/usr/bin/pip", line 9, in 
   from pip import main
   ImportError: cannot import name main
   $ echo $PATH
   
/home/ubuntu/bin:/home/ubuntu/.local/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/games:/usr/local/games:/snap/bin
   ```

   Since, the upgrade to pip doesn't seem to be required here (unless there is 
a counter use case that i am not aware of), we can just omit the upgrade step 
here.
   


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[GitHub] marcoabreu commented on issue #10586: Cannot build ubuntu_gpu CI docker image (java8 sdk missing)

[GitBox]

marcoabreu commented on issue #10586: Cannot build ubuntu_gpu CI docker image 
(java8 sdk missing)
URL: 
https://github.com/apache/incubator-mxnet/issues/10586#issuecomment-382430009
 
 
   I'm indifferent to that. 


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[GitHub] marcoabreu commented on issue #10433: [MXNET-290] MKLDNN support for model quantization

[GitBox]

marcoabreu commented on issue #10433: [MXNET-290] MKLDNN support for model 
quantization
URL: https://github.com/apache/incubator-mxnet/pull/10433#issuecomment-382426955
 
 
   @reminisce could you please review this PR?


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[GitHub] marcoabreu commented on a change in pull request #10433: [MXNET-290] MKLDNN support for model quantization

[GitBox]

marcoabreu commented on a change in pull request #10433: [MXNET-290] MKLDNN 
support for model quantization
URL: https://github.com/apache/incubator-mxnet/pull/10433#discussion_r182468883
 
 

 ##
 File path: src/operator/quantization/quantized_conv.cc
 ##
 @@ -86,12 +89,10 @@ bool QuantizedConvType(const nnvm::NodeAttrs& attrs,
   const ConvolutionParam& param = nnvm::get(attrs.parsed);
   CHECK_EQ(in_type->size(), param.no_bias? 6U : 9U);
   CHECK_EQ(out_type->size(), 3U);
-  TYPE_ASSIGN_CHECK(*in_type, 0, mshadow::kInt8);
 
 Review comment:
   ?


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[GitHub] marcoabreu commented on a change in pull request #10433: [MXNET-290] MKLDNN support for model quantization

[GitBox]

marcoabreu commented on a change in pull request #10433: [MXNET-290] MKLDNN 
support for model quantization
URL: https://github.com/apache/incubator-mxnet/pull/10433#discussion_r182468602
 
 

 ##
 File path: src/operator/quantization/quantize_graph_pass.cc
 ##
 @@ -198,7 +198,7 @@ Graph QuantizeGraph(Graph &) {
 NodePtr mirror_node = mirror_map.at(e.node.get());
 NodeEntry mirror_entry = NodeEntry{
   mirror_node, e.index, e.version};
-size_t num_outputs = e.node->num_outputs();
+size_t num_outputs = mirror_node->num_outputs() - 2;
 
 Review comment:
   This seems like a logic change, right?


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[GitHub] marcoabreu commented on a change in pull request #10433: [MXNET-290] MKLDNN support for model quantization

[GitBox]

marcoabreu commented on a change in pull request #10433: [MXNET-290] MKLDNN 
support for model quantization
URL: https://github.com/apache/incubator-mxnet/pull/10433#discussion_r182468565
 
 

 ##
 File path: src/operator/quantization/quantize_graph_pass.cc
 ##
 @@ -159,7 +159,7 @@ Graph QuantizeGraph(Graph &) {
 uint32_t min_index = 1;
 uint32_t max_index = 2;
 if (quantized_op_map.count(e.node->op())) {
-  size_t  num_outputs = e.node->num_outputs();
+  size_t  num_outputs = mirror_node->num_outputs() - 2;
 
 Review comment:
   This seems like a logic change, right?


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[GitHub] marcoabreu commented on a change in pull request #10433: [MXNET-290] MKLDNN support for model quantization

[GitBox]

marcoabreu commented on a change in pull request #10433: [MXNET-290] MKLDNN 
support for model quantization
URL: https://github.com/apache/incubator-mxnet/pull/10433#discussion_r182467890
 
 

 ##
 File path: src/c_api/c_api_symbolic.cc
 ##
 @@ -595,7 +597,12 @@ int MXQuantizeSymbol(SymbolHandle sym_handle,
 offline.emplace(offline_params[i]);
   }
   g.attrs["offline_params"] = std::make_shared(std::move(offline));
-  g = ApplyPass(std::move(g), "QuantizeGraph");
+#if MXNET_USE_MKLDNN == 1
+  if (dev_type == Context::kCPU && dev_id == 0)
 
 Review comment:
   What is dev_id in the context of a CPU here?


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[GitHub] marcoabreu commented on a change in pull request #10433: [MXNET-290] MKLDNN support for model quantization

[GitBox]

marcoabreu commented on a change in pull request #10433: [MXNET-290] MKLDNN 
support for model quantization
URL: https://github.com/apache/incubator-mxnet/pull/10433#discussion_r182467604
 
 

 ##
 File path: python/mxnet/contrib/quantization.py
 ##
 @@ -72,7 +72,7 @@ def _quantize_params(qsym, params):
 return quantized_params
 
 
-def _quantize_symbol(sym, excluded_symbols=None, offline_params=None):
+def _quantize_symbol(sym, excluded_symbols=None, offline_params=None, 
context=cpu()):
 
 Review comment:
   @reminisce could you check? I don't think we have to specify the context 
explicitely


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[GitHub] marcoabreu commented on a change in pull request #10433: [MXNET-290] MKLDNN support for model quantization

[GitBox]

marcoabreu commented on a change in pull request #10433: [MXNET-290] MKLDNN 
support for model quantization
URL: https://github.com/apache/incubator-mxnet/pull/10433#discussion_r182467087
 
 

 ##
 File path: include/mxnet/c_api.h
 ##
 @@ -1409,13 +1409,17 @@ MXNET_DLL int MXSymbolInferType(SymbolHandle sym,
  * \param excluded_symbols array of symbols to be excluded from being quantized
  * \param num_offline number of parameters that are quantized offline
  * \param offline_params array of c strings representing the names of params 
quantized offline
+ * \param dev_type device type 
+ * \param dev_id device id
  */
 MXNET_DLL int MXQuantizeSymbol(SymbolHandle sym_handle,
SymbolHandle *ret_sym_handle,
const mx_uint num_excluded_symbols,
const SymbolHandle *excluded_symbols,
const mx_uint num_offline,
-   const char **offline_params);
+   const char **offline_params,
 
 Review comment:
   This is an API change, right? @reminisce 


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[GitHub] marcoabreu commented on a change in pull request #10433: [MXNET-290] MKLDNN support for model quantization

[GitBox]

marcoabreu commented on a change in pull request #10433: [MXNET-290] MKLDNN 
support for model quantization
URL: https://github.com/apache/incubator-mxnet/pull/10433#discussion_r182466761
 
 

 ##
 File path: ci/docker/runtime_functions.sh
 ##
 @@ -407,26 +405,28 @@ unittest_ubuntu_python3_gpu() {
 
 # quantization gpu currently only runs on P3 instances
 # need to separte it from unittest_ubuntu_python2_gpu()
-unittest_ubuntu_python2_quantization_gpu() {
+unittest_ubuntu_python2_quantization() {
 set -ex
 export PYTHONPATH=./python/
 # MXNET_MKLDNN_DEBUG is buggy and produces false positives
 # https://github.com/apache/incubator-mxnet/issues/10026
 #export MXNET_MKLDNN_DEBUG=1  # Ignored if not present
 export MXNET_STORAGE_FALLBACK_LOG_VERBOSE=0
 nosetests-2.7 --verbose tests/python/quantization_gpu
+nosetests-2.7 --verbose 
tests/python/quantization/test_quantization_mkldnn.py
 }
 
 # quantization gpu currently only runs on P3 instances
 # need to separte it from unittest_ubuntu_python3_gpu()
-unittest_ubuntu_python3_quantization_gpu() {
+unittest_ubuntu_python3_quantization() {
 set -ex
 export PYTHONPATH=./python/
 # MXNET_MKLDNN_DEBUG is buggy and produces false positives
 # https://github.com/apache/incubator-mxnet/issues/10026
 #export MXNET_MKLDNN_DEBUG=1 # Ignored if not present
 export MXNET_STORAGE_FALLBACK_LOG_VERBOSE=0
 nosetests-3.4 --verbose tests/python/quantization_gpu
+nosetests-3.4 --verbose 
tests/python/quantization/test_quantization_mkldnn.py
 
 Review comment:
   Please only use directories and not filenames


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[GitHub] marcoabreu commented on a change in pull request #10433: [MXNET-290] MKLDNN support for model quantization

[GitBox]

marcoabreu commented on a change in pull request #10433: [MXNET-290] MKLDNN 
support for model quantization
URL: https://github.com/apache/incubator-mxnet/pull/10433#discussion_r182466678
 
 

 ##
 File path: ci/docker/runtime_functions.sh
 ##
 @@ -407,26 +405,28 @@ unittest_ubuntu_python3_gpu() {
 
 # quantization gpu currently only runs on P3 instances
 # need to separte it from unittest_ubuntu_python2_gpu()
-unittest_ubuntu_python2_quantization_gpu() {
+unittest_ubuntu_python2_quantization() {
 set -ex
 export PYTHONPATH=./python/
 # MXNET_MKLDNN_DEBUG is buggy and produces false positives
 # https://github.com/apache/incubator-mxnet/issues/10026
 #export MXNET_MKLDNN_DEBUG=1  # Ignored if not present
 export MXNET_STORAGE_FALLBACK_LOG_VERBOSE=0
 nosetests-2.7 --verbose tests/python/quantization_gpu
+nosetests-2.7 --verbose 
tests/python/quantization/test_quantization_mkldnn.py
 }
 
 # quantization gpu currently only runs on P3 instances
 # need to separte it from unittest_ubuntu_python3_gpu()
-unittest_ubuntu_python3_quantization_gpu() {
+unittest_ubuntu_python3_quantization() {
 
 Review comment:
   No I think we're fine with only testing one flavour, but that should be a 
separate PR


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[GitHub] marcoabreu commented on a change in pull request #10433: [MXNET-290] MKLDNN support for model quantization

[GitBox]

marcoabreu commented on a change in pull request #10433: [MXNET-290] MKLDNN 
support for model quantization
URL: https://github.com/apache/incubator-mxnet/pull/10433#discussion_r182466521
 
 

 ##
 File path: ci/docker/runtime_functions.sh
 ##
 @@ -407,26 +405,28 @@ unittest_ubuntu_python3_gpu() {
 
 # quantization gpu currently only runs on P3 instances
 # need to separte it from unittest_ubuntu_python2_gpu()
-unittest_ubuntu_python2_quantization_gpu() {
+unittest_ubuntu_python2_quantization() {
 set -ex
 export PYTHONPATH=./python/
 # MXNET_MKLDNN_DEBUG is buggy and produces false positives
 # https://github.com/apache/incubator-mxnet/issues/10026
 #export MXNET_MKLDNN_DEBUG=1  # Ignored if not present
 export MXNET_STORAGE_FALLBACK_LOG_VERBOSE=0
 nosetests-2.7 --verbose tests/python/quantization_gpu
+nosetests-2.7 --verbose 
tests/python/quantization/test_quantization_mkldnn.py
 
 Review comment:
   Don't specify files but only directories


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[GitHub] ariwaranosai opened a new pull request #10604: fix strip prefix in HybridBlock with parameter to control it.

[GitBox]

ariwaranosai opened a new pull request #10604: fix strip prefix in HybridBlock 
with parameter to control it.
URL: https://github.com/apache/incubator-mxnet/pull/10604
 
 
   ## Description ##
   
   fix #10601 
   
   add strip_prefix parameter and strip prefix during export model.
   
   code likes
   
   ```python
   net.export("model", 0)
   net.load_params("model-.params", ctx=mx.cpu())
   ```
   can run correct.
   
   ## Checklist ##
   ### Essentials ###
   Please feel free to remove inapplicable items for your PR.
   - [x] Changes are complete (i.e. I finished coding on this PR)
   - [x] All changes have test coverage:
   - [x ] Code is well-documented: 
   - [x] To the my best knowledge, examples are either not affected by this 
change, or have been fixed to be compatible with this change
   
   ### Changes ###
   - add parameter to control which strip prefix during export models or not.


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[GitHub] srochel commented on issue #10449: [MXNET-293] Navigation updates

[GitBox]

srochel commented on issue #10449: [MXNET-293] Navigation updates
URL: https://github.com/apache/incubator-mxnet/pull/10449#issuecomment-382398507
 
 
   The PR is blocking the 1.2 RC creation. Can we keep Gluon in navigation bar 
until we have a complete proposal in place, reviewed and agreed? We should not 
have this discussions past feature freeze. 


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[GitHub] dwSun opened a new pull request #10603: fix MobileNetV2 structure according to 1801.04381 v3

[GitBox]

dwSun opened a new pull request #10603: fix MobileNetV2 structure according to 
1801.04381 v3
URL: https://github.com/apache/incubator-mxnet/pull/10603
 
 
   ## Description ##
   fix net structure according to 1801.04381 v3.
   relu -> relu6 in MobileNetV2.
   
   ## Checklist ##
   - [ Y ] Changes are complete (i.e. I finished coding on this PR)
   - [ Y ] All changes have test coverage:
   - [ Y ] Code is well-documented: 
   - [ Y ] To the my best knowledge, examples are either not affected by this 
change, or have been fixed to be compatible with this change
   


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[GitHub] chinakook commented on issue #10599: [MKLDNN Bug] MKLDNN eats lots of memory and then crash down.

[GitBox]

chinakook commented on issue #10599: [MKLDNN Bug] MKLDNN eats lots of memory 
and then crash down.
URL: 
https://github.com/apache/incubator-mxnet/issues/10599#issuecomment-382382640
 
 
   Thanks! As I've tested before, when inferencing a scene segmentation network 
such as Deeplab or U-Net,  MKL-DNN also consume far more momery.


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[GitHub] pengzhao-intel commented on issue #10599: [MKLDNN Bug] MKLDNN eats lots of memory and then crash down.

[GitBox]

pengzhao-intel commented on issue #10599: [MKLDNN Bug] MKLDNN eats lots of 
memory and then crash down.
URL: 
https://github.com/apache/incubator-mxnet/issues/10599#issuecomment-382380820
 
 
   The case consumes about 40G peak memory w/ MKL-DNN in 8.4 seconds while 12G 
w/ default CPU path in 14.5 seconds.
   
   We're looking into this issue.
   
   > [patric@mlt-skx084 hr101_mxnet]$ python tiny_detection_mxnet.py
   > [20:53:27] src/operator/nn/mkldnn/mkldnn_base.cc:60: Allocate 37632 bytes 
with malloc directly
   > [20:53:27] src/operator/nn/mkldnn/mkldnn_base.cc:60: Allocate 65536 bytes 
with malloc directly
   > [20:53:27] src/operator/nn/mkldnn/mkldnn_base.cc:60: Allocate 524288 bytes 
with malloc directly
   > [20:53:27] src/operator/nn/mkldnn/mkldnn_base.cc:60: Allocate 2097152 
bytes with malloc directly
   > ('time', 8.401818037033081, 'secs.')
   > (729, 5)
   > 
   > [patric@mlt-skx084 hr101_mxnet]$ python tiny_detection_mxnet.py
   > ('time', 14.575803995132446, 'secs.')
   > (729, 5)
   


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[GitHub] chinakook commented on issue #10600: Gluon Interpolation Layer

[GitBox]

chinakook commented on issue #10600: Gluon Interpolation Layer
URL: 
https://github.com/apache/incubator-mxnet/issues/10600#issuecomment-382375451
 
 
   I don't know. I think this op is weird.


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[GitHub] crazyleg opened a new issue #10602: mxnet.model.server custom Service model.get_outputs() returns only one result

[GitBox]

crazyleg opened a new issue #10602:  mxnet.model.server custom Service 
model.get_outputs() returns only one result
URL: https://github.com/apache/incubator-mxnet/issues/10602
 
 
   ## Description
   When using mxnet.model.server custom Service model.get_outputs() returns 
only one result, while data supplied to self.mx_model.forward(DataBatch(data), 
is_train=False) has a list of many.
   
   ## Environment info (Required)
   
   I assume not required here
   I'am using Python.
   
   ## Minimum reproducible example
   def _inference(self, data):
  
   data = [item.as_in_context(self.ctx) for item in data]
   #print(len(data)) gives 100
   #print(len(DataBatch(data).data)) gives 100
 
   self.mx_model.forward(DataBatch(data), is_train=False)
   q = self.mx_model.get_outputs()
   
   #print(len(q)) gives 1
  
   return self.mx_model.get_outputs()
   
   ## What have you tried to solve it?
   
   Currently I am iterating over data and wrap each separate sample into 
DataBatch and run separate inference. While this works, I assume that running 
forward with full DataBatch will give better performance.
   
   How should I do model.forward(DataBatch(data)) to get a list of outputs that 
is equal to len(data) ? Looks like a problem.


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[GitHub] marcoabreu commented on a change in pull request #10433: [MXNET-290] MKLDNN support for model quantization

[GitBox]

marcoabreu commented on a change in pull request #10433: [MXNET-290] MKLDNN 
support for model quantization
URL: https://github.com/apache/incubator-mxnet/pull/10433#discussion_r182411485
 
 

 ##
 File path: ci/docker/runtime_functions.sh
 ##
 @@ -371,7 +371,6 @@ unittest_ubuntu_python2_cpu() {
 export MXNET_STORAGE_FALLBACK_LOG_VERBOSE=0
 nosetests-2.7 --verbose tests/python/unittest
 nosetests-2.7 --verbose tests/python/train
-nosetests-2.7 --verbose tests/python/quantization
 
 Review comment:
   Please leave this in. It's supposed to be here, right @reminisce ?


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[GitHub] marcoabreu commented on a change in pull request #10433: [MXNET-290] MKLDNN support for model quantization

[GitBox]

marcoabreu commented on a change in pull request #10433: [MXNET-290] MKLDNN 
support for model quantization
URL: https://github.com/apache/incubator-mxnet/pull/10433#discussion_r182411505
 
 

 ##
 File path: ci/docker/runtime_functions.sh
 ##
 @@ -382,7 +381,6 @@ unittest_ubuntu_python3_cpu() {
 #export MXNET_MKLDNN_DEBUG=1  # Ignored if not present
 export MXNET_STORAGE_FALLBACK_LOG_VERBOSE=0
 nosetests-3.4 --verbose tests/python/unittest
-nosetests-3.4 --verbose tests/python/quantization
 
 Review comment:
   Please leave this in. It's supposed to be here, right @reminisce ?


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[GitHub] PKurnikov commented on issue #10600: Gluon Interpolation Layer

[GitBox]

PKurnikov commented on issue #10600: Gluon Interpolation Layer
URL: 
https://github.com/apache/incubator-mxnet/issues/10600#issuecomment-382372938
 
 
   @chinakook ,
   Thanks, this way is work!
   But the function BilinearResize2D does not work with 'width' more then 1000.
   Are there any alternative approaches to create interpolation layer without 
this restrictions?
   
   > value 1025 for Parameter width exceed bound [1,1000], in operator 
_contrib_BilinearResize2D(name="", height="513", width="1025")


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[GitHub] ariwaranosai opened a new issue #10601: load parameters error with the same code exported by HybridBlock

[GitBox]

ariwaranosai opened a new issue #10601: load parameters error  with the same 
code exported by HybridBlock
URL: https://github.com/apache/incubator-mxnet/issues/10601
 
 
   Note: Providing complete information in the most concise form is the best 
way to get help. This issue template serves as the checklist for essential 
information to most of the technical issues and bug reports. For non-technical 
issues and feature requests, feel free to present the information in what you 
believe is the best form.
   
   For Q & A and discussion, please start a discussion thread at 
https://discuss.mxnet.io 
   
   ## Description
   
   HybridBlock export don't remove self.prefix in name, but load_params will 
insert_prefix. This is confusing for 
   
   ```python
   net = get_mode()
   # some train step
   net.export(filename)
   
   new_net = get_model()
   new_net.load_params("path to params", ctx=mx.cpu()) // this will raise error 
AssertionError: Parameter XXX is missing in file XXX
   ```
   since prefix will be insert twice during load params.
   
   It would be nice, give a parameter to control whether remove  self.prefix or 
not. 
   
   ## Environment info (Required)
   
   ```
   --Python Info--
   Version  : 3.6.3
   Compiler : GCC 4.2.1 Compatible Clang 4.0.1 (tags/RELEASE_401/final)
   Build: ('default', 'Oct  6 2017 12:04:38')
   Arch : ('64bit', '')
   Pip Info---
   Version  : 9.0.1
   Directory: /Users/feiquan/anaconda3/lib/python3.6/site-packages/pip
   --MXNet Info---
   
/Users/feiquan/anaconda3/lib/python3.6/site-packages/urllib3/contrib/pyopenssl.py:46:
 DeprecationWarning: OpenSSL.rand is deprecated - you should use os.urandom 
instead
 import OpenSSL.SSL
   Version  : 1.0.0
   Directory: /Users/feiquan/anaconda3/lib/python3.6/site-packages/mxnet
   Commit Hash   : 25720d0e3c29232a37e2650f3ba3a2454f9367bb
   --System Info--
   Platform : Darwin-16.7.0-x86_64-i386-64bit
   system   : Darwin
   node : feiquandeMacBook-Pro.local
   release  : 16.7.0
   version  : Darwin Kernel Version 16.7.0: Thu Jun 15 17:36:27 PDT 2017; 
root:xnu-3789.70.16~2/RELEASE_X86_64
   --Hardware Info--
   machine  : x86_64
   processor: i386
   b'machdep.cpu.extfeatures: SYSCALL XD 1GBPAGE EM64T LAHF LZCNT PREFETCHW 
RDTSCP TSCI'
   b'machdep.cpu.leaf7_features: SMEP ERMS RDWRFSGS TSC_THREAD_OFFSET BMI1 HLE 
AVX2 BMI2 INVPCID RTM SMAP RDSEED ADX IPT SGX FPU_CSDS MPX CLFSOPT'
   b'machdep.cpu.features: FPU VME DE PSE TSC MSR PAE MCE CX8 APIC SEP MTRR PGE 
MCA CMOV PAT PSE36 CLFSH DS ACPI MMX FXSR SSE SSE2 SS HTT TM PBE SSE3 PCLMULQDQ 
DTES64 MON DSCPL VMX SMX EST TM2 SSSE3 FMA CX16 TPR PDCM SSE4.1 SSE4.2 x2APIC 
MOVBE POPCNT AES PCID XSAVE OSXSAVE SEGLIM64 TSCTMR AVX1.0 RDRAND F16C'
   b'machdep.cpu.brand_string: Intel(R) Core(TM) i5-7360U CPU @ 2.30GHz'
   ```
   
   Package used (Python/R/Scala/Julia):
   I'm using Python
   
   ## Error Message:
   Traceback (most recent call last):
 File "/Users/feiquan/Code/work/wai-models/tachikoma/audio/tdcnn_mxnet.py", 
line 126, in 
   check_model.load_params("checkpoints/res-.params", ctx=mx.cpu())
 File 
"/Users/feiquan/anaconda3/envs/tf1.3/lib/python3.5/site-packages/mxnet/gluon/block.py",
 line 317, in load_params
   self.prefix)
 File 
"/Users/feiquan/anaconda3/envs/tf1.3/lib/python3.5/site-packages/mxnet/gluon/parameter.py",
 line 673, in load
   "Parameter %s is missing in file %s"%(name[lprefix:], filename)
   AssertionError: Parameter batchnorm0_gamma is missing in file 
checkpoints/res-.params
   
   ## Minimum reproducible example
   
   ```python
   net = get_mode() # create model by HybridBlock or gluon
   # some train step
   net.export(filename) 
   
   new_net = get_model()
   new_net.load_params("path to params", ctx=mx.cpu()) // this will raise error 
AssertionError: Parameter XXX is missing in file XXX
   ```
   
   ## What have you tried to solve it?
   
   I try to solve it by change HybridBlock's export function in 
`mxnet/gluon/block.py` 
   
   ```python
   for name, param in self.collect_params().items():
   if name in arg_names:
   name = name[name.startswith(self.prefix) and 
len(self.prefix):]
   arg_dict['arg:%s'%name] = param._reduce()
   else:
   assert name in aux_names
   name = name[name.startswith(self.prefix) and 
len(self.prefix):]
   arg_dict['aux:%s'%name] = param._reduce()
   ```


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[GitHub] chinakook commented on issue #10600: Gluon Interpolation Layer

[GitBox]

chinakook commented on issue #10600: Gluon Interpolation Layer
URL: 
https://github.com/apache/incubator-mxnet/issues/10600#issuecomment-382346176
 
 
   ```
   def hybrid_forward(self, F, x):
   return F.contrib.BilinearResize2D(x, self.height, self.width)
   ```
   or 
   ```
   def hybrid_forward(self, F, x):
   return F.BilinearResize2D(x, self.height, self.width)
   ```


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[GitHub] PKurnikov commented on issue #10600: Gluon Interpolation Layer

[GitBox]

PKurnikov commented on issue #10600: Gluon Interpolation Layer
URL: 
https://github.com/apache/incubator-mxnet/issues/10600#issuecomment-382344098
 
 
   Unfortunately, I can't to use this approach 
   
   > nn.Block
   
   , because I use BatchNorm, HybridSequential classes which contains 
HybridBlock realisation.
   
   > Children of HybridBlock must also be HybridBlock
   All children layers of HybridBlock must also be HybridBlock.
   


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[GitHub] chinakook commented on issue #10600: Gluon Interpolation Layer

[GitBox]

chinakook commented on issue #10600: Gluon Interpolation Layer
URL: 
https://github.com/apache/incubator-mxnet/issues/10600#issuecomment-382339302
 
 
   del hybrid
   ```
   class BilinearInterp(nn.Block):
   def __init__(self, target_size, **kwargs):
   super(BilinearInterp, self).__init__(**kwargs)
   self.height = target_size[0]
   self.width = target_size[1]
   def forward(self, x):
   return mx.nd.contrib.BilinearResize2D(x, self.height, self.width)
   ```


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[GitHub] PKurnikov opened a new issue #10600: Gluon Interpolation Layer

[GitBox]

PKurnikov opened a new issue #10600: Gluon Interpolation Layer
URL: https://github.com/apache/incubator-mxnet/issues/10600
 
 
   I tried to implement the layer on gluon like this:
   ```
   class BilinearInterp(nn.HybridBlock):
   def __init__(self, target_size, **kwargs):
   super(BilinearInterp, self).__init__(**kwargs)
   self.height = target_size[0]
   self.width = target_size[1]
   def forward(self, x):
   return mx.nd.contrib.BilinearResize2D(x, self.height, self.width)
   ```
   
   But I've got error msg:
   
   > Argument data must have NDArray type, but got (Symbol 
icnet0_batchnorm0_fwd)
   
   Is it possible to implement gluon interpolation layer?
   I tried a different approach (mx.nd.GridGenerator + mx.nd.BilinearSampler), 
also unsuccessfully.
   


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