[GitHub] MonsterPeng opened a new issue #8771: Build source

[GitBox]

MonsterPeng opened a new issue #8771: Build source
URL: https://github.com/apache/incubator-mxnet/issues/8771
 
 
   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
   (Brief description of the problem in no more than 2 sentences.)
   
   ## Environment info (Required)
   
   ```
   What to do:
   1. Download the diagnosis script from 
https://raw.githubusercontent.com/apache/incubator-mxnet/master/tools/diagnose.py
   2. Run the script using `python diagnose.py` and paste its output here.
   
   ```
   
   Package used (Python/R/Scala/Julia):
   (I'm using ...)
   
   For Scala user, please provide:
   1. Java version: (`java -version`)
   2. Maven version: (`mvn -version`)
   3. Scala runtime if applicable: (`scala -version`)
   
   For R user, please provide R `sessionInfo()`:
   
   ## Build info (Required if built from source)
   
   Compiler (gcc/clang/mingw/visual studio):
   
   MXNet commit hash:
   (Paste the output of `git rev-parse HEAD` here.)
   
   Build config:
   (Paste the content of config.mk, or the build command.)
   
   ## Error Message:
   (Paste the complete error message, including stack trace.)
   
   ## Minimum reproducible example
   (If you are using your own code, please provide a short script that 
reproduces the error. Otherwise, please provide link to the existing example.)
   
   ## Steps to reproduce
   (Paste the commands you ran that produced the error.)
   
   1.
   2.
   
   ## What have you tried to solve it?
   
   1.
   2.
   


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[GitHub] MonsterPeng opened a new issue #8772: Build source code problem cannot convert from 'mshadow::Stream *' to 'mshadow::Stream *'

[GitBox]

MonsterPeng opened a new issue #8772: Build source code problem  cannot convert 
from 'mshadow::Stream *' to 'mshadow::Stream *'   
URL: https://github.com/apache/incubator-mxnet/issues/8772
 
 
   I try to build source code on windows server2012 R2. I have got this error.
   error C2440: 'default argument' : cannot convert from 
'mshadow::Stream *' to 'mshadow::Stream *'   
   
   what does it mean?
   


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[GitHub] YujiOshima commented on a change in pull request #8722: Profiler: set cpu/gpu num during execution

[GitBox]

YujiOshima commented on a change in pull request #8722: Profiler: set cpu/gpu 
num during execution
URL: https://github.com/apache/incubator-mxnet/pull/8722#discussion_r152521064
 
 

 ##
 File path: src/engine/profiler.cc
 ##
 @@ -45,12 +50,11 @@ Profiler::Profiler()
   : state_(kNotRunning), enable_output_(false), filename_("profile.json") {
   this->init_time_ = NowInUsec();
 
-  // TODO(ziheng) get device number during execution
-  int kMaxNumCpus = 64;
-  this->cpu_num_ = kMaxNumCpus;
+  this->cpu_num_ = std::thread::hardware_concurrency();
 #if MXNET_USE_CUDA
-  int kMaxNumGpus = 32;
-  this->gpu_num_ = kMaxNumGpus;
+  int gpu_num = 0;
+  CUDA_CALL(cudaGetDeviceCount(&gpu_num));
 
 Review comment:
   @piiswrong Thank you for your comment.
   I understood the purpose of using the constant number.
   How about dynamically setting only the number of CPUs?
   More than 64 CPUs are not ordinary but not impossible.


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[GitHub] DevinCheung opened a new issue #8773: undefined reference to `gotoblas' Makefile:406: recipe for target 'bin/im2rec' failed

[GitBox]

DevinCheung opened a new issue #8773: undefined reference to `gotoblas' 
Makefile:406: recipe for target 'bin/im2rec' failed
URL: https://github.com/apache/incubator-mxnet/issues/8773
 
 
   cd /dev/shm/multitask/mx-maskrcnn/incubator-mxnet/dmlc-core; make libdmlc.a 
USE_SSE=1 config=/dev/shm/multitask/mx-maskrcnn/incubator-mxnet/make/config.mk; 
cd /dev/shm/multitask/mx-maskrcnn/incubator-mxnet
   make[1]: Entering directory 
'/dev/shm/multitask/mx-maskrcnn/incubator-mxnet/dmlc-core'
   make[1]: 'libdmlc.a' is up to date.
   make[1]: Leaving directory 
'/dev/shm/multitask/mx-maskrcnn/incubator-mxnet/dmlc-core'
   g++ -DMSHADOW_FORCE_STREAM -Wall -Wsign-compare -O3 -DNDEBUG=1 
-I/dev/shm/multitask/mx-maskrcnn/incubator-mxnet/mshadow/ 
-I/dev/shm/multitask/mx-maskrcnn/incubator-mxnet/dmlc-core/include -fPIC 
-I/dev/shm/multitask/mx-maskrcnn/incubator-mxnet/nnvm/include 
-I/dev/shm/multitask/mx-maskrcnn/incubator-mxnet/dlpack/include -Iinclude 
-funroll-loops -Wno-unused-variable -Wno-unused-parameter -Wno-unknown-pragmas 
-Wno-unused-local-typedefs -msse3 -I/usr/local/cuda/include 
-DMSHADOW_USE_CBLAS=1 -DMSHADOW_USE_MKL=0 -DMSHADOW_RABIT_PS=0 
-DMSHADOW_DIST_PS=0 -DMSHADOW_USE_PASCAL=0 -DMXNET_USE_OPENCV=1 
-I/usr/include/opencv -fopenmp -DMXNET_USE_LAPACK -DMSHADOW_USE_CUDNN=1 
-fno-builtin-malloc -fno-builtin-calloc -fno-builtin-realloc -fno-builtin-free  
-I/dev/shm/multitask/mx-maskrcnn/incubator-mxnet/cub 
-DMXNET_USE_LIBJPEG_TURBO=0 -std=c++11  -o bin/im2rec tools/im2rec.cc 
build/src/operator/mkl/mkl_cppwrapper.o build/src/operator/mkl/mkl_memory.o 
build/src/operator/random/sample_multinomial_op.o 
build/src/operator/random/multisample_op.o 
build/src/operator/random/sample_op.o 
build/src/operator/tensor/elemwise_binary_broadcast_op_extended.o 
build/src/operator/tensor/elemwise_binary_op_logic.o 
build/src/operator/tensor/elemwise_binary_op_extended.o 
build/src/operator/tensor/square_sum.o build/src/operator/tensor/dot.o 
build/src/operator/tensor/elemwise_sum.o build/src/operator/tensor/init_op.o 
build/src/operator/tensor/elemwise_binary_broadcast_op_basic.o 
build/src/operator/tensor/cast_storage.o 
build/src/operator/tensor/elemwise_binary_op.o 
build/src/operator/tensor/elemwise_binary_scalar_op_logic.o 
build/src/operator/tensor/elemwise_scatter_op.o 
build/src/operator/tensor/elemwise_unary_op_basic.o 
build/src/operator/tensor/broadcast_reduce_op_value.o 
build/src/operator/tensor/ordering_op.o 
build/src/operator/tensor/elemwise_binary_op_basic.o 
build/src/operator/tensor/elemwise_binary_scalar_op_basic.o 
build/src/operator/tensor/indexing_op.o 
build/src/operator/tensor/elemwise_binary_broadcast_op_logic.o 
build/src/operator/tensor/la_op.o 
build/src/operator/tensor/broadcast_reduce_op_index.o 
build/src/operator/tensor/sparse_retain.o 
build/src/operator/tensor/control_flow_op.o 
build/src/operator/tensor/elemwise_binary_scalar_op_extended.o 
build/src/operator/tensor/matrix_op.o 
build/src/operator/tensor/elemwise_unary_op_trig.o 
build/src/operator/nnpack/nnpack_util.o 
build/src/operator/contrib/multibox_target.o 
build/src/operator/contrib/proposal.o build/src/operator/contrib/count_sketch.o 
build/src/operator/contrib/dequantize.o 
build/src/operator/contrib/deformable_psroi_pooling.o 
build/src/operator/contrib/fft.o build/src/operator/contrib/multibox_prior.o 
build/src/operator/contrib/ctc_loss.o 
build/src/operator/contrib/multi_proposal.o 
build/src/operator/contrib/psroi_pooling.o 
build/src/operator/contrib/quantize.o 
build/src/operator/contrib/deformable_convolution.o 
build/src/operator/contrib/ifft.o 
build/src/operator/contrib/multibox_detection.o 
build/src/operator/custom/native_op.o build/src/operator/custom/ndarray_op.o 
build/src/operator/custom/custom.o build/src/operator/nn/softmax.o 
build/src/io/image_aug_default.o build/src/io/io.o build/src/io/iter_csv.o 
build/src/io/iter_image_det_recordio.o build/src/io/image_io.o 
build/src/io/image_det_aug_default.o build/src/io/iter_image_recordio.o 
build/src/io/iter_mnist.o build/src/io/iter_image_recordio_2.o 
build/src/io/iter_libsvm.o build/src/common/rtc.o build/src/common/utils.o 
build/src/nnvm/legacy_op_util.o build/src/nnvm/legacy_json_util.o 
build/src/imperative/cached_op.o build/src/imperative/imperative.o 
build/src/ndarray/ndarray_function.o build/src/ndarray/ndarray.o 
build/src/operator/instance_norm.o build/src/operator/pooling.o 
build/src/operator/crop.o build/src/operator/spatial_transformer.o 
build/src/operator/swapaxis.o build/src/operator/convolution_v1.o 
build/src/operator/pad.o build/src/operator/batch_norm.o 
build/src/operator/softmax_output.o build/src/operator/cudnn_algoreg.o 
build/src/operator/correlation.o build/src/operator/operator_util.o 
build/src/operator/sequence_reverse.o build/src/operator/bilinear_sampler.o 
build/src/operator/sequence_last.o build/src/operator/svm_output.o 
build/src/operator/operator.o build/src/operator/optimizer_op.o 
build/src/operator/lrn.o build/sr

[GitHub] DevinCheung commented on issue #8773: undefined reference to `gotoblas' Makefile:406: recipe for target 'bin/im2rec' failed

[GitBox]

DevinCheung commented on issue #8773: undefined reference to `gotoblas' 
Makefile:406: recipe for target 'bin/im2rec' failed
URL: 
https://github.com/apache/incubator-mxnet/issues/8773#issuecomment-346328081
 
 
   And I find the following about libblas in /usr/lib/:
   libblas
   libblas.a
   libblas.so
   libblas.so.3
   libblas.so.3gf


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[GitHub] aijanai closed issue #8750: terminate called after throwing an instance of 'std::bad_alloc'

[GitBox]

aijanai closed issue #8750: terminate called after throwing an instance of 
'std::bad_alloc'
URL: https://github.com/apache/incubator-mxnet/issues/8750
 
 
   


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[GitHub] aijanai commented on issue #8750: terminate called after throwing an instance of 'std::bad_alloc'

[GitBox]

aijanai commented on issue #8750: terminate called after throwing an instance 
of 'std::bad_alloc'
URL: 
https://github.com/apache/incubator-mxnet/issues/8750#issuecomment-346330802
 
 
   Thanks for the keen eye.
   It was actually a bug in the code that generated the vocabulary, resulting 
in abnormally sized vocabularies and, thus, too wide network topologies.


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[GitHub] aijanai commented on issue #8750: terminate called after throwing an instance of 'std::bad_alloc'

[GitBox]

aijanai commented on issue #8750: terminate called after throwing an instance 
of 'std::bad_alloc'
URL: 
https://github.com/apache/incubator-mxnet/issues/8750#issuecomment-346330895
 
 
   Anyway, some more useful debugging messages from the framework would help


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[GitHub] edmBernard closed issue #8747: Memory GPU leak with Gluon

[GitBox]

edmBernard closed issue #8747: Memory GPU leak with Gluon
URL: https://github.com/apache/incubator-mxnet/issues/8747
 
 
   


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[GitHub] szha commented on issue #7573: how to use autograd in c++

[GitBox]

szha commented on issue #7573: how to use autograd in c++
URL: 
https://github.com/apache/incubator-mxnet/issues/7573#issuecomment-346335902
 
 
   This issue is closed due to lack of activity in the last 90 days. Feel free 
to ping me to reopen if this is still an active issue. Thanks!
   Also, do please check out our [forum](https://discuss.mxnet.io/) (and 
[Chinese version](https://discuss.gluon.ai/)) for general "how-to" questions.


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[GitHub] szha closed issue #7573: how to use autograd in c++

[GitBox]

szha closed issue #7573: how to use autograd in c++
URL: https://github.com/apache/incubator-mxnet/issues/7573
 
 
   


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[GitHub] huangyingsong commented on issue #8772: Build source code problem cannot convert from 'mshadow::Stream *' to 'mshadow::Stream *'

[GitBox]

huangyingsong commented on issue #8772: Build source code problem  cannot 
convert from 'mshadow::Stream *' to 'mshadow::Stream *' 
URL: 
https://github.com/apache/incubator-mxnet/issues/8772#issuecomment-346344395
 
 
   Do u install Microsoft Visual C++ Compiler Nov 2013 CTP? 
https://mxnet.incubator.apache.org/get_started/windows_setup.html


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[GitHub] Soonhwan-Kwon closed pull request #8674: ADD CapsNet example

[GitBox]

Soonhwan-Kwon closed pull request #8674: ADD CapsNet example
URL: https://github.com/apache/incubator-mxnet/pull/8674
 
 
   

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/example/capsnet/README.md b/example/capsnet/README.md
new file mode 100644
index 00..9e52da0583
--- /dev/null
+++ b/example/capsnet/README.md
@@ -0,0 +1,45 @@
+**CapsNet-MXNet**
+=
+
+This example is MXNet implementation of 
[CapsNet](https://arxiv.org/abs/1710.09829):  
+Sara Sabour, Nicholas Frosst, Geoffrey E Hinton. Dynamic Routing Between 
Capsules. NIPS 2017
+- The current best test error is 0.41%  
+- The average test error on paper is 0.25%  
+
+Due to the permission issue, this example is maintained in this 
[repository](https://github.com/samsungsds-rnd/capsnet.mxnet) separately.
+* * *
+## **Usage**
+Install scipy with pip  
+```
+pip install scipy
+```
+
+On Single gpu
+```
+python capsulenet.py --devices gpu0
+```
+On Multi gpus
+```
+python capsulenet.py --devices gpu0,gpu1
+```
+
+* * *
+## **Prerequisities**
+
+MXNet version above (0.11.0)
+scipy version above (0.19.0)
+
+***
+## **Results**  
+Train time takes about 36 seconds for each epoch (batch_size=100, lr=0.001, 2 
gtx 1080 gpus)  
+and we limited number of epoch to 100 as default to limit our training time(1 
hour).
+
+CapsNet classification test error on MNIST  
+
+```
+python capsulenet.py --devices gpu0,gpu1 --lr 0.0005 --batch_size 100 
--num_routing 3 --decay 0.9
+```
+
+| Epoch | train err | test err | train loss | test loss |
+| :---: | :---: | :---: | :---: | :---: |
+| 62 | 0.25 | 0.41 | 0.000247 | 0.000267 |
diff --git a/example/capsnet/capsulelayers.py b/example/capsnet/capsulelayers.py
new file mode 100644
index 00..5ac4fad491
--- /dev/null
+++ b/example/capsnet/capsulelayers.py
@@ -0,0 +1,106 @@
+# 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.
+
+import mxnet as mx
+
+
+def squash(data, squash_axis, name=''):
+epsilon = 1e-08
+s_squared_norm = mx.sym.sum(data=mx.sym.square(data, name='square_'+name),
+axis=squash_axis, keepdims=True, 
name='s_squared_norm_'+name)
+scale = s_squared_norm / (1 + s_squared_norm) / 
mx.sym.sqrt(data=(s_squared_norm+epsilon),
+
name='s_squared_norm_sqrt_'+name)
+squashed_net = mx.sym.broadcast_mul(scale, data, name='squashed_net_'+name)
+return squashed_net
+
+
+def primary_caps(data, dim_vector, n_channels, kernel, strides, name=''):
+out = mx.sym.Convolution(data=data,
+ num_filter=dim_vector * n_channels,
+ kernel=kernel,
+ stride=strides,
+ name=name
+ )
+out = mx.sym.Reshape(data=out, shape=(0, -1, dim_vector))
+out = squash(out, squash_axis=2)
+return out
+
+
+class CapsuleLayer:
+"""
+The capsule layer with dynamic routing.
+[batch_size, input_num_capsule, input_dim_vector] => [batch_size, 
num_capsule, dim_vector]
+"""
+
+def __init__(self, num_capsule, dim_vector, batch_size, 
kernel_initializer, bias_initializer, num_routing=3):
+self.num_capsule = num_capsule
+self.dim_vector = dim_vector
+self.batch_size = batch_size
+self.num_routing = num_routing
+self.kernel_initializer = kernel_initializer
+self.bias_initializer = bias_initializer
+
+def __call__(self, data):
+_, out_shapes, __ = data.infer_shape(data=(self.batch_size, 1, 28, 28))
+_, input_num_capsule, input_dim_vector = out_shapes[0]
+
+# build w and bias
+# W : (input_num_capsule, num_capsule, input_dim_vector, dim_vector)
+# bias : (batch_size, input_num_capsule, num_capsule ,1, 1)
+w = mx.sym.Variable('Weight',
+shape=(1, input_num_capsule, self.num_capsule, 
input_dim_vector, self.dim_vector),
+ 

[GitHub] analog-cbarber commented on issue #8756: As there are many JAVA programer, and JDK9 has HAD JAVA REPL JSHELL like PYTHON OR SCALA shell, it will be easy to use JAVA training model. , When wi

[GitBox]

analog-cbarber commented on issue #8756: As there are many JAVA programer, and 
JDK9 has HAD JAVA REPL JSHELL like  PYTHON OR SCALA shell, it will be easy to 
use JAVA training model. , When will MXNET support JAVA programing language? 
URL: 
https://github.com/apache/incubator-mxnet/issues/8756#issuecomment-346360904
 
 
   While I agree that a Java front-end makes a lot of sense, I really would not 
expect to see one until someone contributes one and commits to maintaining it.
   


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[GitHub] analog-cbarber commented on issue #8668: Precision error setting NDArray from np.float32 scalar

[GitBox]

analog-cbarber commented on issue #8668: Precision error setting NDArray from 
np.float32 scalar
URL: 
https://github.com/apache/incubator-mxnet/issues/8668#issuecomment-346361655
 
 
   Obviously passing floating point data as (decimal?) strings is horribly 
inefficient and prone to loss of precision. Is this something that is expected 
to change at some point?


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[GitHub] cjolivier01 commented on issue #8668: Precision error setting NDArray from np.float32 scalar

[GitBox]

cjolivier01 commented on issue #8668: Precision error setting NDArray from 
np.float32 scalar
URL: 
https://github.com/apache/incubator-mxnet/issues/8668#issuecomment-346370555
 
 
   Yes
   
   On Wed, Nov 22, 2017 at 6:14 AM Christopher Barber 
   wrote:
   
   > Obviously passing floating point data as (decimal?) strings is horribly
   > inefficient and prone to loss of precision. Is this something that is
   > expected to change at some point?
   >
   > ?
   > 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] ZiyueHuang opened a new pull request #8774: remove meaningless type qualifier

[GitBox]

ZiyueHuang opened a new pull request #8774: remove meaningless type qualifier
URL: https://github.com/apache/incubator-mxnet/pull/8774
 
 
   ## Description ##
   Otherwise there are so many warnings `warning: type qualifier on return type 
is meaningless`.
   
   ```
   g++ --version
   g++ (GCC) 4.8.5 20150623 (Red Hat 4.8.5-11)
   Copyright (C) 2015 Free Software Foundation, Inc.
   This is free software; see the source for copying conditions.  There is NO
   warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
   ```
   cc @eric-haibin-lin @cjolivier01 
   
   ## Checklist ##
   ### Essentials ###
   - [ ] Passed code style checking (`make lint`)
   - [ ] Changes are complete (i.e. I finished coding on this PR)
   - [ ] All changes have test coverage
   - [ ] For user-facing API changes, API doc string has been updated. For new 
C++ functions in header files, their functionalities and arguments are 
well-documented. 
   - [ ] To 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] tdomhan commented on issue #8334: Bugfix: Python 3 compatiblity during optimizer serialization.

[GitBox]

tdomhan commented on issue #8334: Bugfix: Python 3 compatiblity during 
optimizer serialization.
URL: https://github.com/apache/incubator-mxnet/pull/8334#issuecomment-346376475
 
 
   alright, finally all checks passed. Can we merge this?


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[GitHub] starimpact opened a new issue #8775: Is the newest cpp package compatible with v0.8.0?

[GitBox]

starimpact opened a new issue #8775: Is the newest cpp package compatible with 
v0.8.0?
URL: https://github.com/apache/incubator-mxnet/issues/8775
 
 
   


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[GitHub] madjam opened a new pull request #8776: Fix security doc link

[GitBox]

madjam opened a new pull request #8776: Fix security doc link
URL: https://github.com/apache/incubator-mxnet/pull/8776
 
 
   


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[GitHub] cjolivier01 commented on issue #8774: remove meaningless type qualifier

[GitBox]

cjolivier01 commented on issue #8774: remove meaningless type qualifier
URL: https://github.com/apache/incubator-mxnet/pull/8774#issuecomment-346391831
 
 
   That?s actually there because my gcc complains without it. The alternative 
was the const_cast in the function above it. Can you return via the const_cast 
reference as well? It?s changed to that in one of my other PRs as well.


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[GitHub] cjolivier01 commented on issue #8774: remove meaningless type qualifier

[GitBox]

cjolivier01 commented on issue #8774: remove meaningless type qualifier
URL: https://github.com/apache/incubator-mxnet/pull/8774#issuecomment-346395600
 
 
   Note it is changed here, but feel free to do it in this PR, which will 
likely go in sooner: 
https://github.com/apache/incubator-mxnet/pull/8719/files#diff-bf9721b2b5dd01c635c6efe941fa9da9R188


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[GitHub] ZiyueHuang commented on issue #8774: remove meaningless type qualifier

[GitBox]

ZiyueHuang commented on issue #8774: remove meaningless type qualifier
URL: https://github.com/apache/incubator-mxnet/pull/8774#issuecomment-346399433
 
 
   @cjolivier01 Thanks for your reference! Update :)


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[GitHub] tanhm07 opened a new issue #8777: Error: package or namespace load failed for ?mxnet?:

[GitBox]

tanhm07 opened a new issue #8777: Error: package or namespace load failed for 
?mxnet?:
URL: https://github.com/apache/incubator-mxnet/issues/8777
 
 
   ## Description
   I have downloaded the package for R according to the instructions here: 
http://mxnet.incubator.apache.org/get_started/install.html
   for GPU. I'm unable to load the package. 
   
   This is the error it gives.
   
   > library('mxnet')
   Error: package or namespace load failed for ?mxnet?:
.onLoad failed in loadNamespace() for 'mxnet', details:
 call: inDL(x, as.logical(local), as.logical(now), ...)
 error: unable to load shared object 
'D:/R/R-3.4.2/library/mxnet/libs/x64/libmxnet.dll':
 LoadLibrary failure:  The specified module could not be found.
   
   
   Package used (Python/R/Scala/Julia):
   I'm using R.
   
   For R user, please provide R `sessionInfo()`:
   
   R version 3.4.2 (2017-09-28)
   Platform: x86_64-w64-mingw32/x64 (64-bit)
   Running under: Windows >= 8 x64 (build 9200)
   
   Matrix products: default
   
   locale:
   [1] LC_COLLATE=English_United States.1252  LC_CTYPE=English_United 
States.1252LC_MONETARY=English_United States.1252 LC_NUMERIC=C  

   [5] LC_TIME=English_United States.1252
   
   attached base packages:
   [1] stats graphics  grDevices utils datasets  methods   base 
   
   loaded via a namespace (and not attached):
[1] Rcpp_0.12.13   compiler_3.4.2 RColorBrewer_1.1-2 
influenceR_0.1.0   plyr_1.8.4 bindr_0.1  viridis_0.4.0  
tools_3.4.2digest_0.6.12 
   [10] jsonlite_1.5   viridisLite_0.2.0  tibble_1.3.4   gtable_0.2.0   
rgexf_0.15.3   pkgconfig_2.0.1rlang_0.1.4igraph_1.1.2   
rstudioapi_0.7
   [19] bindrcpp_0.2   gridExtra_2.3  downloader_0.4 
DiagrammeR_0.9.2   dplyr_0.7.4stringr_1.2.0  htmlwidgets_0.9
hms_0.3grid_3.4.2
   [28] glue_1.2.0 R6_2.2.2   Rook_1.1-1 XML_3.98-1.9   
readr_1.1.1purrr_0.2.4tidyr_0.7.2ggplot2_2.2.1  
magrittr_1.5  
   [37] scales_0.5.0   htmltools_0.3.6assertthat_0.2.0   
colorspace_1.3-2   brew_1.0-6 stringi_1.1.6  visNetwork_2.0.1   
lazyeval_0.2.1 munsell_0.4.3 
   > 
   
   ## Build info (Required if built from source)
   
   Compiler (gcc/clang/mingw/visual studio):
   
   MXNet commit hash:
   (Paste the output of `git rev-parse HEAD` here.)
   
   Build config:
   (Paste the content of config.mk, or the build command.)
   
   ## Error Message:
   (Paste the complete error message, including stack trace.)
   
   ## Minimum reproducible example
   (If you are using your own code, please provide a short script that 
reproduces the error. Otherwise, please provide link to the existing example.)
   
   ## Steps to reproduce
   
   1. install CUDA 9 and CUDNN
   2. install the mxnet R package
   3. run command library('mxnet')
   
   ## What have you tried to solve it?
   
   1. restarting.
   2. checking version of CUDA.
   3. check that CUDA is in my environment paths


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[GitHub] cjolivier01 commented on a change in pull request #8737: Use RAII and fix Coverity resource leaks #10371 and others

[GitBox]

cjolivier01 commented on a change in pull request #8737: Use RAII and fix 
Coverity resource leaks #10371 and others
URL: https://github.com/apache/incubator-mxnet/pull/8737#discussion_r152614153
 
 

 ##
 File path: cpp-package/example/alexnet.cpp
 ##
 @@ -215,7 +215,7 @@ int main(int argc, char const *argv[]) {
   args_map["label"] = NDArray(Shape(batch_size), ctx);
 
   /*with data and label, executor can be generated automatically*/
-  auto *exec = Net.SimpleBind(ctx, args_map);
+  auto exec = Net.SimpleBind(ctx, args_map);
 
 Review comment:
   Why not use unique_ptr rather than a stack variable?
   


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[GitHub] cjolivier01 commented on a change in pull request #8737: Use RAII and fix Coverity resource leaks #10371 and others

[GitBox]

cjolivier01 commented on a change in pull request #8737: Use RAII and fix 
Coverity resource leaks #10371 and others
URL: https://github.com/apache/incubator-mxnet/pull/8737#discussion_r152614153
 
 

 ##
 File path: cpp-package/example/alexnet.cpp
 ##
 @@ -215,7 +215,7 @@ int main(int argc, char const *argv[]) {
   args_map["label"] = NDArray(Shape(batch_size), ctx);
 
   /*with data and label, executor can be generated automatically*/
-  auto *exec = Net.SimpleBind(ctx, args_map);
+  auto exec = Net.SimpleBind(ctx, args_map);
 
 Review comment:
   Why not use unique_ptr rather than a stack variable?  That 
wouldn't change the interface.
   


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[GitHub] cjolivier01 commented on a change in pull request #8737: Use RAII and fix Coverity resource leaks #10371 and others

[GitBox]

cjolivier01 commented on a change in pull request #8737: Use RAII and fix 
Coverity resource leaks #10371 and others
URL: https://github.com/apache/incubator-mxnet/pull/8737#discussion_r152614866
 
 

 ##
 File path: cpp-package/example/alexnet.cpp
 ##
 @@ -215,7 +215,7 @@ int main(int argc, char const *argv[]) {
   args_map["label"] = NDArray(Shape(batch_size), ctx);
 
   /*with data and label, executor can be generated automatically*/
-  auto *exec = Net.SimpleBind(ctx, args_map);
+  auto exec = Net.SimpleBind(ctx, args_map);
 
 Review comment:
   Ok, I see it is returning unique_ptr. ANy chance you can not use auto in 
this case because it's not obvious what the type is from the code line.


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[incubator-mxnet] branch master updated: Explicitly convert float value (#8758)

[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 5518986  Explicitly convert float value (#8758)
5518986 is described below

commit 55189860dbeb9486f745403760e10619f40de488
Author: reminisce 
AuthorDate: Wed Nov 22 08:25:55 2017 -0800

Explicitly convert float value (#8758)

* Explicitly convert float value

* Add unit test function
---
 python/mxnet/ndarray/ndarray.py   |  2 +-
 tests/python/unittest/test_ndarray.py | 10 ++
 2 files changed, 11 insertions(+), 1 deletion(-)

diff --git a/python/mxnet/ndarray/ndarray.py b/python/mxnet/ndarray/ndarray.py
index 91d0e03..a45a6a8 100644
--- a/python/mxnet/ndarray/ndarray.py
+++ b/python/mxnet/ndarray/ndarray.py
@@ -691,7 +691,7 @@ fixed-size items.
 value.copyto(self)
 elif isinstance(value, numeric_types):
 _internal._full(shape=shape, ctx=self.context,
-dtype=self.dtype, value=value, out=self)
+dtype=self.dtype, value=float(value), 
out=self)
 elif isinstance(value, (np.ndarray, np.generic)):
 if isinstance(value, np.generic) or value.shape != shape:
 value = np.broadcast_to(value, shape)
diff --git a/tests/python/unittest/test_ndarray.py 
b/tests/python/unittest/test_ndarray.py
index 8e1f68f..5512b07 100644
--- a/tests/python/unittest/test_ndarray.py
+++ b/tests/python/unittest/test_ndarray.py
@@ -926,6 +926,16 @@ def test_ndarray_indexing():
 test_getitem_autograd(np_array, index[0])
 
 
+def test_assign_float_value_to_ndarray():
+"""Test case from https://github.com/apache/incubator-mxnet/issues/8668""";
+a = np.array([47.844944], dtype=np.float32)
+b = mx.nd.zeros(1, dtype=np.float32)
+b[0] = a
+assert same(a, b.asnumpy())
+b[0] = a[0]
+assert same(a, b.asnumpy())
+
+
 if __name__ == '__main__':
 import nose
 nose.runmodule()

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[GitHub] cjolivier01 closed pull request #8758: Explicitly convert float value

[GitBox]

cjolivier01 closed pull request #8758: Explicitly convert float value
URL: https://github.com/apache/incubator-mxnet/pull/8758
 
 
   

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/python/mxnet/ndarray/ndarray.py b/python/mxnet/ndarray/ndarray.py
index 91d0e03e3d..a45a6a8247 100644
--- a/python/mxnet/ndarray/ndarray.py
+++ b/python/mxnet/ndarray/ndarray.py
@@ -691,7 +691,7 @@ def _set_nd_basic_indexing(self, key, value):
 value.copyto(self)
 elif isinstance(value, numeric_types):
 _internal._full(shape=shape, ctx=self.context,
-dtype=self.dtype, value=value, out=self)
+dtype=self.dtype, value=float(value), 
out=self)
 elif isinstance(value, (np.ndarray, np.generic)):
 if isinstance(value, np.generic) or value.shape != shape:
 value = np.broadcast_to(value, shape)
diff --git a/tests/python/unittest/test_ndarray.py 
b/tests/python/unittest/test_ndarray.py
index 8e1f68fd62..5512b07c77 100644
--- a/tests/python/unittest/test_ndarray.py
+++ b/tests/python/unittest/test_ndarray.py
@@ -926,6 +926,16 @@ def test_getitem_autograd(np_array, index):
 test_getitem_autograd(np_array, index[0])
 
 
+def test_assign_float_value_to_ndarray():
+"""Test case from https://github.com/apache/incubator-mxnet/issues/8668""";
+a = np.array([47.844944], dtype=np.float32)
+b = mx.nd.zeros(1, dtype=np.float32)
+b[0] = a
+assert same(a, b.asnumpy())
+b[0] = a[0]
+assert same(a, b.asnumpy())
+
+
 if __name__ == '__main__':
 import nose
 nose.runmodule()


 


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[GitHub] anirudh2290 commented on a change in pull request #8767: Factorization machine example & sparse example folder re-org

[GitBox]

anirudh2290 commented on a change in pull request #8767: Factorization machine 
example & sparse example folder re-org
URL: https://github.com/apache/incubator-mxnet/pull/8767#discussion_r152615969
 
 

 ##
 File path: example/sparse/factorization_machine/train.py
 ##
 @@ -0,0 +1,105 @@
+# 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.
+
+import mxnet as mx
+from metric import *
+from mxnet.test_utils import *
+from data import DummyIter
+from factorization_machine_model import *
+import argparse, os
+
+parser = argparse.ArgumentParser(description="Run factorization machine with 
criteo dataset",
+ 
formatter_class=argparse.ArgumentDefaultsHelpFormatter)
+parser.add_argument('--data', type=str, default="./data/",
+help='training LibSVM files to use.')
+parser.add_argument('--num-epoch', type=int, default=1,
+help='number of epochs to train')
+parser.add_argument('--batch-size', type=int, default=1,
+help='number of examples per batch')
+parser.add_argument('--input-size', type=int, default=200,
+help='number of features in the input')
+parser.add_argument('--factor-size', type=int, default=16,
+help='number of latent variables')
+parser.add_argument('--log-interval', type=int, default=100,
+help='number of batches between logging messages')
+parser.add_argument('--kvstore', type=str, default='local',
+help='what kvstore to use', choices=["dist_async", 
"local"])
+
+if __name__ == '__main__':
+import logging
+head = '%(asctime)-15s %(message)s'
+logging.basicConfig(level=logging.INFO, format=head)
+
+# arg parser
+args = parser.parse_args()
+logging.info(args)
+num_epoch = args.num_epoch
+batch_size = args.batch_size
+kvstore = args.kvstore
+factor_size = args.factor_size
+num_features = args.input_size
+log_interval = args.log_interval
+
+# create kvstore
+kv = mx.kvstore.create(kvstore)
+# data iterator
+train_data = mx.io.LibSVMIter(data_libsvm=args.data, 
data_shape=(num_features,),
+  batch_size=batch_size)
+# model
+model = factorization_machine_model(factor_size, num_features)
+
+# module
+mod = mx.mod.Module(symbol=model)
+mod.bind(data_shapes=train_data.provide_data, 
label_shapes=train_data.provide_label)
+mod.init_params()
+optimizer_params=(('learning_rate', 0.001), ('wd', 0.0001), ('beta1', 0.9),
 
 Review comment:
   Should we add these hyperparameters to user passed arguments with defaults ?


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[GitHub] anirudh2290 commented on a change in pull request #8767: Factorization machine example & sparse example folder re-org

[GitBox]

anirudh2290 commented on a change in pull request #8767: Factorization machine 
example & sparse example folder re-org
URL: https://github.com/apache/incubator-mxnet/pull/8767#discussion_r152615413
 
 

 ##
 File path: example/sparse/factorization_machine/data.py
 ##
 @@ -0,0 +1,62 @@
+# 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.
+
+import os, gzip, argparse, sys
+import mxnet as mx
+import logging
+head = '%(asctime)-15s %(message)s'
+logging.basicConfig(level=logging.INFO, format=head)
+
+class DummyIter(mx.io.DataIter):
+"A dummy iterator that always return the same batch, used for speed 
testing"
+def __init__(self, real_iter):
+super(DummyIter, self).__init__()
+self.real_iter = real_iter
+self.provide_data = real_iter.provide_data
+self.provide_label = real_iter.provide_label
+self.batch_size = real_iter.batch_size
+
+for batch in real_iter:
+self.the_batch = batch
+break
+
+def __iter__(self):
+return self
+
+def next(self):
+return self.the_batch
+
+
+def get_criteo_data(data_dir):
+if not os.path.isdir(data_dir):
+os.mkdir(data_dir)
+try:
+logging.info("Downloading dataset criteo to " + data_dir + " now ...")
+os.system("aws s3 cp --recursive --no-sign-request 
s3://sparse-dataset/criteo " + data_dir)
 
 Review comment:
   How big is this directory. Maybe add a warning about the size here?


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[GitHub] cjolivier01 commented on a change in pull request #8680: Fix cmake library path when installing python package

[GitBox]

cjolivier01 commented on a change in pull request #8680: Fix cmake library path 
when installing python package
URL: https://github.com/apache/incubator-mxnet/pull/8680#discussion_r152616626
 
 

 ##
 File path: python/mxnet/libinfo.py
 ##
 @@ -31,7 +31,7 @@ def find_lib_path():
 """
 curr_path = os.path.dirname(os.path.abspath(os.path.expanduser(__file__)))
 api_path = os.path.join(curr_path, '../../lib/')
-cmake_build_path = os.path.join(curr_path, '../../build/Release/')
+cmake_build_path = os.path.join(curr_path, '../../build/')
 
 Review comment:
   CMake often tends to make a separate output directory for each build 
configuration "Debug", "Release", "RelWithDebInfo", etc. (when tiolkd to do so, 
for example by CLion, except it calls it cmake-build-debug, 
cmake-build-release, etc.). While I am not crazy about trying to guess the 
cmake output directory, I think explicitly pointing to "Release" when what you 
think you're running is "Debug" is dangerous.


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[GitHub] cjolivier01 commented on a change in pull request #8680: Fix cmake library path when installing python package

[GitBox]

cjolivier01 commented on a change in pull request #8680: Fix cmake library path 
when installing python package
URL: https://github.com/apache/incubator-mxnet/pull/8680#discussion_r152616626
 
 

 ##
 File path: python/mxnet/libinfo.py
 ##
 @@ -31,7 +31,7 @@ def find_lib_path():
 """
 curr_path = os.path.dirname(os.path.abspath(os.path.expanduser(__file__)))
 api_path = os.path.join(curr_path, '../../lib/')
-cmake_build_path = os.path.join(curr_path, '../../build/Release/')
+cmake_build_path = os.path.join(curr_path, '../../build/')
 
 Review comment:
   CMake often tends to make a separate output directory for each build 
configuration "Debug", "Release", "RelWithDebInfo", etc. (when told to do so, 
for example by CLion, except it calls it cmake-build-debug, 
cmake-build-release, etc.). While I am not crazy about trying to guess the 
cmake output directory, I think explicitly pointing to "Release" when what you 
think you're running is "Debug" is dangerous.


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[GitHub] alexmosc commented on issue #7524: Is there a tutorial of using mxnet R LSTM for time series forecasting?

[GitBox]

alexmosc commented on issue #7524: Is there a tutorial of using mxnet R LSTM 
for time series forecasting? 
URL: 
https://github.com/apache/incubator-mxnet/issues/7524#issuecomment-346409398
 
 
   It would still be **very** helpful to have a tutorial on a simple 
time-series modelling with MXNET in R.


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[incubator-mxnet] branch v1.0.0 updated: Explicitly convert float value (#8758)

[cjolivier01]

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

cjolivier01 pushed a commit to branch v1.0.0
in repository https://gitbox.apache.org/repos/asf/incubator-mxnet.git


The following commit(s) were added to refs/heads/v1.0.0 by this push:
 new b63bec6  Explicitly convert float value (#8758)
b63bec6 is described below

commit b63bec687099cdb09dde8b521b9d0eb930cbc8db
Author: reminisce 
AuthorDate: Wed Nov 22 08:25:55 2017 -0800

Explicitly convert float value (#8758)

* Explicitly convert float value

* Add unit test function
---
 python/mxnet/ndarray/ndarray.py   |  2 +-
 tests/python/unittest/test_ndarray.py | 10 ++
 2 files changed, 11 insertions(+), 1 deletion(-)

diff --git a/python/mxnet/ndarray/ndarray.py b/python/mxnet/ndarray/ndarray.py
index 91d0e03..a45a6a8 100644
--- a/python/mxnet/ndarray/ndarray.py
+++ b/python/mxnet/ndarray/ndarray.py
@@ -691,7 +691,7 @@ fixed-size items.
 value.copyto(self)
 elif isinstance(value, numeric_types):
 _internal._full(shape=shape, ctx=self.context,
-dtype=self.dtype, value=value, out=self)
+dtype=self.dtype, value=float(value), 
out=self)
 elif isinstance(value, (np.ndarray, np.generic)):
 if isinstance(value, np.generic) or value.shape != shape:
 value = np.broadcast_to(value, shape)
diff --git a/tests/python/unittest/test_ndarray.py 
b/tests/python/unittest/test_ndarray.py
index 8e1f68f..5512b07 100644
--- a/tests/python/unittest/test_ndarray.py
+++ b/tests/python/unittest/test_ndarray.py
@@ -926,6 +926,16 @@ def test_ndarray_indexing():
 test_getitem_autograd(np_array, index[0])
 
 
+def test_assign_float_value_to_ndarray():
+"""Test case from https://github.com/apache/incubator-mxnet/issues/8668""";
+a = np.array([47.844944], dtype=np.float32)
+b = mx.nd.zeros(1, dtype=np.float32)
+b[0] = a
+assert same(a, b.asnumpy())
+b[0] = a[0]
+assert same(a, b.asnumpy())
+
+
 if __name__ == '__main__':
 import nose
 nose.runmodule()

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[incubator-mxnet] branch v1.0.0 updated: Remove spureous std::move, fix warning regarding RVO being prevented (#8755)

[cjolivier01]

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

cjolivier01 pushed a commit to branch v1.0.0
in repository https://gitbox.apache.org/repos/asf/incubator-mxnet.git


The following commit(s) were added to refs/heads/v1.0.0 by this push:
 new e51da4c  Remove spureous std::move, fix warning regarding RVO being 
prevented (#8755)
e51da4c is described below

commit e51da4c549b96a562e68fdfa5813edf49d6383e0
Author: Pedro Larroy <928489+lar...@users.noreply.github.com>
AuthorDate: Tue Nov 21 19:47:58 2017 -0800

Remove spureous std::move, fix warning regarding RVO being prevented (#8755)
---
 src/operator/operator_tune.h | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/operator/operator_tune.h b/src/operator/operator_tune.h
index 4f92c9d..2088d46 100644
--- a/src/operator/operator_tune.h
+++ b/src/operator/operator_tune.h
@@ -56,7 +56,7 @@ class OperatorTuneBase {
* \return Tick object representing the current itmestamp
*/
   static MSHADOW_CINLINE Tick Now() {
-return std::move(std::chrono::high_resolution_clock::now());
+return std::chrono::high_resolution_clock::now();
   }
 
   /*!

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[incubator-mxnet] branch master updated: Updating ps-lite submodule (#8769)

[cjolivier01]

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cjolivier01 pushed a commit to branch master
in repository https://gitbox.apache.org/repos/asf/incubator-mxnet.git


The following commit(s) were added to refs/heads/master by this push:
 new 89d2a71  Updating ps-lite submodule (#8769)
89d2a71 is described below

commit 89d2a71876672944fb7f077168087b97442af088
Author: Madan Jampani 
AuthorDate: Wed Nov 22 09:32:39 2017 -0800

Updating ps-lite submodule (#8769)
---
 ps-lite | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/ps-lite b/ps-lite
index bdd4c67..2ce8b9a 16
--- a/ps-lite
+++ b/ps-lite
@@ -1 +1 @@
-Subproject commit bdd4c67e9e34dc0b8350ce306b0caa737eb31c83
+Subproject commit 2ce8b9a256207947acfa2cb9b09ab74b8de74547

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[GitHub] cjolivier01 closed pull request #8769: Updating ps-lite submodule

[GitBox]

cjolivier01 closed pull request #8769: Updating ps-lite submodule
URL: https://github.com/apache/incubator-mxnet/pull/8769
 
 
   

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diff --git a/ps-lite b/ps-lite
index bdd4c67e9e..2ce8b9a256 16
--- a/ps-lite
+++ b/ps-lite
@@ -1 +1 @@
-Subproject commit bdd4c67e9e34dc0b8350ce306b0caa737eb31c83
+Subproject commit 2ce8b9a256207947acfa2cb9b09ab74b8de74547


 


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[incubator-mxnet] branch v1.0.0 updated: Updating ps-lite submodule (#8769)

[cjolivier01]

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cjolivier01 pushed a commit to branch v1.0.0
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The following commit(s) were added to refs/heads/v1.0.0 by this push:
 new c4a5aad  Updating ps-lite submodule (#8769)
c4a5aad is described below

commit c4a5aad0480a63f7b74b80ca766fe444ed5b5bf9
Author: Madan Jampani 
AuthorDate: Wed Nov 22 09:32:39 2017 -0800

Updating ps-lite submodule (#8769)
---
 ps-lite | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/ps-lite b/ps-lite
index bdd4c67..2ce8b9a 16
--- a/ps-lite
+++ b/ps-lite
@@ -1 +1 @@
-Subproject commit bdd4c67e9e34dc0b8350ce306b0caa737eb31c83
+Subproject commit 2ce8b9a256207947acfa2cb9b09ab74b8de74547

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[GitHub] mbaijal commented on issue #8770: [Merge into v1.0.0 ONLY][Copy of PR #8704] Prep1.0: bump the version number and 0.12.1 updates

[GitBox]

mbaijal commented on issue #8770: [Merge into v1.0.0 ONLY][Copy of PR #8704] 
Prep1.0: bump the version number and 0.12.1 updates
URL: https://github.com/apache/incubator-mxnet/pull/8770#issuecomment-346424454
 
 
   @szha Can you please review and merge. 


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[GitHub] cjolivier01 opened a new pull request #8778: cast scalar value in invoke to float

[GitBox]

cjolivier01 opened a new pull request #8778: cast scalar value in invoke to 
float
URL: https://github.com/apache/incubator-mxnet/pull/8778
 
 
   Doing float() cast in other places since we know now there's a precision 
problem with scalar numpy object types
   


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[incubator-mxnet] branch v1.0.0 updated: [Merge into v1.0.0 ONLY][Copy of PR #8704] Prep1.0: bump the version number and 0.12.1 updates (#8770)

[zhasheng]

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zhasheng pushed a commit to branch v1.0.0
in repository https://gitbox.apache.org/repos/asf/incubator-mxnet.git


The following commit(s) were added to refs/heads/v1.0.0 by this push:
 new 998b29d  [Merge into v1.0.0 ONLY][Copy of PR #8704] Prep1.0: bump the 
version number and 0.12.1 updates (#8770)
998b29d is described below

commit 998b29d6a9dde313f22853bb31228bff721d9b94
Author: mbaijal <30911248+mbai...@users.noreply.github.com>
AuthorDate: Wed Nov 22 10:36:19 2017 -0800

[Merge into v1.0.0 ONLY][Copy of PR #8704] Prep1.0: bump the version number 
and 0.12.1 updates (#8770)

* Initial Prep for 1.0 and 0.12.1 updates

* Adding the NEWS.md changes for 0.12.1 to update master
---
 NEWS.md | 13 +
 R-package/DESCRIPTION   |  2 +-
 README.md   |  1 +
 docs/build_version_doc/build_all_version.sh |  2 +-
 include/mxnet/base.h|  6 +++---
 python/mxnet/libinfo.py |  2 +-
 scala-package/assembly/linux-x86_64-cpu/pom.xml |  6 +++---
 scala-package/assembly/linux-x86_64-gpu/pom.xml |  6 +++---
 scala-package/assembly/osx-x86_64-cpu/pom.xml   |  6 +++---
 scala-package/assembly/pom.xml  |  2 +-
 scala-package/core/pom.xml  |  6 +++---
 scala-package/examples/pom.xml  |  4 ++--
 scala-package/init-native/linux-x86_64/pom.xml  |  4 ++--
 scala-package/init-native/osx-x86_64/pom.xml|  4 ++--
 scala-package/init-native/pom.xml   |  2 +-
 scala-package/init/pom.xml  |  2 +-
 scala-package/macros/pom.xml|  6 +++---
 scala-package/native/linux-x86_64-cpu/pom.xml   |  4 ++--
 scala-package/native/linux-x86_64-gpu/pom.xml   |  4 ++--
 scala-package/native/osx-x86_64-cpu/pom.xml |  4 ++--
 scala-package/native/pom.xml|  2 +-
 scala-package/pom.xml   |  2 +-
 scala-package/spark/pom.xml |  4 ++--
 setup-utils/install-mxnet-osx-python.sh |  2 +-
 snapcraft.yaml  |  2 +-
 25 files changed, 56 insertions(+), 42 deletions(-)

diff --git a/NEWS.md b/NEWS.md
index 666b5d8..7406210 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -1,5 +1,18 @@
 MXNet Change Log
 
+## 0.12.1
+### Bug-fixes
+  - Added GPU support for the `syevd` operator which ensures that there is GPU 
support for all linalg-operators.
+  - Bugfix for `syevd` on CPU such that it works for `float32`.
+  - Fixed API call when `OMP_NUM_THREADS` environment variable is set. 
+  - Fixed `MakeNonlossGradNode` bug.
+  - Fixed bug related to passing `dtype` to `array()`. 
+  - Fixed some minor bugs for sparse distributed training.
+  - Fixed a bug on `Slice` accessing uninitialized memory in `param.begin` in 
the file `matrix_op-inl.h`. 
+  - Fixed `gluon.data.RecordFileDataset`.
+  - Fixed a bug that caused `autograd` to crash on some networks.
+  
+  
 ## 0.12.0
 ### Performance
   - Added full support for NVIDIA Volta GPU Architecture and CUDA 9. Training 
CNNs is up to 3.5x faster than Pascal when using float16 precision.
diff --git a/R-package/DESCRIPTION b/R-package/DESCRIPTION
index 3d57ea8..6e0f932 100644
--- a/R-package/DESCRIPTION
+++ b/R-package/DESCRIPTION
@@ -1,7 +1,7 @@
 Package: mxnet
 Type: Package
 Title: MXNet: A Flexible and Efficient Machine Learning Library for 
Heterogeneous Distributed Systems
-Version: 0.12.1
+Version: 1.0.0
 Date: 2017-06-27
 Author: Tianqi Chen, Qiang Kou, Tong He
 Maintainer: Qiang Kou 
diff --git a/README.md b/README.md
index fc252a7..0326412 100644
--- a/README.md
+++ b/README.md
@@ -22,6 +22,7 @@ deep learning systems, and interesting insights of DL systems 
for hackers.
 
 What's New
 --
+* [Version 0.12.1 
Release](https://github.com/apache/incubator-mxnet/releases/tag/0.12.1) - MXNet 
0.12.1 Patch Release.
 * [Version 0.12.0 
Release](https://github.com/apache/incubator-mxnet/releases/tag/0.12.0) - MXNet 
0.12.0 Release.
 * [Version 0.11.0 
Release](https://github.com/apache/incubator-mxnet/releases/tag/0.11.0) - MXNet 
0.11.0 Release.
 * [Apache Incubator](http://incubator.apache.org/projects/mxnet.html) - We are 
now an Apache Incubator project.
diff --git a/docs/build_version_doc/build_all_version.sh 
b/docs/build_version_doc/build_all_version.sh
index 2d33bd7..bf02a62 100755
--- a/docs/build_version_doc/build_all_version.sh
+++ b/docs/build_version_doc/build_all_version.sh
@@ -21,7 +21,7 @@
 # Built files are stored in $built
 # Version numbers are stored in $tag_list.
 # Version numbers are ordered from latest to old and final one is master.
-tag_list="0.12.0 0.11.0 master"
+tag_list="1.0.0 0.12.0 0.11.0 master"
 
 mxnet_url="https://github.com/apache/incubator-mxnet.git";
 mxnet_folder="apache_mxnet"
diff --git a/include/mxnet/base.h b/inc

[GitHub] szha closed pull request #8770: [Merge into v1.0.0 ONLY][Copy of PR #8704] Prep1.0: bump the version number and 0.12.1 updates

[GitBox]

szha closed pull request #8770: [Merge into v1.0.0 ONLY][Copy of PR #8704] 
Prep1.0: bump the version number and 0.12.1 updates
URL: https://github.com/apache/incubator-mxnet/pull/8770
 
 
   

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/NEWS.md b/NEWS.md
index 666b5d88e6..740621038d 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -1,5 +1,18 @@
 MXNet Change Log
 
+## 0.12.1
+### Bug-fixes
+  - Added GPU support for the `syevd` operator which ensures that there is GPU 
support for all linalg-operators.
+  - Bugfix for `syevd` on CPU such that it works for `float32`.
+  - Fixed API call when `OMP_NUM_THREADS` environment variable is set. 
+  - Fixed `MakeNonlossGradNode` bug.
+  - Fixed bug related to passing `dtype` to `array()`. 
+  - Fixed some minor bugs for sparse distributed training.
+  - Fixed a bug on `Slice` accessing uninitialized memory in `param.begin` in 
the file `matrix_op-inl.h`. 
+  - Fixed `gluon.data.RecordFileDataset`.
+  - Fixed a bug that caused `autograd` to crash on some networks.
+  
+  
 ## 0.12.0
 ### Performance
   - Added full support for NVIDIA Volta GPU Architecture and CUDA 9. Training 
CNNs is up to 3.5x faster than Pascal when using float16 precision.
diff --git a/R-package/DESCRIPTION b/R-package/DESCRIPTION
index 3d57ea876f..6e0f93294b 100644
--- a/R-package/DESCRIPTION
+++ b/R-package/DESCRIPTION
@@ -1,7 +1,7 @@
 Package: mxnet
 Type: Package
 Title: MXNet: A Flexible and Efficient Machine Learning Library for 
Heterogeneous Distributed Systems
-Version: 0.12.1
+Version: 1.0.0
 Date: 2017-06-27
 Author: Tianqi Chen, Qiang Kou, Tong He
 Maintainer: Qiang Kou 
diff --git a/README.md b/README.md
index fc252a7a72..0326412541 100644
--- a/README.md
+++ b/README.md
@@ -22,6 +22,7 @@ deep learning systems, and interesting insights of DL systems 
for hackers.
 
 What's New
 --
+* [Version 0.12.1 
Release](https://github.com/apache/incubator-mxnet/releases/tag/0.12.1) - MXNet 
0.12.1 Patch Release.
 * [Version 0.12.0 
Release](https://github.com/apache/incubator-mxnet/releases/tag/0.12.0) - MXNet 
0.12.0 Release.
 * [Version 0.11.0 
Release](https://github.com/apache/incubator-mxnet/releases/tag/0.11.0) - MXNet 
0.11.0 Release.
 * [Apache Incubator](http://incubator.apache.org/projects/mxnet.html) - We are 
now an Apache Incubator project.
diff --git a/docs/build_version_doc/build_all_version.sh 
b/docs/build_version_doc/build_all_version.sh
index 2d33bd72c4..bf02a62a15 100755
--- a/docs/build_version_doc/build_all_version.sh
+++ b/docs/build_version_doc/build_all_version.sh
@@ -21,7 +21,7 @@
 # Built files are stored in $built
 # Version numbers are stored in $tag_list.
 # Version numbers are ordered from latest to old and final one is master.
-tag_list="0.12.0 0.11.0 master"
+tag_list="1.0.0 0.12.0 0.11.0 master"
 
 mxnet_url="https://github.com/apache/incubator-mxnet.git";
 mxnet_folder="apache_mxnet"
diff --git a/include/mxnet/base.h b/include/mxnet/base.h
index 7c136a6470..84b2fea712 100644
--- a/include/mxnet/base.h
+++ b/include/mxnet/base.h
@@ -109,11 +109,11 @@
 #endif
 
 /*! \brief major version */
-#define MXNET_MAJOR 0
+#define MXNET_MAJOR 1
 /*! \brief minor version */
-#define MXNET_MINOR 12
+#define MXNET_MINOR 0
 /*! \brief patch version */
-#define MXNET_PATCH 1
+#define MXNET_PATCH 0
 /*! \brief mxnet version */
 #define MXNET_VERSION (MXNET_MAJOR*1 + MXNET_MINOR*100 + MXNET_PATCH)
 /*! \brief helper for making version number */
diff --git a/python/mxnet/libinfo.py b/python/mxnet/libinfo.py
index d4d100e12d..ce60606236 100644
--- a/python/mxnet/libinfo.py
+++ b/python/mxnet/libinfo.py
@@ -61,4 +61,4 @@ def find_lib_path():
 
 
 # current version
-__version__ = "0.12.1"
+__version__ = "1.0.0"
diff --git a/scala-package/assembly/linux-x86_64-cpu/pom.xml 
b/scala-package/assembly/linux-x86_64-cpu/pom.xml
index f15a7e315d..10f5d39638 100644
--- a/scala-package/assembly/linux-x86_64-cpu/pom.xml
+++ b/scala-package/assembly/linux-x86_64-cpu/pom.xml
@@ -6,7 +6,7 @@
   
 ml.dmlc.mxnet
 mxnet-full-parent_2.11
-0.12.1-SNAPSHOT
+1.0.0-SNAPSHOT
 ../pom.xml
   
 
@@ -18,12 +18,12 @@
 
   ml.dmlc.mxnet
   mxnet-core_${scala.binary.version}
-  0.12.1-SNAPSHOT
+  1.0.0-SNAPSHOT
 
 
   ml.dmlc.mxnet
   libmxnet-scala-linux-x86_64-cpu
-  0.12.1-SNAPSHOT
+  1.0.0-SNAPSHOT
   so
 
   
diff --git a/scala-package/assembly/linux-x86_64-gpu/pom.xml 
b/scala-package/assembly/linux-x86_64-gpu/pom.xml
index 81e4d1ec59..9c9af8422d 100644
--- a/scala-package/assembly/linux-x86_64-gpu/pom.xml
+++ b/scala-package/assembly/linux-x86_64-gpu/pom.xml
@@ -6,7 +6,7 @@
   
 ml.dmlc.mxnet
 mxnet-full-parent_2.11
-0.12.1-SNAPSHOT
+1.0.0-SNAPSHOT
 ../pom.xml
  

[incubator-mxnet] branch master updated: Fix doc link (#8776)

[madjam]

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

madjam 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 e835777  Fix doc link (#8776)
e835777 is described below

commit e835777bdf2dd586ccefa94e4dc34678cced1835
Author: Madan Jampani 
AuthorDate: Wed Nov 22 10:38:18 2017 -0800

Fix doc link (#8776)
---
 docs/faq/index.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/docs/faq/index.md b/docs/faq/index.md
index e29bda0..883d8e6 100644
--- a/docs/faq/index.md
+++ b/docs/faq/index.md
@@ -41,7 +41,7 @@ and full working examples, visit the [tutorials 
section](../tutorials/index.md).
 * [How to convert MXNet models to Apple CoreML 
format?](https://github.com/apache/incubator-mxnet/tree/master/tools/coreml)
 
 ## Security
-* [How to run MXNet securely?](http://mxnet.io/how_to/security.md)
+* [How to run MXNet securely?](http://mxnet.io/how_to/security.html)
 
 ## Extend and Contribute to MXNet
 

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[GitHub] madjam closed pull request #8776: Fix security doc link

[GitBox]

madjam closed pull request #8776: Fix security doc link
URL: https://github.com/apache/incubator-mxnet/pull/8776
 
 
   

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As GitHub hides the original diff on merge, it is displayed below for
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diff --git a/docs/faq/index.md b/docs/faq/index.md
index e29bda0b68..883d8e6188 100644
--- a/docs/faq/index.md
+++ b/docs/faq/index.md
@@ -41,7 +41,7 @@ and full working examples, visit the [tutorials 
section](../tutorials/index.md).
 * [How to convert MXNet models to Apple CoreML 
format?](https://github.com/apache/incubator-mxnet/tree/master/tools/coreml)
 
 ## Security
-* [How to run MXNet securely?](http://mxnet.io/how_to/security.md)
+* [How to run MXNet securely?](http://mxnet.io/how_to/security.html)
 
 ## Extend and Contribute to MXNet
 


 


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[GitHub] sxjscience commented on issue #8556: [Call for Contribution] Image augmenter operators

[GitBox]

sxjscience commented on issue #8556: [Call for Contribution] Image augmenter 
operators
URL: 
https://github.com/apache/incubator-mxnet/issues/8556#issuecomment-346438800
 
 
   I've checked again the APIs in torchvision.
   The input to all the random augmentation ops (like random_color_jitter) 
should be a uint8 tensor with (H, W, C) shape.


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[GitHub] larroy commented on a change in pull request #8680: Fix cmake library path when installing python package

[GitBox]

larroy commented on a change in pull request #8680: Fix cmake library path when 
installing python package
URL: https://github.com/apache/incubator-mxnet/pull/8680#discussion_r152651220
 
 

 ##
 File path: python/mxnet/libinfo.py
 ##
 @@ -31,7 +31,7 @@ def find_lib_path():
 """
 curr_path = os.path.dirname(os.path.abspath(os.path.expanduser(__file__)))
 api_path = os.path.join(curr_path, '../../lib/')
-cmake_build_path = os.path.join(curr_path, '../../build/Release/')
+cmake_build_path = os.path.join(curr_path, '../../build/')
 
 Review comment:
   I never saw mxnet being left in this folder, did you observe it? Maybe with 
a different CMake version or intellij? Agreed with your remarks.


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[GitHub] larroy commented on a change in pull request #8737: Use RAII and fix Coverity resource leaks #10371 and others

[GitBox]

larroy commented on a change in pull request #8737: Use RAII and fix Coverity 
resource leaks #10371 and others
URL: https://github.com/apache/incubator-mxnet/pull/8737#discussion_r152651527
 
 

 ##
 File path: cpp-package/example/alexnet.cpp
 ##
 @@ -215,7 +215,7 @@ int main(int argc, char const *argv[]) {
   args_map["label"] = NDArray(Shape(batch_size), ctx);
 
   /*with data and label, executor can be generated automatically*/
-  auto *exec = Net.SimpleBind(ctx, args_map);
+  auto exec = Net.SimpleBind(ctx, args_map);
 
 Review comment:
   I can change it for sure to the proper type. Are we going to merge this PR 
though? I really dislike returning unmaged pointers and would like to see this 
merged, even if it breaks the interface very slightly.


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[GitHub] cjolivier01 closed pull request #8680: Fix cmake library path when installing python package

[GitBox]

cjolivier01 closed pull request #8680: Fix cmake library path when installing 
python package
URL: https://github.com/apache/incubator-mxnet/pull/8680
 
 
   

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/python/mxnet/libinfo.py b/python/mxnet/libinfo.py
index d4d100e12d..551c786eff 100644
--- a/python/mxnet/libinfo.py
+++ b/python/mxnet/libinfo.py
@@ -31,7 +31,7 @@ def find_lib_path():
 """
 curr_path = os.path.dirname(os.path.abspath(os.path.expanduser(__file__)))
 api_path = os.path.join(curr_path, '../../lib/')
-cmake_build_path = os.path.join(curr_path, '../../build/Release/')
+cmake_build_path = os.path.join(curr_path, '../../build/')
 dll_path = [curr_path, api_path, cmake_build_path]
 if os.name == 'nt':
 dll_path.append(os.path.join(curr_path, '../../build'))


 


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[GitHub] cjolivier01 commented on a change in pull request #8680: Fix cmake library path when installing python package

[GitBox]

cjolivier01 commented on a change in pull request #8680: Fix cmake library path 
when installing python package
URL: https://github.com/apache/incubator-mxnet/pull/8680#discussion_r152654071
 
 

 ##
 File path: python/mxnet/libinfo.py
 ##
 @@ -31,7 +31,7 @@ def find_lib_path():
 """
 curr_path = os.path.dirname(os.path.abspath(os.path.expanduser(__file__)))
 api_path = os.path.join(curr_path, '../../lib/')
-cmake_build_path = os.path.join(curr_path, '../../build/Release/')
+cmake_build_path = os.path.join(curr_path, '../../build/')
 
 Review comment:
   Someone would need to do it manually when running cmake, but it's sort of a 
common practice.


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[incubator-mxnet] branch master updated: [CMAKE] Fix cmake library path when installing python package (#8680)

[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 5ad6eab  [CMAKE] Fix cmake library path when installing python package 
(#8680)
5ad6eab is described below

commit 5ad6eab643ad7725338af9204f2fc1e46a1965ea
Author: Pedro Larroy <928489+lar...@users.noreply.github.com>
AuthorDate: Wed Nov 22 11:05:09 2017 -0800

[CMAKE] Fix cmake library path when installing python package (#8680)
---
 python/mxnet/libinfo.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/python/mxnet/libinfo.py b/python/mxnet/libinfo.py
index d4d100e..551c786 100644
--- a/python/mxnet/libinfo.py
+++ b/python/mxnet/libinfo.py
@@ -31,7 +31,7 @@ def find_lib_path():
 """
 curr_path = os.path.dirname(os.path.abspath(os.path.expanduser(__file__)))
 api_path = os.path.join(curr_path, '../../lib/')
-cmake_build_path = os.path.join(curr_path, '../../build/Release/')
+cmake_build_path = os.path.join(curr_path, '../../build/')
 dll_path = [curr_path, api_path, cmake_build_path]
 if os.name == 'nt':
 dll_path.append(os.path.join(curr_path, '../../build'))

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[GitHub] cjolivier01 commented on a change in pull request #8737: Use RAII and fix Coverity resource leaks #10371 and others

[GitBox]

cjolivier01 commented on a change in pull request #8737: Use RAII and fix 
Coverity resource leaks #10371 and others
URL: https://github.com/apache/incubator-mxnet/pull/8737#discussion_r152655135
 
 

 ##
 File path: cpp-package/example/alexnet.cpp
 ##
 @@ -215,7 +215,7 @@ int main(int argc, char const *argv[]) {
   args_map["label"] = NDArray(Shape(batch_size), ctx);
 
   /*with data and label, executor can be generated automatically*/
-  auto *exec = Net.SimpleBind(ctx, args_map);
+  auto exec = Net.SimpleBind(ctx, args_map);
 
 Review comment:
   It doesn't necessarily have to return a unique_ptr as long as you 
immediately assign it to one.  Might be a benefit for it not being returned as 
unique_ptr from SImpleBind() since maybe they want it to be a shared_ptr in 
their calling context.  


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[GitHub] cjolivier01 commented on a change in pull request #8737: Use RAII and fix Coverity resource leaks #10371 and others

[GitBox]

cjolivier01 commented on a change in pull request #8737: Use RAII and fix 
Coverity resource leaks #10371 and others
URL: https://github.com/apache/incubator-mxnet/pull/8737#discussion_r152655571
 
 

 ##
 File path: cpp-package/example/alexnet.cpp
 ##
 @@ -215,7 +215,7 @@ int main(int argc, char const *argv[]) {
   args_map["label"] = NDArray(Shape(batch_size), ctx);
 
   /*with data and label, executor can be generated automatically*/
-  auto *exec = Net.SimpleBind(ctx, args_map);
+  auto exec = Net.SimpleBind(ctx, args_map);
 
 Review comment:
   Are these pointers returns to python as object references? I think they 
might be...


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[GitHub] cjolivier01 commented on a change in pull request #8737: Use RAII and fix Coverity resource leaks #10371 and others

[GitBox]

cjolivier01 commented on a change in pull request #8737: Use RAII and fix 
Coverity resource leaks #10371 and others
URL: https://github.com/apache/incubator-mxnet/pull/8737#discussion_r152655571
 
 

 ##
 File path: cpp-package/example/alexnet.cpp
 ##
 @@ -215,7 +215,7 @@ int main(int argc, char const *argv[]) {
   args_map["label"] = NDArray(Shape(batch_size), ctx);
 
   /*with data and label, executor can be generated automatically*/
-  auto *exec = Net.SimpleBind(ctx, args_map);
+  auto exec = Net.SimpleBind(ctx, args_map);
 
 Review comment:
   Are these pointers returns to python as object references? I think they 
might be...


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[GitHub] cjolivier01 commented on a change in pull request #8737: Use RAII and fix Coverity resource leaks #10371 and others

[GitBox]

cjolivier01 commented on a change in pull request #8737: Use RAII and fix 
Coverity resource leaks #10371 and others
URL: https://github.com/apache/incubator-mxnet/pull/8737#discussion_r152656119
 
 

 ##
 File path: cpp-package/example/alexnet.cpp
 ##
 @@ -215,7 +215,7 @@ int main(int argc, char const *argv[]) {
   args_map["label"] = NDArray(Shape(batch_size), ctx);
 
   /*with data and label, executor can be generated automatically*/
-  auto *exec = Net.SimpleBind(ctx, args_map);
+  auto exec = Net.SimpleBind(ctx, args_map);
 
 Review comment:
   Oh wait, this is for cpp-package only?  I understand the "changing the 
interface" thing now.  Maybe bring it up on dev if you still want to change it? 
 But in that case, I prefer shared_ptr since this seems like something they're 
goingto want to save (just my personal preference).


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[GitHub] cjolivier01 commented on issue #8777: Error: package or namespace load failed for ?mxnet?:

[GitBox]

cjolivier01 commented on issue #8777: Error: package or namespace load failed 
for ?mxnet?:
URL: 
https://github.com/apache/incubator-mxnet/issues/8777#issuecomment-346448475
 
 
   If the dll is indeed there, run depends.ex on it and it should tell you what 
dll is missing:
   
   http://www.dependencywalker.com/


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[GitHub] cjolivier01 commented on issue #8771: Build source

[GitBox]

cjolivier01 commented on issue #8771: Build source
URL: 
https://github.com/apache/incubator-mxnet/issues/8771#issuecomment-346448861
 
 
   Is there a question?


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[GitHub] cjolivier01 closed issue #8771: Build source

[GitBox]

cjolivier01 closed issue #8771: Build source
URL: https://github.com/apache/incubator-mxnet/issues/8771
 
 
   


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[GitHub] cjolivier01 commented on issue #8771: Build source

[GitBox]

cjolivier01 commented on issue #8771: Build source
URL: 
https://github.com/apache/incubator-mxnet/issues/8771#issuecomment-346448861
 
 
   Is there a question?  If so, please reopen.


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[GitHub] cjolivier01 commented on issue #8772: Build source code problem cannot convert from 'mshadow::Stream *' to 'mshadow::Stream *'

[GitBox]

cjolivier01 commented on issue #8772: Build source code problem  cannot convert 
from 'mshadow::Stream *' to 'mshadow::Stream *'   
URL: 
https://github.com/apache/incubator-mxnet/issues/8772#issuecomment-346449310
 
 
   Can you attach full output?  Doesn't show file and line.


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[GitHub] cjolivier01 closed issue #8775: Is the newest cpp package compatible with mxnetv0.8.0?

[GitBox]

cjolivier01 closed issue #8775: Is the newest cpp package compatible with 
mxnetv0.8.0?
URL: https://github.com/apache/incubator-mxnet/issues/8775
 
 
   


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[GitHub] cjolivier01 commented on issue #8775: Is the newest cpp package compatible with mxnetv0.8.0?

[GitBox]

cjolivier01 commented on issue #8775: Is the newest cpp package compatible with 
mxnetv0.8.0?
URL: 
https://github.com/apache/incubator-mxnet/issues/8775#issuecomment-346452343
 
 
   Are you asking if the code in cpp-package subdirectory in master branch of 
mxnet can be used to wrap the older mxnet 0.8.0 branch?  Sorry, that's very 
unlikely :(


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[GitHub] sxjscience commented on a change in pull request #8680: Fix cmake library path when installing python package

[GitBox]

sxjscience commented on a change in pull request #8680: Fix cmake library path 
when installing python package
URL: https://github.com/apache/incubator-mxnet/pull/8680#discussion_r152660794
 
 

 ##
 File path: python/mxnet/libinfo.py
 ##
 @@ -31,7 +31,7 @@ def find_lib_path():
 """
 curr_path = os.path.dirname(os.path.abspath(os.path.expanduser(__file__)))
 api_path = os.path.join(curr_path, '../../lib/')
-cmake_build_path = os.path.join(curr_path, '../../build/Release/')
+cmake_build_path = os.path.join(curr_path, '../../build/')
 
 Review comment:
   I'm using Visual Studio in Windows and after building the solution file the 
dll will be in `build/Release`. I think this path should be added back.


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[GitHub] sxjscience commented on a change in pull request #8680: Fix cmake library path when installing python package

[GitBox]

sxjscience commented on a change in pull request #8680: Fix cmake library path 
when installing python package
URL: https://github.com/apache/incubator-mxnet/pull/8680#discussion_r152660794
 
 

 ##
 File path: python/mxnet/libinfo.py
 ##
 @@ -31,7 +31,7 @@ def find_lib_path():
 """
 curr_path = os.path.dirname(os.path.abspath(os.path.expanduser(__file__)))
 api_path = os.path.join(curr_path, '../../lib/')
-cmake_build_path = os.path.join(curr_path, '../../build/Release/')
+cmake_build_path = os.path.join(curr_path, '../../build/')
 
 Review comment:
   I'm using Visual Studio in Windows and after building the solution file the 
dll will be in `build/Release`. I think this path should be added back.


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[GitHub] sxjscience commented on a change in pull request #8680: Fix cmake library path when installing python package

[GitBox]

sxjscience commented on a change in pull request #8680: Fix cmake library path 
when installing python package
URL: https://github.com/apache/incubator-mxnet/pull/8680#discussion_r152661318
 
 

 ##
 File path: python/mxnet/libinfo.py
 ##
 @@ -31,7 +31,7 @@ def find_lib_path():
 """
 curr_path = os.path.dirname(os.path.abspath(os.path.expanduser(__file__)))
 api_path = os.path.join(curr_path, '../../lib/')
-cmake_build_path = os.path.join(curr_path, '../../build/Release/')
+cmake_build_path = os.path.join(curr_path, '../../build/')
 
 Review comment:
   OK, forget about the previous comment. The release option is added in the 
codes below.


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[GitHub] cjolivier01 commented on issue #8726: CI: Remove building from Unit Test-Jobs

[GitBox]

cjolivier01 commented on issue #8726: CI: Remove building from Unit Test-Jobs
URL: 
https://github.com/apache/incubator-mxnet/issues/8726#issuecomment-346454446
 
 
   @KellenSunderland 


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[GitHub] cjolivier01 commented on issue #8751: Distributed Training has inverse results when imported (8 GPUS is slower than 1!)

[GitBox]

cjolivier01 commented on issue #8751: Distributed Training has inverse results 
when imported (8 GPUS is slower than 1!)
URL: 
https://github.com/apache/incubator-mxnet/issues/8751#issuecomment-346455880
 
 
   1) The reason that something small like mnist is slower on multiple GPUs is 
that the computation is so fast on such small images that the distribution 
system (amon g GPUs) is more expensive than the computation, and thus the 
distribution system becomes the bottleneck. For larger networks such as resnet, 
the computation remains the bottleneck and therefore the distribution system, 
acting in parallel to the computations, does not factor into the total time.
   Hope this helps,
   
   -Chris


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[GitHub] EsraaRagaa commented on issue #6958: Data provided by label_shapes don't match names specified by label_names ([] vs. ['softmax_label'])

[GitBox]

EsraaRagaa commented on issue #6958: Data provided by label_shapes don't match 
names specified by label_names ([] vs. ['softmax_label'])
URL: 
https://github.com/apache/incubator-mxnet/issues/6958#issuecomment-346458947
 
 
   You can check this 
   
https://stackoverflow.com/questions/44947104/mxnet-label-shapes-dont-match-names-specified-by-label-names


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[GitHub] SumNeuron commented on issue #8751: Distributed Training has inverse results when imported (8 GPUS is slower than 1!)

[GitBox]

SumNeuron commented on issue #8751: Distributed Training has inverse results 
when imported (8 GPUS is slower than 1!)
URL: 
https://github.com/apache/incubator-mxnet/issues/8751#issuecomment-346462374
 
 
   @cjolivier01 I understand this principal and that makes sense. However, you 
are overlooking that this behavior is **NOT** consistent. Running on **8** gpus 
can take from *2.3* seconds (when the net and training is defined in the same 
file)  to up to *17* seconds (when the net is **imported** from another file). 
That is the difference.
   
   Saying that for small images like MNIST takes longer on distributed systems 
is fine **if** this is a consistent behavior. It is not.


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[GitHub] cjolivier01 commented on issue #8751: Distributed Training has inverse results when imported (8 GPUS is slower than 1!)

[GitBox]

cjolivier01 commented on issue #8751: Distributed Training has inverse results 
when imported (8 GPUS is slower than 1!)
URL: 
https://github.com/apache/incubator-mxnet/issues/8751#issuecomment-346463794
 
 
   what does "when the net is imported" mean in this context, as opposed to 
"when everything is in the same file"?


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[GitHub] SumNeuron commented on issue #8751: Distributed Training has inverse results when imported (8 GPUS is slower than 1!)

[GitBox]

SumNeuron commented on issue #8751: Distributed Training has inverse results 
when imported (8 GPUS is slower than 1!)
URL: 
https://github.com/apache/incubator-mxnet/issues/8751#issuecomment-346463918
 
 
   @cjolivier01  please see file 2 and 3. File 3 is the net definition, File 2 
imports the net and runs it


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[GitHub] piiswrong commented on a change in pull request #8766: NDArray Indexing tutorial and Gradient Compression FAQ

[GitBox]

piiswrong commented on a change in pull request #8766: NDArray Indexing 
tutorial and Gradient Compression FAQ
URL: https://github.com/apache/incubator-mxnet/pull/8766#discussion_r152674195
 
 

 ##
 File path: docs/faq/gradient_compression.md
 ##
 @@ -0,0 +1,107 @@
+# Gradient Compression
+
+Gradient Compression reduces communication bandwidth to make distributed 
training with GPUs more scalable and efficient without significant loss in 
convergence rate or accuracy.
 
 Review comment:
   Its not restricted to distributed or GPUs


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[GitHub] piiswrong commented on a change in pull request #8766: NDArray Indexing tutorial and Gradient Compression FAQ

[GitBox]

piiswrong commented on a change in pull request #8766: NDArray Indexing 
tutorial and Gradient Compression FAQ
URL: https://github.com/apache/incubator-mxnet/pull/8766#discussion_r152674342
 
 

 ##
 File path: docs/faq/gradient_compression.md
 ##
 @@ -0,0 +1,107 @@
+# Gradient Compression
+
+Gradient Compression reduces communication bandwidth to make distributed 
training with GPUs more scalable and efficient without significant loss in 
convergence rate or accuracy.
 
 Review comment:
   Also there is no guarantee that you won't loss convergence or accuracy 
significantly.


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[GitHub] piiswrong commented on a change in pull request #8766: NDArray Indexing tutorial and Gradient Compression FAQ

[GitBox]

piiswrong commented on a change in pull request #8766: NDArray Indexing 
tutorial and Gradient Compression FAQ
URL: https://github.com/apache/incubator-mxnet/pull/8766#discussion_r152674798
 
 

 ##
 File path: docs/tutorials/basic/ndarray_indexing.md
 ##
 @@ -0,0 +1,377 @@
+
+# NDArray Indexing - Array indexing features
 
 Review comment:
   why not merge this into the ndarray tutorial?


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[GitHub] piiswrong commented on a change in pull request #8766: NDArray Indexing tutorial and Gradient Compression FAQ

[GitBox]

piiswrong commented on a change in pull request #8766: NDArray Indexing 
tutorial and Gradient Compression FAQ
URL: https://github.com/apache/incubator-mxnet/pull/8766#discussion_r152674943
 
 

 ##
 File path: docs/faq/gradient_compression.md
 ##
 @@ -0,0 +1,107 @@
+# Gradient Compression
+
+Gradient Compression reduces communication bandwidth to make distributed 
training with GPUs more scalable and efficient without significant loss in 
convergence rate or accuracy.
+
+
+## Benefits
+
+**Increased Speed**
+
+For architectures with fully connected components, the gradient compression 
capability is observed to speedup training by about 2x, depending on the size 
of the model and the network bandwidth of the instance. Bigger models see 
larger speedup with gradient compression.
 
 Review comment:
   fully connected components -> fully connected layers


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[GitHub] piiswrong commented on a change in pull request #8766: NDArray Indexing tutorial and Gradient Compression FAQ

[GitBox]

piiswrong commented on a change in pull request #8766: NDArray Indexing 
tutorial and Gradient Compression FAQ
URL: https://github.com/apache/incubator-mxnet/pull/8766#discussion_r152675141
 
 

 ##
 File path: docs/faq/gradient_compression.md
 ##
 @@ -0,0 +1,107 @@
+# Gradient Compression
+
+Gradient Compression reduces communication bandwidth to make distributed 
training with GPUs more scalable and efficient without significant loss in 
convergence rate or accuracy.
+
+
+## Benefits
+
+**Increased Speed**
+
+For architectures with fully connected components, the gradient compression 
capability is observed to speedup training by about 2x, depending on the size 
of the model and the network bandwidth of the instance. Bigger models see 
larger speedup with gradient compression.
+
+**Minimal Accuracy Loss**
+
+Gradient compression uses the approach of delaying the synchronization of 
weight updates which are small. Although small weight updates might not be sent 
for that batch, this information is not discarded. Once the weight updates for 
this location accumulate to become a larger value, they will be propagated. 
Since there is no information loss, but only delayed updates, it does not lead 
to a significant loss in accuracy or convergence rate. In distributed training 
experiments[1], the accuracy loss observed due to gradient compression was as 
low as 1%
+
+
+## When to Use Gradient Compression
+
+When training models whose architectures include large fully connected 
components, it can be helpful to use gradient compression. For larger models, 
the communication cost becomes a major factor. Such models stand to benefit 
greatly with gradient compression.
 
 Review comment:
   Common in recurrent neural networks.


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[GitHub] piiswrong commented on issue #8766: NDArray Indexing tutorial and Gradient Compression FAQ

[GitBox]

piiswrong commented on issue #8766: NDArray Indexing tutorial and Gradient 
Compression FAQ
URL: https://github.com/apache/incubator-mxnet/pull/8766#issuecomment-346469139
 
 
   The introduction part of gradient compression seems unnecessarily verbose 
and repetitive.


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[GitHub] piiswrong closed pull request #8757: [ImageIO] Fix image io for opencv3.3

[GitBox]

piiswrong closed pull request #8757: [ImageIO] Fix image io for opencv3.3
URL: https://github.com/apache/incubator-mxnet/pull/8757
 
 
   

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/plugin/opencv/cv_api.cc b/plugin/opencv/cv_api.cc
index 1508de376d..1ca14aa460 100644
--- a/plugin/opencv/cv_api.cc
+++ b/plugin/opencv/cv_api.cc
@@ -100,7 +100,11 @@ MXNET_DLL int MXCVImdecode(const unsigned char *img, const 
mx_uint len,
   ndout.CheckAndAlloc();
   cv::Mat buf(1, len, CV_8U, img_cpy);
   cv::Mat dst(dims[0], dims[1], flag == 0 ? CV_8U : CV_8UC3, 
ndout.data().dptr_);
+#if (CV_MAJOR_VERSION > 3 || (CV_MAJOR_VERSION == 3 && CV_MINOR_VERSION >= 3))
+  cv::imdecode(buf, flag | cv::IMREAD_IGNORE_ORIENTATION, &dst);
+#else
   cv::imdecode(buf, flag, &dst);
+#endif
   CHECK(!dst.empty());
   delete[] img_cpy;
 }, ndout.ctx(), {}, {ndout.var()});
diff --git a/src/io/image_io.cc b/src/io/image_io.cc
index d95e750e79..491370d9a7 100644
--- a/src/io/image_io.cc
+++ b/src/io/image_io.cc
@@ -156,7 +156,10 @@ void ImdecodeImpl(int flag, bool to_rgb, void* data, 
size_t size,
   } else {
 dst = cv::Mat(out->shape()[0], out->shape()[1], flag == 0 ? CV_8U : 
CV_8UC3,
 out->data().dptr_);
-#if (CV_MAJOR_VERSION > 2 || (CV_MAJOR_VERSION == 2 && CV_MINOR_VERSION >=4))
+#if (CV_MAJOR_VERSION > 3 || (CV_MAJOR_VERSION == 3 && CV_MINOR_VERSION >= 3))
+cv::imdecode(buf, flag | cv::IMREAD_IGNORE_ORIENTATION, &dst);
+CHECK(!dst.empty()) << "Decoding failed. Invalid image file.";
+#elif(CV_MAJOR_VERSION > 2 || (CV_MAJOR_VERSION == 2 && CV_MINOR_VERSION >= 4))
 cv::imdecode(buf, flag, &dst);
 CHECK(!dst.empty()) << "Decoding failed. Invalid image file.";
 #else


 


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[incubator-mxnet] branch master updated: [ImageIO] Fix image io for opencv3.3 (#8757)

[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 1f6d586  [ImageIO] Fix image io for opencv3.3 (#8757)
1f6d586 is described below

commit 1f6d586c1c6aab40947724050039e00afed1fb4f
Author: Xingjian Shi 
AuthorDate: Wed Nov 22 12:50:02 2017 -0800

[ImageIO] Fix image io for opencv3.3 (#8757)

* fix image io for opencv3.3

* update function in cv_api

* fix bug

* fix lint
---
 plugin/opencv/cv_api.cc | 4 
 src/io/image_io.cc  | 5 -
 2 files changed, 8 insertions(+), 1 deletion(-)

diff --git a/plugin/opencv/cv_api.cc b/plugin/opencv/cv_api.cc
index 1508de3..1ca14aa 100644
--- a/plugin/opencv/cv_api.cc
+++ b/plugin/opencv/cv_api.cc
@@ -100,7 +100,11 @@ MXNET_DLL int MXCVImdecode(const unsigned char *img, const 
mx_uint len,
   ndout.CheckAndAlloc();
   cv::Mat buf(1, len, CV_8U, img_cpy);
   cv::Mat dst(dims[0], dims[1], flag == 0 ? CV_8U : CV_8UC3, 
ndout.data().dptr_);
+#if (CV_MAJOR_VERSION > 3 || (CV_MAJOR_VERSION == 3 && CV_MINOR_VERSION >= 3))
+  cv::imdecode(buf, flag | cv::IMREAD_IGNORE_ORIENTATION, &dst);
+#else
   cv::imdecode(buf, flag, &dst);
+#endif
   CHECK(!dst.empty());
   delete[] img_cpy;
 }, ndout.ctx(), {}, {ndout.var()});
diff --git a/src/io/image_io.cc b/src/io/image_io.cc
index d95e750..491370d 100644
--- a/src/io/image_io.cc
+++ b/src/io/image_io.cc
@@ -156,7 +156,10 @@ void ImdecodeImpl(int flag, bool to_rgb, void* data, 
size_t size,
   } else {
 dst = cv::Mat(out->shape()[0], out->shape()[1], flag == 0 ? CV_8U : 
CV_8UC3,
 out->data().dptr_);
-#if (CV_MAJOR_VERSION > 2 || (CV_MAJOR_VERSION == 2 && CV_MINOR_VERSION >=4))
+#if (CV_MAJOR_VERSION > 3 || (CV_MAJOR_VERSION == 3 && CV_MINOR_VERSION >= 3))
+cv::imdecode(buf, flag | cv::IMREAD_IGNORE_ORIENTATION, &dst);
+CHECK(!dst.empty()) << "Decoding failed. Invalid image file.";
+#elif(CV_MAJOR_VERSION > 2 || (CV_MAJOR_VERSION == 2 && CV_MINOR_VERSION >= 4))
 cv::imdecode(buf, flag, &dst);
 CHECK(!dst.empty()) << "Decoding failed. Invalid image file.";
 #else

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[GitHub] piiswrong commented on a change in pull request #8719: Tune without Launch specialization macros

[GitBox]

piiswrong commented on a change in pull request #8719: Tune without Launch 
specialization macros
URL: https://github.com/apache/incubator-mxnet/pull/8719#discussion_r152676543
 
 

 ##
 File path: src/operator/mxnet_op.h
 ##
 @@ -441,8 +447,80 @@ struct Kernel {
 OP::Map(0, N, args...);
 #endif
   }
+
+  /*!
+   * \brief Launch a tunable OP with explicitly-supplied data type
+   * \tparam DType Data type
+   * \tparam OP type
+   * \tparam Args Varargs type to eventually pass to the OP::Map() functoion
+   * \param s Stream (usually null for CPU)
+   * \param N Number of iterations
+   * \param args Varargs to eventually pass to the OP::Map() functoion
+   * \return Always true
+   */
+  template
+  static MSHADOW_CINLINE
+  typename std::enable_if::value, bool>::type
+  LaunchWithType(mshadow::Stream *s, const int N, Args... args) {
+LaunchTuned(s, N, args...);
+return true;
+  }
+
+  /*!
+   * \brief Launch a tunable OP with implicitly-supplied data type
+   * \tparam DType Data type
+   * \tparam T OP type
+   * \tparam Args Varargs type to eventually pass to the OP::Map() functoion
+   * \param s Stream (usually null for CPU)
+   * \param N Number of iterations
+   * \param args Varargs to eventually pass to the OP::Map() functoion
+   * \return Always true
+   */
+  template
+  static MSHADOW_CINLINE
+  typename std::enable_if::value, bool>::type
+  Launch(mshadow::Stream *s, const int N, DType *dest, Args... args) {
+return LaunchWithType(s, N, dest, args...);
 
 Review comment:
   Adding more interface means there will be more backward compatibility issues 
in the future. 
   Let's hold off.


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[GitHub] piiswrong commented on a change in pull request #8719: Tune without Launch specialization macros

[GitBox]

piiswrong commented on a change in pull request #8719: Tune without Launch 
specialization macros
URL: https://github.com/apache/incubator-mxnet/pull/8719#discussion_r152676710
 
 

 ##
 File path: src/operator/mxnet_op.h
 ##
 @@ -441,8 +447,82 @@ struct Kernel {
 OP::Map(0, N, args...);
 #endif
   }
+
+  /*!
+   * \brief Launch a tunable OP with explicitly-supplied data type
+   * \tparam DType Data type
+   * \tparam OP type
+   * \tparam Args Varargs type to eventually pass to the OP::Map() functoion
+   * \param s Stream (usually null for CPU)
+   * \param N Number of iterations
+   * \param args Varargs to eventually pass to the OP::Map() functoion
+   * \return Always true
+   */
+  template
+  static MSHADOW_CINLINE
+  typename std::enable_if::value, bool>::type
+  LaunchWithType(mshadow::Stream *s, const int N, Args... args) {
 
 Review comment:
   Is LaunchWithType used anywhere? Can we remove it for now if its not 
necessary?


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[GitHub] piiswrong commented on a change in pull request #8719: Tune without Launch specialization macros

[GitBox]

piiswrong commented on a change in pull request #8719: Tune without Launch 
specialization macros
URL: https://github.com/apache/incubator-mxnet/pull/8719#discussion_r152677355
 
 

 ##
 File path: src/operator/operator_tune.cc
 ##
 @@ -125,16 +125,16 @@ struct static_init_var {
  * \brief Implement tuning objects for a backward unary kernel operator
  */
 #define _IMPLEMENT_UNARY_WORKLOAD_BWD(__op$, __typ$) \
-  IMPLEMENT_WORKLOAD_VALUE_FOR_TYPE(mxnet::op::mxnet_op::backward_grad<__op$>, 
__typ$); \
+  
IMPLEMENT_WORKLOAD_VALUE_FOR_TYPE(mxnet::op::mxnet_op::backward_grad_tuned<__op$>,
 __typ$); \
   namespace mxnet_op { \
 
 Review comment:
   don't put namespace in macro.


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[GitHub] piiswrong commented on a change in pull request #8719: Tune without Launch specialization macros

[GitBox]

piiswrong commented on a change in pull request #8719: Tune without Launch 
specialization macros
URL: https://github.com/apache/incubator-mxnet/pull/8719#discussion_r152677397
 
 

 ##
 File path: src/operator/operator_tune.cc
 ##
 @@ -125,16 +125,16 @@ struct static_init_var {
  * \brief Implement tuning objects for a backward unary kernel operator
  */
 #define _IMPLEMENT_UNARY_WORKLOAD_BWD(__op$, __typ$) \
-  IMPLEMENT_WORKLOAD_VALUE_FOR_TYPE(mxnet::op::mxnet_op::backward_grad<__op$>, 
__typ$); \
+  
IMPLEMENT_WORKLOAD_VALUE_FOR_TYPE(mxnet::op::mxnet_op::backward_grad_tuned<__op$>,
 __typ$); \
   namespace mxnet_op { \
   template<> \
-  bool 
mxnet::op::mxnet_op::tuned_op, 
__typ$>::UseOMP( \
-size_t N, size_t omp_threads) { \
+  bool 
mxnet::op::mxnet_op::tuned_op, 
__typ$>:: \
 
 Review comment:
   use :: at the begining


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[GitHub] piiswrong commented on a change in pull request #8719: Tune without Launch specialization macros

[GitBox]

piiswrong commented on a change in pull request #8719: Tune without Launch 
specialization macros
URL: https://github.com/apache/incubator-mxnet/pull/8719#discussion_r152677489
 
 

 ##
 File path: src/operator/operator_tune.cc
 ##
 @@ -125,16 +125,16 @@ struct static_init_var {
  * \brief Implement tuning objects for a backward unary kernel operator
  */
 #define _IMPLEMENT_UNARY_WORKLOAD_BWD(__op$, __typ$) \
 
 Review comment:
   can we simplify these macros a little? maybe by wrapping all static 
variables in a struct?


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[GitHub] piiswrong commented on a change in pull request #8719: Tune without Launch specialization macros

[GitBox]

piiswrong commented on a change in pull request #8719: Tune without Launch 
specialization macros
URL: https://github.com/apache/incubator-mxnet/pull/8719#discussion_r152677681
 
 

 ##
 File path: src/operator/tensor/init_op.h
 ##
 @@ -263,16 +263,15 @@ void InitFillWithScalarCompute(const nnvm::NodeAttrs 
&attrs,
   CHECK_EQ(inputs.size(), 0);
   CHECK_EQ(outputs.size(), 1U);
   const auto& param = nnvm::get(attrs.parsed);
-  Fill(ctx.get_stream(), outputs[0], req[0], param.value);
+  Fill(ctx.get_stream(), outputs[0], req[0], param.value);
 
 Review comment:
   ?


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[GitHub] piiswrong commented on issue #8763: [WIP] Add text apis

[GitBox]

piiswrong commented on issue #8763: [WIP] Add text apis
URL: https://github.com/apache/incubator-mxnet/pull/8763#issuecomment-346471744
 
 
   These looks too adhoc to be put in to the repo.
   
   I'm considering making a text preprocessing package similar to part of NLTK 
and pytorch's text package.


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[GitHub] cjolivier01 commented on a change in pull request #8719: Tune without Launch specialization macros

[GitBox]

cjolivier01 commented on a change in pull request #8719: Tune without Launch 
specialization macros
URL: https://github.com/apache/incubator-mxnet/pull/8719#discussion_r152678045
 
 

 ##
 File path: src/operator/mxnet_op.h
 ##
 @@ -441,8 +447,82 @@ struct Kernel {
 OP::Map(0, N, args...);
 #endif
   }
+
+  /*!
+   * \brief Launch a tunable OP with explicitly-supplied data type
+   * \tparam DType Data type
+   * \tparam OP type
+   * \tparam Args Varargs type to eventually pass to the OP::Map() functoion
+   * \param s Stream (usually null for CPU)
+   * \param N Number of iterations
+   * \param args Varargs to eventually pass to the OP::Map() functoion
+   * \return Always true
+   */
+  template
+  static MSHADOW_CINLINE
+  typename std::enable_if::value, bool>::type
+  LaunchWithType(mshadow::Stream *s, const int N, Args... args) {
 
 Review comment:
   We can remove


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[GitHub] cjolivier01 commented on a change in pull request #8719: Tune without Launch specialization macros

[GitBox]

cjolivier01 commented on a change in pull request #8719: Tune without Launch 
specialization macros
URL: https://github.com/apache/incubator-mxnet/pull/8719#discussion_r152678380
 
 

 ##
 File path: src/operator/tensor/init_op.h
 ##
 @@ -263,16 +263,15 @@ void InitFillWithScalarCompute(const nnvm::NodeAttrs 
&attrs,
   CHECK_EQ(inputs.size(), 0);
   CHECK_EQ(outputs.size(), 1U);
   const auto& param = nnvm::get(attrs.parsed);
-  Fill(ctx.get_stream(), outputs[0], req[0], param.value);
+  Fill(ctx.get_stream(), outputs[0], req[0], param.value);
 
 Review comment:
   Minor trivial change that doesn;t actually cause problems now, but it should 
be false for consistency.


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[GitHub] cjolivier01 commented on a change in pull request #8719: Tune without Launch specialization macros

[GitBox]

cjolivier01 commented on a change in pull request #8719: Tune without Launch 
specialization macros
URL: https://github.com/apache/incubator-mxnet/pull/8719#discussion_r152678586
 
 

 ##
 File path: src/operator/operator_tune.cc
 ##
 @@ -125,16 +125,16 @@ struct static_init_var {
  * \brief Implement tuning objects for a backward unary kernel operator
  */
 #define _IMPLEMENT_UNARY_WORKLOAD_BWD(__op$, __typ$) \
-  IMPLEMENT_WORKLOAD_VALUE_FOR_TYPE(mxnet::op::mxnet_op::backward_grad<__op$>, 
__typ$); \
+  
IMPLEMENT_WORKLOAD_VALUE_FOR_TYPE(mxnet::op::mxnet_op::backward_grad_tuned<__op$>,
 __typ$); \
   namespace mxnet_op { \
   template<> \
-  bool 
mxnet::op::mxnet_op::tuned_op, 
__typ$>::UseOMP( \
-size_t N, size_t omp_threads) { \
+  bool 
mxnet::op::mxnet_op::tuned_op, 
__typ$>:: \
 
 Review comment:
   ok


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[GitHub] szha commented on issue #8763: [WIP] Add text apis

[GitBox]

szha commented on issue #8763: [WIP] Add text apis
URL: https://github.com/apache/incubator-mxnet/pull/8763#issuecomment-346472665
 
 
   Aston is already doing it.


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[GitHub] cjolivier01 commented on a change in pull request #8719: Tune without Launch specialization macros

[GitBox]

cjolivier01 commented on a change in pull request #8719: Tune without Launch 
specialization macros
URL: https://github.com/apache/incubator-mxnet/pull/8719#discussion_r152678684
 
 

 ##
 File path: src/operator/operator_tune.cc
 ##
 @@ -125,16 +125,16 @@ struct static_init_var {
  * \brief Implement tuning objects for a backward unary kernel operator
  */
 #define _IMPLEMENT_UNARY_WORKLOAD_BWD(__op$, __typ$) \
-  IMPLEMENT_WORKLOAD_VALUE_FOR_TYPE(mxnet::op::mxnet_op::backward_grad<__op$>, 
__typ$); \
+  
IMPLEMENT_WORKLOAD_VALUE_FOR_TYPE(mxnet::op::mxnet_op::backward_grad_tuned<__op$>,
 __typ$); \
   namespace mxnet_op { \
 
 Review comment:
   why? this would make the macro sensitive to what namespace it is declared in.


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[GitHub] cjolivier01 commented on a change in pull request #8719: Tune without Launch specialization macros

[GitBox]

cjolivier01 commented on a change in pull request #8719: Tune without Launch 
specialization macros
URL: https://github.com/apache/incubator-mxnet/pull/8719#discussion_r152678794
 
 

 ##
 File path: src/operator/operator_tune.cc
 ##
 @@ -125,16 +125,16 @@ struct static_init_var {
  * \brief Implement tuning objects for a backward unary kernel operator
  */
 #define _IMPLEMENT_UNARY_WORKLOAD_BWD(__op$, __typ$) \
 
 Review comment:
   Not sure I follow you. 


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[GitHub] cjolivier01 commented on a change in pull request #8719: Tune without Launch specialization macros

[GitBox]

cjolivier01 commented on a change in pull request #8719: Tune without Launch 
specialization macros
URL: https://github.com/apache/incubator-mxnet/pull/8719#discussion_r152679000
 
 

 ##
 File path: src/operator/mxnet_op.h
 ##
 @@ -441,8 +447,80 @@ struct Kernel {
 OP::Map(0, N, args...);
 #endif
   }
+
+  /*!
+   * \brief Launch a tunable OP with explicitly-supplied data type
+   * \tparam DType Data type
+   * \tparam OP type
+   * \tparam Args Varargs type to eventually pass to the OP::Map() functoion
+   * \param s Stream (usually null for CPU)
+   * \param N Number of iterations
+   * \param args Varargs to eventually pass to the OP::Map() functoion
+   * \return Always true
+   */
+  template
+  static MSHADOW_CINLINE
+  typename std::enable_if::value, bool>::type
+  LaunchWithType(mshadow::Stream *s, const int N, Args... args) {
+LaunchTuned(s, N, args...);
+return true;
+  }
+
+  /*!
+   * \brief Launch a tunable OP with implicitly-supplied data type
+   * \tparam DType Data type
+   * \tparam T OP type
+   * \tparam Args Varargs type to eventually pass to the OP::Map() functoion
+   * \param s Stream (usually null for CPU)
+   * \param N Number of iterations
+   * \param args Varargs to eventually pass to the OP::Map() functoion
+   * \return Always true
+   */
+  template
+  static MSHADOW_CINLINE
+  typename std::enable_if::value, bool>::type
+  Launch(mshadow::Stream *s, const int N, DType *dest, Args... args) {
+return LaunchWithType(s, N, dest, args...);
 
 Review comment:
   ok


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[GitHub] cjolivier01 commented on a change in pull request #8719: Tune without Launch specialization macros

[GitBox]

cjolivier01 commented on a change in pull request #8719: Tune without Launch 
specialization macros
URL: https://github.com/apache/incubator-mxnet/pull/8719#discussion_r152680177
 
 

 ##
 File path: src/operator/operator_tune.cc
 ##
 @@ -125,16 +125,16 @@ struct static_init_var {
  * \brief Implement tuning objects for a backward unary kernel operator
  */
 #define _IMPLEMENT_UNARY_WORKLOAD_BWD(__op$, __typ$) \
-  IMPLEMENT_WORKLOAD_VALUE_FOR_TYPE(mxnet::op::mxnet_op::backward_grad<__op$>, 
__typ$); \
+  
IMPLEMENT_WORKLOAD_VALUE_FOR_TYPE(mxnet::op::mxnet_op::backward_grad_tuned<__op$>,
 __typ$); \
   namespace mxnet_op { \
 
 Review comment:
   Ok, I see what you're saying. The namespaces aren't all the same.


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[incubator-mxnet] branch v1.0.0 updated: Fix doc link (#8776)

[cjolivier01]

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

cjolivier01 pushed a commit to branch v1.0.0
in repository https://gitbox.apache.org/repos/asf/incubator-mxnet.git


The following commit(s) were added to refs/heads/v1.0.0 by this push:
 new ede7d11  Fix doc link (#8776)
ede7d11 is described below

commit ede7d11d33371bed1ad815835aa18cf87b503a49
Author: Madan Jampani 
AuthorDate: Wed Nov 22 10:38:18 2017 -0800

Fix doc link (#8776)
---
 docs/faq/index.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/docs/faq/index.md b/docs/faq/index.md
index e29bda0..883d8e6 100644
--- a/docs/faq/index.md
+++ b/docs/faq/index.md
@@ -41,7 +41,7 @@ and full working examples, visit the [tutorials 
section](../tutorials/index.md).
 * [How to convert MXNet models to Apple CoreML 
format?](https://github.com/apache/incubator-mxnet/tree/master/tools/coreml)
 
 ## Security
-* [How to run MXNet securely?](http://mxnet.io/how_to/security.md)
+* [How to run MXNet securely?](http://mxnet.io/how_to/security.html)
 
 ## Extend and Contribute to MXNet
 

-- 
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['"comm...@mxnet.apache.org" '].

[GitHub] cjolivier01 commented on a change in pull request #8719: Tune without Launch specialization macros

[GitBox]

cjolivier01 commented on a change in pull request #8719: Tune without Launch 
specialization macros
URL: https://github.com/apache/incubator-mxnet/pull/8719#discussion_r152681207
 
 

 ##
 File path: src/operator/mxnet_op.h
 ##
 @@ -441,8 +447,82 @@ struct Kernel {
 OP::Map(0, N, args...);
 #endif
   }
+
+  /*!
+   * \brief Launch a tunable OP with explicitly-supplied data type
+   * \tparam DType Data type
+   * \tparam OP type
+   * \tparam Args Varargs type to eventually pass to the OP::Map() functoion
+   * \param s Stream (usually null for CPU)
+   * \param N Number of iterations
+   * \param args Varargs to eventually pass to the OP::Map() functoion
+   * \return Always true
+   */
+  template
+  static MSHADOW_CINLINE
+  typename std::enable_if::value, bool>::type
+  LaunchWithType(mshadow::Stream *s, const int N, Args... args) {
 
 Review comment:
   done


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[GitHub] mbaijal commented on issue #8766: NDArray Indexing tutorial and Gradient Compression FAQ

[GitBox]

mbaijal commented on issue #8766: NDArray Indexing tutorial and Gradient 
Compression FAQ
URL: https://github.com/apache/incubator-mxnet/pull/8766#issuecomment-346479680
 
 
   @reminisce Can you please review these changes?
   


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[GitHub] mbaijal commented on issue #8766: NDArray Indexing tutorial and Gradient Compression FAQ

[GitBox]

mbaijal commented on issue #8766: NDArray Indexing tutorial and Gradient 
Compression FAQ
URL: https://github.com/apache/incubator-mxnet/pull/8766#issuecomment-346479680
 
 
   @reminisce Can you please review these changes?
   


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[GitHub] cjolivier01 commented on a change in pull request #8719: Tune without Launch specialization macros

[GitBox]

cjolivier01 commented on a change in pull request #8719: Tune without Launch 
specialization macros
URL: https://github.com/apache/incubator-mxnet/pull/8719#discussion_r152684521
 
 

 ##
 File path: src/operator/operator_tune.cc
 ##
 @@ -125,16 +125,16 @@ struct static_init_var {
  * \brief Implement tuning objects for a backward unary kernel operator
  */
 #define _IMPLEMENT_UNARY_WORKLOAD_BWD(__op$, __typ$) \
 
 Review comment:
   There's two static variables that are used externally, tuned_op<>::workload_ 
(size_t) and tuned_op<>::workload_ex (vector). Those reside in the same struct 
(tuned_op).  
   
   The other static var is a trivial target for a startup init call and has no 
use outside of the scope of this file, so it is not included in the tuned_op<> 
struct.  The call for this variable varies depending on the type of operator 
(unary, binar, etc).
   
   Other definitions are UseOMP() implementations which vary based upon the 
type of operator (unary, binary, custom, etc).   For more custom ops, they 
would be created by hand (like broadcast was).


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[GitHub] eric-haibin-lin closed pull request #8401: Make make lint compatible with python3 (don't call python2 explicitly)

[GitBox]

eric-haibin-lin closed pull request #8401: Make make lint compatible with 
python3 (don't call python2 explicitly)
URL: https://github.com/apache/incubator-mxnet/pull/8401
 
 
   

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/Makefile b/Makefile
index 5d5dcdfc79..ceed645043 100644
--- a/Makefile
+++ b/Makefile
@@ -435,7 +435,7 @@ test: $(TEST)
 lint: cpplint rcpplint jnilint pylint
 
 cpplint:
-   python2 dmlc-core/scripts/lint.py mxnet cpp include src plugin 
cpp-package tests \
+   dmlc-core/scripts/lint.py mxnet cpp include src plugin cpp-package 
tests \
--exclude_path src/operator/contrib/ctc_include
 
 pylint:
@@ -467,7 +467,7 @@ cyclean:
 
 # R related shortcuts
 rcpplint:
-   python2 dmlc-core/scripts/lint.py mxnet-rcpp ${LINT_LANG} R-package/src
+   dmlc-core/scripts/lint.py mxnet-rcpp ${LINT_LANG} R-package/src
 
 rpkg:
mkdir -p R-package/inst
@@ -525,7 +525,7 @@ scaladeploy:
-Dlddeps="$(LIB_DEP) $(ROOTDIR)/lib/libmxnet.a")
 
 jnilint:
-   python2 dmlc-core/scripts/lint.py mxnet-jnicpp cpp 
scala-package/native/src
+   dmlc-core/scripts/lint.py mxnet-jnicpp cpp scala-package/native/src
 
 ifneq ($(EXTRA_OPERATORS),)
 clean: cyclean $(EXTRA_PACKAGES_CLEAN)


 


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