* opencv2-->opencv; deleted duplicate content

* update troubleshooting info

* Fix exception handling bug

* Trigger CI

* Add test for exc handling

* Trigger CI

* Resolve conflicts

* fix bug in prelu

* add unit test

* add mentions of the gluon toolkits and links to resources

* fix nlp and cv text

* upgrade onnx

* import helpers

* upgrade version in ci

* addressing comments

* fix

* test name changed

* retrigger tests

* adding comments

* char RNN tutorial

* nit fixes

…che#12668)

* document env.

* update.

* update.

* retrigger

…12674)

* update mshadow

* bump

…e script (apache#12556)

* Initial Commit for docker automation python

* Fixes

* change dir for tests

* Fix more issues

* fix docker tag command

* cosmetic changes

* update README

* update test to fail on version mismatch

* remove debug mode

* Update README.md

* Update README.md

* update README

* Add Licenses

* Some review comments

* Add Cuda80 and cuda92 dockerfiles and build steps

* Add renamed and hence untracked files for cu90

* Update README

* More ways to login

* Update README with login options

* Update README with links to test. test_mxnet link will work only after merge

* Rebase to align the latest changes on test_gluon.py

* Referring the issue link to skip message

* Retrigger the PRECI

* Remove previous changes

* Modify the cases trying to eliminate the errors on GPU

* Resolving conflict

* Further reduce the tensor size

* minor changes

* move to mkl

* fix flaky case

* Remove the test_mkldnn_gluon.py

* Move the cases back to test_gluon.py

* Update contribute.md

Fixed grammar

* Update contribute.md

Fixed Grammar

* added R LSTM examples

* added tutorial to whitelist

* fix encoding

* added seed and fixed few formatting issues

* addressed PR comments

* formatting fixes'

* nit fixes

* fix epochs

* fixed tutorial link

git-subtree-dir: julia
git-subtree-mainline: c595f2d
git-subtree-split: 224ae96

- enable Jenkins CI build for Julia
- add license headers to Julia source code
- update links for Julia README

* [MXNET-860] Use emplace where helpful

* [MXNET-860] Add emplace as an error in clang-tidy

* [MXNET-860] Remove std::moves that have no affect

* [MXNET-860] Check for unneeded moves as errors

…pache#12678)

* Fix apache#12672

Problem is in using np.ascontiguousarray,
which is buggy for zero-dimensional arrays
 (see numpy/numpy#5300 for details).

Here I use the solution proposed by numpy team:
switch to asarray with order='C'.

Add some tests for this situation (for array() and for setitem too).

* typo in tests

This PR removes some redundant build tasks and removes some slow tests
to try and decrease the number of TravisCI timeouts that would otherwise
occur on large PRs.

* Throw exception if MXSymbolInferShape fails.

* scala-package/native/src/main/native/org_apache_mxnet_native_c_api.cc:
  (Java_org_apache_mxnet_LibInfo_mxSymbolInferShape): throw
  IllegalArgumentException with the content of MXGetError if call to
  MXSymbolInferShape fails.

* Remove stray space.

* Don't throw in JNI.

checkCall in scala code will do the right thing with a nonzero exit
status.

* Don't repeat the memory free code.

Just wrap the FillSymbolInferShape calls in `if (ret == 0) { ... }`.

* Fix too-long line.

* Adding Scala Inference Benchmark base class + an example of how to run it

* Fixed scalastyle issues

* Added platform check to the classpath

* Formatting the metrics to print upto 2 decimal digits in float

* Added bash script to fetch resnet-18 data and params

* Added flag for cpu/gpu for running the script

* Fixed duplicate if check

…1742)

* Fix integer overflow when the array size is too large

* Update issue templates

* Update issue templates

* Remove files added by mistake

* Fix compilation error after type index_t changed to int64_t

* Explicity specify type in std::max template to avoid platform dependent compilation error

* Add nightly test for large array

* Update submodule mshadow

* Fix compilation warning

* Fix compilation warning

* Change index variable type to size_t

* Fix integer overflow when the array size is too large

* Update issue templates

* Remove files added by mistake

* Fix compilation error after type index_t changed to int64_t

* Explicity specify type in std::max template to avoid platform dependent compilation error

* Add nightly test for large array

* [MXNET-531] NeuralStyle Example for Scala (apache#11621)

* add initial neuralstyle and test coverage

* Add two more test and README

* kill comments

* patch on memory leaks fix

* fix formatting issues

* remove redundant files

* disable the Gan example for now

* add ignore method

* add new download scheme to match the changes

* Update submodule mshadow

* Fix compilation warning

* Fix compilation warning

* Change index variable type to size_t

* Change temp_size type from size_t to index_t

* Fix lint error

* Fix compilation error in GPU

* Fix compilation error on GPU

* Fix compilation error in cpp-package

* Fix unit test in GPU

* Change correct type for nnvmGraph

* update mshadow submodule to local repo to verify

* update mshadow submodule

* change some data type to size_t

* change unit test style

* fix lint

* fix compilation error in Windows

* fix compilation error in Windows

* use forked submodule to verify

* temporarily update submodule to verify the fix

* update mshadow submodule to use remote

* add test to nightly test script

…nts (apache#12711)

Default numpy version in The Python Package Index (PyPI) is 1.15.2

* reenable the test

* Trigger CI

* update the installation document

* fix minor text

* update the rename process

* fix wording

* remind users. of env and vs version

* leave only the required dll

* fix the link

* update the R anchor

* refine the description of step 7

* add missing .

* fix spelling

* update links and fix wording

* [apache#12345] Enabling two tests in the Straight Dope Nightly.

Two straight dope notebook tests were disabled due to a timeout so they
were disabled. I've updated one of the notebooks (rnn-gluon) to use the
gpu instead of the cpu so it takes ~ 5 minutes on a p3.2xl, and verified
the other notebook takes a minute and was a false alarm (visual-qa). The
PR in the Straight Dope is:
zackchase/mxnet-the-straight-dope#540

* Add dependency for IPython update.

* Detect errors in notebook execution failure.

* Clean up of naming in retry code.

Fixes apache#10977

…ensorcore for fp32 (apache#12722)

…12739)

* * Added randn function
* Internal SELU function on C++ layer
* Predict now accepts ndarray as well
* Gluon: Only warn when the blocks are unregistered.
* Better sparse support for gluon
* Gpu memory info via mxnet api call.
* Gluon: Improved block summary.
* Added validation docs for MXNet installation for Perl.
* Flexible perl env for examples.
* Gluon: Custom dtypes for the symbol block
* Separate eval metric for the epoch level.

* fixed typo.

…apache#12636)

* Adding the example to demonstrate the usage of CSVIter

* Addressed the review comments to make the example configurable. Moved the unittests folder in 'examples' directory.

* Updated the code to address the cpp lint errors.

* Removed the author tag.

* Fixing the lint errors and usage message.

* Update README file for cpp-package and provide README file for example directory.

* Revert "Update README file for cpp-package and provide README file for example directory."

This reverts commit 02e784a.

These files were part of fix for JIRA issue 1017. These files were mistakenly committed in this PR.

* Addressed the review comments regarding usage of atoi and avoiding string copy.

* Updated to use strtol instead of atoi

* Implement ctc_loss as a normal operator

* Update unit test

* Update unit test and fix bug in backward

* fix lint error

* refactoring

* Fix compilation error in CUDA

* Fix CPU compilation error

* Move ctc_include to nn folder and refactor

* temporarily disable lint on 3rd party includes

* move ctc_include to 3rdparty

* remove contrib ctc_loss operator

* revert a change by mistake

* Fix a bug in kDevCPU

* revert change by mistake

* add alias to make it backward compatible

* add unit test for backward compatibility

* linting

* add resnet50-v1 to benchmark_score

* rename back and duplicated

* rename v2 back to resnet.py

…he#12758)

* reflect the PR

* add 1 more metric

* Implement mkldnn convolution fusion.
Implement mkldnn convolution quantization.

* Fix lint

* Fix performance regression caused by mkldnn fallback.

* clean up include

* Fix msbuild on openmp pragma.

* Fix quantization test, allow to use original op names as exclude layer for quantization.

* Fix unittest.

* Fix unittest

* fix lint

* Add post quantize fusion

* add test case

* add head license in test case

* Remove GetBoolHash()

* Remove mkldnn fallback change.

* Address Haibin's comments.

* Add TIsMKLDNN for _sg_mkldnn_conv temporarily.

* Address reminisce's comments.

* Handle the case that inplace fail.

* pass unit test.

* Add symbol api get_backend_symbol()

* Retrigger ci

* update the test case

* Check subgraph index.

* Use index as FAvoidQuantizeInput's parameter.

* Add mkldnn_hwigo support as quantizaiton needs.

* Address KellenSunderland's comments.

* Handle input order change after subgraph pass.

* Fix ci test

* Core Java API class commit

* Update ScalaStyle max line length to 132 instead of 100

* add mkl-dnn to docker install method

* add mkl for gpu

* add docker for windows

* add flag to elementwise_add

* fix flatteng

* retrigger

…to committers section (apache#12766)

* Add fix_beta support in BatchNorm CPU implementation

* Fix lint checks. Update GPU tests

* Fix gpu tests

* make fix_beta not available for sparse. Update fix_beta for mkldnn

* Make default fix_beta to False for backward compatibility

* Add fix_beta to cudnn batchnorm operator

* Add tests for missing fix_beta and fix_gamma params

* fix indentation

* Fix failing tests

* simplify the cases with defaults for gamma, beta

…#12639)

* [MXNET-947] Scala imclassification example with Resnet

…apache#12789)

This reverts commit 0bab6d5.
Because master branch started to fail with this change.

* Updated tvm submodule head

* Remove FInplaceIdentity attr for cast and _backward_cast

* Proximal Group Adagrad optimizer

* Remove proximal implementation and rename to GroupAdagrad

* Remove superfluous doc

* Remove superfluous argument

* mismatch shape switch

* closing bracket

* closing bracket

* use rename trick to achieve atomic write but didn't support python2 and windows

* add test for multiprocess download

* implement atomic_replace referred by https://github.com/untitaker/python-atomicwrites

* change the number of testing process to 10

* add docstring and disable linter

* half way to address some issue reviewer have

* use warning instead of raise UserWarn

* check for sha1

* Trigger CI

* fix the logic of checking hash

* refine the error message

* add more comments and expose the error message to the user

* delete trailing whitespace

* rename _path_to_encode to _str_to_unicode

* fix the error message bug and add remove when the movefile fail on windows

* add remove temp file for non-windows os

* handle the OSError caused by os.remove

* Trigger CI

* use finally to raise failure of atomic replace

* add missing try except block for os.remove

* add retries value to error message

* PoissonNLLLoss function to compute negative log likelihood loss

* Removing debugging print statements

* Pylint code formatting problems addressed

* Added Stirling approximation for factorial term in the denominator and test case for the same

* Separated the test cases for Flag value for logits and compute_full

* Added comments for package- numpy inclusion and some pylint formatting

* Trigger CI

* Markdown file updted. Added entry for Poissons NLLLoss

* Fixing pending documentation issue

* Documentation docstring changed

* PR Comment to remove extra newline removed.

* Symbol PI corrected

* epsilon spellicng correction

* More unit tests added - testing with mod.score() and mod.fit()

* changed the number of epochs

* PR Comments addressed added mod score tests and a newline

* Empty line added

* Adding hybridized test

* Trigger CI

* Variable names changed

Added "apple" to USE_BLAS comment because it is one of the versions that are possible. 
Currently the comment only has "mkl, blas, atlas, openblas" that can be used

…o navigation (apache#12704)

* refactor and sync nav bar between desktop and mobile

* update dev wiki url

* bump file for CI

* remove htaccess change from this pr

* removing keras for now

* bumping for CI

* fixed symbols naming in RNNCell and LSTMCell

* fixed GRUCell as well

* added test

* fixed tests?

* remove guard that prevent omp flag in mac

* udpate doc for mac make build

* update docs

* update readme

* set opencv to 1 in instructions

* remove disable opencv line

* update mac docs

* fix indent

* 1. move the shuffle to the reset 2. modify the roll_over behavior accordingly

* refactor the concat part

* refactor the code

* implement unit test for last_batch_handle

* refactor the getdata part

* add docstring and refine the code according to linter

* 1. add test case for NDArrayIter_h5py 2. refactor the implementation

* update contributions doc

* fix wording

* update doc for roll_over

* 1. add test for second iteration of roll_over 2. add shuffle test case

* fix some wording and refine the variables naming

* move utility function to new file

* move utility function to io_utils.py

* change shuffle function name to avoid redefining name

* make io as a module

* rename the utility functions

* disable wildcard-import

* fix the algorithm

* refactor the code

* test the NDArrayIter with different combinations of shuffle=True, data_source type and lables

* add edge case of label data for csr NDArrayIter

* trigger Travis CI

* handle the 'list' of data source

* check the list of data source

* fix the extra blank

* Trigger CI

* add _ to the utility functions

* Trigger CI

* update several test cases

* add test case for airbnb

* fix the typo

* fix wrong labels data shape

* switch the order of condition to make more sense

* Add unittest to coreml converter

* Add unittest to coreml converter

* Add docstring and remove unused method

* updated test and removed unittest folder

* remove unittest

* Add coreml test to CI

* fix lint

* install mxnet-to-coreml for testing

* exclude test that takes too long

* linting to 100 max line width

…pache#12731)

* ONNX export/import: DepthToSpace operator

* ONNX import/export: SpaceToDepth operator

* ONNX import/export: Tests for SpaceToDepth

* add prereqs for R installation on Mac

* pin openblas for mac R install to 0.3.1

* fixed indentation

* simplified code

…ache#12826)

This PR makes sure perf information printed during TensorRT test runs
is correctly displayed when run in CI.

* update op creation docs

* add flakiness checker and link to gradient checking

* address comments

* update reference line number

* fix comments

* fix flaky topk

* try to fix

* remove the usage of IndexFill

* fix

* add docstring

* add psroipooling cpu impl

* minor fix

* revert copyright

* fix testcase

* add openmp

* no openmp for backward

…ache#12646)

* ONNX export: Fully connected operator with no bias

* ONNX export: Helper function to convert bool string attributes to int

* ONNX export: ReduceSum operator

* ONNX import/export: Make pow backward compatible

* ONNX export: Square operator

* Undefined name: load_model() --> utils.load_model()

As discussed at:
* apache@815f36c#r30956015

* Force a rebuild

* Force a rebuild

* remove check

* fix lint

* fix gpu build

* add tutorial.

* update.

* update.

* update.

* add test.

* fix subgraph test.

* update.

* update.

* update.

* add comments.

* remove test.

* update image path.

* update.

* update.

* update.

* fix lint.

* add link.

* fix lint.

* add gluoncv support

* add ssd readme

* improve ssd readme

* add custom readme

* add ssd model link

* add squeezenet

* add ssd quantization script

* fix topo of args

* improve custom readme

* fix topo bug

* fix squeezenet

* add squeezenet accuracy

* Add initializer for min max to support quantization

* add dummy data inference

* add test case for init_param

* add subgraph docs

* improve docs

* add two models and fix default rgb_std to 1

* fix doc link

* improve MKLDNN_README

* add quantization for mobilenetv1

* fix ssd benchmark_score label shapes

* add resnet101_v1 and inceptionv3 support

* Refine some descriptions in the MKLDNN_README

* improve docs

* improve link in perf.md

…2840)

* remove num_labels check in multibox_target

* add unit test

* test both cpu and gpu

* add contrib operator to GPU unit test

* do not test all contrib operator in gpu

* Fix CPUPinned unexpected behaviour

* fix lint

* add guards

* Actually, this may affect perf

* trigger ci

* fix lint

* fix documentation

* fix for dist_sync_device

* add guard

* fix bug with memory

* try fix for gluon mp interaction

* blah

* trigger jenkins

* Try fix for gluon multiprocessing bug

Thanks Nvidia!

* edit

* try nvidia fix

* address Haibin and Lin's comments

* get rid of blank line in Makefile

* add Generic MXNetHandle trait and MXNetHandlePhantomRef class that will be used by all MXNetObjects

* Generic Handle with AutoCloseable

* add NativeResource and NativeResourceManager with Periodic GC calling

* use NativeResource trait in NDArray, Symbol and Executor

* add run train mnist script

* create a Generic ResourceScope that can collect all NativeResources to dispose at the end

* modify NativeResource and ResourceScope, extend NativeResource in NDArray, Symbol and Executor

* remove GCExecutor

* deRegister PhantomReferences by when calling dispose()

* add Finalizer(temporary) to NativeResource

* refactor NativeResource.dispose() method

* update NativeResource/add Unit Test for NativeResource

* updates to NativeResource/NativeResourceRef and unit tests to NativeResource

* remove redundant code added because of the object equality that was needed

* add ResourceScope

* Fix NativeResource to not remove from Scope, add Unit Tests to ResourceScope

* cleanup log/print debug statements

* use TreeSet inplace of ArrayBuffer to speedup removal of resources from ResourceScope
Fix Executor dispose and make KVStore a NativeResource

* fix segfault that was happening because of NDArray creation on the fly in Optimizer

* Add comments for dispose(param:Boolean)