CudnnFind() usage improvements #12804

DickJC123 · 2018-10-12T02:12:30Z

Description

This PR improves the MXNet's use of cudnnFind() to address a few issues:
1. With the gluon imperative style, cudnnFind() is called during forward(), and so might have its timings perturbed by other GPU activity (including potentially other cudnnFind() calls).
2. With some cuda drivers versions, care is needed to ensure that the large I/O and workspace cudaMallocs() performed by cudnnFind() are immediately released and available to MXNet.
3. cudnnFind() makes both conv I/O and workspace allocations that must be covered by the GPU global memory headroom defined by MXNET_GPU_MEM_POOL_RESERVE. Per issue #12662, large convolutions can result in out-of-memory errors, even when MXNet's storage allocator has free memory in its pool.

This PR addresses these issues, providing the following benefits:
1. Consistent algo choice for a given convolution type in a model, both for instances in the same GPU and in other GPUs in a multi-GPU training setting.
2. Consistent algo choice from run to run, based on eliminating sources of interference of the cudnnFind() timing process.
3. Consistent model global memory footprint, both because of the consistent algo choice (algo's can have markedly different workspace requirements) and changes to MXNet's use of cudaMalloc.
4. Increased training performance based on being able to consistently run with models that approach the GPU's full global memory footprint.
5. Adds a unittest for and solves issue #12662.

Now specifically, the PR makes the following changes/additions:
1. Merges the cudnn algo registry separate Find() and Register() methods into a single FindOrElseRegister() call protected by a mutex. Before, there was a window of time between when a thread found no algo entry and when it registered a new entry. This window could allow a different thread to call cudnnFind() on the same convolution type, getting a different answer. FindOrElseRegister() takes a callback that determines the algo via cudnnFind() and makes access to the cudnn algo registry effectively atomic. The callbacks provided with cudnn_convolution and cudnn_deconvolution also grab the storage allocator's mutex to quiet the GPU activity from other threads during the running of cudnnFind().
2. Changes MXNet's storage allocator to round large allocations to a multiple of 2MB. This value ensures that small permanent allocations that might have shared a cuda memory allocation slab with a prior large allocation don't prevent the reclaiming of that slab area.
3. Includes use of the MXNet storage allocator's Alloc() and DirectFree() API to coax a convolution's I/O storage needs away from MXNet's storage allocator prior to calling cudnnFind().

The first commit introduces a unittest that demonstrates issue #12662 in the current codebase. In order to make the test adaptable to GPUs of varying global memory, a C-level API was brought out to the python API by introducing mx.context.gpu_memory_info(dev_id). Follow-up commits supply the fix and the rest of the PR.

Hopefully Interested parties: @KellenSunderland @piiswrong @eric-haibin-lin @zheng-da

Checklist

Essentials

Please feel free to remove inapplicable items for your PR.

The PR title starts with [MXNET-$JIRA_ID], where $JIRA_ID refers to the relevant JIRA issue created (except PRs with tiny changes)
[ X] Changes are complete (i.e. I finished coding on this PR)
[X ] All changes have test coverage:
Unit tests are added for small changes to verify correctness (e.g. adding a new operator)
Nightly tests are added for complicated/long-running ones (e.g. changing distributed kvstore)
Build tests will be added for build configuration changes (e.g. adding a new build option with NCCL)
[X ] Code is well-documented:
For user-facing API changes, API doc string has been updated.
For new C++ functions in header files, their functionalities and arguments are documented.
For new examples, README.md is added to explain the what the example does, the source of the dataset, expected performance on test set and reference to the original paper if applicable
Check the API doc at http://mxnet-ci-doc.s3-accelerate.dualstack.amazonaws.com/PR-$PR_ID/$BUILD_ID/index.html
[X ] To the my best knowledge, examples are either not affected by this change, or have been fixed to be compatible with this change

Changes

Feature1, tests, (and when applicable, API doc)
Feature2, tests, (and when applicable, API doc)

Comments

The following command was run on an 8-GPU system to demonstrate the new consistency of global memory footprint:

python /opt/mxnet/example/image-classification/train_imagenet.py --gpu 0,1,2,3,4,5,6,7 --batch-size 256 --num-epochs 1 --data-train /data/iman-val-recordio-352/train.rec --disp-batches 10 --network inception-v3 --data-nthreads 32 --image-shape 3,299,299

Two nvidia-smi outputs are shown. The first is before the PR (showing footprints in the range of 5GB to 8GB), while the second is after (showing consistent 5GB footprints with < 1% variation).

Before PR:

+-----------------------------------------------------------------------------+
| NVIDIA-SMI 410.45                 Driver Version: 410.45                    |
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|===============================+======================+======================|
|   0  Tesla V100-SXM2...  On   | 00000000:06:00.0 Off |                    0 |
| N/A   58C    P0   247W / 300W |   6312MiB / 32480MiB |     86%      Default |
+-------------------------------+----------------------+----------------------+
|   1  Tesla V100-SXM2...  On   | 00000000:07:00.0 Off |                    0 |
| N/A   60C    P0   274W / 300W |   5542MiB / 32480MiB |     86%      Default |
+-------------------------------+----------------------+----------------------+
|   2  Tesla V100-SXM2...  On   | 00000000:0A:00.0 Off |                    0 |
| N/A   63C    P0   255W / 300W |   5152MiB / 32480MiB |     89%      Default |
+-------------------------------+----------------------+----------------------+
|   3  Tesla V100-SXM2...  On   | 00000000:0B:00.0 Off |                    0 |
| N/A   54C    P0   258W / 300W |   6730MiB / 32480MiB |     88%      Default |
+-------------------------------+----------------------+----------------------+
|   4  Tesla V100-SXM2...  On   | 00000000:85:00.0 Off |                    0 |
| N/A   57C    P0   222W / 300W |   5158MiB / 32480MiB |     87%      Default |
+-------------------------------+----------------------+----------------------+
|   5  Tesla V100-SXM2...  On   | 00000000:86:00.0 Off |                    0 |
| N/A   59C    P0   260W / 300W |   5168MiB / 32480MiB |     84%      Default |
+-------------------------------+----------------------+----------------------+
|   6  Tesla V100-SXM2...  On   | 00000000:89:00.0 Off |                    0 |
| N/A   63C    P0   266W / 300W |   5160MiB / 32480MiB |     88%      Default |
+-------------------------------+----------------------+----------------------+
|   7  Tesla V100-SXM2...  On   | 00000000:8A:00.0 Off |                    0 |
| N/A   58C    P0   255W / 300W |   8252MiB / 32480MiB |     90%      Default |
+-------------------------------+----------------------+----------------------+
                                                                               
+-----------------------------------------------------------------------------+
| Processes:                                                       GPU Memory |
|  GPU       PID   Type   Process name                             Usage      |
|=============================================================================|
|    0     53319      C   python                                      6289MiB |
|    1     53319      C   python                                      5519MiB |
|    2     53319      C   python                                      5129MiB |
|    3     53319      C   python                                      6707MiB |
|    4     53319      C   python                                      5135MiB |
|    5     53319      C   python                                      5145MiB |
|    6     53319      C   python                                      5137MiB |
|    7     53319      C   python                                      8229MiB |
+-----------------------------------------------------------------------------+

After PR:

+-----------------------------------------------------------------------------+
| NVIDIA-SMI 410.45                 Driver Version: 410.45                    |
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|===============================+======================+======================|
|   0  Tesla V100-SXM2...  On   | 00000000:06:00.0 Off |                    0 |
| N/A   55C    P0   271W / 300W |   5044MiB / 32480MiB |     85%      Default |
+-------------------------------+----------------------+----------------------+
|   1  Tesla V100-SXM2...  On   | 00000000:07:00.0 Off |                    0 |
| N/A   57C    P0   221W / 300W |   5042MiB / 32480MiB |     87%      Default |
+-------------------------------+----------------------+----------------------+
|   2  Tesla V100-SXM2...  On   | 00000000:0A:00.0 Off |                    0 |
| N/A   59C    P0   214W / 300W |   5042MiB / 32480MiB |     84%      Default |
+-------------------------------+----------------------+----------------------+
|   3  Tesla V100-SXM2...  On   | 00000000:0B:00.0 Off |                    0 |
| N/A   52C    P0   263W / 300W |   5040MiB / 32480MiB |     82%      Default |
+-------------------------------+----------------------+----------------------+
|   4  Tesla V100-SXM2...  On   | 00000000:85:00.0 Off |                    0 |
| N/A   55C    P0   252W / 300W |   5048MiB / 32480MiB |     82%      Default |
+-------------------------------+----------------------+----------------------+
|   5  Tesla V100-SXM2...  On   | 00000000:86:00.0 Off |                    0 |
| N/A   56C    P0   180W / 300W |   5056MiB / 32480MiB |     81%      Default |
+-------------------------------+----------------------+----------------------+
|   6  Tesla V100-SXM2...  On   | 00000000:89:00.0 Off |                    0 |
| N/A   59C    P0   244W / 300W |   5060MiB / 32480MiB |     79%      Default |
+-------------------------------+----------------------+----------------------+
|   7  Tesla V100-SXM2...  On   | 00000000:8A:00.0 Off |                    0 |
| N/A   54C    P0   255W / 300W |   5084MiB / 32480MiB |     83%      Default |
+-------------------------------+----------------------+----------------------+
                                                                               
+-----------------------------------------------------------------------------+
| Processes:                                                       GPU Memory |
|  GPU       PID   Type   Process name                             Usage      |
|=============================================================================|
|    0     47478      C   python                                      5021MiB |
|    1     47478      C   python                                      5019MiB |
|    2     47478      C   python                                      5019MiB |
|    3     47478      C   python                                      5017MiB |
|    4     47478      C   python                                      5025MiB |
|    5     47478      C   python                                      5033MiB |
|    6     47478      C   python                                      5037MiB |
|    7     47478      C   python                                      5061MiB |
+-----------------------------------------------------------------------------+

…sue.

tests/python/gpu/test_gluon_gpu.py

eric-haibin-lin · 2018-10-12T20:06:06Z

This is awesome! Is the change complete? Is the plan to add the rest of changes in this PR or the next one?

DickJC123 · 2018-10-12T20:41:08Z

I'm still resolving issues with the CI test I introduced. The rest of the PR is complete, but not yet pushed.

DickJC123 · 2018-10-14T21:31:44Z

@KellenSunderland @piiswrong @eric-haibin-lin @zheng-da

It took a bit of playing with my newly introduced 'test_large_models' test to get it to fail on the correct CI nodes and not others. The logs of commit 7bf8d51show the proper misbehavior present with the current codebase. I've now committed the PR code, which demonstrates the issue is fixed. See initial description for additional PR benefits.

As I look over the diffs now, I see the PR might look larger than it really is. Much of the PR change involves moving most of SelectAlgo() code intact into a new callback function CuDNNAlgoSetter.

Also, I see now that I didn't mention introducing an environment variable MXNET_GPU_MEM_LARGE_ALLOC_ROUND_SIZE that defaults to the ideal value 2MB- my preference here rather than hardcoding a magic constant.

DickJC123 · 2018-10-14T22:48:57Z

To remotely debug the issues with my new test as run on the CI systems, I added stderr output that will be emitted on the same nosetests output line (even without the '-s'). Here shown during a failing run:

test_gluon_gpu.test_large_models ... testing global memory of size 7988903936 ... 1200x1200 1190x1190 1180x1180 1170x1170
ERROR

KellenSunderland · 2018-10-15T08:21:30Z

Thanks for the great work Dick. Looking forward to digging into this during the week (sorry, been a bit tied up with a relocation). I'll try and verify offline that it also fixes some other selectAlgo issues I've seen.

sergeykolychev

Perl related changes look good.

KellenSunderland · 2018-10-22T04:39:49Z

Did some testing over the weekend and can verify this fixes a number of issues I've seen including our recent batch/slice test failures. Will do a quick syntax pass tomorrow.

KellenSunderland · 2018-10-23T17:42:10Z

perl-package/AI-MXNetCAPI/mxnet.i

@@ -349,7 +349,7 @@ int MXGetGPUCount(int* out);
 * \param total_mem pointer to the integer holding total GPU memory
 * \return 0 when success, -1 when failure happens
 */
-int MXGetGPUMemoryInformation(int dev, int *out, int *out);
+int MXGetGPUMemoryInformation(int dev, uint64_t *out, uint64_t *out);


@szha Given the usage I'd consider this a non-breaking change, but it is technically changing types to an argument. From a SemVer perspective are you ok with changing this in a minor update?

I also pondered this question and it's worth discussing. As the MXGetGPUMemoryInformation interface stands now, it would only report global memory total and free bytes < 2MB correctly. It's been many years since GPUs had so little global memory, so it's hard to imagine anyone out there using an interface so broken. MXNet didn't wrap this C++ API in Python, although it was exposed in Perl I think.

Yeah I also grepped through the code and only see references to this API being used from Perl.

I think @DickJC123 you meant 2GB? One alternative is to provide the new interface as MXGetGPUMemoryInformation64 and update the old interface in major version

roywei · 2018-10-23T19:55:35Z

@eric-haibin-lin @szha @zheng-da @anirudh2290 @sandeep-krishnamurthy @nswamy could you help review? Thanks a lot!
This could fix ##12767 which is failing in multiple PRs

KellenSunderland · 2018-10-23T20:31:01Z

Agree with @roywei, this PR will fix many issues and it would be great to get it merged soon. Let's still do due diligence in terms of review as it's an important component.

KellenSunderland · 2018-10-23T21:52:27Z

tests/python/gpu/test_gluon_gpu.py

+    sys.stderr.write(' testing global memory of size {} ... '.format(total_mem_bytes))
+    sys.stderr.flush()
+    for i in range(num_trials):
+        sz = start_size - 10 * i


Edit: ok I see what's going on here. Sorry for the confusion.

Is it intended that we test sz at 1200x1200 1190x1190 1180x1180 1170x1170 1160x1160 1150x1150 1140x1140 1130x1130 1120x1120 1110x1110? Is there a good reason to test these values?

We don't want to test the same size, since that would be a hit in the algo cache and cudnnFind() would not be re-run. The idea is to test different sizes that are roughly the size as chosen initially. I observed that with the progression of these models, the MXNet storage manager would slowly allocate up to 95% of memory by default (although much of it ends up in its free store). At that point, if MXNet's storage manager is asked for a big allocation that doesn't match the size of something in the free store, it will trigger a beneficial ReleaseAll():

if (free <= total * reserve_ / 100 || size > free - total * reserve_ / 100) ReleaseAll();

However, if instead cudnnFind is called at that point, the large allocations it wants to make for I/Os and workspace will cause an out of memory or 'no algo found' error, despite the fact that unused allocations are in the free store. I'm using the existing Alloc/DirectFree API to possibly trigger a ReleaseAll() prior to calling cudnn within the algo-setting callback.

And to get back to your question more succinctly, there's nothing magic about the initial 1200x1200 starting point. It was calculated based on the 8GB global memory of the CI machines. I verified that the test initially failed, then passed, on 16GB and 32GB GPUs (with different sizes in each case).

Ah that makes total sense, you're just using dimensions to make sure we're not pulling the alg straight from the registry and bypassing the auto-tuning. Gotcha, thanks Dick.

KellenSunderland · 2018-10-24T04:33:42Z

src/operator/nn/cudnn/cudnn_algoreg-inl.h

@@ -75,7 +81,7 @@ class CuDNNAlgoReg {
            bool add_to_weight,
            CuDNNAlgo<cudnnConvolutionFwdAlgo_t> *fwd,
            CuDNNAlgo<cudnnConvolutionBwdDataAlgo_t> *bwd,
-            CuDNNAlgo<cudnnConvolutionBwdFilterAlgo_t> *flt) {
+            CuDNNAlgo<cudnnConvolutionBwdFilterAlgo_t> *flt, AlgoSetter_t algo_setter) {


Would using a const ref for algo_setter save us a copy?

KellenSunderland

LGTM and resolves several issues.

roywei

LGTM!

szha · 2018-10-24T21:48:23Z

src/storage/pooled_storage_manager.h

@@ -57,6 +57,7 @@ class GPUPooledStorageManager final : public StorageManager {
  GPUPooledStorageManager() {
    reserve_ = dmlc::GetEnv("MXNET_GPU_MEM_POOL_RESERVE", 5);
    page_size_ = dmlc::GetEnv("MXNET_GPU_MEM_POOL_PAGE_SIZE", 4096);
+    large_alloc_round_size_ = dmlc::GetEnv("MXNET_GPU_MEM_LARGE_ALLOC_ROUND_SIZE", 2 * 1024 * 1024);


I developed another rounding memory manager that uses a combination of exponential rounding size and linear rounding size and has shown good results. If adding rounding to GPU is desired by default, I think we can combine them into a single memory manager that offer these knobs.

let's address the memory pool change in a separate PR.

szha · 2018-10-24T21:55:54Z

src/operator/nn/cudnn/cudnn_convolution-inl.h

+        LOG(FATAL) << nalgo << " forward algorithms with minimum memory requirement "
+                   << min_memory_needs << " bytes have been tried. Workspace size is set to "
+                   << workspace_byte << " bytes, please consider reducing the batch/model size, "
+                   << "or increasing workspace size.";


There are several messages that look alike. Consider wrapping it into a macro

blac2kite · 2018-10-24T23:50:24Z

python/mxnet/context.py

+
+    Returns
+    -------
+    (free, total) : (int, int)


Minor: 'total' - is it referring to total used, total available or the total size of the physical GPU. Also, aren't they 64 bit integers. So maybe 'long' would be more appropriate. Since we are exposing this API in python, it'd be a good idea to document it well.

I prefer to leave this as is. Regarding int vs long, I'm not a Python wizard, but ints are 'plain integers' and longs have unlimited precision:

$ python Python 2.7.12 (default, Dec 4 2017, 14:50:18) [GCC 5.4.0 20160609] on linux2 Type "help", "copyright", "credits" or "license" for more information. >>> import sys >>> x = sys.maxsize >>> x 9223372036854775807 >>> type(x) <type 'int'> >>> y=2*x >>> y 18446744073709551614L >>> type(y) <type 'long'> >>>

And unfortunately, there's not a real short answer to what 'total' memory means. We're wrapping the cuda call cudaMemGetInfo(), and the NVIDIA documentation says:

Returns in *free and *total respectively, the free and total amount of memory available for allocation by the device in bytes.

Let's say you've got a GPU with published memory T. The GPU driver puts some control structures like the page table in that memory, so call that driver overhead D. Finally, your GPU may be driving a monitor, so a window manager is using the GPU with overhead W. So what does the API return for 'total' in this scenario? The answer is T - D. The long answer then is: 'total' means the total memory available to both your MXNet process and other processes that may be using the GPU. I don't know a way to suggest this succinctly without introducing more confusion.

blac2kite · 2018-10-25T00:01:52Z

src/operator/nn/cudnn/cudnn_algoreg-inl.h

@@ -75,7 +81,7 @@ class CuDNNAlgoReg {
            bool add_to_weight,
            CuDNNAlgo<cudnnConvolutionFwdAlgo_t> *fwd,
            CuDNNAlgo<cudnnConvolutionBwdDataAlgo_t> *bwd,
-            CuDNNAlgo<cudnnConvolutionBwdFilterAlgo_t> *flt) {
+            CuDNNAlgo<cudnnConvolutionBwdFilterAlgo_t> *flt, AlgoSetter_t algo_setter) {


Minor: Other parameters are on their own lines. Maybe algo_setter can go in its own line.

src/storage/pooled_storage_manager.h

eric-haibin-lin · 2018-10-25T22:13:21Z

@DickJC123 could you address the build issue in CI?

src/c_api/c_api.cc:130:43: error: 'free_mem64' may be used uninitialized in this function [-Werror=maybe-uninitialized]

   *free_mem = static_cast<int>(free_mem64);

                                           ^

src/c_api/c_api.cc:131:45: error: 'total_mem64' may be used uninitialized in this function [-Werror=maybe-uninitialized]

   *total_mem = static_cast<int>(total_mem64);

DickJC123 · 2018-10-26T00:31:41Z

@eric-haibin-lin I've fixed the latest uninitialized var issue you pointed out and am passing CI. Thanks to all for the careful review! @KellenSunderland has been following even the last tweeks and approves this PR.

KellenSunderland · 2018-10-26T01:01:51Z

Yep, updates look good, did some testing and it fixes a few issues (including some CI failures we've been getting recently).

Thanks for the quick iteration @DickJC123.

Fixed by apache#12804

* Add mx.context.gpu_memory_info() to python api for flexible tests. * Add test_gluon_gpu.py:test_large_models to show cudnnFind headroom issue. * Output model sizes tried by test_gluon_gpu.py:test_large_models. * Fix perl interface to MXGetGPUMemoryInformation. * Increase difficulty of test_gluon_gpu.py:test_large_models. * Forgot a file in fix for perl. * Modify test to pass on no-cudnn CI runner. * Mutex algo reg updates, serialize cudnnFind calls. * Fix for cudnnFind memory headroom issue. * Fix cpplint. * Respond to reviewers comments. * Guard against improper MXNET_GPU_MEM_LARGE_ALLOC_ROUND_SIZE values. * Fix potentially unassigned var.

* Change dependencies documentation opencv2-->opencv (#12654) * opencv2-->opencv; deleted duplicate content * update troubleshooting info * fix bug, issue 12613 (#12614) * [MXNET-780] Fix exception handling bug (#12051) * Fix exception handling bug * Trigger CI * Add test for exc handling * Trigger CI * Resolve conflicts * fix bug in prelu , issue 12061 (#12660) * fix bug in prelu * add unit test * add mentions of the gluon toolkits and links to resources (#12667) * add mentions of the gluon toolkits and links to resources * fix nlp and cv text * Remove fixed seed for test_ctc_loss (#12686) * remove apachecon promo (#12695) * Onnx version update from 1.2.1 to 1.3 in CI (#12633) * upgrade onnx * import helpers * upgrade version in ci * addressing comments * fix * test name changed * retrigger tests * adding comments * [MXNET-833] [R] Char-level RNN tutorial fix (#12670) * char RNN tutorial * nit fixes * Add documents for two new environment variables for memory pool. (#12668) * document env. * update. * update. * retrigger * update mshadow for omp acceleration when nvcc is not present (#12674) * update mshadow * bump * fix for test order (#12358) * [MXNET-951] Python dockerfiles built on pip binaries and build/release script (#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 * [MXNET-500]Test cases improvement for MKLDNN on Gluon (#10921) * 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 * Enable test_gluon.test_export (#12688) * Update contribute.md (#12685) * Update contribute.md Fixed grammar * Update contribute.md Fixed Grammar * Update proposal_target.py (#12709) * [MXNET-637] Multidimensional LSTM example for MXNetR (#12664) * 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 * import Julia binding - enable Jenkins CI build for Julia - add license headers to Julia source code - update links for Julia README * Fix static / dynamic linking of gperftools and jemalloc (#12714) * Disable test batchnorm slice (#12716) * [MXNET-860] Use emplace where helpful (#12694) * [MXNET-860] Use emplace where helpful * [MXNET-860] Add emplace as an error in clang-tidy * [MXNET-953] Correct ASAN cflags flag (#12659) * [MXNET-860] Remove std::moves that have no affect (#12730) * [MXNET-860] Remove std::moves that have no affect * [MXNET-860] Check for unneeded moves as errors * add FListInputNames attribute to softmax_cross_entropy (#12701) * Fix #12672, importing numpy scalars (zero-dimensional arrays) (#12678) * Fix https://github.com/apache/incubator-mxnet/issues/12672 Problem is in using np.ascontiguousarray, which is buggy for zero-dimensional arrays (see https://github.com/numpy/numpy/issues/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 * [MXNET-908] Speed up travis builds to avoid timeouts (#12706) 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. (#12733) * 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. * [MXNET-716] Adding Scala Inference Benchmarks (#12721) * 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 * [MXNET-623] Fixing an integer overflow bug in large NDArray (#11742) * 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 (#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 * Change numpy version to 1.15.2 in python and docker install requirements (#12711) Default numpy version in The Python Package Index (PyPI) is 1.15.2 * Reenable test_gluon.test_conv (#12718) * reenable the test * Trigger CI * Refine mxnet python installation (#12696) * 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 * Update packages and tests in the straight dope nightly (#12744) * [#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: https://github.com/zackchase/mxnet-the-straight-dope/pull/540 * Add dependency for IPython update. * Detect errors in notebook execution failure. * Clean up of naming in retry code. * Fix failing GPU test on single GPU host (kvstore) (#12726) Fixes #10977 * Add option for automatic downcasting dtype for cudnn to allow using Tensorcore for fp32 (#12722) * [MXNET-1026] [Perl] Sync with recent changes in Python's API (#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. * fix benchmark on control flow operators. (#12693) * [MXNET-982] Provide example to illustrate usage of CSVIter in C++ API (#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 02e784aaf927d465447d08a978b202bd5677a979. 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 * [MXNET-912] Refactoring ctc loss operator (#12637) * 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 new name to CONTRIBUTORS.md (#12763) * Add resnet50-v1 to benchmark_score (#12595) * add resnet50-v1 to benchmark_score * rename back and duplicated * rename v2 back to resnet.py * [MXNET-716][MIRROR #12723] Scala Benchmark Extension pack (#12758) * reflect the PR * add 1 more metric * Implement mkldnn convolution fusion and quantization. (#12530) * 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 * Introduction to Clojure-MXNet video link. (#12754) * [MXNET-915] Java Inference API core wrappers and tests (#12757) * Core Java API class commit * Update ScalaStyle max line length to 132 instead of 100 * Disabled flaky test: test_mkldnn.test_Deconvolution (#12770) * Add mkl-dnn to docker install method (#12643) * add mkl-dnn to docker install method * add mkl for gpu * add docker for windows * Improve mkldnn fallback. (#12663) * Fix regression in MKLDNN caused by PR 12019 (#12740) * add flag to elementwise_add * fix flatteng * retrigger * Fixed broken link for Baidu's WARP CTC (#12774) * Updated CONTRIBUTORS.md to include lebeg and gigasquid, moved mabreu to committers section (#12766) * Use modern onnx API to load model from file (#12777) * Update env_var.md (#12702) * fix cnn visualization tutorial (#12719) * [MXNET-979] Add fix_beta support in BatchNorm (#12625) * 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 * [MXNET-947] Expand scala imclassification example with resnet (#12639) * [MXNET-947] Scala imclassification example with Resnet * R fix metric shape (#12776) * Revert "[MXNET-979] Add fix_beta support in BatchNorm (#12625)" (#12789) This reverts commit 0bab6d529343f0ce186859ba75c9bb02067e9cfe. Because master branch started to fail with this change. * Updated tvm submodule head (#12764) * Updated tvm submodule head * Remove FInplaceIdentity attr for cast and _backward_cast * Adagrad optimizer with row-wise learning rate (#12365) * Proximal Group Adagrad optimizer * Remove proximal implementation and rename to GroupAdagrad * Remove superfluous doc * Remove superfluous argument * Fix mismatch shapes (#12793) * mismatch shape switch * closing bracket * closing bracket * Make Gluon download function to be atomic (#12572) * 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 * Re-enables test_dropout (#12717) * [MXNET -1004] Poisson NegativeLog Likelihood loss (#12697) * 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 * Update osx.mk - Added "apple" to USE_BLAS comment (#12819) 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 * [MXNet-1002] Add GluonCV and NLP tookits, Keras, and developer wiki to navigation (#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, LSTMCell, GRUCell (#12794) * fixed symbols naming in RNNCell and LSTMCell * fixed GRUCell as well * added test * fixed tests? * simplify mac mkldnn build (#12724) * 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 * Change the way NDArrayIter handle the last batch (#12545) * 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 * [MXNET-707] Add unit test for mxnet to coreml converter (#11952) * 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 * Add embedding to print_summary (#12796) * Scala Docs - Replace old Symbol api usages (#12759) * [MXNET-892] ONNX export/import: DepthToSpace, SpaceToDepth operators (#12731) * ONNX export/import: DepthToSpace operator * ONNX import/export: SpaceToDepth operator * ONNX import/export: Tests for SpaceToDepth * R install instructions update for macOS (#12832) * add prereqs for R installation on Mac * pin openblas for mac R install to 0.3.1 * Fixed __setattr__ method of _MXClassPropertyMetaClass (#12811) * fixed indentation * simplified code * Fixed regex for matching platform type in Scala Benchmark scripts (#12826) * Added context object to run TestCharRnn example (#12841) * [MXNET-703] Show perf info for TensorRT during tests (#12656) This PR makes sure perf information printed during TensorRT test runs is correctly displayed when run in CI. * Update Operator Implementation Tutorial (#12230) * update op creation docs * add flakiness checker and link to gradient checking * address comments * update reference line number * fix comments * Fix broken links (#12856) * Fix Flaky Topk (#12798) * fix flaky topk * try to fix * remove the usage of IndexFill * fix * add docstring * Add Psroipooling CPU implementation (#12738) * add psroipooling cpu impl * minor fix * revert copyright * fix testcase * add openmp * no openmp for backward * ONNX export: Fully connected operator w/o bias, ReduceSum, Square (#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() (#12867) * Undefined name: load_model() --> utils.load_model() As discussed at: * https://github.com/apache/incubator-mxnet/commit/815f36ce8b4ed16fe27d500f5c8c930cd10cee5c#r30956015 * Force a rebuild * Force a rebuild * ONNX export/import: Selu (#12785) * Sparse support for logic ops (#12860) * remove check * fix lint * fix gpu build * add a tutorial for the subgraph API. (#12698) * 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. * MKL-DNN Quantization Examples and README (#12808) * 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 * [MXNET-1033] Fix a bug in MultiboxTarget GPU implementation (#12840) * 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 * [MXNET-1107] Fix CPUPinned unexpected behaviour (#12031) * 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 * NativeResource Management in Scala (#12647) * 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) * add/update infer_range docs (#12879) * Fix __all__ in optimizer/optimizer.py (#12886) * Add index_copy() operator (#12810) * add index_copy operator * add index_copy op * update index_copy op * add unittest for index_copy() * update index_copy * update index_copy * use mxnet_op::copy * update index_copy * update index_copy * update index_copy * update index_copy test * update index_copy test * sparse support for take(csr, axis=0) (#12889) * initial commit * add test cases for mode * fix bug * add comment * more comments * Add more models to benchmark_score (#12780) * add models to cnn benchmark * improve benchmark score * add benchmark_gluon * improve lint * improve lint * add licsence for script * improve script lint * mv benchmark_gluon to new location * support multi-gpus * Add a new parameter 'global batchsize' for the batch size multiplication for multi-gpu case * add batch size argument help * improve help and change default batchsize * simplify benchmark_gluon * [MXNET-1025] Add Jetpack 3.3 support to Jetson (#12735) * Fix Batch input issue with Scala Benchmark (#12848) * add initial change * add fix * improved usage of Shape as well as warning message on performance * change into parallel * drop dropBack * apply Andrew's comments * remove add dim inside img 2 pixel * addressed Naveen's comment * update comments * fix type inference in index_copy. (#12890) * Extending the DCGAN example implemented by gluon API to provide a more straight-forward evaluation on the generated image (#12790) * add inception_score to metric dcgan model * Update README.md * add two pic * updata readme * updata * Update README.md * add license * refine1 * refine2 * refine3 * fix review comments * Update README.md * Update example/gluon/DCGAN/README.md * Update example/gluon/DCGAN/README.md * Update example/gluon/DCGAN/README.md * Update example/gluon/DCGAN/README.md * Update example/gluon/DCGAN/README.md * Update example/gluon/DCGAN/README.md * Update example/gluon/DCGAN/README.md * Update example/gluon/DCGAN/README.md * Update example/gluon/DCGAN/README.md * Update example/gluon/DCGAN/README.md * Update example/gluon/DCGAN/README.md * modify sn_gan file links to DCGAN * update pic links to web-data * update the pic path of readme.md * rm folder pic/, and related links update to https://github.com/dmlc/web-data/mxnet/example/gluon/DCGAN/ * Update README.md * [MXNET-674] Speed up GPU builds in CI (#12782) * [MXNET-674] Speed up GPU builds in CI * [MXNET-674] Refactor SMs into shell variable * [MXNET-674] Build CMake GPU CI jobs without PTX * [MXNET-793] ★ Virtualized testing in CI with QEMU ★ (#12094) * virtual testing with qemu * Add install procedure * update installation * Refine test run * use direct ssh * update readme * Fix uneccesary cp * Minor refinements * Refine error conditions in startup * requirements installed inside QEMU * Update base image * Fix license * Dockerfile rename fallout * license fixes * refine documentation * license fix * update readme * Update qemu base image and refine documentation * Address CR comments wrt shebangs. * Address CR comments wrt comments. * adjust vda2 -> vda1 * Disable SMP, bug with newer kernel * Remove commented out code * Fix licenses * CR comments addressed * increase ram to 4096mb * Revert dockerfile renaming * Fix undo rename of dockerfiles * Address CR comments * CR * [MXNET-1017] Updating the readme file for cpp-package and adding readme file for example directory. (#12773) * Updating the readme file for cpp-package and adding readme file for example directory. * Updating the readme file for cpp-package and adding readme file for example directory. * Addressed the review comments. * Addressed the review comments * Fail the broken link job when broken links are found (#12905) * Fix typo in formula in docstring for GRU cell and layer and add clarification to description (gluon.rnn) (#12896) * Fix typo in GRU cell and layers (gluon.rnn) docstring * empty * fix the paths issue for downloading script (#12913) * Ignore generated scala files. (#12928) * use ResourceScope in Model/Trainer/FeedForward.scala (#12882) * use ResourceScope in Model/Trainer/FeedForward.scala * add moveToOuterScope public method to move resources to a outerScope if it exists * fix memory leak in FeedForward.scala by making it a native resource and disposing argparams, auxParams in dispose() method * Disabled flaky test: test_gluon_gpu.test_slice_batchnorm_reshape_batchnorm (#12768) * Fix the operator API documentation (#12942) * Fix the operator API documentation * update message * fix indpt[0] for take(csr) (#12927) * getnnz operator for CSR matrix (#12908) * nnz * update err msg * skip nnz test on gpu * fix broken docs (#12871) * Add bytearray support back to imdecode (#12855, #12868) (#12912) 1. Avoid raise exception when input is bytearray. 2. Avoid OpenCV crash for empty input. 3. Added unittests. * Update tree lstm example (#12960) * update tree lstm example * update README.md * Update README.md * Update bilstm integer array sorting example (#12929) * Update the bilstm example to Gluon * Update formating * Update example/vae/VAE_example.ipynb Co-Authored-By: ThomasDelteil <thomas.delteil1@gmail.com> * Fix the bug of assigning large integer to NDArray (#12921) * 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 the large int assign problem * Refactor mkldnn test files (#12410) * move mkldnn helper funcs to diff file * create test file to test helper functions * update comments in header * move helpers into include dir * fix lint * update comment * add stdlib headers * remove unused headers * add endif * add missing header * add inlines * fix lint * move copyfrom test to mkldnn_test * CudnnFind() usage improvements (#12804) * Add mx.context.gpu_memory_info() to python api for flexible tests. * Add test_gluon_gpu.py:test_large_models to show cudnnFind headroom issue. * Output model sizes tried by test_gluon_gpu.py:test_large_models. * Fix perl interface to MXGetGPUMemoryInformation. * Increase difficulty of test_gluon_gpu.py:test_large_models. * Forgot a file in fix for perl. * Modify test to pass on no-cudnn CI runner. * Mutex algo reg updates, serialize cudnnFind calls. * Fix for cudnnFind memory headroom issue. * Fix cpplint. * Respond to reviewers comments. * Guard against improper MXNET_GPU_MEM_LARGE_ALLOC_ROUND_SIZE values. * Fix potentially unassigned var. * fix mac r install and windows python build from source docs (#12919) * fix mac r install and windows python build from source docs * reorder macos r install instructions * enable batchnorm unit tests (#12986) * enable bn unit tests * travis timed out, trigger ci * Update CONTRIBUTORS.md (#12996) I have made two minor contributions with pull requests so far. I forgot to add my name here earlier. * fix Sphinx errors for tutorials and install ToCs (#12945) * missing line break fix for tutorials toc * fix the install index toc errors * [MXNET -1030] Cosine Embedding Loss (#12750) * COsine Embedding Loss function added * Added unit tests for Cosine Embedding Loss Function * Added Latex code for formula for cosine embedding loss * Fixing document rendering * Fixing documentation issue * PR Comments addressed for using F (NDArray or Symbol) to calculate norm, renaming parameters * Markdown file updated. Added entry for CosineEmbeddingLoss * Added a line after .. math:: to fix documentation * Documentation check - pylint fix * Formula update * Making the formula simpler for correct rendering incrementally - Update 1 * Making the formula simpler for correct rendering incrementally - Update 2 * Making the formula simpler for correct rendering incrementally - Update 3 * Making the formula simpler for correct rendering incrementally - Update 4 * Making the formula simpler for correct rendering incrementally - Update 5 * Trigger CI * making the utility function cosine similarity internal * Added a test case for label = -1, for dissimilar vectors * Refactored names of parameters to the loss functions and updated the formula in docstring * PR comments addressed changes in documentation * Added random input vectors and labelled tests * Renaming variables * Pylint issues fixed * Resolving conflicts * Pylint issues fixed * Style issues fixed trailing whitespaces removed * Review comment addressed, sample_weight added in the parameter * Trigger CI * Reordered Parameter description * comments addressed - spelling errors * nit comments addressed * Trigger CI * Trugger CI * Trigger CI * Trigger CI * [MXNET-1173] Debug operators - isfinite, isinf and isnan (#12967) * is_finite and is_inf implementation for front-end python api debug operator * updated unit-tests * updated test cases and incorporated is_nan function * solved index out of bounds issue and added comments * simplified abs function call and added isnan to contrib.py and all debug ops to doc * changed dimensions, added regular number, assert_equal instead of almost, removed ctx and added data.abs * [MXNET-1111] Remove CPUPinned in ImageRecordIter (#12666) * squash commit * get rid of argument * undo a lot of unnecessary changes * undo more changes * fix typo * fix lint * address comments and fix rebase mistake * fix typo made during rebase * revert cpu_pinned * revert changes, because works without needing to copy params to GPU. thanks @yuxihu for testing and @apeforest for raising this issue! * revert changes to comm and nccl * Added/changed file_name, brief description comments in some files (#13033) * sample_like operators (#13034) * [MXNET-1179] Enforce deterministic algorithms in convolution layers (#12992) * add env variable to choose deterministic cudnn alg * set default value to false * fix build failure in Windows GPU * revert the previous change * only check determinism in CUDNN 7.x release * Add cudnn version check * fix lint error * Add a deprecate message (#13042) * Fix the operator API documentation * update message * deprecate old command * Disable flaky test test_operator.test_dropout (#13057) * Disable flaky test test_prelu (#13060) * la_op_inline.h to la_op-inl.h for consistency (#13045) * la_op_inline.h to la_op-inl.h for consistency * operator/tensor left-over doc changes * Improve clojure tutorial (#12974) * Switch tutorial to dependency/ies that exist on Maven * Improve Clojure Module tutorial * Add namespace docstring * Bring verbiage up to date with https://mxnet.incubator.apache.org/api/clojure/module.html * Add newlines for readability and to keep line length <80 * Nix duplicated section in Clojure Symbol API docs "Multiple Outputs" is a (deprecated) repeat of "Group Multiple Symbols". * Improve Clojure Symbol tutorial * Add namespace docstring * Bring verbiage up to date with https://mxnet.incubator.apache.org/api/clojure/symbol.html * Add newlines for readability and to keep line length <80 * Fix missing end-code-block in Clojure NDArray API docs * Improve Clojure NDArray tutorial * Add namespace docstring * Bring verbiage up to date with https://mxnet.incubator.apache.org/api/clojure/ndarray.html * Add newlines for readability and to keep line length <80 * Improve Clojure KVStore tutorial * Add namespace docstring * Bring verbiage up to date with https://mxnet.incubator.apache.org/api/clojure/kvstore.html * Add newlines for readability and to keep line length <80 * [MXNET-1017] Updating the readme file for cpp-package and adding readme file for example directory. (#12773) * Updating the readme file for cpp-package and adding readme file for example directory. * Updating the readme file for cpp-package and adding readme file for example directory. * Addressed the review comments. * Addressed the review comments * Fail the broken link job when broken links are found (#12905) * Fix typo in formula in docstring for GRU cell and layer and add clarification to description (gluon.rnn) (#12896) * Fix typo in GRU cell and layers (gluon.rnn) docstring * empty * fix the paths issue for downloading script (#12913) * removed unused header (#13066) * Moves f16c autodetection to its own cmake module (#12331) * Set correct update on kvstore flag in dist_device_sync mode (#12786) * Set correct update on kvstore flag in dist_device_sync mode * Add warning message for batch-size change in dist mode * Empty commit * Fix lint issues * ONNX export: Cleanup (#12878) * ONNX export: Cleanup input retrieval - Create a common function to get inputs for conversion functions - Do not register functions if onnx is not found * ONNX export: Add helper for creating node * Maven Surefire bug workaround (#13081) * remove legacy installation of Roxygen2 5.0 and add R-specific clean target (#12993) (#12998) * remove installation of legacy Roxygen2 vers. 5.0 * add R-specific clean target (#12993) * fixup! remove installation of legacy Roxygen2 vers. 5.0 * fixup! remove installation of legacy Roxygen2 vers. 5.0 * Gluon LSTM Projection and Clipping Support (#13056) * support projection in LSTM * add tests * update rnn to use cudnn ex * extend cudnn test to handle different versions * add lstm clip * use CUDNN_VERSION * merge USE_CUDNN_LSTM_CLIP and USE_CUDNN_LSTM_PROJ * assign false value to clip nan explicitly to RNN and GRU * update test * fix readme (#13082) * [MXNET-1180] Scala Image API (#12995) * add image and image suite * apply toImage function and tests * bug fix * apply the commented change * add test to apply border * fix scalastyle * [MXNET-793] Virtual testing with Qemu, refinement and extract test results to root MXNet folder (#13065) * Improve Qemu infrastructure Add documentation about running it interactively * Separate provision * Improve provisioning * Refine provisioning and interactive * Cant provision when the volumes arent mounted * Fix running tests * raise log output to INFO * adjust logging * flush stdout and stderr * Refine by copying test results back to the host * Fix license * remove config file and different way to run QEMU * remove config file and different way to run QEMU, remove ansible * Updated / Deleted some examples (#12968) * Updated / Deleted some examples * remove onnx test * remove onnx test * Fix variable name in tutorial code snippet (#13052) Fixes incorrect variable name in tutorial code as raised in issue https://github.com/apache/incubator-mxnet/issues/13051 * customized take forward for CPU (#12997) * Update module example (#12961) * Update Module example * trigger CI * ONNX export: Scalar, Reshape - Set appropriate tensor type (#13067) np.array sets default dtype to float64 which is not supported by ONNX. Setting these to appropriate type. * Fix example for mxnet.nd.contrib.cond and fix typo in src/engine (#12954) * fix typo in src/engine * fix example for mx.nd.contrib.cond * Improve the Clojure Package README to Make it Easier to Get Started (#12881) * Improve the README and make it easier to get started * Implement feedback from @ChaiBapchya and @daveliepmann * combined deps * Add wget Co-Authored-By: gigasquid <cmeier@gigasquidsoftware.com> * WIP: update readme * WIP: readme option 3 * Add section links to Clojure README Link each install option with the corresponding README section containing instructions for that option. An existing link to Maven search is removed because it interferes with the section links and it is replicated in the Option 1 instructions below. Per my PR suggestion: https://github.com/apache/incubator-mxnet/pull/12881/files/22bbe55d8d62be9ff3aebf693f73fa6049afc01d#r226822148 * fix typo Co-Authored-By: gigasquid <cmeier@gigasquidsoftware.com> * fix formatting Co-Authored-By: gigasquid <cmeier@gigasquidsoftware.com> * fix formatting Co-Authored-By: gigasquid <cmeier@gigasquidsoftware.com> * fix link Co-Authored-By: gigasquid <cmeier@gigasquidsoftware.com> * Some more updates for the Clojure README * [MXNET-918] Introduce Random module / Refact code generation (#13038) * refactor code gen * remove xxxAPIMacroBase (overkill) * CI errors / scala-style * PR review comments * Fix a typo in operator guide (#13115) * Fix the operator API documentation * update message * deprecate old command * fix typo in op guide * [Issue #11912] throw mxnet exceptions when decoding invalid images. (#12999) * Raise an excption when passing an empty buffer to imdecode. * src/io/image_io.cc: Check the length of the input buffer. * tests/python/unittest/test_image.py: Update the (already existing) test to expect a mx.base.MXNetError. * Raise an exception when passing an invalid data buffer to imdecode. * src/io/image_io.cc: Raise an exception when the image could not be decoded instead of just logging. * tests/python/unittest/test_image.py: Add a new test test_imdecode_invalid_image. * Raise an exception when passing an invalid data buffer to imdecode. * src/io/image_io.cc: Raise an exception when the image could not be decoded instead of just logging. * tests/python/unittest/test_image.py: Add a new test test_imdecode_invalid_image. * Rollback a "empty buffer" check in the image python bindings that's now more generally handled in the core code. * python/mxnet/image/image.py: remove buffer length check. * Update adversary attack generation example (#12918) * Fix adversary example generation * Update README.md * Fix test_utils.list_gpus() * fix unused variable * Disable travis tests (#13137) * Update Gluon example folder (#12951) * Reorganized the Gluon folder in example * trigger CI * update reference * fix out of place accumulation * Document the newly added env variable (#13049) * add env variable to choose deterministic cudnn alg * set default value to false * fix build failure in Windows GPU * revert the previous change * only check determinism in CUDNN 7.x release * Add cudnn version check * fix lint error * document env variable MXNET_ENFORCE_DETERMINISM * use cudnnGet instead of cudnnFind when determinism required * Revert "use cudnnGet instead of cudnnFind when determinism required" This reverts commit d1bdf0f38f50b8c499f22ae1d50770b819f27678. * Updated CONTRIBUTORS.md to include mxnet-label-bot (#13048) * Updated CONTRIBUTERS.md to include label-bot * Created section for label bot and included wiki page * Moved Label Bot section in CONTRIBUTORS.md file to a more convenient location * Retriggering * Fix docker cleanup race condition (#13092) * Improved git reset for CI builds (#12784) * Refactor L2_normalization (#13059) * Refactor L2_normalization * Fix windows build * Fix windows build * Move cpu optimization into l2_normalization.cc * Retrigger CI * Retrigger CI * Fix variational autoencoder example (#12880) * Add documentation on GPU performance on Quantization example (#13145) * Add documentation on GPU performance * Update README.md * [MXNET-1194] Reenable nightly tutorials tests for Python2 and Python3 (#13099) * Reenable nightly tests tutorials * small fix to settings * optimize a few more tutorials * Update tests * Update runtime_functions.sh * Update fine_tuning_gluon.md * Update JenkinsfileForBinaries * Update JenkinsfileForBinaries * remove coverage * Update dec example (#12950) * update dec example * trigger CI * update to remove dependency on sklearn data * Update MKL-DNN dependency (#12953) * update mkldnn and fix conv/deconv * fix * fix indent * fix cmake * fix cmake * fix cpp test for mkldnn * fix typo * fix conficts after merge * debug: remove 5d test * debug: remove 4d test * add comments * debug: remove 2d test * update mklml in ci * fix mklml * Revert "fix mklml" This reverts commit 328a22a373c49aacb914badd0db431bfbc8234f3. * Revert "update mklml in ci" This reverts commit 9ff3687892f85f43b8eac72ba935ceda928ae7e8. * Revert "debug: remove 2d test" This reverts commit 32551b3662fc30d5c9758a86c7664b4f2e367128. * Revert "debug: remove 4d test" This reverts commit 5412d643c2b00ce54c05e7387aca6779dee120d5. * Revert "debug: remove 5d test" This reverts commit 1fe9f8806d29c765e05f91c584799a947af2eb1d. * debug illegal core dump * debug illegal core dump * Revert "debug illegal core dump" This reverts commit 39321d578ae589465c0d4edcae7f92b88fdf3feb. * Revert "debug illegal core dump" This reverts commit 153b068b6d3a18a33f399076d3420ac42f2bc387. * change cmake * pin mkldnn version to 0.17rc * change format number * remove include directories in cmake * fix cpp test * address cpplint complaint * remove comment code * update mkldnn head * License header (#13178) * Minor fix to license_header documentation * Handle UnicodeError when checking license * Updated capsnet example (#12934) * Updated capsnet * trigger CI * Update README.md * Updates to several examples (#13068) * Minor updates to several examples * fix typo * update following review * Fix Sphinx python docstring formatting error. (#13177) * [Doc] Fix repo paths in Ubuntu build doc (#13101) * [Doc] Fix repo paths in Ubuntu build doc * [Doc] Use relative path in Ubuntu build doc * Update scala intellij tutorial (#12827) * Update scala intellij tutorial Update mxnet version log4j fixes Instructions from source * Remove version numbers and various improvements * Improve cpp-package example project build files. (#13093) 1. Change output to build folder. 2. Remove files that not been deleted by make clean. * Fix Sphinx document parsing error. (#13195) Fixes #12935 * Fix #13090, Add image.imread to python API doc. (#13176) * Fix Sphinx docstring formatting error. (#13004, #13005, #13006) (#13175) * Fix #12944, Fix Sphinx python docstring formatting error. (#13174) * Fix #13013, Fix Sphinx python docstring error. (#13173) * update the README (#13186) * Fixed Sparse astype doc string formatting error (#13171) * Fix problem with some OSX not handling the cast on imDecode (#13207) * Port of scala Image API to clojure (#13107) * Port of scala Image API to clojure * Minor style changes * Add specs and other minor fixes * Fix unit tests (:facepalm:) * Fixed Documentation issues (#13215) 1. mxnet.metric.EvalMetric.get_config doc error 2. mxnet.module.SequentialModule.add doc error * update the doc (#13205) * Fix Sphinx doc errors (#13170) * Fix Sphinx python docstring error: initializer.InitDesc (#12939) (#13148) * Fix Sphinx python docstring error: text contrib module (#12949) (#13149) * Sphinx failure fixes (#13213) * [MXNET-793] Virtualized ARMv7 with Qemu CI integration (#13203) * Testing just ndarray, since otherwise we require test refactoring which will be done later * Add QEMU ARMv7 test stage to CI * test_ndarray fails, so change for test_engine until UT are fixed in ARM * Refactor kvstore test (#13140) * Refactor kvstore test * Fix pylint * Fix problem with some OSX not handling the cast on imDecode (#13207) * Fix num_gpus * remove unused variable rotateM_ (#10803) * Revert "Sphinx failure fixes" (#13230) * Revert "Refactor kvstore test (#13140)" This reverts commit d8d2d6ef3d688a465e47f7170c2a11da804c2835. * Revert "[MXNET-793] Virtualized ARMv7 with Qemu CI integration (#13203)" This reverts commit fd3dedc621919b6fee7d8ca7fa2a85749e190907. * Revert "Sphinx failure fixes (#13213)" This reverts commit 2e4d6c8c1064b74d4e1c1b3441c2ecf12b81c6e2. * [MXNET-953] Fix oob memory read (#12631) * update log4j version of Scala package (#13131) * Disable Flaky test test_operator.test_clip (#12902) * Update multi-task learning example (#12964) * Update multi task learning example * Updating README.md * Update MKLML dependency (#13181) * update mkml * refine DownloadMKLML.cmake * merge DownloadMKLML.cmake from #11148 * fix mkldnn release version * fix windows compilation * Add --no-cache option to build.py when building containers (#13182) Add functionality to build.py to disable caching * Tool to ease compilation and reproduction of test results (#13202) * Add tool to simplify reproducing tests * add local build * Add cmake_options.yaml * minor * Fix license * Fix licenses * Rename file, address CR comments about gpu build function * Address Marco's comments * support for upper triangular matrices in linalg (#12904) * Fix Sphinx python docstrings (#13160) * Doc fixes * addressing feedback * base_module fix * fixing cross-reference issues * Implemented a regression unit test for #11793 (#12975) When using C++-based iterators, it's important that only a single batch is referenced at a time. Because C++ iterators are exposed to the Python code through a C API, there is no concept of reference counting. Hence, typically C++ iterators will deallocate a batch when next() is called on them. So, we need to make sure the Python code only references a single batch at a time, otherwise the Python code will attempt to access freed memory, resulting in either (a) garbage accuracy or (b) a segmentation fault. The test passes with the latest mxnet build. I verified it failed on previous releases, such as mxnet==1.2.0. * Add Java API docs generation (#13071) * add Java API docs generation; split out from Scala API docs * bumping file for ci * make scala docs build compatible for 2.11.x and 2.12.x scala fix typo * fix exit bug * Fix Sphinx error in ONNX file (#13251) * [Example] Fixing Gradcam implementation (#13196) * fixing gradcam * changed loading parameters code * fixing type conversions issue with previous versions of matplotlib * Fix test failure due to hybridize call in test_gluon_rnn.test_layer_fill_shape (#13043) * Restore hybridize call in test_gluon_rnn.test_layer_fill_shape * reset bulk_size when cached op forward hit error to fix the test failure * add try-catch block to reset bulk_size in more places to prevent potential bugs * more cleanup upon exception in Imperative::Backward * Addressed sphinx build issue (#13246) * Add gauss err function operator (#13229) * erf register gpu * add doc * Add Turing and Volta support to arch_name (#13168) * Bugfix in ci/docker_cache.py (#13249) * Fix scaladoc build errors (#13189) * Fix scaladoc errors from missing classpath Remove duplicate scalastyle plugin * Fix scaladoc warnings Also enable and fix all feature and deprecation warnings * Add missing documentations for getnnz (#13128) * Addressed ONNX module documentation warnings and added notes for short-form representation (#13259) * Manually track num_max_thread (#12380) * use cached version of get thread max * reserve core affects omp singleton * omp_thread_max_ updated in one line * remove enabled block * add brackets * re-add excluded reserved * add missing var * refactor macro * adding unit test for MKLDNN FullyConnected operator (#12985) * adding unit test for MKLDNN FullyConnected operator * removing mkldnn filter * removing mkldnn filter * Doc fixes (#13256) * fix train mnist for inception-bn and resnet (#13239) * Fix a bug in index_copy (#13218) * fix. * add test. * retrigger * Addressed doc issues (#13165) * Addressed doc issues * Update optimizer.py * Force APT cache update before executing install (#13285) * [Example] Gradcam consolidation in tutorial (#13255) * fixing gradcam * changed loading parameters code * fixing type conversions issue with previous versions of matplotlib * gradcam consolidation * creating directory structures in utils * changing location * empty commit * [MXNET-1203] Tutorial infogan (#13144) * Adding info_gan example * adjust paths of filenames * Update index.md * Update index.md * Update index.md * Update info_gan.md Added an image * Update info_gan.md Applied some fixes * Update info_gan.md Applied some fixes * Update info_gan.md Applied some fixes * Update info_gan.md * Updated index.md file * Updated index.md file * change links * Fixed typo * Delete Untitled.ipynb * Adding Vishaals comments * Adding Anirudh's comments * Fixed some bugs * Adding Anirudh's comments * some minor fixes * Remove obsolete memory cost example (#13235) * stop gap fix to let website builds through; scaladoc fix pending (#13298) * Fix Sphinx errors in box_nms (#13261) * Fix Sphinx errors (#13252) * Sphinx errors in Gluon (#13275) * Fix Sphinx python docstring formatting error. (#13194) * Fix Sphinx python docstring formatting error (#13021). Fixes #13021 * Update src/operator/nn/batch_norm.cc Co-Authored-By: frankfliu <frankfliu2000@gmail.com> * Visualization doc fix. Added notes for shortform (#13291) * Addressed "dumplicate object reference" issues (#13214) * Update basic_layers.py (#13299) * add url and license to clojure package project (#13304) * [Example] Add docstring for test optimizer and test score (#13286) * update the doc for test_optimizer * add docstring for test_score * [Example] Update cpp example README (#13280) * update the README to solve the library cannot find problem * fix the broken format * remove redundancy and broken format * add . * [Example]update NER example readme on module prediction (#13184) * update readme on module prediction * fix typo * update url * improve grammar * update link * [MXNET-1198] MXNet Java API (#13162) * [MXNET-984] Add Java NDArray and introduce Java Operator Builder class (#12816) * clean history and add commit * add lint header * bypass the java unittest when make the package * clean up redundant test * clean spacing issue * revert the change * clean up * cleanup the JMacros * adding line escape * revert some changes and fix scala style * fixes regarding to Naveen's comment * Java Inference api and SSD example (#12830) * New Java inference API and SSD example * Adding license to java files and fixing SSD example * Fixing SSD example to point to ObjectDetector instead of ImageClassifier * Make scripts for object detector independent to os and hw cpu/gpu * Added API Docs to Java Inference API. Small fixes for PR * Cosmetic updates for API DOCS requested during PR * Attempt to fix the CI Javafx compiler issue * Migrate from Javafx to apache commons for Pair implementation * Removing javafx from pom file * Fixes to appease the ScalaStyle deity * Minor fix in SSD script and Readme * Added ObjectDetectorOutput which is a POJO for Object Detector to simplify the return type * Removing Apache Commons Immutable Pair * Adding license to new file * Minor style fixes * minor style fix * Updating to be in scala style and not explicitly declare some unnecessary variables * NativeResource Management in Scala (#12647) (#12883) * 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) * Added unit tests for Resource Scope in Java (#12955) * Bumping down minimum java support from 8 to 7 (#12965) * [MXNET-984] Java NDArray Documentation Generation (#12835) * cherry pick javaDoc changes * update NDArray changes * refactoring change and merge all docGen in a single place * clean the scalastyle * take on Piyush nit * drop the comments * First pass at adding JavaDocs for new java api classes (#12963) * First pass at adding JavaDocs for new java api classes * Fix a scalastyle issue * Updating JavaDoc based on feedback * [MXNET-1160] add Java build/run example (#12969) * add example * clean up nit * find the pain point * add java tut into whitelist * Trigger CI * add java demo and split scala demo * address the comments * change the examples * fix the wrong configuration * Maven Surefire bug workaround (#13097) * use ResourceScope in Model/Trainer/FeedForward.scala (#12882) (#13164) * use ResourceScope in Model/Trainer/FeedForward.scala * add moveToOuterScope public method to move resources to a outerScope if it exists * fix memory leak in FeedForward.scala by making it a native resource and disposing argparams, auxParams in dispose() method * [MXNET-1187] Added Tutorial for Java under mxnet.io/docs/tutorials (#13183) * Added tutorial for Java installation on IntelliJ for mxnet.io website * Added correct image resources * Removed spurious quotes * Added java tutorial to whitelisting * Added community download edition link to intelliJ section * [MXNET-1202] Change Builder class into a better way (#13159) * applying changes for Builder functions * simplify the code structure * update docgen * follow Naveen's suggestion * apply comments to Param * clean up param build * change on the comments * add one description line * [MXNET-1041] Add Java benchmark (#13095) * add java benchmark * applied changes based on Piyush comments * applies Andrew's change * fix clojure test issue * update the statistic names * follow Naveen's instruction * [MXNET-918] [Introduce Random module / Refact code generation (#13038)][Cherry pick] (#13242) * [MXNET-918] Introduce Random module / Refact code generation (#13038) * refactor code gen * remove xxxAPIMacroBase (overkill) * CI errors / scala-style * PR review comments * clean up the duplicated code * add comments * Fixed missing break statement (#13257) * Java Benchmark failure (#13258) * patch fix * update ignore * rename getContext to bindToDevice * Update JavaBenchmark.java * Addressing PR feedback for merging Java API into master (#13277) * Addressing PR feedback for merging Java API into master * Changed constructors to package private instead of private * clean up the NDArray follow the comments (#13281) * [MXNET-1181] Added command line alternative to IntelliJ in install instructions (#13267) * Added command line alternative to IntelliJ * Removed the duplicate file * Fixed typos * Fixed minor command issue * add defaults and clean up the tests (#13295) * [MXNET-1187] Added Java SSD Inference Tutorial for website (#13201) * Added Java SSD Inference Tutorial for website * Added whitelisting to SSD tutorial * Address PR feedback * Marking intelliJ as optional * [MXNET-1182] Predictor example (#13237) * add initial commit * push back predictor * name fix and bug fix * update readme and script to run * minor fix * minor fix * fix on doc * update predictor * Reducing the length of setup tutorial (#13306) * enabling test_dropout after fixing flaky issue (#13276) * enabling test_dropout after fixing flaky issue * adding a check for positive seed * fix the flag (#13293) * Made fixes to sparse.py and sparse.md (#13305) * Fix descriptions in scaladocs for macro ndarray/sybmol APIs (#13210) * [Example] Gradcam- Fixing a link (#13307) * fixing gradcam * changed loading parameters code * fixing type conversions issue with previous versions of matplotlib * gradcam consolidation * creating directory structures in utils * changing location * empty commit * fix file lock issue * fix link * removing other commits * remove commit * Updated the Instructions for use of the label bot (#13192) * Updated Instructions for Label Bot * Updated instructions for mxnet-label-bot * Including myself as a contributor * Clarified usage of label bot * Fixed typos and instructions/examples have been made more clear * Added link for available labels * [MXNET-33] Enhance mkldnn pooling to support full convention (#11047) * fix mkldnn pooling to support full convention * backward with full convention * fix * add pooling test for full convention * add function for computing padding size * fix unit test * only support max-pooling * fix pooling bwd * address review comment * [MXNET-1213] add Cent OS build for Scala (#13279) * add centos build for Scala * migrate the build portion to docker * update build script and chmod +x * address Jenkins change * allow CentOS provide all depdencies * fix file lock issue (#13296) * modify code for working in gpu context. (#13302)

* Add mx.context.gpu_memory_info() to python api for flexible tests. * Add test_gluon_gpu.py:test_large_models to show cudnnFind headroom issue. * Output model sizes tried by test_gluon_gpu.py:test_large_models. * Fix perl interface to MXGetGPUMemoryInformation. * Increase difficulty of test_gluon_gpu.py:test_large_models. * Forgot a file in fix for perl. * Modify test to pass on no-cudnn CI runner. * Mutex algo reg updates, serialize cudnnFind calls. * Fix for cudnnFind memory headroom issue. * Fix cpplint. * Respond to reviewers comments. * Guard against improper MXNET_GPU_MEM_LARGE_ALLOC_ROUND_SIZE values. * Fix potentially unassigned var.

DickJC123 added 2 commits October 10, 2018 16:49

Add mx.context.gpu_memory_info() to python api for flexible tests.

7ad40a2

Add test_gluon_gpu.py:test_large_models to show cudnnFind headroom is…

94614a5

…sue.

DickJC123 requested review from anirudh2290 and szha as code owners October 12, 2018 02:12

sandeep-krishnamurthy added CUDA pr-awaiting-review PR is waiting for code review labels Oct 12, 2018

szha reviewed Oct 12, 2018

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tests/python/gpu/test_gluon_gpu.py Outdated Show resolved Hide resolved

DickJC123 added 3 commits October 12, 2018 14:23

Output model sizes tried by test_gluon_gpu.py:test_large_models.

8369e1e

Fix perl interface to MXGetGPUMemoryInformation.

aff8df4

Increase difficulty of test_gluon_gpu.py:test_large_models.

e95eb25

DickJC123 requested a review from sergeykolychev as a code owner October 13, 2018 00:18

DickJC123 added 5 commits October 12, 2018 17:32

Forgot a file in fix for perl.

7434d4b

Modify test to pass on no-cudnn CI runner.

7bf8d51

Mutex algo reg updates, serialize cudnnFind calls.

7f724c9

Fix for cudnnFind memory headroom issue.

7596ad6

Fix cpplint.

aa60af6

DickJC123 mentioned this pull request Oct 14, 2018

Memory leak when passing images of different dimensions with MXNET_CUDNN_AUTOTUNE_DEFAULT #12662

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sergeykolychev approved these changes Oct 15, 2018

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larroy mentioned this pull request Oct 22, 2018

Disabled: test_gluon_gpu.test_slice_batchnorm_reshape_batchnorm #12768

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KellenSunderland reviewed Oct 23, 2018

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KellenSunderland reviewed Oct 24, 2018

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KellenSunderland approved these changes Oct 24, 2018

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roywei approved these changes Oct 24, 2018

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szha reviewed Oct 24, 2018

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blac2kite reviewed Oct 24, 2018

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blac2kite reviewed Oct 25, 2018

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Respond to reviewers comments.

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larroy reviewed Oct 25, 2018

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src/storage/pooled_storage_manager.h Show resolved Hide resolved

KellenSunderland approved these changes Oct 25, 2018

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DickJC123 and others added 2 commits October 25, 2018 13:44

Guard against improper MXNET_GPU_MEM_LARGE_ALLOC_ROUND_SIZE values.

83df6d5

Merge branch 'master' into cudnnfind_usage_improvements

e043791

Fix potentially unassigned var.

810af44

KellenSunderland approved these changes Oct 25, 2018

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eric-haibin-lin merged commit ee5f699 into apache:master Oct 26, 2018

roywei mentioned this pull request Oct 26, 2018

enable batchnorm unit tests #12986

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larroy added a commit to larroy/mxnet that referenced this pull request Oct 26, 2018

Reenable tests that were failing due to CuDNN selection

459a28f

Fixed by apache#12804

larroy mentioned this pull request Oct 26, 2018

Reenable tests that were failing due to CuDNN selection #12987

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lebeg mentioned this pull request Nov 5, 2018

CudnnFind() usage improvements (v1.3.x) #13123

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CudnnFind() usage improvements #12804

CudnnFind() usage improvements #12804

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CudnnFind() usage improvements #12804

CudnnFind() usage improvements #12804

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