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Add seed_aug parameter for ImageRecordItr to fix random seed for default augmentation #11247
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…t module (apache#11140) * gluon import * gluon tests * shape issues. * remove the dim_change list * onnx backend tests * changes to match onnx op set version 7 * fix * lint fix * add new folder * fix * fix * rename test file * tile topk clip * more ops * fix * fix
Hi @wenyangchu , thanks a lot for your contribution! Would you mind adding a test to ensure that the behaviour is actually deterministic now and that everything is behaving as expected? |
* Important ndarray feature * merge generic function Invoke * Pass the Scala Style test * add Experimental tags * Change with NDArgs addition * change dir for Experimental tag * reTrigger CI * add Symbol Macros change * Add some workaround on NDArray * Simplify the base part * add changes on ND and Symbols... * avoid vars * add Symbol Macros * Trigger the CI * Trigger CI
Hi @marcoabreu , |
Hi @marcoabreu or any others, another question is that, I have a test failure in python3 cpu win and python3 MKL-DNN cpu. I have checked them and I do not think they have anything to do with my commit. Do you have a clue on this? Thanks! |
Don't use tempdir on osx since this is not mountable by default in Docker in osx
Hi, our tests are in https://github.com/apache/incubator-mxnet/tree/master/tests/cpp Yes, sorry, we are encountering quite a decent number of flaky tests. Ammending your commit should be sufficient to retrigger a new job. Sorry for the inconvenience. |
* Adding examples to list * Update links add demo * remove onnx-mxnet as it is now part of contrib * Trigger build * Adding Awesome-MXNet * Trigger build
* use nearest power of 2 for gpu memory pool sizes * add linear * add test
* disable scalatest on Spark * Kill the entire build * Disable test in test folder and add dummy label
* mkldnn support for quantization * fix output number in graph * update licsence * modify Jenkinsfile * modify Jenkinsfile * mkldnn has no int8 fc api, excluded_sym_names includes fc for cpu * add mkldnn uint8 pass for quantization graph * update ut * retrig ic * remove no mkldnn quantization test temp * seperate mkldnn quantization ut from gpu quantization ut * rm dev_id check for cpu * add mkl tests dictionary * resolve review comments * simplify DequantizeStorageType() logic * simplify quantize/quantized_conv storage type logic * Add mkldnn_OIhw4i16o4i type case (needed by int8) * INT8 conv/pooling: share with FP32 convolution/pooling class/function * minor indent changes * Remove unnecessary mkldnn_quantized_pooling-inl.h * Fix minor issue * Fix lint * delete duplicated data type * fix bugs and convert requantize data to NDArray * fix lint * fix requantize storgetype * fix requantize storge type * Fix coding style comments * Fix compile issue * Change to use quantized_dtype option to support uint8/int8 scenarios * fix gpu test quantization failure * Fix indent * fix quantized pooling param parser * Fix imagenet_gen_qsym.py option style * retrigger jenkins * retrigger again * trigger jenkins * Resolve further comments * share test code * remove unnecessary test code * add test_quantize_model for cpu * add comments in quantize_graph_pass.cc * jenkins * jenkins * improve coding style * improve coding style * Add naive CPU quantization test back and share quantization code between naive-CPU/MKLDNN/GPU * rename test_quantization_cpu.py to test_quantization_mkldnn.py * code style * trigger * Adjust variable naming for test quantization * add qdtype for quantized op test case to test/bypass all cases explicitly * change expressions to be consistent * revert unnecessary change
* add import_ for SymbolBlock * fix * Update block.py * add save_parameters * fix * fix lint * fix * fix * fix * fix * fix * Update save_load_params.md
* Fixes Scala memory leak (apache#10436)
* Adding the first set of Facebook OG tags to layout.html * Adding the direct link to the Facebook OG image * Re-arranging the og description tag * Changes to fix merge conflicts * Adding secure_url to the og:image tag * Adding the redundant og:image tag
* add test for mkldnnsum * add extra comment * fix verify * only run if mkldnn supported * divide size by size of type * filter out regular arrays * fix cond * add verify mes * filter views * different outputs arrays * move print message * add in place test * update copy fn * refactor copyfrom * use arr.copy instead of tmpmemmg * use InitMKLDNNArray helper * fix params * pass correct type to copyfrom * add print message for inplace sum * remove copyfrom refactor * remove redundant header * remove extra line * fix lint * retrigger
* Improve hybridblock doc * fix
* disable testcase test_gru_bidirectional temporarily * retrigger the build and see if permission denied /efs-ccache can pass
…rs() (apache#11210) * flipping official and alternative * Update block.py * Add new line * fix trailing whitespaces * clarify docs * Update block.py * Update block.py * fix typo * trailing whitespace * Trigger build
Hi @marcoabreu or others, the c++ tests for iterators in mxnet are not there and iterator's code is entirely in cpp file which is very difficult to test in c++ without refactoring. I found other tests for c++ iterators were done in python. I follow the same way to perform tests on this augmentation seed. Is it correct that the following document should be updated automatically after merging this PR? |
* Enable shared ccache * Increase cache size * Don't fail if EFS ccache is not available
* improve transforms.Resize * fix * Trigger CI * Trigger CI * improve * Trigger CI * Trigger CI * fix unittest * keep_ratio is false by default, to keep consistency
Yes, this will automatically update after merging. A python test is totally fine as well |
* add count_include_pad argument * add cound_include_pad in cudnn pooling and corresponding tests * add gluon support for the new option * switch to built-in functions for artificial NaN * add doc for gluon * change isAvg/getAvg to is_avg/get_avg
…e#11316) * MXNET_FORCE_ADDTAKEGRAD to disable AddTakeGradLargeBatchCaller If MXNET_FORCE_ADDTAKEGRAD is set, EmbeddingOpBackward will always use AddTakeGrad independently of gradient input and output shape * Read MXNET_FORCE_ADDTAKEGRAD to a static variable
…am.save(). Fix trainer init_kvstore (apache#11266) * clip sparse grad. fix _reduce for rowsparse param * fix kvstore init for local kv * trigger
src/io/image_aug_default.cc
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@@ -136,6 +139,8 @@ struct DefaultImageAugmentParam : public dmlc::Parameter<DefaultImageAugmentPara | |||
DMLC_DECLARE_FIELD(pad).set_default(0) | |||
.describe("Change size from ``[width, height]`` into " | |||
"``[pad + width + pad, pad + height + pad]`` by padding pixes"); | |||
DMLC_DECLARE_FIELD(seed_aug).set_default(-1) |
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better use dmlc::optional() and check has_value() rather than compare with -1.
Literally we can use any number as seed.
* Add first draft of profiler tutorial * Minor changes - Add images from web-data - Add <!--notebook-skip-line--> * Language corrections * Minor changes - Fix image URLs - Fix formatting of output * Minor changes - Add download button. - Hide profile_stats.png in notebook. * Add tutorial to index. * Add tutorial to tests. * Add a note about nd.waitall() * Remove the example build command. Link to installation page is sufficient. * Fix typo * Include info about env variables related to profiling * Add a further reading section
…11302) * Add ccache reporting to CI * Restructure dockcross dockerfiles to fix caching
* add resnet augmentation * add test * fix scope * fix warning * fix lint * fix lint * add color jitter and pca noise * fix center crop * merge * fix lint * Trigger CI * fix * fix augmentation implementation * add checks for parameters * modify training script * fix compile error * Trigger CI * Trigger CI * modify error message * Trigger CI * Trigger CI * Trigger CI * improve script in example * fix script * clear code * Trigger CI * set min_aspect_ratio to optional, move rotation and pad before random resized crop * fix * Trigger CI * Trigger CI * Trigger CI * fix default values * Trigger CI
I think I have flaky test again |
* add softmax imporvement * reuse CheckAxis code * update comment * add tests with negative axis
see if rebase fix the flaky test |
@wenyangchu thanks for the contribution, this is merged. |
…ult augmentation (apache#11247) * add seed_aug parameter for ImageRecordItr to fix random seed for augmentation * remove white space * add test * fix test * improve according to review: using dmlc::optional and has_value() * missing header * change data type and way to get value
…ult augmentation (apache#11247) * add seed_aug parameter for ImageRecordItr to fix random seed for augmentation * remove white space * add test * fix test * improve according to review: using dmlc::optional and has_value() * missing header * change data type and way to get value
Description
Add random seed control to augmentations in io.ImageRecordIter.
Motivation: I am doing a medical imaging project where reproducibility of the complete training procedure is important for a legal purpose.
Checklist
Essentials
Please feel free to remove inapplicable items for your PR.
Changes
(Add seed_aug parameter for ImageRecordItr to fix random seed for default augmentation)
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