Update #2
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Update #2
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* add length check * fix style * fix * modify as reviews * fix style
…support (#4941) * Support directly import pytorch and keras model * support more torch forecaster * add a autoformer forecaster * add a ut file * add a test class Co-authored-by: Xinyi Zhang <[email protected]>
* init * update * update
…ta (#4996) * fix all_reduce for pytorch estimator fitting with validation_data * fix style
* add PPMLContextWrapper.scala * add method load_keys * add init context with conf * fix java map to scala map * add read function * update for debug * update for debug * py args to scala args * update * add api package * update * add import * update * del old file * del files for test * revert * add textFile & init method * update * add py textfile method * update * get DefaultMinPartitions * update * update * fix init context with SparkConf * fix java list to scala list * update test Co-authored-by: Zhou <[email protected]>
* add BigDL-Nano PyTorch Quickstart * Update BigDL-Nano PyTorch Quickstart * Update BigDL-Nano PyTorch Quickstart * Add Nano inference quickstart - add inference onnx quickstart - add inference openvino quickstart - add quantization inc quickstart - add quantization inc onnx quickstart - add quantization openvino quickstart * update quickstart * update quickstart * Add Nano quantization quickstart * update nano docs * Update docs * Update Nano OpenVINO tutorial * Update * Update index.md * Resize Images * Resize Images * Update * Update Nano docs * Update nano documents * Update doc & notebook * clear output of cells * add unit tests for tutorial notebooks * fix errors in yaml * fix error in notebook * reduce quantization time * Update yaml * Add unit test for tutorial * Add tests for tutorial * fix shell
* install java & scala & spark in kms-util image
* remove scala
* get jsonObject from response
* update decrypt parameter name
* download bigdl lib
* remove spark-encrypt-io.jar since ppml.jar is already under ${BIGDL_HOME}/jars/
* update Java classpath
* Update build-docker-image.sh
* Update Dockerfile
* Update Dockerfile
* use ubuntu 20.04
* Update Dockerfile
* Update Dockerfile
* Update Dockerfile
* update bionic to focal
* remove log4j 1.x jars
* ADD log4j2.xml
* remove splitandencrypt
* fix issues of `save_checkpoint` and test it more strictly * extract the test of `save_checkpoint` to a new unit test
* Data lifecycle * HDFS Security * Spark Security * K8S Security
* forecaster support dataloader inputs * move __all__ * add dataloader support * fix some issue * move torch.no_grad * remove redundant "()" * sync split onnxrt
* modify predict method * extend inference method * sync evaluate method * change params description * remove training
* trusted_big_bata_analytics_and_ml.md -> trusted_big_data_analytics_and_ml.md
fix hpo api docs
* fix docs * add resources
* fix exception * style * remove duplicate * exclude dienl
* Add support for channels_last * Add license * Fix code style * fix code style * fix code style and refactor * fix code style * fix code style * fix code style * add correctness test for channels last * Update datasets for correctness to 2 channels * remove comments * Add comment * fix tf inc metric format * undo commit * re-run actions
* add device option to openvino model * add openvino api * reformat * add bigdl.nano.openvino
…culation (#5126) * modify objective to enable MO-HPO * add callback * move hposearcher and add reset callback * enable basic latency HPO for single and multi preocess * fix self.log * fix bug of metric * delete useless line * fix bug of objective and add ut * fix bug, add check and ut for directions * fix bug of reset error * update code to fix style * update hpo_api, add kwargs of num_processes
* add PPMLContextWrapper.scala * add method load_keys * add init context with conf * fix java map to scala map * add read function * update for debug * update for debug * py args to scala args * update * add api package * update * add import * update * del old file * del files for test * revert * first commit * update * update * update * update Co-authored-by: Zhou <[email protected]>
add ipex and ddp support for lightning-lite
* fix the issue of ray backend and its test
* add the result to readme. add the validation dataset when training. modify the metrics calculation function. add the scheduler. modify the torch_distributed backend to ray backend. add the brainMRI to the test script. * delete test script. * modify the print content * change the ray backend to torch_distributed. * change the ray backend to torch_distributed. * modify the pip command
* Move attestation doc to end of doc * Update Spark Pi conf * Update XGBoost conf * Update Cifar conf
* add brainMRI test * add the requirements * delete other test, only brainMRI * change the torch_distributed backend to ray backend * add the ray dependence * add the other example * add the pillow package * add the tabulate package * change the gym version * add 2 packages * change the gym version and dependence * add tree package * add tree package * add the version of ray * add the version of ray * add the version of ray * add the version of ray * add the version of ray * add the tensorflow * add the atari * add the atari version * add the torchmetrics package * add the pyarrow * update the pyarrow version * update the pyarrow version * update the pyarrow version * delete tensorflow dependence * change the zoo to bigdl * delete tensorboard package. * delete tensorboard package. * add the torch version * change the torch version * add newline
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