Torch handler Unit test : AttributeError: 'bytes' object has no attribute 'metrics' #772
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abishekchiffon
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…attribute 'metrics'
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…te 'metrics' (#774) Co-authored-by: Aaqib <maaquib@gmail.com>
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* - updated image classifier default handler - updated custom resnet and mnist handlers - update docs * documentation update - removed stale Transformer_readme.md * updated docs * Doc restructure and code fixes * Updated example as per fix in default handlers * Enhanced base and custom handler examples * Missing checking for manifest * Fixed some typos * Removed commented code * Refactor BaseHandler * Adding in unit tests * Fixed gitignore in this branch * Fix a bug with Image Segmenter * Updated Object Detector to reuse functionality; consistency * Fix pylint errors * Backwards compat for index_names.json * Fixed Image Segmenter again * Made the compat layer in text actually compat. * Removed batching from text classifier * Adding comments per review. * Fixing doc feedback. * Updating docs about batching. * Initial commit of envelopes. * Got the end-to-end working * Undoing a change for local stuff. * Fixing a few broken tests. * Fixed error introduced due to conflict resolution via web based merge tool * Corrected code comment * - Updated Object detection & text classification handlers - updated docs * fixed python linting errors * updated index to name json text classifier * fixed object detector handler for batch support * Fixed the batch inference output * update expected output as per new handler changes * updated text classification mar name in sanity suite * updated text classifier mar name and removed bert scripted models * updated model zoo with new text classification url * added model_name in while registering model in sanity suite * updated text classification model name * added upgrade option for installing python dependencies in install utils * added upgrade option for installing python dependencies and extra numpy package in regression suite * refectored pytests in regression suite for better performance and reporting * Merge upstream * Got the end-to-end working * Merge upstream (2) * Fixing a few broken tests. * Undoing a bad merge. * minor fix in torch-archiver command * reverted postprocess removal * updated mar files in model zoo to use updated handlers * updated regression suite to use updated mar files * suppressed pylint warning in UT * fixed resnet-152 mar name and expected output * updated inference tests data - added tolerence value for resent152 models * Added custom handler in vgg11 example (#559) * added custom handler for vgg11 * added readme for vgg11 example * fixed typo in readme * updated model zoo * reverted back changes for scripted vgg11 mar file * added vgg11 model to regression test suite * disabled pylint check in UT * updated expected response for vgg11 inference in regression suite * updated expected response for vgg11 inference in regression suite * updated expected for densenet scripted * Fixing bad file format * Fixed the 'no newman npm' issue in regression test suite, solution suggested in PR 757 * Fixed the metrics bug #772 for test_envelopes Co-authored-by: Shivam Shriwas <shivamshriwas21@gmail.com> Co-authored-by: Harsh Bafna <harshbafna619@gmail.com> Co-authored-by: dhaniram kshirsagar <dhaniram_kshirsagar@persistent.com> Co-authored-by: dhaniram-kshirsagar <26479924+dhaniram-kshirsagar@users.noreply.github.com> Co-authored-by: Henry Tappen <htappen@gmail.com> Co-authored-by: harshbafna <harsh_bafna@persistent.co.in> Co-authored-by: Aaqib <maaquib@gmail.com> Co-authored-by: Henry Tappen <htappen@google.com> Co-authored-by: Geeta Chauhan <4461127+chauhang@users.noreply.github.com>
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* - updated image classifier default handler - updated custom resnet and mnist handlers - update docs * documentation update - removed stale Transformer_readme.md * updated docs * Doc restructure and code fixes * Updated example as per fix in default handlers * Enhanced base and custom handler examples * Missing checking for manifest * Fixed some typos * Removed commented code * Refactor BaseHandler * Adding in unit tests * Fixed gitignore in this branch * Fix a bug with Image Segmenter * Updated Object Detector to reuse functionality; consistency * Fix pylint errors * Backwards compat for index_names.json * Fixed Image Segmenter again * Made the compat layer in text actually compat. * Removed batching from text classifier * Adding comments per review. * Fixing doc feedback. * Updating docs about batching. * Initial commit of envelopes. * Got the end-to-end working * Undoing a change for local stuff. * Fixing a few broken tests. * Fixed error introduced due to conflict resolution via web based merge tool * Corrected code comment * - Updated Object detection & text classification handlers - updated docs * fixed python linting errors * updated index to name json text classifier * fixed object detector handler for batch support * Fixed the batch inference output * update expected output as per new handler changes * updated text classification mar name in sanity suite * updated text classifier mar name and removed bert scripted models * updated model zoo with new text classification url * added model_name in while registering model in sanity suite * updated text classification model name * added upgrade option for installing python dependencies in install utils * added upgrade option for installing python dependencies and extra numpy package in regression suite * refectored pytests in regression suite for better performance and reporting * Merge upstream * Got the end-to-end working * Merge upstream (2) * Fixing a few broken tests. * Undoing a bad merge. * minor fix in torch-archiver command * reverted postprocess removal * updated mar files in model zoo to use updated handlers * updated regression suite to use updated mar files * suppressed pylint warning in UT * fixed resnet-152 mar name and expected output * updated inference tests data - added tolerence value for resent152 models * Added custom handler in vgg11 example (#559) * added custom handler for vgg11 * added readme for vgg11 example * fixed typo in readme * updated model zoo * reverted back changes for scripted vgg11 mar file * added vgg11 model to regression test suite * disabled pylint check in UT * updated expected response for vgg11 inference in regression suite * updated expected response for vgg11 inference in regression suite * updated expected for densenet scripted * Fixing bad file format * Request envelope for KFServing * Modified Response of KFServing Envelope * KFServing envelope, classifier modified * fixed text variable issue in text_classifier_kf * Added kfserving envelope support for docker * Kfserving api changes to handle predict * Envelope modified for kFServing_V1 * text classifier captum with kfv1 explain endpoint * Added captum in mnist example * KFServing V1 endpoints with Captum for mnist and Text classifier * Captum changes in BERT, mnist and text class * Added mnist example for KFserving Transformers * Added KFserving wrappers and dockerfile * Modified kfserving dockerfile and entrypoint * Modified kfserving dockerfile and entrypoint to accept multiple arguments * Modified kf envelope and mnist handler for kf Transformer * Added load unload in kfserving wrapper * Modified docker files for kfserving load unload * Modified kfserving wrapper's dockerfile * Modified inference address and port in kfwrapper * Fixed the infaddress in kfwrapper * Modified MODEL_STORE and CONFIG_PATH location in kfwrapper for image testing * Response changes in base handler and kf envelope * Refactored base_handler and text_classifier_kf * Moved kf response from Base handler to postprocess of kf handlers * Bert fixed, removed load,unload in kfserving_wrapper * Refactored kfenvelope, mnist, base, text_classifier handlers with doc strings * Added separate bert handlers for kf and ts * Refactored kf_Bert * Fixed the Can't instantiate abstract class error in bert * Refactored kf_wrapper and relocated to kubernetes folder * Modified the readme for kfserving v1, relocated kf docker files to k8s folder * removed explain from envelope and base_handler * Contains kf v1_beta1 inference, with kf_wrapper * Fixed config.properties * Fixed context in text_handler * Fix the text_classifier_kf default handler's mar creation bug * Fixed InferenceRequestHandler sanity error * Removed remnant explain lines in vision and image classifier * kfwrapper log error fixed * Unification of kf and torchserve handlers * Handled unicode issue in bert to unify KF and TS handlers * Added kfserving image transformer to help image inference * postprocess function modified for kf request in text classifier - handles string of bytesarray in vision handler * Clean the handlers and envelope * Moved response for kfserving from postprocess to envelope * Fixed kf postprocess of text_classifier and bert * Unified dockerfile for kfserving and torchserve * Moved the unified KF and TS dockerfile to docker folder * Refactored kf image transformer * Dockerfile modified for kfserve and serve unification * modified kf and ts unified docker and entrypoint * modified docker entrypoint * Individual dockerfiles artifacts for kfserving and torchserve * Added kfserving in readmes of mnist, bert, text_class * Added mnist and mnist_kf test cases * Modified unnecessary array conversion in image_transform * Fixed kf dockerfile change directory * Fixed the 'no newman npm' issue in regression test suite, solution suggested in PR 757 * Fixed the gradle error in kf_infer api * Fixed the 'no newman npm' issue in the regression test suite, solution suggested as per PR #757 * fix: pylint and CI issue on running torchserve_sanity cuda101 * Removed kfserving mnist and bert handler files * Added bert, mnist and text classifier json inputs for kfserving curl requests * Modified the Readme files with with kfserving functionalities for mnist, text_classifier and bert * Modified kfserving dockerfile and config.properties * Moved kf request json files to kf_request_json folder and modified the readmes accordingly * Removed kfserving docs from the original readmes * KFServing files relocated and delta changes added to the kfserving readmes * Removed readme from kf_predictor_docker folder * Modified mnist handler to remove comments * Added img2bytearray conversion script for image_classifier * Unit test Mockcontext cleaned * Mock context cleaned * Mock context cleaned * Transformer handler cleaned * Fixed the metrics bug #772 for test_envelopes * cleaned test_envelope * Minor fixes in the image transformer and kfserving wrapper * Pylint fixes and doc string changes in the kfserving wrapper and kfserving image transformer Co-authored-by: Shivam Shriwas <shivamshriwas21@gmail.com> Co-authored-by: Harsh Bafna <harshbafna619@gmail.com> Co-authored-by: dhaniram kshirsagar <dhaniram_kshirsagar@persistent.com> Co-authored-by: dhaniram-kshirsagar <26479924+dhaniram-kshirsagar@users.noreply.github.com> Co-authored-by: Henry Tappen <htappen@gmail.com> Co-authored-by: harshbafna <harsh_bafna@persistent.co.in> Co-authored-by: Aaqib <maaquib@gmail.com> Co-authored-by: Henry Tappen <htappen@google.com> Co-authored-by: Geeta Chauhan <4461127+chauhang@users.noreply.github.com>
maaquib
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…#809) * - updated image classifier default handler - updated custom resnet and mnist handlers - update docs * documentation update - removed stale Transformer_readme.md * updated docs * Doc restructure and code fixes * Updated example as per fix in default handlers * Enhanced base and custom handler examples * Missing checking for manifest * Fixed some typos * Removed commented code * Refactor BaseHandler * Adding in unit tests * Fixed gitignore in this branch * Fix a bug with Image Segmenter * Updated Object Detector to reuse functionality; consistency * Fix pylint errors * Backwards compat for index_names.json * Fixed Image Segmenter again * Made the compat layer in text actually compat. * Removed batching from text classifier * Adding comments per review. * Fixing doc feedback. * Updating docs about batching. * Initial commit of envelopes. * Got the end-to-end working * Undoing a change for local stuff. * Fixing a few broken tests. * Fixed error introduced due to conflict resolution via web based merge tool * Corrected code comment * - Updated Object detection & text classification handlers - updated docs * fixed python linting errors * updated index to name json text classifier * fixed object detector handler for batch support * Fixed the batch inference output * update expected output as per new handler changes * updated text classification mar name in sanity suite * updated text classifier mar name and removed bert scripted models * updated model zoo with new text classification url * added model_name in while registering model in sanity suite * updated text classification model name * added upgrade option for installing python dependencies in install utils * added upgrade option for installing python dependencies and extra numpy package in regression suite * refectored pytests in regression suite for better performance and reporting * Merge upstream * Got the end-to-end working * Merge upstream (2) * Fixing a few broken tests. * Undoing a bad merge. * minor fix in torch-archiver command * reverted postprocess removal * updated mar files in model zoo to use updated handlers * updated regression suite to use updated mar files * suppressed pylint warning in UT * fixed resnet-152 mar name and expected output * updated inference tests data - added tolerence value for resent152 models * Added custom handler in vgg11 example (#559) * added custom handler for vgg11 * added readme for vgg11 example * fixed typo in readme * updated model zoo * reverted back changes for scripted vgg11 mar file * added vgg11 model to regression test suite * disabled pylint check in UT * updated expected response for vgg11 inference in regression suite * updated expected response for vgg11 inference in regression suite * updated expected for densenet scripted * Fixing bad file format * Request envelope for KFServing * Modified Response of KFServing Envelope * KFServing envelope, classifier modified * fixed text variable issue in text_classifier_kf * Added kfserving envelope support for docker * Kfserving api changes to handle predict * Envelope modified for kFServing_V1 * text classifier captum with kfv1 explain endpoint * Added captum in mnist example * KFServing V1 endpoints with Captum for mnist and Text classifier * Captum changes in BERT, mnist and text class * Added mnist example for KFserving Transformers * Added KFserving wrappers and dockerfile * Modified kfserving dockerfile and entrypoint * Modified kfserving dockerfile and entrypoint to accept multiple arguments * Modified kf envelope and mnist handler for kf Transformer * Added load unload in kfserving wrapper * Modified docker files for kfserving load unload * Modified kfserving wrapper's dockerfile * Modified inference address and port in kfwrapper * Fixed the infaddress in kfwrapper * Modified MODEL_STORE and CONFIG_PATH location in kfwrapper for image testing * Response changes in base handler and kf envelope * Refactored base_handler and text_classifier_kf * Moved kf response from Base handler to postprocess of kf handlers * Bert fixed, removed load,unload in kfserving_wrapper * Refactored kfenvelope, mnist, base, text_classifier handlers with doc strings * Added separate bert handlers for kf and ts * Refactored kf_Bert * Fixed the Can't instantiate abstract class error in bert * Refactored kf_wrapper and relocated to kubernetes folder * Modified the readme for kfserving v1, relocated kf docker files to k8s folder * Created unified text_classifier handler for kf and TS with captum * Added explanations api for torchserve * Created unified mnist handler for kf and TS with captum * Added end to end readme to run torchserve in kfserving predictor * Created the Unified bert handler for KFserving and TS * Added kfserving image transformer with explain * Modified kfserving wrapper and predictor_docker to reflect infer changes * Removed unneccessary image_transform code in kfserving transformer * Modified describe api and inference_open_api json files for gradle error * Build gradle issue fix: file formatting, syntax formatting * Added torchserve explanations curl request and modified end to end kfserving url in the readmes * Cleaned the code and made it pylint compatible * Modified ts branch name in kf_predictor docker file * Modified kf_predictor_docker readme to add explain request * Add torchserve json request files for bert, mnist, text_classifier * Moved kf request json files to kubernetes/kf_request_json folder * Added explainations unit test unders ts/torch_handler/unit_test/image_classifier * Modified Readmes to change the path of kfserving json files * Fix for unit test metrics issue in mock context * Fix no newman error in regression test suite * Added captum in requirements cpu and gpu * Removed the separate handlers of kfserving * Modified run_unit_test.sh * Cleaned mock context * Added utils in text_classifier * Added captum explanations to the readmes of mnist, text_classification and bert * KFServing files relocated and delta changes added to the kfserving readmes * Removed readme from kf_predictor_docker folder * Modified kfserving readmes * Modified KFserving readme and added img2bytearray script * handler readme modifications and text_classifier captum note * Modified img2bytearray in kfserving readme * Added captum explanations example and readmes for bert * Added captum explanations readme * Bert captum visualization image rendered in notebook * Updated bert Readme with captum approach * Captum folder with visualization implementation guide for mnist and bert * Modified the mnist, bert notebooks and readmes * Removed duplicate captum visualization notebook files, fixed text_handler pylint issue * Added captum in custom_service.md, Added kf_v1 health check api in the docs * Separated the envelope test in run_unit_tests * Fixed the metrics bug #772 for test_envelopes * Fixed pylint newline in test_envelope * Fixed pylint torchserve test_envelope.py * Moved captum requirements from torch.txt to common.txt * Added comments in listinferenceapi for kfserving v1 api * Modified the comment in listinferenceapi * Format error in listinferenceapi for comment * Formatted Opentutils * Fixed pylint and changed doc string in Kfserving * Added Unit testcases for kf and captum apis in frontend Co-authored-by: Shivam Shriwas <shivamshriwas21@gmail.com> Co-authored-by: Harsh Bafna <harshbafna619@gmail.com> Co-authored-by: dhaniram kshirsagar <dhaniram_kshirsagar@persistent.com> Co-authored-by: dhaniram-kshirsagar <26479924+dhaniram-kshirsagar@users.noreply.github.com> Co-authored-by: Henry Tappen <htappen@gmail.com> Co-authored-by: harshbafna <harsh_bafna@persistent.co.in> Co-authored-by: Aaqib <maaquib@gmail.com> Co-authored-by: Henry Tappen <htappen@google.com>
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Context
The handler unit tests in the ts/torch_handler folder fails in the master branch.
It fails with the following error "AttributeError: 'bytes' object has no attribute 'metrics'" in the base_handler handle function at the line.
metrics = self.context.metrics, when you run ./run_unit_test.sh
Your Environment
[If public url then provide link.]:
Expected Behavior
The unit tests should all pass, without any metrics issue.
Current Behavior
AttributeError: 'bytes' object has no attribute 'metrics'
Possible Solution
Fix the mock_context and add metrics.
Steps to Reproduce
Failure Logs [if any]
unit_tests_metrics_master.log
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