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[feature/Pipeline] PipelineConfig #318
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…P,IC,OD pipelines (#317) * base commit - make pydantic a general req * Pipeline base class implementation (#315) * Pipeline base class implementation * constructor default values * __call__ inputs/outputs parsing + validation * documentation * pipeline 'alias' argument * review fixes * [feature/Pipeline] PipelineConfig (#318) * PipelineConfig pydantic model + Pipeline.from_config * Pipeline.to_config() function * [feature/Pipeline] refactor deepsparse.server to use deepsparse.Pipeline (#319) * PipelineConfig pydantic model + Pipeline.from_config * Pipeline.to_config() function * refactor deepsparse.server to use deepsparse.Pipeline * review nit fix remove files for separate feature * Image Classification Pipeline Integration (#322) * Create a command line installable for image classification pipeline * Intermediate Commit * Image Classification pipeline implementation * Remove faulty entry point * Apply suggestions from @bogunowicz * Changed function name from `_infer_input_shape` to `_infer_image_shape` * Add validation script for Image Classification pipeline (#328) * Add Validation Script for Image Classification Models * Update pipelines and corresponding schemas to work with numpy arrays * Bugfix if prediction to be converted to int if it's a string * Update docstring * Update src/deepsparse/image_classification/validation_script.py * [feature/Pipeline] fixes for ic-pipelines implementation (#336) * fixes for ic-pipelines implementation * sparsezoo support Co-authored-by: Benjamin Fineran <bfineran@users.noreply.github.com> * Update src/deepsparse/pipeline.py * quality * [feature/Pipeline] deepsparse.Pipeline implementations for transformers (#320) * add parsing layer for deepsparse.Pipeline for implementation flexibility * initial deepsparse.transformers.pipelines implementation base class + text_classification * make tokenizer and config attributes 'public', but not properties * decorator fix * use kwargs for transforemrs pipeline parent class args * token classification impl * token classification output schema parsing * quality * question answering pipeline impl * fixes for pipline impls - bs1 santity check inferences working * [feature/Pipeline] deprecate and migrate existing transformers pipelines (#335) * remove old pipeline pathway and files, add API for deprecated pathway * migrate eval_downstream * update readme * server pipeline input fix * hf license attribution * `YOLO` pipeline integration for deepsparse (#327) * Added YOLO pipeline Add an installable for yolo integration Added a task for YOLO To install run: * `pip install --editable "./[yolo]"` * Changed function name from `_infer_input_shape` to `_infer_image_shape` * Update docstring * Comments from @bogunowicz * Moved COCO classes to a file * Adds support to annotate images using YOLO (#332) * Adds support to annotate images using YOLO * Makes `YOLOOutput` iterable * Returns a named tuple of image outputs when `next` is called on `YOLOOutput` * Adds an annotate function to yolo utils * Adds an annotation script, testing + minor fixes remain * Intermediate-commit * Intermediate WIP * Working State with required bugfixes * style fixes Co-authored-by: Benjamin <ben@neuralmagic.com> Co-authored-by: Benjamin <ben@neuralmagic.com> * [feature/Pipeline] rename input/output _model to _schema (#340) * rename input/output _model to _schema * refactor yolo pipeline * default model support for Pipeline.register (#339) * default model support for Pipeline.register * update default stubs for transformers and IC * yolo default model * minor fixes * model->schema for server Co-authored-by: Rahul Tuli <rahul@neuralmagic.com>
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* SparseServer.UI example [WIP] (#308) * add megasparse dir * edited readme to support DS integration * small edit to docstring * edited settings.py module so only 2 models are loaded. * added more context to the readme about adding more models. * fixed image * added different host to streamlit client as default * quality check edits * quality check commit * passing copyright quality check * content edits * rename dir to sparseserver-ui * added new config file for quick start * edited multipipelineclient in settings.py * changed name of config file * edited model stubs * edited readme * added dependency pins * changed server pin * edited model choice logic * altered front-end features * style update * renamed samples file * added variant descriptions * style changes * edited samples.py module * style changes * added new pic * edited README * updated readme cmds * SparseServer edit (#314) * edit number of models * edit settings.py * edit readme * Update label mapping for deepsparse.transformers.eval_downstream (#323) * Update label mapping for deepsparse.transformers.eval_downstream * Fix MNLI as well * bump up main to 0.13.0 (#313) Co-authored-by: dhuang <dhuang@dhuangs-MacBook-Pro.local> * AWS Sagemaker example integration (#305) * AWS Sagemaker example integration * documentation, sample config, dockerfile fixes * fix ecr repo name * readme code changes from testing * Update huggingface-transformers/README.md with new models (#329) * Update README.md (#330) * Update README.md various grammatical edits additional edits for section headline consistency * Topology file for HB120rs_v3 (#334) * Topology file for HB120rs_v3 Specifies core-per-CCX grouping for HB120rs_v3 VM's, used by multi-process script. * Update README.md to reference Azure topo file * Move all benchmarking within deepsparse/benchmark/ (#333) * Move all benchmarking within deepsparse/benchmark/ * Update benchmark_model * Expose results at benchmark base * isort * Skip flake8 * server integration check bug fix (#331) * server integration check bug fix need to verify integration is set before calling `integration.lower()` * respond to review - click choice * add default integration val to server config schema (#337) * deepsparse.Pipeline - generic pipeline, deepsparse.server support, NLP,IC,OD pipelines (#317) * base commit - make pydantic a general req * Pipeline base class implementation (#315) * Pipeline base class implementation * constructor default values * __call__ inputs/outputs parsing + validation * documentation * pipeline 'alias' argument * review fixes * [feature/Pipeline] PipelineConfig (#318) * PipelineConfig pydantic model + Pipeline.from_config * Pipeline.to_config() function * [feature/Pipeline] refactor deepsparse.server to use deepsparse.Pipeline (#319) * PipelineConfig pydantic model + Pipeline.from_config * Pipeline.to_config() function * refactor deepsparse.server to use deepsparse.Pipeline * review nit fix remove files for separate feature * Image Classification Pipeline Integration (#322) * Create a command line installable for image classification pipeline * Intermediate Commit * Image Classification pipeline implementation * Remove faulty entry point * Apply suggestions from @bogunowicz * Changed function name from `_infer_input_shape` to `_infer_image_shape` * Add validation script for Image Classification pipeline (#328) * Add Validation Script for Image Classification Models * Update pipelines and corresponding schemas to work with numpy arrays * Bugfix if prediction to be converted to int if it's a string * Update docstring * Update src/deepsparse/image_classification/validation_script.py * [feature/Pipeline] fixes for ic-pipelines implementation (#336) * fixes for ic-pipelines implementation * sparsezoo support Co-authored-by: Benjamin Fineran <bfineran@users.noreply.github.com> * Update src/deepsparse/pipeline.py * quality * [feature/Pipeline] deepsparse.Pipeline implementations for transformers (#320) * add parsing layer for deepsparse.Pipeline for implementation flexibility * initial deepsparse.transformers.pipelines implementation base class + text_classification * make tokenizer and config attributes 'public', but not properties * decorator fix * use kwargs for transforemrs pipeline parent class args * token classification impl * token classification output schema parsing * quality * question answering pipeline impl * fixes for pipline impls - bs1 santity check inferences working * [feature/Pipeline] deprecate and migrate existing transformers pipelines (#335) * remove old pipeline pathway and files, add API for deprecated pathway * migrate eval_downstream * update readme * server pipeline input fix * hf license attribution * `YOLO` pipeline integration for deepsparse (#327) * Added YOLO pipeline Add an installable for yolo integration Added a task for YOLO To install run: * `pip install --editable "./[yolo]"` * Changed function name from `_infer_input_shape` to `_infer_image_shape` * Update docstring * Comments from @bogunowicz * Moved COCO classes to a file * Adds support to annotate images using YOLO (#332) * Adds support to annotate images using YOLO * Makes `YOLOOutput` iterable * Returns a named tuple of image outputs when `next` is called on `YOLOOutput` * Adds an annotate function to yolo utils * Adds an annotation script, testing + minor fixes remain * Intermediate-commit * Intermediate WIP * Working State with required bugfixes * style fixes Co-authored-by: Benjamin <ben@neuralmagic.com> Co-authored-by: Benjamin <ben@neuralmagic.com> * [feature/Pipeline] rename input/output _model to _schema (#340) * rename input/output _model to _schema * refactor yolo pipeline * default model support for Pipeline.register (#339) * default model support for Pipeline.register * update default stubs for transformers and IC * yolo default model * minor fixes * model->schema for server Co-authored-by: Rahul Tuli <rahul@neuralmagic.com> * Remove: startlette dep (#338) * Update src/deepsparse/version.py Co-authored-by: Ricky Costa <79061523+InquestGeronimo@users.noreply.github.com> Co-authored-by: Michael Goin <michael@neuralmagic.com> Co-authored-by: dhuangnm <74931910+dhuangnm@users.noreply.github.com> Co-authored-by: dhuang <dhuang@dhuangs-MacBook-Pro.local> Co-authored-by: Benjamin Fineran <bfineran@users.noreply.github.com> Co-authored-by: Jeannie Finks <74554921+jeanniefinks@users.noreply.github.com> Co-authored-by: Govind Ramnarayan <77341216+govindr-nm@users.noreply.github.com> Co-authored-by: Rahul Tuli <rahul@neuralmagic.com> Co-authored-by: Konstantin Gulin <66528950+KSGulin@users.noreply.github.com>
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(main feature: #317)
pydantic
PipelineConfigto serialize arguments tocreateintended usage is for users to easily be able to construct and save pipeline arguments as script inputs, and to be a part of configurations for servers with multiple models.example usages: