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* Copying new seedot files

* Added batching for compiling large programs without blowing up memory

* Updated README.md to FastGRNN example

* Fixed copyright messages, included m3 codegen files

* Removed unnecessary commented code

* Added high level comments and added dlx executables

* Fixed formatting of C/C++ files

* Adding architecture diagram

* Adding tutorial on extending the compiler

* Fix typo

* Fix Scale Nomenclature and Remove Redundant Function Arguments in MatVec Code

* Consolidate c_reference/ and m3/library codes

* Revise C and C++ Code To The Agreed Convention

* Remove Redundant M3 Library and Add TODO for Memory Management

* Re-Index Sparse Model According to Optimal Strategy

* Fix Redundant Array Issue

* Fix stray spaces and grammatical issues

* Make Multi-Dimensional Arrays Uni-Dimensional for M3

* Hacky Fix for Widx and Uidx

* Fix Grammar and Remove Unused Code

* Make SeeDot Directly Runnable

* Remove Stray Spaces

* Fix Grammar

* Fix Comments

* Incorporate Changes from Aayan

* Fix x86 pipeline on FirstFitPriority

* Optimize x86 pipeline on FirstFitPriority

* Add Wno-narrowing flag to x86 codegen

* Prettier Printing.  (#1)

* Replaced the print stagement using logging (error, warning, info and debug levels used).
Added progress bar using tqdm package in performSearch function for the 4 stages of exploration.
Changes Antlr Check version to 4.9.1.
Added requirements.txt

* Added more information to the print statment that prints the stage of exploration.

* Added log level as a command line argument.
Added  descriptive error messages.

* Reverted parameters to old state

* Slight changes to the strings printed by logging

* Resolved formatting comments

* Updated README.md with comand to change logging level

* Converted the log level input arguments to lowercase strings

* Minor Improvements

* Changes to improve README.md in SeeDot and respective modifications. (#2)

* Replaced the print stagement using logging (error, warning, info and debug levels used).
Added progress bar using tqdm package in performSearch function for the 4 stages of exploration.
Changes Antlr Check version to 4.9.1.
Added requirements.txt

* Added more information to the print statment that prints the stage of exploration.

* Added log level as a command line argument.
Added  descriptive error messages.

* Reverted parameters to old state

* Slight changes to the strings printed by logging

* Resolved formatting comments

* Updated README.md with comand to change logging level

* Converted the log level input arguments to lowercase strings

* Updated requirements and Readme

* Replaced argument version with argument encoding
Removed dependency on Results.csv

* Readme formatting change

* Changed the help strings in argument parser, renamed rnn as fastgrnn

* Some more changes to SeeDot-dev.py for the argument parser.
Added line that shows that the available fastgrnn model belongs to usps10 dataset.

* Added descriptive comments to python files except ONNX and TF folders.

* Removed unnecessary comma in launch.json

* Corrected default SeeDot values in README.md

* Minor changes to improv README.md's readablility.

* Added legacy_scales.csv and restored the legacy_scales processor in SeeDot-dev.py

* Replaced rnn keyword with fastgrnn in launch.json

* Changed all comments to a single format

* Added face detection run instructions.
Removed lsf flag from README and uppressed it in help.

* Replaced maximisingMetric with metric in the main.py, config.py and test.py.
Made the respective changes in README.md.

* Removed instructions to run face detection

* Architecture.md started

* Architecture.md iteration 1 completed

* Improved line spacing

* Removed incorrect line

* Replaced architecture.svg

* replaced version with encoding

* made FastGRNN on usps10 with reduced disagreemts the default for seedot

* Points added to architecture.md

* Included suggestions from reviewer.

* Added instructions to fetch face detection dataset and licenses to newly added files (#3)

* Replaced the print stagement using logging (error, warning, info and debug levels used).
Added progress bar using tqdm package in performSearch function for the 4 stages of exploration.
Changes Antlr Check version to 4.9.1.
Added requirements.txt

* Added more information to the print statment that prints the stage of exploration.

* Added log level as a command line argument.
Added  descriptive error messages.

* Reverted parameters to old state

* Slight changes to the strings printed by logging

* Resolved formatting comments

* Updated README.md with comand to change logging level

* Converted the log level input arguments to lowercase strings

* Updated requirements and Readme

* Replaced argument version with argument encoding
Removed dependency on Results.csv

* Readme formatting change

* Changed the help strings in argument parser, renamed rnn as fastgrnn

* Some more changes to SeeDot-dev.py for the argument parser.
Added line that shows that the available fastgrnn model belongs to usps10 dataset.

* Added descriptive comments to python files except ONNX and TF folders.

* Removed unnecessary comma in launch.json

* Corrected default SeeDot values in README.md

* Minor changes to improv README.md's readablility.

* Added legacy_scales.csv and restored the legacy_scales processor in SeeDot-dev.py

* Replaced rnn keyword with fastgrnn in launch.json

* Changed all comments to a single format

* Added face detection run instructions.
Removed lsf flag from README and uppressed it in help.

* Replaced maximisingMetric with metric in the main.py, config.py and test.py.
Made the respective changes in README.md.

* Removed instructions to run face detection

* Architecture.md started

* Architecture.md iteration 1 completed

* Improved line spacing

* Removed incorrect line

* Replaced architecture.svg

* replaced version with encoding

* made FastGRNN on usps10 with reduced disagreemts the default for seedot

* Points added to architecture.md

* Included suggestions from reviewer.

* Added rnnpool.sd to folder of seedot models

* Added faceDetection code fetcher

* Added face detection run instructions and licenses

* Updated face Detection instructions and readme.md

* Minor correction to readmes

* Added rnnpool as an option in SeeDot-dev.py

* Added support for face-2 dataset

* Error in cleanup in fetchFDDataset.py

* Added information about input to Predictor in faceDetection.md

* Included reviewr comments to fix typos

* Fixed typos in faceDetection.md

* Added code to run the quantized face detection on images

* Added instructions to run face detection on extra images in faceDetection.md

* Added argument support to scale_image.pu

* Fixed typos in faceDetection.md

* Added info about the output of eval_fromquant in faceDetection.md

* Added instructions to fetch an image in faceDetection.md

* Added load_sf condition to printing PASS or FAIL

* Added instructions to install libraries for detecting bounding boxes

* Minor changes to faceDetection.md and main.cpp

* Removed duplicate files from the repository and added instructions to copy them for running image to text converters and vice-versa

* Minor change to faceDetection.md

* Changes to face detection readme  (#4)

* Replaced the print stagement using logging (error, warning, info and debug levels used).
Added progress bar using tqdm package in performSearch function for the 4 stages of exploration.
Changes Antlr Check version to 4.9.1.
Added requirements.txt

* Added more information to the print statment that prints the stage of exploration.

* Added log level as a command line argument.
Added  descriptive error messages.

* Reverted parameters to old state

* Slight changes to the strings printed by logging

* Resolved formatting comments

* Updated README.md with comand to change logging level

* Converted the log level input arguments to lowercase strings

* Updated requirements and Readme

* Replaced argument version with argument encoding
Removed dependency on Results.csv

* Readme formatting change

* Changed the help strings in argument parser, renamed rnn as fastgrnn

* Some more changes to SeeDot-dev.py for the argument parser.
Added line that shows that the available fastgrnn model belongs to usps10 dataset.

* Added descriptive comments to python files except ONNX and TF folders.

* Removed unnecessary comma in launch.json

* Corrected default SeeDot values in README.md

* Minor changes to improv README.md's readablility.

* Added legacy_scales.csv and restored the legacy_scales processor in SeeDot-dev.py

* Replaced rnn keyword with fastgrnn in launch.json

* Changed all comments to a single format

* Added face detection run instructions.
Removed lsf flag from README and uppressed it in help.

* Replaced maximisingMetric with metric in the main.py, config.py and test.py.
Made the respective changes in README.md.

* Removed instructions to run face detection

* Architecture.md started

* Architecture.md iteration 1 completed

* Improved line spacing

* Removed incorrect line

* Replaced architecture.svg

* replaced version with encoding

* made FastGRNN on usps10 with reduced disagreemts the default for seedot

* Points added to architecture.md

* Included suggestions from reviewer.

* Added rnnpool.sd to folder of seedot models

* Added faceDetection code fetcher

* Added face detection run instructions and licenses

* Updated face Detection instructions and readme.md

* Minor correction to readmes

* Added rnnpool as an option in SeeDot-dev.py

* Added support for face-2 dataset

* Error in cleanup in fetchFDDataset.py

* Added information about input to Predictor in faceDetection.md

* Included reviewr comments to fix typos

* Fixed typos in faceDetection.md

* Added code to run the quantized face detection on images

* Added instructions to run face detection on extra images in faceDetection.md

* Added argument support to scale_image.pu

* Fixed typos in faceDetection.md

* Added info about the output of eval_fromquant in faceDetection.md

* Added instructions to fetch an image in faceDetection.md

* Added load_sf condition to printing PASS or FAIL

* Added instructions to install libraries for detecting bounding boxes

* Minor changes to faceDetection.md and main.cpp

* Removed duplicate files from the repository and added instructions to copy them for running image to text converters and vice-versa

* Minor change to faceDetection.md

* Updated faceDetection.md

* Added trace to seedot converstion scripts

* Fixed trace dimensions in convert_to_seedot files

* Removed torch from the requirements.txt file

* Updated face detection readme

* Updated faceDetection.md with corrected instructions to install edgeml_pytorch

* Reset the changes made to requiments-cpu.txt and requirements-gpu.txt in EdgeML/pytorch

* Added multi-line commands to face detection.md

* Added instructions for SeeDot installation as well

* Some more refactoring

* Merged the two convert_to_seedot_scripts into one

* fixed typo in convert_RPool_Face_to_SeeDot

* Minor addition to faceDetection.md

* Minor Nitpicks

* Fixed copy instructions in faceDetection.md (#5)

* Replaced the print stagement using logging (error, warning, info and debug levels used).
Added progress bar using tqdm package in performSearch function for the 4 stages of exploration.
Changes Antlr Check version to 4.9.1.
Added requirements.txt

* Added more information to the print statment that prints the stage of exploration.

* Added log level as a command line argument.
Added  descriptive error messages.

* Reverted parameters to old state

* Slight changes to the strings printed by logging

* Resolved formatting comments

* Updated README.md with comand to change logging level

* Converted the log level input arguments to lowercase strings

* Updated requirements and Readme

* Replaced argument version with argument encoding
Removed dependency on Results.csv

* Readme formatting change

* Changed the help strings in argument parser, renamed rnn as fastgrnn

* Some more changes to SeeDot-dev.py for the argument parser.
Added line that shows that the available fastgrnn model belongs to usps10 dataset.

* Added descriptive comments to python files except ONNX and TF folders.

* Removed unnecessary comma in launch.json

* Corrected default SeeDot values in README.md

* Minor changes to improv README.md's readablility.

* Added legacy_scales.csv and restored the legacy_scales processor in SeeDot-dev.py

* Replaced rnn keyword with fastgrnn in launch.json

* Changed all comments to a single format

* Added face detection run instructions.
Removed lsf flag from README and uppressed it in help.

* Replaced maximisingMetric with metric in the main.py, config.py and test.py.
Made the respective changes in README.md.

* Removed instructions to run face detection

* Architecture.md started

* Architecture.md iteration 1 completed

* Improved line spacing

* Removed incorrect line

* Replaced architecture.svg

* replaced version with encoding

* made FastGRNN on usps10 with reduced disagreemts the default for seedot

* Points added to architecture.md

* Included suggestions from reviewer.

* Added rnnpool.sd to folder of seedot models

* Added faceDetection code fetcher

* Added face detection run instructions and licenses

* Updated face Detection instructions and readme.md

* Minor correction to readmes

* Added rnnpool as an option in SeeDot-dev.py

* Added support for face-2 dataset

* Error in cleanup in fetchFDDataset.py

* Added information about input to Predictor in faceDetection.md

* Included reviewr comments to fix typos

* Fixed typos in faceDetection.md

* Added code to run the quantized face detection on images

* Added instructions to run face detection on extra images in faceDetection.md

* Added argument support to scale_image.pu

* Fixed typos in faceDetection.md

* Added info about the output of eval_fromquant in faceDetection.md

* Added instructions to fetch an image in faceDetection.md

* Added load_sf condition to printing PASS or FAIL

* Added instructions to install libraries for detecting bounding boxes

* Minor changes to faceDetection.md and main.cpp

* Removed duplicate files from the repository and added instructions to copy them for running image to text converters and vice-versa

* Minor change to faceDetection.md

* Updated faceDetection.md

* Added trace to seedot converstion scripts

* Fixed trace dimensions in convert_to_seedot files

* Removed torch from the requirements.txt file

* Updated face detection readme

* Updated faceDetection.md with corrected instructions to install edgeml_pytorch

* Reset the changes made to requiments-cpu.txt and requirements-gpu.txt in EdgeML/pytorch

* Added multi-line commands to face detection.md

* Added instructions for SeeDot installation as well

* Some more refactoring

* Merged the two convert_to_seedot_scripts into one

* fixed typo in convert_RPool_Face_to_SeeDot

* Minor addition to faceDetection.md

* Fixed location of copying from SCUT_Head_Part_B

* Minor addition to faceDetection.md

* GCC version check added to build.py (#6)

* Replaced the print stagement using logging (error, warning, info and debug levels used).
Added progress bar using tqdm package in performSearch function for the 4 stages of exploration.
Changes Antlr Check version to 4.9.1.
Added requirements.txt

* Added more information to the print statment that prints the stage of exploration.

* Added log level as a command line argument.
Added  descriptive error messages.

* Reverted parameters to old state

* Slight changes to the strings printed by logging

* Resolved formatting comments

* Updated README.md with comand to change logging level

* Converted the log level input arguments to lowercase strings

* Updated requirements and Readme

* Replaced argument version with argument encoding
Removed dependency on Results.csv

* Readme formatting change

* Changed the help strings in argument parser, renamed rnn as fastgrnn

* Some more changes to SeeDot-dev.py for the argument parser.
Added line that shows that the available fastgrnn model belongs to usps10 dataset.

* Added descriptive comments to python files except ONNX and TF folders.

* Removed unnecessary comma in launch.json

* Corrected default SeeDot values in README.md

* Minor changes to improv README.md's readablility.

* Added legacy_scales.csv and restored the legacy_scales processor in SeeDot-dev.py

* Replaced rnn keyword with fastgrnn in launch.json

* Changed all comments to a single format

* Added face detection run instructions.
Removed lsf flag from README and uppressed it in help.

* Replaced maximisingMetric with metric in the main.py, config.py and test.py.
Made the respective changes in README.md.

* Removed instructions to run face detection

* Architecture.md started

* Architecture.md iteration 1 completed

* Improved line spacing

* Removed incorrect line

* Replaced architecture.svg

* replaced version with encoding

* made FastGRNN on usps10 with reduced disagreemts the default for seedot

* Points added to architecture.md

* Included suggestions from reviewer.

* Added rnnpool.sd to folder of seedot models

* Added faceDetection code fetcher

* Added face detection run instructions and licenses

* Updated face Detection instructions and readme.md

* Minor correction to readmes

* Added rnnpool as an option in SeeDot-dev.py

* Added support for face-2 dataset

* Error in cleanup in fetchFDDataset.py

* Added information about input to Predictor in faceDetection.md

* Included reviewr comments to fix typos

* Fixed typos in faceDetection.md

* Added code to run the quantized face detection on images

* Added instructions to run face detection on extra images in faceDetection.md

* Added argument support to scale_image.pu

* Fixed typos in faceDetection.md

* Added info about the output of eval_fromquant in faceDetection.md

* Added instructions to fetch an image in faceDetection.md

* Added load_sf condition to printing PASS or FAIL

* Added instructions to install libraries for detecting bounding boxes

* Minor changes to faceDetection.md and main.cpp

* Removed duplicate files from the repository and added instructions to copy them for running image to text converters and vice-versa

* Minor change to faceDetection.md

* Updated faceDetection.md

* Added trace to seedot converstion scripts

* Fixed trace dimensions in convert_to_seedot files

* Removed torch from the requirements.txt file

* Updated face detection readme

* Updated faceDetection.md with corrected instructions to install edgeml_pytorch

* Reset the changes made to requiments-cpu.txt and requirements-gpu.txt in EdgeML/pytorch

* Added multi-line commands to face detection.md

* Added instructions for SeeDot installation as well

* Some more refactoring

* Merged the two convert_to_seedot_scripts into one

* fixed typo in convert_RPool_Face_to_SeeDot

* Minor addition to faceDetection.md

* Fixed location of copying from SCUT_Head_Part_B

* Minor addition to faceDetection.md

* Gcc version restriction added to seedot/Predictor/Makefile

* Added GCC version check to SeeDot

* Removed extra new-line

* Data processing (#7)

* Replaced the print stagement using logging (error, warning, info and debug levels used).
Added progress bar using tqdm package in performSearch function for the 4 stages of exploration.
Changes Antlr Check version to 4.9.1.
Added requirements.txt

* Added more information to the print statment that prints the stage of exploration.

* Added log level as a command line argument.
Added  descriptive error messages.

* Reverted parameters to old state

* Slight changes to the strings printed by logging

* Resolved formatting comments

* Updated README.md with comand to change logging level

* Converted the log level input arguments to lowercase strings

* Updated requirements and Readme

* Replaced argument version with argument encoding
Removed dependency on Results.csv

* Readme formatting change

* Changed the help strings in argument parser, renamed rnn as fastgrnn

* Some more changes to SeeDot-dev.py for the argument parser.
Added line that shows that the available fastgrnn model belongs to usps10 dataset.

* Added descriptive comments to python files except ONNX and TF folders.

* Removed unnecessary comma in launch.json

* Corrected default SeeDot values in README.md

* Minor changes to improv README.md's readablility.

* Added legacy_scales.csv and restored the legacy_scales processor in SeeDot-dev.py

* Replaced rnn keyword with fastgrnn in launch.json

* Changed all comments to a single format

* Added face detection run instructions.
Removed lsf flag from README and uppressed it in help.

* Replaced maximisingMetric with metric in the main.py, config.py and test.py.
Made the respective changes in README.md.

* Removed instructions to run face detection

* Architecture.md started

* Architecture.md iteration 1 completed

* Improved line spacing

* Removed incorrect line

* Replaced architecture.svg

* replaced version with encoding

* made FastGRNN on usps10 with reduced disagreemts the default for seedot

* Points added to architecture.md

* Included suggestions from reviewer.

* Added rnnpool.sd to folder of seedot models

* Added faceDetection code fetcher

* Added face detection run instructions and licenses

* Updated face Detection instructions and readme.md

* Minor correction to readmes

* Added rnnpool as an option in SeeDot-dev.py

* Added support for face-2 dataset

* Error in cleanup in fetchFDDataset.py

* Added information about input to Predictor in faceDetection.md

* Included reviewr comments to fix typos

* Fixed typos in faceDetection.md

* Added code to run the quantized face detection on images

* Added instructions to run face detection on extra images in faceDetection.md

* Added argument support to scale_image.pu

* Fixed typos in faceDetection.md

* Added info about the output of eval_fromquant in faceDetection.md

* Added instructions to fetch an image in faceDetection.md

* Added load_sf condition to printing PASS or FAIL

* Added instructions to install libraries for detecting bounding boxes

* Minor changes to faceDetection.md and main.cpp

* Removed duplicate files from the repository and added instructions to copy them for running image to text converters and vice-versa

* Minor change to faceDetection.md

* Updated faceDetection.md

* Added trace to seedot converstion scripts

* Fixed trace dimensions in convert_to_seedot files

* Removed torch from the requirements.txt file

* Updated face detection readme

* Updated faceDetection.md with corrected instructions to install edgeml_pytorch

* Reset the changes made to requiments-cpu.txt and requirements-gpu.txt in EdgeML/pytorch

* Added multi-line commands to face detection.md

* Added instructions for SeeDot installation as well

* Some more refactoring

* Merged the two convert_to_seedot_scripts into one

* fixed typo in convert_RPool_Face_to_SeeDot

* Minor addition to faceDetection.md

* Fixed location of copying from SCUT_Head_Part_B

* Minor addition to faceDetection.md

* Gcc version restriction added to seedot/Predictor/Makefile

* Added GCC version check to SeeDot

* Removed extra new-line

* Added data preprocessing line

* The script to fix ranges (#8)

* Replaced the print stagement using logging (error, warning, info and debug levels used).
Added progress bar using tqdm package in performSearch function for the 4 stages of exploration.
Changes Antlr Check version to 4.9.1.
Added requirements.txt

* Added more information to the print statment that prints the stage of exploration.

* Added log level as a command line argument.
Added  descriptive error messages.

* Reverted parameters to old state

* Slight changes to the strings printed by logging

* Resolved formatting comments

* Updated README.md with comand to change logging level

* Converted the log level input arguments to lowercase strings

* Updated requirements and Readme

* Replaced argument version with argument encoding
Removed dependency on Results.csv

* Readme formatting change

* Changed the help strings in argument parser, renamed rnn as fastgrnn

* Some more changes to SeeDot-dev.py for the argument parser.
Added line that shows that the available fastgrnn model belongs to usps10 dataset.

* Added descriptive comments to python files except ONNX and TF folders.

* Removed unnecessary comma in launch.json

* Corrected default SeeDot values in README.md

* Minor changes to improv README.md's readablility.

* Added legacy_scales.csv and restored the legacy_scales processor in SeeDot-dev.py

* Replaced rnn keyword with fastgrnn in launch.json

* Changed all comments to a single format

* Added face detection run instructions.
Removed lsf flag from README and uppressed it in help.

* Replaced maximisingMetric with metric in the main.py, config.py and test.py.
Made the respective changes in README.md.

* Removed instructions to run face detection

* Architecture.md started

* Architecture.md iteration 1 completed

* Improved line spacing

* Removed incorrect line

* Replaced architecture.svg

* replaced version with encoding

* made FastGRNN on usps10 with reduced disagreemts the default for seedot

* Points added to architecture.md

* Included suggestions from reviewer.

* Added rnnpool.sd to folder of seedot models

* Added faceDetection code fetcher

* Added face detection run instructions and licenses

* Updated face Detection instructions and readme.md

* Minor correction to readmes

* Added rnnpool as an option in SeeDot-dev.py

* Added support for face-2 dataset

* Error in cleanup in fetchFDDataset.py

* Added information about input to Predictor in faceDetection.md

* Included reviewr comments to fix typos

* Fixed typos in faceDetection.md

* Added code to run the quantized face detection on images

* Added instructions to run face detection on extra images in faceDetection.md

* Added argument support to scale_image.pu

* Fixed typos in faceDetection.md

* Added info about the output of eval_fromquant in faceDetection.md

* Added instructions to fetch an image in faceDetection.md

* Added load_sf condition to printing PASS or FAIL

* Added instructions to install libraries for detecting bounding boxes

* Minor changes to faceDetection.md and main.cpp

* Removed duplicate files from the repository and added instructions to copy them for running image to text converters and vice-versa

* Minor change to faceDetection.md

* Updated faceDetection.md

* Added trace to seedot converstion scripts

* Fixed trace dimensions in convert_to_seedot files

* Removed torch from the requirements.txt file

* Updated face detection readme

* Updated faceDetection.md with corrected instructions to install edgeml_pytorch

* Reset the changes made to requiments-cpu.txt and requirements-gpu.txt in EdgeML/pytorch

* Added multi-line commands to face detection.md

* Added instructions for SeeDot installation as well

* Some more refactoring

* Merged the two convert_to_seedot_scripts into one

* fixed typo in convert_RPool_Face_to_SeeDot

* Minor addition to faceDetection.md

* Fixed location of copying from SCUT_Head_Part_B

* Minor addition to faceDetection.md

* Gcc version restriction added to seedot/Predictor/Makefile

* Added GCC version check to SeeDot

* Removed extra new-line

* Added data preprocessing line

* Added cpu conversion in convert_RPool_Face_to_SeeDot.py

* Added script to process seedot input files

* Increased precision of printing floating point in fixSeeDotInput.py

* Updated instructions to update ranges by script

* Add newline at the end of fixSeeDotInput.py

* ONNX dependency added to README (#9)

* Replaced the print stagement using logging (error, warning, info and debug levels used).
Added progress bar using tqdm package in performSearch function for the 4 stages of exploration.
Changes Antlr Check version to 4.9.1.
Added requirements.txt

* Added more information to the print statment that prints the stage of exploration.

* Added log level as a command line argument.
Added  descriptive error messages.

* Reverted parameters to old state

* Slight changes to the strings printed by logging

* Resolved formatting comments

* Updated README.md with comand to change logging level

* Converted the log level input arguments to lowercase strings

* Updated requirements and Readme

* Replaced argument version with argument encoding
Removed dependency on Results.csv

* Readme formatting change

* Changed the help strings in argument parser, renamed rnn as fastgrnn

* Some more changes to SeeDot-dev.py for the argument parser.
Added line that shows that the available fastgrnn model belongs to usps10 dataset.

* Added descriptive comments to python files except ONNX and TF folders.

* Removed unnecessary comma in launch.json

* Corrected default SeeDot values in README.md

* Minor changes to improv README.md's readablility.

* Added legacy_scales.csv and restored the legacy_scales processor in SeeDot-dev.py

* Replaced rnn keyword with fastgrnn in launch.json

* Changed all comments to a single format

* Added face detection run instructions.
Removed lsf flag from README and uppressed it in help.

* Replaced maximisingMetric with metric in the main.py, config.py and test.py.
Made the respective changes in README.md.

* Removed instructions to run face detection

* Architecture.md started

* Architecture.md iteration 1 completed

* Improved line spacing

* Removed incorrect line

* Replaced architecture.svg

* replaced version with encoding

* made FastGRNN on usps10 with reduced disagreemts the default for seedot

* Points added to architecture.md

* Included suggestions from reviewer.

* Added rnnpool.sd to folder of seedot models

* Added faceDetection code fetcher

* Added face detection run instructions and licenses

* Updated face Detection instructions and readme.md

* Minor correction to readmes

* Added rnnpool as an option in SeeDot-dev.py

* Added support for face-2 dataset

* Error in cleanup in fetchFDDataset.py

* Added information about input to Predictor in faceDetection.md

* Included reviewr comments to fix typos

* Fixed typos in faceDetection.md

* Added code to run the quantized face detection on images

* Added instructions to run face detection on extra images in faceDetection.md

* Added argument support to scale_image.pu

* Fixed typos in faceDetection.md

* Added info about the output of eval_fromquant in faceDetection.md

* Added instructions to fetch an image in faceDetection.md

* Added load_sf condition to printing PASS or FAIL

* Added instructions to install libraries for detecting bounding boxes

* Minor changes to faceDetection.md and main.cpp

* Removed duplicate files from the repository and added instructions to copy them for running image to text converters and vice-versa

* Minor change to faceDetection.md

* Updated faceDetection.md

* Added trace to seedot converstion scripts

* Fixed trace dimensions in convert_to_seedot files

* Removed torch from the requirements.txt file

* Updated face detection readme

* Updated faceDetection.md with corrected instructions to install edgeml_pytorch

* Reset the changes made to requiments-cpu.txt and requirements-gpu.txt in EdgeML/pytorch

* Added multi-line commands to face detection.md

* Added instructions for SeeDot installation as well

* Some more refactoring

* Merged the two convert_to_seedot_scripts into one

* fixed typo in convert_RPool_Face_to_SeeDot

* Minor addition to faceDetection.md

* Fixed location of copying from SCUT_Head_Part_B

* Minor addition to faceDetection.md

* Gcc version restriction added to seedot/Predictor/Makefile

* Added GCC version check to SeeDot

* Removed extra new-line

* Added data preprocessing line

* Added cpu conversion in convert_RPool_Face_to_SeeDot.py

* Added script to process seedot input files

* Increased precision of printing floating point in fixSeeDotInput.py

* Updated instructions to update ranges by script

* Add newline at the end of fixSeeDotInput.py

* Added ONNX as a dependencey in README

* Minor Fixes

* Improve README

Co-authored-by: ShikharJ <jaiswalshikhar87@gmail.com>
Co-authored-by: G Rahul Kranti Kiran <krantikiran.68@gmail.com>
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The Edge Machine Learning library

This repository provides code for machine learning algorithms for edge devices developed at Microsoft Research India.

Machine learning models for edge devices need to have a small footprint in terms of storage, prediction latency, and energy. One instance of where such models are desirable is resource-scarce devices and sensors in the Internet of Things (IoT) setting. Making real-time predictions locally on IoT devices without connecting to the cloud requires models that fit in a few kilobytes.

Contents

Algorithms that shine in this setting in terms of both model size and compute, namely:

  • Bonsai: Strong and shallow non-linear tree based classifier.
  • ProtoNN: Prototype based k-nearest neighbors (kNN) classifier.
  • EMI-RNN: Training routine to recover the critical signature from time series data for faster and accurate RNN predictions.
  • Shallow RNN: A meta-architecture for training RNNs that can be applied to streaming data.
  • FastRNN & FastGRNN - FastCells: Fast, Accurate, Stable and Tiny (Gated) RNN cells.
  • DROCC: Deep Robust One-Class Classfiication for training robust anomaly detectors.
  • RNNPool: An efficient non-linear pooling operator for RAM constrained inference.

These algorithms can train models for classical supervised learning problems with memory requirements that are orders of magnitude lower than other modern ML algorithms. The trained models can be loaded onto edge devices such as IoT devices/sensors, and used to make fast and accurate predictions completely offline.

A tool that adapts models trained by above algorithms to be inferred by fixed point arithmetic.

  • SeeDot: Floating-point to fixed-point quantization tool.

Applications demonstrating usecases of these algorithms:

  • GesturePod: Gesture recognition pipeline for microcontrollers.
  • MSC-RNN: Multi-scale cascaded RNN for analyzing Radar data.

Organization

  • The tf directory contains the edgeml_tf package which specifies these architectures in TensorFlow, and examples/tf contains sample training routines for these algorithms.
  • The pytorch directory contains the edgeml_pytorch package which specifies these architectures in PyTorch, and examples/pytorch contains sample training routines for these algorithms.
  • The cpp directory has training and inference code for Bonsai and ProtoNN algorithms in C++.
  • The applications directory has code/demonstrations of applications of the EdgeML algorithms.
  • The tools/SeeDot directory has the quantization tool to generate fixed-point inference code.
  • The c_reference directory contains the inference code (floating-point or quantized) for various algorithms in C.

Please see install/run instructions in the README pages within these directories.

Details and project pages

For details, please see our project page, Microsoft Research page, the ICML '17 publications on Bonsai and ProtoNN algorithms, the NeurIPS '18 publications on EMI-RNN and FastGRNN, the PLDI '19 publication on SeeDot compiler, the UIST '19 publication on Gesturepod, the BuildSys '19 publication on MSC-RNN, the NeurIPS '19 publication on Shallow RNNs, the ICML '20 publication on DROCC, and the NeurIPS '20 publication on RNNPool.

Also checkout the ELL project which can provide optimized binaries for some of the ONNX models trained by this library.

Contributors:

Code for algorithms, applications and tools contributed by:

Contributors to this project. New contributors welcome.

Please email us your comments, criticism, and questions.

If you use software from this library in your work, please use the BibTex entry below for citation.

@misc{edgeml04,
   author = {{Dennis, Don Kurian and Gaurkar, Yash and Gopinath, Sridhar and Goyal, Sachin 
              and Gupta, Chirag and Jain, Moksh and Jaiswal, Shikhar and Kumar, Ashish and
              Kusupati, Aditya and  Lovett, Chris and Patil, Shishir G and Saha, Oindrila and
              Simhadri, Harsha Vardhan}},
   title = {{EdgeML: Machine Learning for resource-constrained edge devices}},
   url = {https://github.com/Microsoft/EdgeML},
   version = {0.4},
}

Microsoft Open Source Code of Conduct This project has adopted the

Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact opencode@microsoft.com with any additional questions or comments.