fix: radar_classification's run() dispatched to a dead debug function, not main() by musicalplatypus · Pull Request #34 · TexasInstruments/tinyml-tensorlab

musicalplatypus · 2026-08-14T12:48:59Z

This is part of a 4-PR stack: #34 (this PR) → #35 → #36 → #37. Recommended merge order is numeric; each later PR's diff currently includes the earlier ones' commits until they merge, since none have landed yet.

Summary

radar_classification/train.py's run() called main_debug() — a leftover notebook-parity harness (its own comment: "Following as close as possible steps from jupyter notebook to test if model learning plateau is coming from training loop") — instead of main(), which is fully wired to this codebase's shared training infrastructure.

Concretely, main_debug():

Never calls quantization_wrapped_model — the "QuantTrain" pass produces a second, mislabeled float-training run instead of an actual quantized model.
Never calls resume_from_checkpoint — checkpoint resume is silently a no-op.
Hardcodes a fixed random seed and a plain SGD optimizer with no LR scheduler, unlike main()'s configurable setup shared with every other reference script.

This was a genuine regression risk: main() had zero execution history for radar before this fix. Verified end-to-end on a synthetic fixture with both --quantization 0 and --quantization 1 — the quantized pass now correctly shows QuantTrain phase log entries and exports a second (QDQ) model, which it silently never did before.

Note: at this PR's state, main() does not yet support --compile-model either (neither main() nor main_debug() called compile_model_if_enabled) — that's added in #35, on top of this fix making main() reachable at all.

Changes

run() now dispatches to main, matching every other reference script's pattern
New regression test pinning the dispatch target so this can't silently regress back to main_debug
--compile-model support for radar is added in the follow-up PR (feat: wire compile_model_if_enabled into radar, image, and audio classification #35), which this PR's fix is a prerequisite for (compile wiring only exists in main(), which was previously unreachable)

CI

CI is red on all three OS jobs for this PR — but it's also red on main at this PR's base commit (6f2c11cc), from test_config_validation.py's radar_point_cloud_classification example config (added by PR #13) not being recognized by the task-type/model registries. This PR doesn't touch that config or those registries and doesn't change the failure set.

Test plan

New regression test: tests/test_radar_entrypoint_uses_main.py
Manual E2E on synthetic fixture, both quantization=0 and quantization=1, both completing cleanly with the expected artifacts
Full existing test suite passes locally (2 pre-existing, unrelated CI failures — see CI section above)

Post-fix (main() live per Task 1): CPU 0.621s/epoch, MPS 1.066s/epoch (1.72x slower) -- gap did not close vs pre-fix's 1.90x. Root cause: compile_model_if_enabled/apply_hardware_defaults are never called anywhere in radar_classification/train.py (only wired into the timeseries_* reference scripts), so torch.compile/AMP were off for all four runs regardless of which function run() dispatches to. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>

Whole-plan review flagged that the Goal/Architecture sections still asserted the disproven premise (main() wired to compile_model_if_enabled) 130+ lines above the actual Results. Ledger and Results were already honest; this fixes the presentation for a top-down reader.

Claimed main_debug() alone lacked compile_model_if_enabled/apply_hardware_defaults, implying main() already had it -- at this commit neither function does (that's added in a later change). Corrected to describe what's actually true at this point: main() is the one that CAN be extended with it, not that it already is.

Stripped the 'For agentic workers: REQUIRED SUB-SKILL...' header and normalized checkboxes from - [ ] to - [x] -- every task described is done.

23a2fa30 fix: eliminate Python 3.14 terminal noise from multiprocessing and ONNX REVERT: ed2a0df8 Pull request #97: added soundfile so that the correct backend is installed to support audio_applications REVERT: 3a38e077 added soundfile so that the correct backend is installed to support audio_applications REVERT: 506eb9e3 Pull request #96: Did nan check for loss to check training instability TINYML_ALGO-730 REVERT: 539fe129 Did nan check for loss to check training instability TINYML_ALGO-730 REVERT: f2ff07be Pull request #95: range normalise preprocessing function removed REVERT: 3110abeb range normalise preprocessing function removed REVERT: d34a25f2 Pull request #92: MSPM0 V2 REVERT: 9980157b resolved the comment, added range_normalization argument parser in correct place REVERT: 69e200df all changes due to range normalisation argument addition REVERT: 54a07f27 Pull request #93: Fix: added check for integration in AutoML REVERT: 9e95da6e Added subset = None check to enable integration in AutoML flow REVERT: f0412f8a Merge branch 'MSPM0_V2' of ssh://bitbucket.itg.ti.com/tinyml-algo/tinyml-tinyverse into MSPM0_V2 REVERT: f6b44a45 feature extraction function and its flag is added REVERT: 94251b38 Bug fix REVERT: 19b438f8 Pull request #91: incorporated Qodo suggestions REVERT: f54f0c53 incorporated Qodo suggestions REVERT: b08b4058 Pull request #90: audio and image data loader scripts REVERT: 618b5c8a no message REVERT: 43281d16 no message REVERT: 5da3efd7 no message REVERT: e6170a80 Merge branch 'main-dev' of ssh://bitbucket.itg.ti.com/tinyml-algo/tinyml-tinyverse into MSPM0_V2 REVERT: 9755f8e3 fixes for audio_dataset REVERT: 442dfe4f support for audio added REVERT: eea264cc Pull request #80: Added training data exporting functionality to tinyverse. REVERT: be2564c1 Handled the cases where the raw dataset can be 3d or 4d depending on whether feature extraction is applied or not REVERT: d11f9e01 Added support to export conv2d layer for ondevice learning REVERT: e090edb3 TINYML_ALGO-559: Added training data exporting functionality to tinyverse. Data will be exported in ondevice_training_data.c,.h REVERT: e28db628 Pull request #89: TINYML_ALGO-586: Adding hawq based automatic mixed precision flow in regression, classification, anomaly detection, forecasting train.py REVERT: 92165e59 spacing REVERT: 5d2e78bc adding tolerance flow from params.py, utils.py flow through kwargs, and changes in four flows train.py REVERT: 98869ac4 changing variable name to auto_quantization REVERT: b2247eeb forecasting mixed precision flow REVERT: 73c6929d Changes in train.py for all 3 flows regression, classification and anomaly detection to support automatic mixed precision when partial_quantization is True REVERT: 9580c3e7 adding hawq based partial quantization flow in regression train.py REVERT: 3c02f8d5 Pull request #88: Image Classification transforms + augmentation REVERT: c9733e30 enabled training only online augmentation for image datasets REVERT: 42c4a64f added enable_online_augmentation flag as suggested REVERT: 1da8c217 no message REVERT: 2a525fd0 Merge branch 'main-dev' of ssh://bitbucket.itg.ti.com/tinyml-algo/tinyml-tinyverse into MSPM0_V2 REVERT: ece4ebec no message REVERT: 6e467c8c added opencv-python package for image classification tasks REVERT: fdea5c96 Added GenericImageDataset support for image classification tasks - Added deterministic image preprocessing transforms: - GRAYSCALE - RGB - RESIZE - RESIZE_PAD - AUTOCONTRAST - EQUALIZE - INVERT - CLAHE - SOBEL - LAPLACIAN - BINARIZE REVERT: d8feb816 TINYML_ALGO-706 REVERT: ceadc440 TINYML_ALGO-705 REVERT: 57f17ac7 TINYML_ALGO-703, TINYML_ALGO-704 REVERT: 2f852929 Pull request #87: Added description on how to read the reconstruction error graph REVERT: 8b94009e Added description on how to read the reconstruction error plot REVERT: 6def19ec TINYML_ALGO-678 REVERT: ce0619db TINYML_ALGO-663 REVERT: bb68e886 Pull request #83: edgeai studio regx fix for mspm0 REVERT: 34bab9ef added support for q15-scale-factor( consumed by the rfft preprocessing even for regression task) in train.py and test_onnx.py for timeseries_regression task aswell REVERT: bf30cb3e bug fix causing a difference in feature extraction with RAW based presets REVERT: 02252138 Pull request #82: Updated logs to print the average mse of epoch as well along with the first batch mse REVERT: d7f07bea Updated logs to print the average mse of epoch as well along with the first batch mse REVERT: fb1b3c26 TINYML_ALGO-640 REVERT: 95d00fa2 Pull request #81: Added user_input_config.h flags for pir_fixed point feature extraction REVERT: 189c25fa no message REVERT: d5148d0e TINYML_ALGO-532 REVERT: 1fe83124 TINYML_ALGO-638 REVERT: 6828df1f Pull request #79: Adding LR logs using Metric logger in regression REVERT: e777c8b1 changing log for test to match other flows REVERT: bd15248e lr in logs using metric logger REVERT: 79cf4e87 minor REVERT: 7cd33257 Pull request #78: TINYML_ALGO-609: fix: resolve torch tensor and numpy compatibility issues in timeseries forecasting REVERT: 41837b43 fix: resolve torch tensor and numpy compatibility issues in timeseries forecasting REVERT: a2da1c3f TINYML_ALGO-583 REVERT: 8c55e5b1 TINYML_ALGO-571 REVERT: 47d35155 TINYML_ALGO-573 REVERT: 58553315 Pull request #77: Added fixed point feature extraction fns for MSPM0 REVERT: 5e6e20f4 Resolve qodo comments REVERT: c8f56ed2 Typos fixed REVERT: 2cc925ca Merge branch 'main-dev' of ssh://bitbucket.itg.ti.com/tinyml-algo/tinyml-tinyverse into MSPM0_V2 REVERT: 905ec313 Bug fix REVERT: 1af367e5 Pull request #76: Add PIR Feature Extraction - Fixed point REVERT: 5092ed20 Add PIR Feature Extraction - Fixed point REVERT: 980464fc Pull request #75: 2026/adithya/modelzoo REVERT: 05b58ad7 updated the 55k generic TS models architecture to make sure all the layers are optimized to run on the NPU REVERT: feae6571 minor REVERT: 2d508f97 Pull request #74: args.output_int set by user is None by default REVERT: b29f4df0 args.output_int set by user is None by default REVERT: 30f427e8 Pull request #73: Fixed few datatypes issues in ondevice_training.py and updated the confusion matrix similar to classification style. REVERT: 7efa609f Fixed few datatypes issues in ondevice_training.py and updated the confusion matrix similar to classification style. REVERT: 46a631a6 TINYML_ALGO-457 REVERT: 369d98ae Pull request #72: Similar for image classifiication, forecasting, regression and anomaly detection REVERT: ff4218f5 Similar for image classifiication, forecasting, regression and anomaly detection REVERT: 68796da9 Pull request #71: TINYML_ALGO-566 Enable test_vector for mspm33 REVERT: 3afb4821 TINYML_ALGO-566 Enable test_vector for mspm33 REVERT: 2be6c3f0 Pull request #68: ecg classification model and feature extraction added REVERT: 49352411 Pull request #70: TINYML_ALGO-513 : adding partial quantization variable and flow REVERT: 6de8871e Merge branch 'main-dev' of ssh://bitbucket.itg.ti.com/tinyml-algo/tinyml-tinyverse into MSPM0_V2 REVERT: fc21948f adding parser for partial_quantization REVERT: 0431a19a adding partial quantization variable and flow REVERT: 551f9fe7 changes regarding naming convention of pre-processing function REVERT: 106930c6 Pull request #69: Added 1k model for regression TINYML_ALGO-243 Regression Models REVERT: e529143b Added 1k model for regression TINYML_ALGO-243 Regression Models REVERT: 36b83571 flag input_batch_norm is removed in the newer version, so i removed it too REVERT: 78d06ef2 ecg classification model and feature extraction added REVERT: 332ab419 Bug fix, installing onnx-graphsurgeon REVERT: a0b5bdc6 Pull request #67: Added support to export the trainable model by specifying k layers from last. REVERT: 9f373c79 Added support to export the trainable model by specifying k layers from last. Used onnx_graphsurgeon to extract and export the last k layers REVERT: 7e13fd7e TINYML_ALGO-542 REVERT: 707f8734 Pull request #66: TINYML_ALGO-538 Tinyverse: Support for SKIP_NORMALIZE, when feature extraction isn't used REVERT: bedcfde7 TINYML_ALGO-538 Tinyverse: Support for SKIP_NORMALIZE, when feature extraction isn't used REVERT: 1883e300 TINYML_ALGO-537 REVERT: e0e5b2a6 Pull request #59: Added RNN,LSTM,GRU layers and LSTM(hidden size=5) model REVERT: bd6d7e6e Bug Fix for TINYML_ALGO-531 REVERT: 4c858e07 golden vector generation in forecasting, code structural change that follows latest code changes in main-dev, Removed with_input_batchnorm in the LSTM models REVERT: 99807e5a Merge branch 'main-dev' of bitbucket.itg.ti.com:tinyml-algo/tinyml-tinyverse into 2025/fasna REVERT: a5441771 TINYML_ALGO-531 REVERT: f7738872 Bug fix reported by Fasna REVERT: 9341adea Bug fix reported by Fasna REVERT: 98ac91bb TINYML_ALGO-530 REVERT: a080b508 TINYML_ALGO-530 REVERT: 71bef15a Removed with_input_bathnorm from LSTM models REVERT: 8c02ea3b rebase REVERT: d9576898 TINYML_ALGO-529 REVERT: 21ab3380 TINYML_ALGO-528 REVERT: 31ad11f2 Code Cleanup REVERT: c9eecaa2 TINYML_ALGO-523 REVERT: f4654213 minor REVERT: 15f4356d Added LSTM8 forecasting model REVERT: a13b8b70 Code Cleanup REVERT: c4a6f5b7 TINYML_ALGO-517, TINYML_ALGO-519, TINYML_ALGO-520 REVERT: 3ce34f72 TINYML_ALGO-522 REVERT: a042db6a TINYML_ALGO-522 REVERT: ac077f7c TINYML_ALGO-522 REVERT: 33e673b4 On Device Learning flow made available as an argument for all train scripts REVERT: b132787d Pull request #65: Added support for on device learning in Tinyverse. REVERT: 62f01b0e Added support for on device learning in Tinyverse. Added a model with frozen and trainable parts and exported frozen model with tvm and created trainable_parameters.c/.h for the trainable parts of the model REVERT: 945fd011 Pull request #63: 2025/tushar REVERT: 862771e9 TINYML_ALGO-515 Tinyverse: Incorrect raw_test_input when not using FE REVERT: 97845ffc Pull request #62: fixed a small bug, when num_frame_concat is greater than 1, the feature_size_per_frame and stack frame width are getting populated wrongly REVERT: 455ebd5d fixed a small bug, when num_frame_concat is greater than 1, the feature_size_per_frame and stack frame width are getting populated wrongly REVERT: eb0d7951 max pool layer of kernel_size (1, 1) doesn't make sense REVERT: de63b73d Merge branch 'main-dev' of bitbucket.itg.ti.com:tinyml-algo/tinyml-tinyverse into 2025/fasna REVERT: 0ee46974 Pull request #61: Correction in default value of skip_normalize REVERT: edd5ac28 Correction REVERT: 03f80db3 Pull request #60: TINYML_ALGO-494 ModelMaker: Compilation arguments of skip_normalize and output_int required in user_input_config REVERT: 659a2abc Included model_test_input in test_vector.c so as to align it with newer feature extraction library REVERT: 7c5b8207 corrected output tensor shape REVERT: 12871613 Added RNN,LSTM,GRU layers and LSTM(hidden size=5) model REVERT: 3091af25 TINYML_ALGO-494 ModelMaker: Compilation arguments of skip_normalize and output_int required in user_input_config REVERT: 4b5fd8f3 Pull request #58: mspm0 bin_size Fix REVERT: 23a54813 fixed the bin_size getting generated for bin_q15. earlier the flag was capturing the correct value but the self.bin_size was wrong REVERT: 3164a182 Pull request #54: fix for mnist classification example REVERT: a54577e1 Pull request #55: added support for PIR-net REVERT: 0859ef7c removed print statements in test_onnx.py REVERT: 520c4a14 removed commented out statements REVERT: 49a157ce removed print statements REVERT: f45b88b2 fix after evaluate_classification function was changed REVERT: 65ca0a24 added support for PIR-net REVERT: 1e9123d9 Pull request #52: Added a new model with linear layers and update the existing CNN model to support any length input REVERT: 6a1b079a Merge branch 'main-dev' of ssh://bitbucket.itg.ti.com/tinyml-algo/tinyml-tinyverse into MSPM0 REVERT: d1c463b9 Added a new linear model and update the existing CNN model to support any length input REVERT: 8851a8a2 Pull request #51: washing machine example changes and reg flow REVERT: 21c84f1f washing machine example changes and reg flow REVERT: 8986645e Minor bug fix on window-count REVERT: 2819a433 TINYML_ALGO-468 REVERT: d230ff77 Pull request #50: added support for PIR-net REVERT: ad30f116 ammended __init_.py script to enable PIR model REVERT: 3f8d3191 modified compilation.py script for print statement for CC2755 REVERT: ee1b8a55 added support for PIR-net REVERT: bffe3a61 TINYML_ALGO-463: All flows changed to not reload dataset for quantization REVERT: 86ef2b68 TINYML_ALGO-467- Torchinfo summary breaks Model Composer (but not Modelmaker) REVERT: 7d986e94 Pull request #49: adding 4k washing machine model REVERT: 61f3f994 washing machine 4K params model REVERT: 571098da adding 4k washing machine model REVERT: 970fc80f TINYML_ALGO-465: Bug fix that caused IP models to be printed in model.summary REVERT: 4a8f4de0 TINYML_ALGO-463- Dont re-load dataset for quantization in all flows REVERT: bb8e10b4 Pull request #48: 2025/abhijeet REVERT: 93be44ed relevant changes in regression flow REVERT: 79735ee0 Minor changes in reg train.py REVERT: 972d47f3 Based on discussions with MCE team, the environment variable for MSPM0's compiler is renamed from MSPM0_CGT_PATH to ARM_LLVM_CGT_PATH. This maintains consistency with other MCEs as well as CCS REVERT: 98250ec0 washing machine models and regression flow REVERT: 630299d0 Changes 29th Sept washing machine REVERT: 293725ec TINYML_ALGO-423 : August Example Battery_RUL Regression Model REVERT: 7461f213 Pull request #45: Added anomaly detection flow REVERT: 52d54aab Pull request #47: fixes REVERT: b69081ea fixed the accidental removal of self.preprocessing_flags.append('SKIP_NORMALIZE') REVERT: ddb56ffb Merge branch 'main-dev' of ssh://bitbucket.itg.ti.com/tinyml-algo/tinyml-tinyverse into MSPM0 REVERT: 10450aca Fixed the issues mentioned in the Anomaly detection flow PR REVERT: 226c5b66 Added anomaly detection flow REVERT: 3dff5b52 no message REVERT: d3e6a97a Pull request #46: Correction REVERT: 3b43b964 Correction REVERT: bdf8d2b5 Pull request #44: Minor fixes in forecasting flow REVERT: 8e9a14b9 Flattening axes in scatter plot to prevent indexing issues REVERT: a3c2810c minor REVERT: bdc4f6a6 minor changes REVERT: ff984086 TINYML_ALGO-454 REVERT: e4d81e39 Pull request #43: 2025/tushar REVERT: 2b3868b4 For backward compatability using value of FE_LOG_BASE as evaluated value of e REVERT: 7c368cb8 TINYML_ALGO-452 Tinyverse: Feature extraction params and preprocessing flags for new AI Library REVERT: ba1c2a53 Merge branch 'main-dev' of bitbucket.itg.ti.com:tinyml-algo/tinyml-tinyverse into 2025/fasna REVERT: 2c32eace minor REVERT: 0723948c Pull request #41: TINYML_ALGO-444: Training process to provide feedback on which data files caused false alarms REVERT: 4636a96a Release prep for v1.2 REVERT: 8bb3fe56 Pull request #39: Additional feature extraction functions added for MSPM0 + image_dataset.py and LENET5 model REVERT: 3ef22225 no message REVERT: 10c652d1 changed FE_SCALE nomeclature to FE_COMPLEX_MAG_SCALE and FE_COMPLEX_MAG_SCALE_FACTOR REVERT: 3807389a no message REVERT: 70e51d3b comment out unnecessary info print REVERT: ba23a26a removed blank lines REVERT: 7b0a72d7 renamed MnistDataset to GenericImageDataset and added logger info statements. REVERT: 4dbc4868 removed unncessary parameters from train.py and test_onnx.py for image classification. renamed MnistDataset to GenericImageDataset REVERT: 0e026f04 minor REVERT: 8e87e24b minor changes REVERT: dc890465 minor changes REVERT: 1e77f792 Changed logging configuration of file_level_classification_summary REVERT: 9618dfe5 Training process to provide feedback on which data files caused false alarms REVERT: f0b35589 added torchvision==0.22.1 for image_classification REVERT: a8225167 Merge branch 'main-dev' of ssh://bitbucket.itg.ti.com/tinyml-algo/tinyml-tinyverse into MSPM0 REVERT: f5a3b6e3 no message REVERT: bbe1e091 no message REVERT: 03b7376e minor fix for mnist REVERT: f8d5326d merged mnist branch into mspm0 branch REVERT: def9876c Merge branch 'mspm0-lenet5-mnist' into MSPM0 REVERT: 138a59da no message REVERT: 4ad59997 Pull request #40: Removed model_test_input from test_vector.c since forcasting does not use feature extraction transforms (concat) for now REVERT: d22a5d87 no message REVERT: 708fb469 Fixed error in log transformation , now users can choose their own log base (earlier only 10 and e were allowed), updated preprocessing flags for classification and forecasting so that it takes correct user input from config REVERT: 22e37c17 Removed model_test_input from test_vector.c since forcasting does not use feature extraction transforms (concat) for now REVERT: ddd01d2c temp changes REVERT: 8b2f5a48 minor cosmetic fixes for the pr REVERT: 9d31643b cleaned up the to q15 fn REVERT: 78817869 fix for pytoml to not download from github as we have observed some issues there REVERT: e59e1e09 basic support for lenet5 REVERT: bc2470d7 all modifications done to support timeseries applications for mspm0 REVERT: 639a9a86 Pull request #38: Correction for non availability of feature size per frame REVERT: c1f2e167 Correction for non availability of feature size per frame REVERT: 8e4d584f fixed a tiny bug REVERT: bd393b8a Pull request #36: Running only a model without feature extraction requires these flags in user input config REVERT: 3ac67ee9 Replicating in all files REVERT: 591e8275 Pull request #37: 2025/fasna REVERT: c650fb75 Generate golden vectors for forecasting REVERT: 7b7ba9ba Generate golden vectors for forecasting REVERT: f8dcf1fa Running only a model without feature extraction requires these flags in user input config REVERT: e065b55a TINYML_ALGO-442 REVERT: d3055aae TINYML_ALGO-442: Gain variations for different classes in a classification task REVERT: bbcf5efd Merge remote-tracking branch 'origin' into MSPM0 REVERT: 7bf44162 no message REVERT: 31a57635 updated timeseries_dataset.py to replicare kilby's ac arc feature extraction flow REVERT: a3ed3fcf Pull request #35: Bug Fix: Malformed node or string error for certain files REVERT: 1414d49a Merge branch 'main-dev' of bitbucket.itg.ti.com:tinyml-algo/tinyml-tinyverse into 2025/fasna REVERT: 5f674c57 Minor changes REVERT: afd5d745 Minor edit in logger placement REVERT: 7b4bc89a Minor bug fix REVERT: 0e936f8c Pull request #34: Use tensors to calculate r2_score and smape REVERT: 04907b09 Merge branch 'main-dev' of bitbucket.itg.ti.com:tinyml-algo/tinyml-tinyverse into 2025/fasna REVERT: 5273ee45 added metric logger statements REVERT: d9683239 TINYML_ALGO-412, TINYML_ALGO-413, TINYML_ALGO-414 REVERT: 784c6fe8 Merge branch 'main-dev' of bitbucket.itg.ti.com:tinyml-algo/tinyml-tinyverse into 2025/fasna REVERT: e8adc402 use tensors to calculate r2_score and smape REVERT: c5dd15be Merge branch 'main-dev' REVERT: bb69d679 TINYML_ALGO-404: Quantization accuracy on Windows is generally poor REVERT: 4dad6028 Merge branch 'main-dev' REVERT: 4f1981b0 Pull request #33: TINYML_ALGO-372: Timeseries Forecasting (tinyverse) TINYML_ALGO-405: (GoF now handles multiple file types) REVERT: bb155b12 updated r2_score function REVERT: fc8f8cf0 GoF now handles multiple file types REVERT: 36fff4f3 cleaned code REVERT: 4db482f9 cleaned utils.py REVERT: 8f52d9ce cleaned timeseries_dataset.py REVERT: f7de8731 r2 score bug REVERT: 1b2be41c minor REVERT: b3570fef minor REVERT: f471eabd minor REVERT: a78991df minor REVERT: 8c8d3161 minor REVERT: e4f5a614 removed rnn code REVERT: 5083b626 removed rnn code REVERT: 4685fd35 cleaned code REVERT: ab6955c1 minor REVERT: 79416ff4 minor REVERT: a6e840a5 minor REVERT: aceb7ec1 minor REVERT: bbb0e047 minor changes REVERT: 36ff7a91 deleted files REVERT: 047fd468 Merge branch 'main-dev' REVERT: dbb19fe8 TINYML_ALGO-406: Fixed torch not compiled with CUDA issue REVERT: 1cba1a90 Changed submodules to pip install from specific version instead of main REVERT: 67f0c9ab Changed submodules to pip install from specific version instead of main REVERT: 317a03c9 Pull request #30: Minor bug fix REVERT: 50e01da8 Minor bug fix REVERT: 65b59fb4 Pull request #29: Main dev to main merge REVERT: d51eeaaa TINYML_ALGO-364 - Cleanup of unnecesasry packages and cross platform support REVERT: a0dace5d TINYML_ALGO-397 REVERT: a9145a49 TINYML_ALGO-397-Evaluate TimeSeries_Generic_6k model REVERT: 2fb09496 TINYML_ALGO-398: Dataset Loader fails when file size is small (but larger than frame size) REVERT: 16d2d5a0 Even quantization training now reports best epoch instead of last epoch REVERT: 7707eac6 Pull request #28: 2025/tushar REVERT: 8ce7c65f Enable normalization calculations only when needed REVERT: 1b1ffd9e Added lambda reg param REVERT: 1e9bd1f0 TINYML_ALGO-394, TINYML_ALGO-395 : Support for F29, SDK dependency removed from MSPM0 REVERT: 73b59d2c Merge branch '2025/tushar' of ssh://bitbucket.itg.ti.com/tinyml-algo/tinyml-tinyverse into 2025/tushar REVERT: 24251e83 TINYML_ALGO-243 Regression Models REVERT: 2018d5e9 TINYML_ALGO-367 Enabling golden vectors for regression REVERT: ea45f4dd TINYML_ALGO-243 Regression Models REVERT: e404ba57 TINYML_ALGO-367 Enabling golden vectors for regression REVERT: af397741 TINYML_ALGO-243 Regression Models REVERT: 62a34f2b TINYML_ALGO-367 Enabling golden vectors for regression REVERT: e3269719 TINYML_ALGO-243 Regression Models REVERT: 4dbf4f9e TINYML_ALGO-367 Enabling golden vectors for regression REVERT: fb11d23a Smooth exit to NAS not finding a GPU REVERT: d53a2622 Pull request #27: Adjusments for NAS REVERT: be8bc663 Merge branch '2025/soum' of ssh://bitbucket.itg.ti.com/tinyml-algo/tinyml-tinyverse into 2025/soum REVERT: f29c492c Adjusments for NAS REVERT: a119c972 Adjusments for NAS REVERT: 8309d69e added scalling REVERT: 6c31bfe5 Backup REVERT: 92aac8ce initial commit: Forecasting REVERT: bff06220 TINYML_ALGO-385, TINYML_ALGO-386 - Version upgrade to 1.1 & C2000Ware 6.0 REVERT: a5e2b7c7 Merge branch '2025/tushar' of ssh://bitbucket.itg.ti.com/tinyml-algo/tinyml-tinyverse into 2025/tushar REVERT: ba0cadb9 TINYML_ALGO-243 Regression Models REVERT: 6ea655e4 TINYML_ALGO-367 Enabling golden vectors for regression REVERT: d3d5fefc TINYML_ALGO-243 Regression Models REVERT: bab246b4 TINYML_ALGO-367 Enabling golden vectors for regression REVERT: 54645d0e TINYML_ALGO-380: Modelmaker to be compatible with ti-mcu-nnc-2.0.0 REVERT: 3301c344 TINYML_ALGO-381: Moving away from requirements.txt REVERT: e925666e Merge branch '2025/tushar' of ssh://bitbucket.itg.ti.com/tinyml-algo/tinyml-tinyverse into 2025/tushar REVERT: 97f0b966 TINYML_ALGO-243 Regression Models REVERT: 45a6c967 TINYML_ALGO-367 Enabling golden vectors for regression REVERT: ed25ff1f TINYML_ALGO-243 Regression Models REVERT: c794d418 Added decimation, high pass filter, q15 transformation and fixed point fft (CMSIS DSP Q15) as part of feature extraction. REVERT: 567b1bb5 TINYML_ALGO-376 REVERT: cabbe55a Merge branches '2025/tushar' and '2025/tushar' of ssh://bitbucket.itg.ti.com/tinyml-algo/tinyml-tinyverse into 2025/tushar REVERT: 4b3c6c2d TINYML_ALGO-367 Enabling golden vectors for regression REVERT: e30a3960 Pull request #25: TINYML_ALGO-352: Dataset header handling fix REVERT: 772886e4 TINYML_ALGO-374 : AUC ROC & confusion matrix computation breaks if test dataset does not have ground truth representing all the classes REVERT: ac64597b TINYML_ALGO-373: If every epoch's accuracy is 0 or nan, then it wont export any checkpoint and breaks the flow REVERT: 04804b85 Dataset header handling fix REVERT: d3c72bc5 dataset header handling REVERT: 05973c7c dataset header handling fix REVERT: 5630633a TINYML_ALGO-367 Enabling golden vectors for regression REVERT: 688560ed fixed typo REVERT: 8d76b14b TINYML_ALGO-290: Updated toml with newer packages REVERT: fdca7005 TINYML_ALGO-290: Python package version updated REVERT: 35d97005 Pull request #24: Model Addition and correction in golden output dtype REVERT: 9c12b6e2 TINYML_ALGO-20 Addition of Models from STZoo TINYML_ALGO-353 dtype of golden output based on quantization type and output_dequantize REVERT: 47405172 Pull request #18: TINYML_ALGO-347 Tinyverse: Scale inputs before feature extraction and after loading datafile REVERT: b2c79bf8 TINYML_ALGO-347 Tinyverse: Scale inputs before feature extraction and after loading datafile REVERT: 4e8f13ca Pull request #17: TINYML_ALGO-343 Added argument to get quantized/dequantized output from model REVERT: 687d26e5 TINYML_ALGO-343 Added argument to get quantized/dequantized output from model REVERT: ca3b281a TINYML_ALGO-342 REVERT: b558a717 Minor bug fixes REVERT: c85acec8 Fix for quantization error logging REVERT: 768d678c Exception Handling if Multiclass ROC plots encounter NaN error REVERT: f7afbdcc Updated for quantization_error_logging REVERT: 3c01b294 GOF Utils doesnt display the plots. Just saves them REVERT: 44298e23 Pull request #14: TINYML_ALGO-239: Set default value of frame_skip to 1 REVERT: d9d067f2 made frame_skip internal for gof REVERT: 1b43783f frame_skip set internally inside gof REVERT: 538b7ba4 Merge branch 'main' of https://bitbucket.itg.ti.com/scm/tinyml-algo/tinyml-tinyverse into 2025/fasna REVERT: 4798b93d Minor bug fix if CGT path isnt found REVERT: 20929a74 Updated regression flow bugs REVERT: a24fe384 Minor update to setup files REVERT: 1197abe1 Updated YAML structure REVERT: 3c9d0662 Merge branch 'main' of https://bitbucket.itg.ti.com/scm/tinyml-algo/tinyml-tinyverse into 2025/fasna REVERT: 0f16fb4d Updated YAML structure REVERT: 89c382c6 Minor bug fix REVERT: 22170254 Pull request #15: correction in residual model, assigning values of config dict to self REVERT: 0b6a49b4 correction in residual model, assigning values of config dict to self REVERT: 42179ceb Merge branch 'main' of https://bitbucket.itg.ti.com/scm/tinyml-algo/tinyml-tinyverse into 2025/fasna REVERT: 408e2e0c Set default value of frame_skip to 1 REVERT: bf6b2135 Minor bug fix REVERT: 3eb17c9c Bug fix REVERT: 941a3f47 Minor bugfixes REVERT: 1a243066 Pull request #12: TINYML_ALGO-280 March App Example for slicing model REVERT: caa4c69e Pull request #13: TINYML_ALGO-239: Goodness of Fit Test Integration in tinyverse REVERT: b6c21659 Renamed gof_test.py to gof_utils.py REVERT: f0672103 Modified GoF notes and updated output directory of plot REVERT: 5159945b Merge branch 'main' of https://bitbucket.itg.ti.com/scm/tinyml-algo/tinyml-tinyverse into 2025/fasna REVERT: d0071c81 Goodness of Fit Test Integration REVERT: 3b461b48 removing copy of GenericTSDataset REVERT: cbdde8ab TINYML_ALGO-280 March App Example for slicing model REVERT: f92aa218 Pull request #11: 2025/adithya autoencoder REVERT: 2c294adf Feature Update for Anomaly Detection: TINYML_ALGO-265, TINYML_ALGO-266, TINYML_ALGO-267, TINYML_ALGO-268 REVERT: 13aa6ce5 Flowflush completion REVERT: 597af0dd TINYML_ALGO-282 Models are separated out into different files for better UX. Addition of Autoencoder Model Examples. TINYML_ALGO-265, TINYML_ALGO-266, TINYML_ALGO-267, TINYML_ALGO-268 REVERT: 4faaeabf Draft commit REVERT: 6b5d535a Initial commit REVERT: 8d1dbb16 Pull request #10: 2025/adithya cnn preprocessing REVERT: 716fcc79 updated feature extraction model REVERT: 50b8aa40 change linear to conv_bn_relu as linear is expensive for computation REVERT: acd7f4c5 using FE lInear model and adam optimizer REVERT: 235d73e9 More bug fixes REVERT: 7b4a2875 Draft commit REVERT: ad985f6e Floating point training works and is able to export a model. QAT fails. TVM also fails REVERT: dbfb3e3d Minor update REVERT: 5184f662 Draft commit REVERT: 8e4b3888 Draft REVERT: 6a7c201e Lot of bug fixes REVERT: 75654907 Minor bug fix REVERT: ef0afec9 Minor bug fix REVERT: a6db9a3b Support for gpu compute from tinyml-mlbackend REVERT: a26968d1 Bug Fix REVERT: 106c1f1d Minor bug fixes REVERT: 94a6df5f TINYML_ALGO-250, TINYML_ALGO-251 - Torch mps backend support REVERT: 1f367061 PTQ and QAT support in toolchain, Ternary and 4 bit support in Toolchain: TINYML_ALGO-253, TINYML_ALGO-254, TINYML_ALGO-255, TINYML_ALGO-256, TINYML_ALGO-257 REVERT: 19dd4255 Pull request #9: 2025/tushar REVERT: 3a8dbab9 correction REVERT: b1f139ae working towards support for regression REVERT: 39656031 Minor bug fix REVERT: 1ee07e9c test-bench requires artifacts generated at compilation stage REVERT: 21bce30e correction in FFTBIN 1D, 2D stacking REVERT: ea6d408c TINYML_ALGO-242 , General Cleanup REVERT: ea2f4ac2 Minor changes REVERT: 0c8d235f Feature Support for Timeseries Regression. TINYML_ALGO-235, TINYML_ALGO-233 REVERT: 41055955 Minor readme update REVERT: 6cf28609 Minor bug with redundant statements REVERT: a2d4edc7 Preparation for v1.0 release REVERT: da91ce9a Amended the temporary commit REVERT: 2631abcd Temporary commit REVERT: 4d783ae2 TINYML_ALGO-230 REVERT: 471a2c56 TINYML_ALGO-228, TINYML_ALGO-230 REVERT: b52afb15 TINYML_ALGO-215 REVERT: e6951987 Minor bug fixes REVERT: b37c679b Pull request #8: Enhancements REVERT: b9f4520d using np.sum instead of python inbuilt sum REVERT: cfa29f2c increasing the speed 5x by using different approach for iteration REVERT: 0a9c1b96 Commented out debug statements to speed up data loading significantly REVERT: 2c36a1de Minor readme edit REVERT: d66a283c Pull request #7: 2024/post training analysis REVERT: eb912bf7 TINYML_ALGO-140: Data Augmentation feature REVERT: dde19d79 Stray lines cleaned up REVERT: 3b920413 TINYML_ALGO-147, TINYML_ALGO-226 REVERT: e7ebb480 Code Cleanup REVERT: 450e4901 TINYML_ALGO-225 REVERT: 2dfc4bd3 Minor bug fixes REVERT: f0d1d73b Minor code cleanup REVERT: 44aa682f TINYML_ALGO-224 GPU run support and code cleanup. REVERT: a23090d1 Still editing REVERT: b36137a7 Changed test_onnx.py as well REVERT: afffd072 Work in progress to add AUC ROC score. Yet to add to test_onnx.py REVERT: 935520f8 Draft commit REVERT: 426d0f26 Pull request #6: 2024/tushar concat TS Dataset REVERT: 9f1a6918 removed original dataset loader and changed x_temp to x REVERT: 8f39d429 using dont-train-just-feat-ext instead of test-bench, breakdown of generate_golden_vectors function REVERT: 1c6bbda1 generalized output of basic transforms REVERT: a94aa7d4 added test_bench for tinyml-firmware REVERT: dc17581d correction in bin_size, addition of FE_RAW in preprocessing flags REVERT: 779fefc9 checked difference btw basic_binning and dataloader binning, removed basic binning and bin_size REVERT: 9583f0cc corrected the transform name in preprocessing_flags REVERT: 288e59df Commit message REVERT: 41f2bfde removed unused variable REVERT: cc66eba7 code cleanup and comments REVERT: d8a17c21 added offset and reframed variables REVERT: 4e512800 adding offset and scaling for GenericTSDataset REVERT: 6b397abb code cleanup REVERT: 653d0018 incorporating new transforms REVERT: 6d011e32 Merge branch 'main' into 2024/tushar_concat_TS_Dataset REVERT: 0905e78b changed simple timeseries parameters REVERT: 3f53f8a0 only values that are required will be present in feature extractions REVERT: f6242eff Support for Haar and Hadamard Transforms. TINYML_ALGO-219, TINYML_ALGO-220 REVERT: 2585764a Clones only torchmodelopt directory instead of edgeai-modelopt repo REVERT: 5241c4f3 Changed test_vectors.c to test_vector.c for the sake of 5.04 C2000Ware SDK having it wrongly REVERT: 1c1f5bf0 TINYML_ALGO-214 REVERT: 2fb5df3a cleaning up code REVERT: 26f7ba25 introduced a generic timeseries dataset as GenericTSDataset, including testing functionality for ArcFault, MotorFault REVERT: 2e0631ff TINYML_ALGO-160: Additional generic models REVERT: e8af9e6b TINYML_ALGO-213 REVERT: 81b6eed6 TINYML_ALGO-212 REVERT: 5cae1207 Renamed generic models appropriately REVERT: 09a6c528 renaming of variables REVERT: 4e8a4d9e added transformations Downsample and SimpleWindow of SimpleTSDataset REVERT: 94182736 all cases of mf, af can work simultaneously with kwargs REVERT: b1f5563e Updated tvm wheel to the final release REVERT: 3f90c0fc few edge cases of arc fault left REVERT: 9db70875 all 4 cases of motor fault are working REVERT: 2cf79554 restructuring the feature extraction in a single function REVERT: 1e329944 generic models changed. padding is now used. REVERT: ff768ed4 restructuring the feature extraction in a single function REVERT: 0545d61f Pull request #5: generic models changed. REVERT: da21e31c generic models changed. padding is now used. REVERT: 262ce115 modifying feature_extraction to accomodate variabe channels for future REVERT: 88407b34 arcfault and motorfault dataset combined REVERT: 98a05733 Converted the different fault detection in single class, compressed the shape changer of vax to data_packed using np REVERT: 99167fce Updated with tvm rc5 package. Removed a few unused features in timeseries_dataset REVERT: 3c43e5cc Minor updates REVERT: cc841e61 TINYML_ALGO-200 REVERT: a176ac3f Preprocessing feature updates REVERT: 7ffba99e Added AdaptiveAverage Pool Layer support REVERT: 322d74ea Updated path to latest model optimization repo REVERT: eaa8c747 Preparation for 0.9 release REVERT: d62a616b TINYML_ALGO-197 REVERT: 36224c34 TINYML_ALGO-188: Version number on the log REVERT: 3663b300 Added Average Pool support for tinynn.py. w.r.t: TINYML_ALGO-187 REVERT: 57358093 TINYML_ALGO-192: Integrate with ti_mcu_nnc 1.3.0rc4 REVERT: 5bcdf2d9 Code Clean up REVERT: 6873065c Removed default optimizer and scheduler REVERT: fbd05531 More removal of unused imports, variables and code cleanup REVERT: cf8e8be1 Removed unused imports, code cleanup REVERT: d837c68a Moved time.time() to a platform independent method REVERT: 1448ed9a TINYML_ALGO-186, added support for dual_op REVERT: 52a82fe2 Preparation for 0.9 release, TINYML_ALGO-186, added support for dual_op, TINYML_ALGO-187 : added new motor fault model REVERT: a500ea96 Replaced '..' with os.path.dirname to not assume symlinks REVERT: d8edd418 TINYML_ALGO-171: IP Protection for TI-developed arc-fault and motor-fault models on desktop REVERT: cdf08b0d Added another exception REVERT: 9057f5d3 TINYML_ALGO-179: Invalid datafiles in dataset result in training error REVERT: a1f6d5a2 Change in preprocessing file generated and its content REVERT: c743df34 Total elimination of forward slashes REVERT: 27f8b61a TINYML_ALGO-176: Bug fix for training error during training data of incompatible dimensions REVERT: 589d94d9 Added import of tinyml_proprietary models REVERT: b23979cf Moved references under tinyml_tinyverse package to enable pyinstaller REVERT: 86488573 Updated requirements with nnc-1.3.0rc2 package REVERT: 18b9da84 Doesn't break flow if devc.o is not generated while compilation REVERT: 89aee0a3 Changed workers to 0 for Windows and 16 for Linux REVERT: 919aaf5e Platform dependent workers in train/test.py REVERT: 5158fc4b Onnx version downgrade for Windows REVERT: 64eef918 Downgraded torch from 2.4.0 to 2.3.0 because of fbgemm.dll being unavailable on Windows REVERT: 7056e148 Used pep517 to remove a deprecated warning during pip REVERT: 19e33c0c Moved back to Py3.10 because of onnx-sim, onnx-optimizer packages not supported on Windows for Py3.12 REVERT: f83d33c8 Typo in requirements REVERT: 1196cfb7 Updated README REVERT: dea66c36 v0.8 release prep REVERT: 650863a7 Dynamic Preprocessing updates REVERT: 8d6a308d 'org_sr' changed to 'sampling_rate' REVERT: afc5a2f8 TINYML_ALGO-169, TINYML_ALGO-170 : Moved to Python3.12 REVERT: c227e060 Replaced forward slashes for cross OS compatibility REVERT: fad18cdf Stray space in requirements file was causing packages to not be installed REVERT: 366b9fca TINYML_ALGO-161- Changes for preprocessing handoff REVERT: cc97891c TINYML_ALGO-158 : Ability to let the user choose to keep the libc files for compilation or not TINYML_ALGO-159 : Integrate Modelmaker with TI MCU NNC 1.3.0 REVERT: 347ef83d Added FFT transform in MotorFaultDataset REVERT: b30c3f8d TINYML_ALGO-154: BYOM for testing an external model REVERT: 10ca2f40 Working code of BYOM for testing. (Not without training) REVERT: a2104124 Addressing EDGEST-954 REVERT: 02e67366 TINYML_ALGO-148 . Progress bar added for datafile loading. REVERT: f878fd8b TINYML_ALGO-146 . Graceful handling of incompatible files in the dataset REVERT: ca53a101 Updated confusion matrix display format to be a lot more intuitive REVERT: dffe80b4 Version update from 0.6 to 0.7. Logger update in train.py REVERT: e8103a4f Best Epoch metrics are printed at the end of each train run. REVERT: 5da38536 Added ArcFaultDataset, MotorFaultDataset. TINYML_ALGO-136 REVERT: 9b97c914 Generates a global.h header file in golden_test_vectors directory for easier verification in C code REVERT: 35a02224 TINYML_ALGO-131, TINYML_ALGO-141: Ability to verify a test set either separately/alongwith the dataset REVERT: dd9a371d Saving last frame of raw data for motor bearing fault as well REVERT: 864aa798 Changed TinyML to Tiny ML REVERT: 2b156b2c Bug Fix for TINYML_ALGO-75 in motor fault section. All frames are kept in raw data REVERT: 85dda4a7 Bug Fix for TINYML_ALGO-75 in arc fault section. Now only last frame is kept in raw data REVERT: d9f91907 Pull request #3: TINYML_ALGO-75 : Added raw golden vectors REVERT: 0a88d500 TINYML_ALGO-75 : Added raw golden vectors REVERT: e2f09ec1 Preparation for v0.6 release REVERT: 96afbe59 Minor update in generic_models.py REVERT: 3f18a26c Golden Test Vectors: Raw adc data was not capturing correctly when num_frame_concat was >1 REVERT: a16396c7 export_model avoid warning message REVERT: 8b3fcae6 export_model - avoid warning - changed default opset_version to 17 REVERT: 27edfb23 np.savetxt uses {} instead of [] REVERT: 2f297de5 .npy golden test vectors aren't generated anymore REVERT: 7480cfb1 Updated timeseries_dataset.py with raw adc test vectors. Updated train.py with golden text vectors now being .txt instead of .npy REVERT: f3fc7d53 Code aesthetics cleanup REVERT: f9912949 Updated NNC with Software DL link REVERT: 42216096 Minor logger text change REVERT: acebf97b class labels are in sorted order. Changed in timeseries_dataset.py. TINYML_ALGO-97 REVERT: 17a507e9 Version number update v0.2 to "0.5.0" REVERT: 75f2eb70 Minor change in using kwargs.get() in timeseries_dataset.py REVERT: fbfe2a4f LICENSE updated REVERT: fe1605e7 LICENSE updated REVERT: 20f5fd97 generic models - bug fixed and updated DictPlus to same layer name repeating REVERT: b12b5514 generic models updated - avoiding 1x1 convolution REVERT: 5ccd9c23 generic models updated (no padding for conv/maxpool) REVERT: 4328ce4b bugfix in model name REVERT: e5bf3be4 generic model definitions updated REVERT: 5ec56386 easy dict update using DictPuls REVERT: fdaf1c77 Minor bug fixes REVERT: 893b8c2f Feature Addition: Enabled IP protection using model_spec REVERT: cea17b9f Updated for Thomas's preprocessing modifications. Infer ch,wl,hl from stacking parameter addition REVERT: 3a0ba4d2 Updated for Thomas's preprocessing modifications. Infer ch,wl,hl from stacking parameter addition REVERT: 43d49fa2 TINYML_ALGO-81 -feature_size_per_frame is taken as input instead of feature_size. Changed CNN_AF_3L_LARGE to CNN_AF_3L_1400. Added a new motor fault kilby model REVERT: 036e6c1d generic_model_spec - can be a dict or list, write out model to yaml REVERT: f26335da changes and fixes in generic_model_spec REVERT: d25c5573 TINYML_ALGO-78 -> Kilby models are neither packaged nor shown in logs REVERT: 5fff5e29 Changed TINIE to TINPU, tinie to ti_npu. Updated TVM wheel to final 1.2.0 tag release in requirements REVERT: aa4983c1 daatset.samples_in_sequence has been replaced with input_features (dataset.X.shape[2]) REVERT: 3c281a2d Temporary Fix for a bug. args.variables gets changed based on dataset.X.shape[1] to accommodate concatenation of motor fault data REVERT: cac3c8da Mid way progress in integrating motor fault. Arc fault code restabilised REVERT: 7f364e58 1. Added changes to enable motor fault pre-processing REVERT: ec7abd3b Pull request #2: added model with spec REVERT: 61a777f5 generic models are working now REVERT: d69351a3 generic_model_spec separated out into a different file REVERT: b77719b7 Added generation of golden vectors for model verification. By default it is generated REVERT: 9670333d changed create_ functions to init_ in ModelSpec class REVERT: a9b662be layer types restricted to what is in tinynn REVERT: cfd5bede layer_types support added to create_model_spec REVERT: ce09e456 added model with spec REVERT: e13f294f Model summary shown during training. Added support for CNN_TS_GEN_BASE_13K in generic models. Moved kilby models to a separate kilby_models.py file. Cleaner reporting of confusion matrix REVERT: 11c6f2db Minor logging bug REVERT: c7ac9610 Training saves best validation accuracy checkpoint instead of all checkpoints/last checkpoint. Prints dataset label map. Confusion matrix description is much more cleaner. TINYML_ALGO-73 TINYML_ALGO-74 REVERT: 348bd063 app.c will not be geenrated anymore until proper code is developed. Changed TinyML to Tiny ML to avoid copyright issues. Changed defaults of CNN_AF_3L (num_channel_l1=32->12, num_channel=16->12). x_temp_raw_out is also saved in feat_ext_data REVERT: 1261db3b TINYML_ALGO-72 bug fix REVERT: f02d468a Updated requirements with nnc rc3 REVERT: 9ba3ba0d Added models: ArcFault_cnn_largest_t(CNN_AF_3L_LARGE), ArcFault_cnn_200(CNN_AF_3L_200), ArcFault_cnn_300(CNN_AF_3L_300), ArcFault_cnn_700(CNN_AF_3L_700). Updated documentation accordingly REVERT: 26408283 timeseries_dataset.py had been hard coded to support arc fault labels. Removed this and made it generalised REVERT: cacae58d Replaced dc-remove with min-fft-bin. Added fft-bin-size in train.py. Corresponding changes in timeseries_dataset. Additional feature support to remove dataset's column which has 'time' mentioned in it REVERT: 2d40b183 Updated with TVM v1.2 REVERT: 6fadd91f Updated with the latest TVM wheel v1.2 REVERT: 14c790f5 version updated REVERT: 97470336 Bug fix for class imbalance when dataset.Y is a list REVERT: 607ab40c app.c in compilation is written inside artifacts dir. train.py/load_data() has a separate utility for loading just test data. Better way to print confusion matrix REVERT: eabcee80 Store Feature Extracted Data (+ Store only without training), Class Imbalance Wwights included for training. Resolved bug causing default optimise to be adam instead of sgd. Multiclass confusion matrix is now reporting normalized values REVERT: 18c45405 Automate deletion of intermittent .bin .txt Tinie files REVERT: cb5ceec4 Updated with the latest TVM Compilation API REVERT: b2b79b37 Changes requested by Lei to preprocessing REVERT: 4b9726ab Version update for torcheval in requirements REVERT: 6bcfe0f0 Added basic Jittering code. Not tested REVERT: 33b0bbc3 Added confusion matrix and f1 score metrics REVERT: 46232f96 requirements updated REVERT: 5cb867da removed dependencies that are not needed REVERT: 9068ca2a torchscript model export added REVERT: f30eaf5b Removed accelerator mode argument, code cleanup REVERT: 74da451e Updated installation of gpu version of tinyverse REVERT: 8e8ea6b9 Support for setup_gpu REVERT: 285889da Compilation options updated to latest version of tvm REVERT: c569cfe7 Added resampling factor support REVERT: f8ffd4c3 Logger name changes for Float and Quant Training REVERT: 9a64a121 Appends float train and quant logs together REVERT: 0ea150f5 setup file with cuda support REVERT: 5e8b55db model export - changes to ensure that batch size is 1 in onnx model REVERT: 8cd1583d LICENSE file added REVERT: 859cf803 Added input_features to be passed from train.py to model. Bug fixes in Motor Fault model REVERT: e2a9dcb6 fix for small batch size REVERT: f8e2bc73 dataset generalization fix REVERT: 7f2e77df quant measure_stats is supported only by some quant modes REVERT: e6d17ede quantization_error_logging - convert error stats simplification REVERT: 1545cc84 Generalized into single dataset loader REVERT: 77cb8644 Figured a bug introduced during export model which caused the batch size to be present in the model REVERT: 7882b359 Updated logger to allow printing messages outside the process REVERT: f5e4a4f4 quantization-error-logging option added REVERT: d021caca use actual input for model export REVERT: 087e0692 removed folders that are not needed now, updated copyright headers REVERT: 0b2201ed Commented out unnecessary printing of Dataset Loaders REVERT: d5e4b164 with_input_batchnorm option to enable same model for TINIE v/s non TINIE devices REVERT: 0e470533 Added with_input_batchnorm as an argument to models REVERT: 811fb567 with_input_batchnorm option added for models REVERT: 92bddd3f model-quant-format options is not required, quantization option is used REVERT: 8d5b3a40 quantization choices uodated in training script REVERT: f4db4e33 Pull request #1: updates for TINIE compatible QAT REVERT: 28e329f4 TinyMLModelQuantFormat name change REVERT: 242e3e2b qat interface changes REVERT: ab851b23 model export cleanup REVERT: 2ed100fe model export using tinyml-modeloptimization REVERT: 6081fb6a updates for TINIE compatible QAT REVERT: 5a5423c1 Feature Extraction Preset Addition, Model naming conventions updated REVERT: 32c9d2e9 compilation.py added arg: tinie_mode REVERT: f04b0f26 Added kilby models for Arc Fault and Motor Fault detection. Renamed models as well REVERT: 8dadef3a Feature Update: Added Kilby Models for Arc Fault Detection, Added ability to choose data loaders, Added argumnets for feature extraction REVERT: 5bb89b62 Feature Update: Inter compatibility of feature extractors with Models. Models can also be given a config to change the parameters of the model without touching the definitions - model-config REVERT: 834d602a Better handoff between preprocessings and transforms. Updated a parameter in tvm_input_config.py to handle latest tvm. Support for output_ndim in audio_dataset.py . There is an export problem for post qat matchboxnet.py . REVERT: b65e23c2 Named version as 0.1 REVERT: 4b134738 Bug fix: setup_cpu.sh installs tinyverse package REVERT: b28352a5 TVM build version updated to be latest always. (480-> lastSuccessfulBuild) REVERT: 1ab6960f TVM build version updated REVERT: 33e6ca8c Ease of use to setup. REVERT: 48b0e6e3 Ease of use to setup. REVERT: 14e49d28 Ease of use to setup. REVERT: 54802c6f Git ignorable files removed REVERT: c83e0d35 Backs up QDQ model during QAT REVERT: 586234ae Feature update: Conversion of QDQ model to INT8 model REVERT: 98c3889c Feature update for QAT enabled training and model compilation REVERT: 74cb253c Feature update for QAT enabled training and model compilation REVERT: 6f62c199 Updated README.md REVERT: 9a343799 Moved audio transforms to a separate transforms directory to maintain consistency REVERT: 8b13815c Updated with README and minor bugs in audio models REVERT: 1ea5da67 Added Haar Wavelet Transform REVERT: 88e8b8d6 Tested STFT and MFCC to be working. Added few more combinations of TCResnet and MatchboxNet REVERT: 67df8421 Enabled dataset loading for audio data REVERT: afc7aa49 Enabled dataset loading for timeseries data REVERT: 973018e5 Added MatchboxNet REVERT: b0e50651 Updated with compilation support for models with multi input/multi output. Also minor debugs in train.py for audio and timeseries. REVERT: ca8b2916 Updated with compilation support for C28 + Soft TINIE REVERT: 074e0556 Added missing file that contains models added REVERT: 349a76ce Tested Multivariate Timeseries Classification REVERT: bd198a7a Feature Added: Added STFT, MFCC Preprocessing and Temporal Convolution Resnet Model REVERT: 995fe41b Feature Added: Audio Classification REVERT: f1b31fe8 Updated compilation.py for minor argparse bugs REVERT: b2616547 Updated compilation script support for cmsis-nn mode REVERT: 372d07f1 Updated code for multivariate time series data support REVERT: ec2bd45d Train.py works even if transforms are not chosen REVERT: 423e720f Updated train.py and compilation.py scripts with Loggers REVERT: 9e1e85ed Updated app.c for better UX REVERT: a808c34f First cut version of TinyVerse that can run arc detection REVERT: 5b3297dc Initial Commit REVERT: 4d52a124 Initial Commit REVERT: 0dd276fa Initial Commit git-subtree-dir: tinyml-tinyverse git-subtree-split: 23a2fa30f5e5cecb201045a3a2a4dca365f7465d

02b0abd1 Pull request #131: TINYML_ALGO-794 Modelmaker should be able to tell the estimated RAM & Flash usage for Feature Extraction REVERT: 33041e81 TINYML_ALGO-775 REVERT: 2b6782b3 TINYML_ALGO-778 REVERT: 5257fcb0 updated REVERT: 895b1a8d Pull request #128: correction in the transform of Motor fault preset for mspm0 REVERT: e40fa4e4 Pull request #127: constants.py updated for presets of bearing fault REVERT: 1c061765 constants.py updated for presets of bearing fault REVERT: a0f22bfa Pull request #125: constants.py file to updated to change the preset values of FFT used in bearing fault. REVERT: 831fa185 constants.py file to updated to change the preset values of FFT used in bearing fault. REVERT: 31f97288 Pull request #124: Adding Generic_8Input_ABS_8Feature_1Frame preset for induction motor example in constants.py REVERT: 7e3085c9 TINYML_ALGO-763 REVERT: 1d098d27 updated REVERT: c0a371d5 TINYML_ALGO-772 REVERT: ff5a4dba adding Generic_8Input_ABS_8Feature_1Frame preset for induction motor example in constants.py REVERT: 625851a2 Pull request #123: TINYML_ALGO-753: Add Generic_32Input_FFTBIN_4Feature_8Frame feature extraction preset: Add preset definition for PLAID NILM Submetered dataset support. REVERT: b6e587ce TINYML_ALGO-753: Add Generic_32Input_FFTBIN_4Feature_8Frame feature extraction preset: Add preset definition for PLAID NILM Submetered dataset support. PLAID uses 32-sample frame, FFTBIN transform, 4 features/frame, 8 frames concat. REVERT: c08e0567 Pull request #121: https://jira.itg.ti.com/browse/TINYML_ALGO-734 REVERT: 4ebe4d8f Merge branch 'MSPM0_V2' of ssh://bitbucket.itg.ti.com/tinyml-algo/tinyml-modelmaker into MSPM0_V2 REVERT: c24bc1f8 range normalisation argument removed REVERT: 4b493837 Merge branch 'main-dev' of ssh://bitbucket.itg.ti.com/tinyml-algo/tinyml-modelmaker into MSPM0_V2 REVERT: 0c3cbe6f Pull request #120: TINYML_ALGO-743: Updated SDK versions REVERT: 7afe5858 Updated the sdk version for msp to 2_11_00_xx REVERT: 1ec63b44 https://jira.itg.ti.com/browse/TINYML_ALGO-734 REVERT: aeebdee0 TINYML_ALGO-743: Updated SDK versions REVERT: 5215b249 Pull request #119: variable for range normalisation is added in feature extraction preset, also in other parameter fields REVERT: 789c96ff added description for fall detection and hand reco applications( live preview and data capture). corrected motor fault example name to motor fan blade fault for mspm0 REVERT: b8009a4b no message REVERT: 57916670 no message REVERT: 2e46a41c added support for hand gesture and fan blower dataset. plus added ccs paths for fall detection live preview and data capture REVERT: 18232e4a Updated feature extraction preset REVERT: e769de66 Merge branch 'MSPM0_V2' of ssh://bitbucket.itg.ti.com/tinyml-algo/tinyml-modelmaker into MSPM0_V2 REVERT: 5824a8d8 variable for range normalisation is added in feature extraction preset, also in other parameter fields REVERT: 78d7a569 Pull request #118: MSPM0 V2 REVERT: a5d5355c TINYML_ALGO-724 REVERT: 07519e75 updated REVERT: 34a7c65d Pull request #117: TINYML_ALGO-722: CC1314 PIR support, path updates, Plugin version update REVERT: 77a519b5 TINYML_ALGO-722: CC1314 PIR support, path updates, Plugin version update REVERT: c0241272 Merge branch 'MSPM0_V2' of ssh://bitbucket.itg.ti.com/tinyml-algo/tinyml-modelmaker into MSPM0_V2 REVERT: 633682c3 added feature extraction preset for hand gesture recognition application REVERT: 0568e13e TINYML_ALGO-720 REVERT: 27be6a90 TINYML_ALGO-719 REVERT: 7893618c TINYML_ALGO-708 REVERT: 663c8c67 TINYML_ALGO-716 REVERT: 79b8c759 TINYML_ALGO-717 REVERT: 4c5a0163 updated json REVERT: a62bf65e Pull request #115: Added logger in ModelTraining class REVERT: 922fe5f3 Pull request #116: Added support for vision and audio pipelines REVERT: e2da8422 Added MobileNetV2_58k_NPU model, incorporated Qodo suggestions REVERT: 983d6f5d no message REVERT: f5287fd1 no message REVERT: 3d94f316 Added logger in ModelTraning class REVERT: 7bdd09cd Merge branch 'main-dev' of ssh://bitbucket.itg.ti.com/tinyml-algo/tinyml-modelmaker into MSPM0_V2 REVERT: 62e31446 added support for audio REVERT: 5d7c775e updated REVERT: 761cf2fd Pull request #93: Added default values for export_samples_per_class and added flash and ram data for F28P55 and F29H85 device to enable exporting training data REVERT: 19b94fc1 Added AM13 flash and ram sizes to constants REVERT: f9bfae93 TINYML_ALGO-559 : Added default values for export_samples_per_class and added flash and ram data for F28P55 and F29H85 device to enable exporting training data REVERT: 98dd292c updated REVERT: a2404cc8 Pull request #99: compiler option for regression Hard for F28P55 REVERT: be7f9632 minor error REVERT: 0437a161 changing tolerance comments, appropriately mentioning 200% increase tolerated REVERT: 77a9004a Pull request #114: Bearing fault model for M0 REVERT: 7420a3a0 Bearing fault model for M0 REVERT: b175bebe adding flow of tolerances from params.py, in timeseries_base.py, params.py REVERT: 09704995 changing variable name to auto_quantization from partial_quantization REVERT: b5027131 adding compiler option for regression hard for F28P55 REVERT: 455234d6 Pull request #112: Image Classification Support REVERT: 0013f467 no message REVERT: 9d944fe2 TINYML_ALGO-677 REVERT: 93651853 Pull request #113: MSPM33SWSDK-2204: update MSPM33 live preview examples. REVERT: 1fed0a58 MSPM33SWSDK-2204: update MSPM33 live preview examples. REVERT: 111ebadc TINYML_ALGO-706, TINYML_ALGO-709 REVERT: 8cc1f891 fixed qodo suggestions REVERT: 0acfaad1 added presets/dataset description for coffee bean and machine readable code classification. Refactored image training flow to align with the timeseries base structure - Added image_base.py to centralize common image training/test argv generation - Updated image_classification.py to use the new image base flow REVERT: c9ad7a3f TINYML_ALGO-675, TINYML_ALGO-705 REVERT: 11abd6d5 TINYML_ALGO-706, TINYML_ALGO-709 REVERT: 910ae6bb Pull request #111: Feature/SL EDGEAI-45 enable cc2755xxx device support cls 4k npu model and documentation in ccstudio REVERT: b4f8e889 SL_EDGEAI-52 : Enable CC13xx devices for Fan Blade REVERT: 0c8fc617 Newer models REVERT: 93e5394f SL_EDGEAI-45, SL_EDGEAI-59 : Enable CC2755 and CC35X1 support for motor fault task REVERT: 567b4758 Connectivity based updates REVERT: 6865ebff Pull request #110: SL_EDGEAI-43: Add CC1312 PIR detection support REVERT: c2c945ff SL_EDGEAI-43: Add CC1312 PIR detection support REVERT: aeaeb559 TINYML_ALGO-705, TINYML_ALGO-706 REVERT: 10957481 TINYML_ALGO-703, TINYML_ALGO-704 REVERT: e4c1ad4f TINYML_ALGO-705 REVERT: 0689fdc0 TINYML_ALGO-703, TINYML_ALGO-704 REVERT: aa8c73e6 TINYML_ALGO-703, TINYML_ALGO-704 REVERT: 5ff32cbe updated REVERT: 134f0af5 updated REVERT: 38394c1a updated REVERT: 409278bd Pull request #109: TINYML_ALGO-697: Removed unsupported devices from generic timeseries tasks REVERT: 50ff29b9 TINYML_ALGO-697: Removed unsupported devices from generic timeseries tasks REVERT: b7538d07 Pull request #108: uncommenting timeseries anomaly detection and fixing installation order in setup_all.sh REVERT: 76f351c1 uncommenting timeseries anomaly detection and fixing installation order in setup_all.sh REVERT: 3961c923 Updated for Connectivity Use cases REVERT: c74c7716 Pull request #107: TINYML_ALGO-692: Updated description.py file for F3 and WiFi SDKs REVERT: 9f5a71e1 TINYML_ALGO-692: Updated description.py file for F3 and WiFi SDKs REVERT: eae2d201 TINYML_ALGO-677, TINYML_ALGO-655 REVERT: 8e5a5d12 TINYML_ALGO-677, TINYML_ALGO-675 REVERT: c86d1c24 Pull request #106: MSPM33SWSDK-2155 : Update M33 example details and SDK version. REVERT: f64d369d Pull request #105: Bugfix/TINYML ALGO-687 mnist image classification example failing due to wrong subfolder path REVERT: a5bce091 MSPM33SWSDK-2155 : Update M33 example details and SDK version. REVERT: fb215ee9 Pull request #104: bug fix for MNIST Image classification example failing due to wrong subfolder path generation: https://jira.itg.ti.com/browse/TINYML_ALGO-687 REVERT: 95c3a5e7 bug fix for MNIST Image classification example failing due to wrong subfolder path generation: https://jira.itg.ti.com/browse/TINYML_ALGO-687 REVERT: 87643260 updated REVERT: d1a27c17 Pull request #103: Add jerk detection ASM example, Updates rex dependencies for F29, AM26x REVERT: 0deb6b15 Add jerk detection ASM example, Updates rex dependencies for F29, AM26x REVERT: bf194838 Pull request #102: Add AM13 SDK entry in rex_dependencies REVERT: ea8d8991 Add AM13 SDK entry in rex_dependencies REVERT: 53f6dfd5 TINYML_ALGO-675 REVERT: 96b0625f TINYML_ALGO-663 REVERT: 8121688a updated REVERT: 693b9b7e Pull request #100: mce documentation REVERT: 995879b3 no message REVERT: 76fd6510 no message REVERT: 5d9ea9bb no message REVERT: 2c0d4b75 no message REVERT: ea046c31 added paths to the readme's for pir_detection, ecg_classification, generic_timeseries_classification, arc_fault and motor_fault Task types- for data capture and live preview REVERT: 84154c41 Updated REVERT: 5a50723c Pull request #98: edgeai studio regression task failure fix REVERT: ece69504 Updated mspm0 sdk version REVERT: ffbb3204 added support for q15-scale-factor( consumed by the rfft preprocessing even for regression task) in timeseries_regression.py REVERT: cfbd4765 updated version REVERT: 8d9795c5 updated REVERT: 3da5fc68 updated REVERT: 3d952613 Pull request #97: Updated Paths REVERT: 549b8b10 Connectivirty compiler options changes REVERT: a4f6e824 Updated Paths REVERT: 3fa0a821 Pull request #96: Enabled CDE for CC2755 and CC35X1, Updated Plugin Version, Bug Fixes REVERT: 10429003 Enabled CDE for CC2755 and CC35X1, Updated Plugin Version, Bug Fixes REVERT: 5f59c72a TINYML_ALGO-650 REVERT: e7c6f459 version update REVERT: 1ad53024 TINYML_ALGO-644 REVERT: 12e42201 Pull request #95: Updated regex for anomaly detection logs REVERT: 4a3edff2 Updated the regex for loss to match the scientific notation as well REVERT: 86168367 Updated regex for anomaly detection logs REVERT: 6b3a092a updated REVERT: a40e829d TINYML_ALGO-642 REVERT: a40b4c42 typo fix REVERT: 58c4fcca Pull request #94: MSPM0 V2 REVERT: 5d084378 Removed Anomaly detection & added REGR_2k REVERT: 5f515194 no message REVERT: d4e796e9 no message REVERT: 4923273c no message REVERT: 92495065 Merge branch 'main-dev' of ssh://bitbucket.itg.ti.com/tinyml-algo/tinyml-modelmaker into MSPM0_V2 REVERT: 55ad0b95 updated dataset paths REVERT: e52fac34 TINYML_ALGO-639 REVERT: 9a2aba77 TINYML_ALGO-638, TINYML_ALGO-636, TINYML_ALGO-621, TINYML_ALGO-620, TINYML_ALGO-619, TINYML_ALGO-616 REVERT: 5323cc71 Pull request #91: Adding regex expressions for regression flow REVERT: d21926f2 Pull request #92: TINYML_ALGO-635: Added regex patterns for displaying epoch progress, loss, test metrics for forecasting training REVERT: 162b7ff6 Added regex patterns for displaying epoch progress, loss, test metrics for forecasting training REVERT: 08299f17 regex logs for regression and changes in classification regex logs REVERT: 34073ded Updated c2000ware version to 6.01 REVERT: 47410b62 regenerated REVERT: bb5c949f regenerated REVERT: 23a5ad9f Pull request #88: Added CC1354 device support for PIR detection REVERT: cc15b891 Added CC1354 device support for PIR detection REVERT: 46c61b4b Updated REVERT: d96d8ab7 Pull request #89: TINYML_ALGO-629 Partial Quantization should have skip_norm as false for compilation REVERT: a5dff74a TINYML_ALGO-629 Partial Quantization should have skip_norm as false for compilation REVERT: cf38c1a2 Pull request #90: Added CC35X1 device support for PIR detection REVERT: 335574b7 Added CC35X1 device support for PIR detection REVERT: ddc164b4 TINYML_ALGO-624, TINYML_ALGO-621, TINYML_ALGO-620, TINYML_ALGO-619 REVERT: 448b4acf Minor typos REVERT: 8f8d59c9 regenerated REVERT: 019074fc Fixed typos REVERT: 8d2a7207 Pull request #87: enabled all task_types for all 3 mspm0 devices REVERT: 94de9a4f no message REVERT: 4df69f80 enabled all task_types for all 3 mspm0 devices REVERT: 7dd6698c Updated REVERT: 1421dcad hello_world renamed to generic_timeseries_classification for consistency REVERT: 0f642138 Updated REVERT: 9d51bf6a Pull request #86: TINYML_ALGO-497: Revert C28x compilation to -O3 optimization after compiler bug fix REVERT: 5224a3c4 Revert C28x compilation to -O3 optimization after compiler bug fix REVERT: b9b8e179 Pull request #85: TINYML_ALGO-611, TINYML_ALGO-612, TINYML_ALGO-613: Add compiler options for F29x , AM26x and MSPM33C32 devices REVERT: a9ea1da3 Fixed the sdk link of am261 REVERT: 506735c6 Enabled compiler options for AM26x, F29x, M33 REVERT: 20b5b1cb Add comprehensive documentation for deploying time series forecasting models to TI MCUs REVERT: 15ee9a21 fix device family classification for MSPM33C321Ax REVERT: 6ef9d956 Added compiler options for F29H85 REVERT: 0fea18d8 docs: add guide for deploying forecasting models from ModelMaker to device REVERT: 057c58c4 Pull request #84: Enabled compilation options for anomaly detection and added compilation option for F29H85 device REVERT: 99dbb5ca Enabled compilation options for anomaly detection and added compilation option for F29H85 device REVERT: 7ec2b0fb Updated REVERT: 8dac85c2 Updated REVERT: a650eab4 Bug fix that prevents forced_soft_npu_preset being used for devices without NPU REVERT: 95e49e58 Updated json REVERT: 4fe8faef TINYML_ALGO-571 REVERT: 7b4e12e0 TINYML_ALGO-589 REVERT: c24b2319 updated REVERT: fd7ebdb6 Updated to make Training properties dynamic. TINYML_ALGO-589 REVERT: 66b2510f Pull request #82: New device_ new task type for MSPM0 REVERT: 00ed0311 no message REVERT: 19f6f178 Merge branch 'main-dev' of ssh://bitbucket.itg.ti.com/tinyml-algo/tinyml-modelmaker into MSPM0_V2 REVERT: b534aa92 updated data capture and live preview sdk paths to the new applications for msp0:ecg, pir. corrected the baud rate for mspm0 ac arc fault data capture REVERT: 87433a4e Temporarily commented out example datasets for Model Composer REVERT: 2fb3a3cd no message REVERT: 097f2180 Pull request #81: Dev akshat REVERT: 5c10fcf9 Resolved PR comments REVERT: 2e263706 Merge branch 'MSPM0_V2' of ssh://bitbucket.itg.ti.com/tinyml-algo/tinyml-modelmaker into dev_akshat REVERT: 08f56b60 updated permissions REVERT: 850f680d Typos fixed REVERT: 55f75672 Added F29 devices REVERT: 1b19dd9a Merge branch 'main-dev' of ssh://bitbucket.itg.ti.com/tinyml-algo/tinyml-modelmaker into dev_akshat REVERT: 6cd6a736 Merge branch 'main-dev' of ssh://bitbucket.itg.ti.com/tinyml-algo/tinyml-modelmaker into MSPM0_V2 REVERT: d8a68e4b Merge branch 'main-dev' of ssh://bitbucket.itg.ti.com/tinyml-algo/tinyml-modelmaker into MSPM0_V2 REVERT: 54eb751d no message REVERT: 1de858b1 Added support for MSPM0G3519 and regression task REVERT: 2b22cecb Updated versions of codegen compilers REVERT: f9b98286 no message REVERT: 519f8bcf added ecg classification as a sepearate task REVERT: 534d859c Updated REVERT: e834a38d TINYML_ALGO-584 REVERT: 2a55be68 Bug fix causing task categories to be present under device preset descriptions whereas only task type should have been REVERT: 2dde541b no message REVERT: da8b2f8b Model Composer requirements REVERT: f2f561db TIYNML_ALGO-579 REVERT: c95222a9 no message REVERT: 18d8ce43 Pull request #80: Add PIR detection app support for MSPM0 REVERT: 0b37eaf1 Add PIR detection app support for MSPM0 REVERT: 96be8d89 1. updated afci config file with the log300 dataset and preset. Added the labelling script aswell as a detailed readme for it REVERT: a9a0ed5f Pull request #79: 2026/adithya/modelzoo REVERT: 7be383fb TINYML_ALGO-576 REVERT: c1831687 TINYML_ALGO-457 REVERT: 1c96e112 no message REVERT: 3219a49b no message REVERT: 1bcb28a2 Changed DARM_MATH_CM33 to DARM_CPU_INTRINSICS_EXIST REVERT: 6656ecf1 Updated REVERT: 81d92e95 TINYML_ALGO-565 REVERT: b1160652 TINYML_ALGO-564 REVERT: 54d839e7 reduced epochs REVERT: 295aa672 TINYML_ALGO-563 REVERT: f99dc006 TINYML_ALGO-562 REVERT: a26a3a09 TINYML_ALGO-562 REVERT: d995c733 Pull request #73: ECG classification example REVERT: b4fb9149 Pull request #78: TINYML_ALGO-513 - adding partial quantization variable and flow REVERT: de047ddc merge conflict regarding dataset name REVERT: cb7606c4 adding partial quantization variable and flow REVERT: d2277efb dataset download link updated REVERT: 3b179c9e ecg 2 class dataset renamed REVERT: 08640e41 merge conflict resolved REVERT: f80bbeab Pull request #75: TINYML_ALGO-420 October App Example: Induction Motor Speed Prediction REVERT: 5a6c577f Updated the model to TimeSeries_Generic_Regr_1k_t and device to F29H85x REVERT: 825ae6e6 TINYML_ALGO-420 October App Example: Induction Motor Speed Prediction REVERT: 5b7dc9f4 Minor REVERT: c0e67d76 Pull request #74: Updated readme and config in modelmaker for electrical fault, grid stability, gas detection REVERT: 27f5e38e Dataset correction REVERT: f5e8357d Dataset correction REVERT: 5470fcba Dataset correction REVERT: 1795889e Updated readme and config in modelmaker for electrical fault, grid stability, gas detection REVERT: f5861c94 Pull request #71: TINYML_ALGO-513:adding partial quantization results in washing machine example REVERT: ee8d569a Minor bug fix REVERT: 5edd76a8 Minor bug fix REVERT: 02f3768f feature extraction preset name change REVERT: cddfddcc ecg classification model and its feature extraction added REVERT: b4619383 Pull request #70: Added support to export the trainable model by specifying the trainable_layers_from_last parameter in the config file REVERT: 8989c038 Bug fixes REVERT: 048fa3a3 TINYML_ALGO-513:adding partial quantization results in washing machine example REVERT: b5ef1394 TINYML_ALGO-553 REVERT: 36badf0e TINYML_ALGO-552 REVERT: eceb8b06 TINYML_ALGO-552 REVERT: 941a8a7b bug_fix REVERT: 42d3876e updated REVERT: f2ddc82a TINYML_ALGO-551 REVERT: 8f467b9a TINYML_ALGO-551 REVERT: 18e65ce1 TINYML_ALGO-551 REVERT: a64cc4bc Added support to export the trainable model by specifying the trainable_layers_from_last parameter in the config file REVERT: d1c45c40 Bug fix REVERT: 878c7906 Dynamically infer target_module from task_type REVERT: ec11199b Bug fixes REVERT: 51f8279a Minor addition REVERT: 483a9c3e updated json REVERT: eb0d2bb8 TINYML_ALGO-548 REVERT: e452ea02 Pull request #65: Added CC1352R device support for PIR detection REVERT: 95a5d5ef TINYML_ALGO-548 REVERT: 47aa8f6e Added CC1352R device support for PIR detection REVERT: 0506a8ef Minor update REVERT: 6b10f304 Pull request #68: Updates to config and readme for electrical fault, grid_fault and gas sensor REVERT: 80b8fb21 Pull request #67: removing feature_size_per_frame from washing machine config.yaml REVERT: 510da062 removing not-required params from config.yaml, washing machine REVERT: 0f4a4168 removing not-required params from config.yaml, washing machine REVERT: 96774436 removing model_config from washing machine config.yaml REVERT: a7d4d330 removing feature_size_per_frame from washing machine config.yaml REVERT: 50a2f13a Added model performance in each readme REVERT: 3e75f586 TINYML_ALGO-547 REVERT: c858cda9 Made Washing Machine Models Generic REVERT: 448b0ba6 Updates to readme for electrical fault, grid_fault and gas sensor REVERT: 029aa545 TINYML_ALGO-546 REVERT: 8112bc38 TINYML_ALGO-543, TINYML_ALGO-544 REVERT: 4cfee1bc Pull request #66: changes in washing machine config.yaml REVERT: 6eeab662 changes in washing machine config.yaml REVERT: d0e9d829 TIYNML_ALGO-543, TIYNML_ALGO-544, TIYNML_ALGO-545 REVERT: c88730a3 Renamed a mce script REVERT: 96ef8153 TINYML_ALGO-542 REVERT: 816986a9 Minor bug fix REVERT: a0b07673 Pull request #64: TINYML_ALGO-539 Modelmaker: Support for regression compiler options for c29 REVERT: d5f6004e TINYML_ALGO-539 Modelmaker: Support for regression compiler options for c29 REVERT: cd28fec2 Bug fix for TINYML_ALGO-537 REVERT: 4de80508 TINYML_ALGO-537 REVERT: ae1d2b46 dockerfile update REVERT: 339f8270 Minor bug fixes with Fasna REVERT: f6875eb3 TINYML_ALGO-528 REVERT: 12e19898 Pull request #60: Added RNN,LSTM,GRU layers TINYML_ALGO-434 TINYML_ALGO-435 REVERT: 426440dc Added compilation presets for RNN/GRU/LSTM models with quantization REVERT: 514a2dbe Merge branch 'main-dev' of ssh://bitbucket.itg.ti.com/tinyml-algo/tinyml-modelmaker into 2025/fasna REVERT: b2fc86d6 NILM documentation REVERT: 9fe1e0c1 Added PLAID NILM Classification example REVERT: 865a3f10 Updated prediction plots of hvac indoor temperature forecast example REVERT: 970b228b Added HVAC indoor temperature forecast example REVERT: 5c889240 Updated performance metrics of forecast_pmsm_example REVERT: 0e2c4ec6 Bug Fix for TINYML_ALGO-531 REVERT: 4125f60b Updated arc_fault_example_dsk to dc_arc_fault_example_dsk REVERT: f559efba Error in Documentation: Link that points to examples, run using npu and without npu were interchanged REVERT: 75870f42 Deleted readme_old.md REVERT: 9ea80b56 Updated Forecasting PMSM Example with updated model REVERT: 50ed5541 TINYML_ALGO-535 REVERT: 6061cfc5 TINYML_ALGO-525, TINYML_ALGO-535 REVERT: e9dd9fba changes from main-dev REVERT: 3772037b TINYML_ALGO-534 REVERT: 48946059 TINYML_ALGO-531 REVERT: b2114375 Bug fix reported by Fasna REVERT: 852652c2 TINYML_ALGO-530 REVERT: 4f109c0d TINYML_ALGO-530 REVERT: daddd5c8 TINYML_ALGO-530 REVERT: e5747d7a TINYML_ALGO-530 REVERT: da25254a rebase REVERT: d80f9880 TINYML_ALGO-528 REVERT: b6fa0606 TINYML_ALGO-527 REVERT: 29f40baa TINYML_ALGO-526 REVERT: 98c7c628 TINYML_ALGO-523 REVERT: ee96f7c2 TINYML_ALGO-523 REVERT: cfe5cbf8 minor REVERT: 99624d20 minor REVERT: 135bc7a1 minor REVERT: c8d5870d Updating pmsm example with new model (no scaling of dataset) REVERT: 949cedb5 Updating pmsm example with new model (no scaling of dataset) REVERT: cc82a230 Merge branch 'main-dev' of ssh://bitbucket.itg.ti.com/tinyml-algo/tinyml-modelmaker into 2025/fasna REVERT: 59f3f068 Code cleanup REVERT: 83bfd804 description json update REVERT: 846b1566 TINYML_ALGO-517, TINYML_ALGO-519, TINYML_ALGO-520 REVERT: d93deeec TINYML_ALGO-521 REVERT: b2e4c5be Minor fix for On device training REVERT: 4b7eaec4 Pull request #63: Added support for ondevice learning for anomaly detection in modelmaker. REVERT: 6b179ccb TINYML_ALGO-521 REVERT: 75fc689b TINYML_ALGO-521 REVERT: 2fb9ab13 TINYML_ALGO-511 REVERT: 534ddf2b TINYML_ALGO-521 REVERT: 9ed207d2 TINYML_ALGO-521 REVERT: 5e5cae25 TINYML_ALGO-511 REVERT: 526e6c57 Added support for ondevice learning for anomaly detection in modelmaker. Now, all the artifacts that are needed for ondevice learning are generated. REVERT: 9feca716 Pull request #62: TINYML_ALGO-419 September App Example: Tushar REVERT: 61ec1c40 Updated the link of dataset REVERT: 8cd65ae7 Added torque example as a use case in readme REVERT: 0d5875f4 Completed the readme REVERT: a809a964 Wrote partial readme REVERT: a92023bb Merge branch 'main-dev' of ssh://bitbucket.itg.ti.com/tinyml-algo/tinyml-modelmaker into 2025/fasna REVERT: 2225aa03 TINYML_ALGO-419 September App Example: Tushar REVERT: 19377a39 Pull request #61: TINYML_ALGO-494 ModelMaker: Compilation arguments of skip_normalize and output_int required in user_input_config REVERT: bb3d009e Merge branch 'main-dev' of ssh://bitbucket.itg.ti.com/tinyml-algo/tinyml-modelmaker into 2025/fasna REVERT: 340161d3 minor REVERT: e5e3140a Added RNN,LSTM,GRU layers REVERT: 9a94c625 TINYML_ALGO-494 ModelMaker: Compilation arguments of skip_normalize and output_int required in user_input_config REVERT: 80585932 Pull request #58: TINYML_ALGO-496 REVERT: 296d0ad4 Pull request #53: Added readme's for Autoencoder architectuer, Training and evaluation strategy for anomaly detection and Fan blade anomlay detection example REVERT: 156d5211 minor REVERT: 817b4d5b Removed forecasting task from mspm0g3507 REVERT: e41ca22c Applied -O1 optimization only for forecasting applications REVERT: f95b2087 Merge branch 'main-dev' of ssh://bitbucket.itg.ti.com/tinyml-algo/tinyml-modelmaker into 2025/fasna REVERT: 5ff101d3 Updated NILM readme: Added ondevice results REVERT: 90426892 TINYML_ALGO-506 REVERT: 5b7b068e TINYML_ALGO-504 REVERT: 790e4ebb Minor duplication bug fix REVERT: 42724758 Added motor fault anomaly detection example Fixed typos in other readmes Updated the feature extraction name in motor fault anomaly detection to newly crated preset REVERT: b2ee6c2d Added readme's for Autoencoder architectuer, Training and evaluation strategy for anomaly detection and Fan blade anomlay detection example REVERT: 474acc91 Pull request #59: updated description.py script for live capture/preview for pir_detection REVERT: ab170f7a updated description.py script for live capture/preview for pir_detection REVERT: b764e915 Temporary workaround: Use -O1 optimization for C28x compilation until compiler bug is fixed REVERT: b7f4697a Set output_int=false in C28_HARD_TINPU compilation preset for consistency with golden vectors REVERT: d166d8e5 Minor model factor updates REVERT: b8bf4dd0 Pull request #56: Updates for MCE docs REVERT: 88f7b20a Merge branch 'main-dev' of ssh://bitbucket.itg.ti.com/tinyml-algo/tinyml-modelmaker into mce-fix-akshat REVERT: 2672df09 TINYML_ALGO-493 REVERT: 06386872 PR fix for additional information section REVERT: c06bd455 Merge branch 'main-dev' of ssh://bitbucket.itg.ti.com/tinyml-algo/tinyml-modelmaker into mce-fix-akshat REVERT: 8ade5993 script fix for model readme REVERT: 40c1983b Readme Updates to models without the md files REVERT: 22660c9b Updates for MCE docs update REVERT: daceeccd TINYML_ALGO-490 REVERT: 1000c284 json update REVERT: 431384d3 Minor update REVERT: 723a5825 Pull request #55: 2025/rahul tmp REVERT: 58bca399 bug fixes within timeseries_classification.py REVERT: 9fe49cc0 made changes to timeseries_Classification.py REVERT: fc6da652 ammended help_url for PIRDetection task REVERT: 6b784d4b Updates to descriptions.json REVERT: f99ffc34 Pull request #54: addition to description REVERT: 0780b0a2 * added paths to msp projectspecs in descriptions.py *For live capture, generic_timeseries_classification should not have both samples and sampling time. Please remove sampling time in the default values and propInfo and Second issue * For live preview example motor fault F28P55 case, the baudRate should be 2343750. This is for ASM) REVERT: 9dfeb7a4 Bug fixes to connectivity additions REVERT: 90496406 Pull request #52: MSPM0 MF and ac arc fault yaml fix REVERT: 6c951eb7 Updated json REVERT: 4d9b56db Pull request #51: 2025/rahul tmp REVERT: 6b77ed67 changed input dataset for pir_detection/config.yaml REVERT: dd60cb96 modified changes in description_timeseries.json REVERT: 9c67b683 fixed the yamls: model_name: 'TimeSeries_Generic_1k_t'( as arc fault and MF models are only present in the gui) REVERT: 4b395310 bug fixes REVERT: 52e92673 added support for CC2755 and PIR_Detection Task REVERT: babc57b4 Bug fixes REVERT: c9da2d5c added support for CC2755 and PIR_Detection Task REVERT: dd976379 Bug fixes REVERT: f2aafc45 added support for CC2755 and PIR_Detection Task REVERT: 2083addc Bug fixes REVERT: 631dbca2 added support for CC2755 and PIR_Detection Task REVERT: 2e4d763e bug fixes REVERT: 719ccced added support for CC2755 and PIR_Detection Task REVERT: 4f426fe8 Bug fixes REVERT: 78426114 added support for CC2755 and PIR_Detection Task REVERT: 002927a2 Bug fixes REVERT: d64e41bf added support for CC2755 and PIR_Detection Task REVERT: ae69f3de Bug fixes REVERT: 77392f5e added support for CC2755 and PIR_Detection Task REVERT: 4810b5c4 bug fixes REVERT: 07cf8af2 added support for CC2755 and PIR_Detection Task REVERT: 72c45d9d Bug fixes REVERT: 2dfe0fa0 added support for CC2755 and PIR_Detection Task REVERT: 7ca37aba Bug fixes REVERT: 0584e11f added support for CC2755 and PIR_Detection Task REVERT: 3e932878 Bug fixes REVERT: a3d40ba9 added support for CC2755 and PIR_Detection Task REVERT: 12e47e0a added support for CC2755 and PIR_Detection Task REVERT: 2933b944 Bug fixes REVERT: f8b3498f added support for CC2755 and PIR_Detection Task REVERT: b78e3237 Bug fixes REVERT: 45770b64 added support for CC2755 and PIR_Detection Task REVERT: 1bd881f0 Bug fixes REVERT: 21f0c63f added support for CC2755 and PIR_Detection Task REVERT: 13dc5dde Updated devices for respective applications REVERT: c1501367 Added a newer model 'TimeSeries_Generic_100_t' REVERT: 3dc16795 TINYML_ALGO-468 REVERT: 5439d1cb TINYML_ALGO-466 REVERT: c65e0ef4 Default inference_time, flash and sram setting is "TBD" instead of null REVERT: e032467d bug fixes REVERT: a117c27c bug fixes for fixing pir_detection task + added changes to pir_detection/config.yaml file REVERT: 2a43a9ff bug fixes to constants.py REVERT: e938d173 bug fixes REVERT: 774576e6 added support for CC2755 and PIR_Detection Task REVERT: 8ad758b5 Bug fixes REVERT: 09f05e3b added support for CC2755 and PIR_Detection Task REVERT: cf630ea8 Bug fixes REVERT: f29ca8a9 added support for CC2755 and PIR_Detection Task REVERT: 27a16cfe Bug fixes REVERT: 77141753 added support for CC2755 and PIR_Detection Task REVERT: f0923262 bug fixes REVERT: e9a66155 added support for CC2755 and PIR_Detection Task REVERT: 5b39c721 Bug fixes REVERT: aebe1c7c added support for CC2755 and PIR_Detection Task REVERT: 36b792e2 Bug fixes REVERT: 04c1acb0 added support for CC2755 and PIR_Detection Task REVERT: 4573ca77 Bug fixes REVERT: d53bbf4e added support for CC2755 and PIR_Detection Task REVERT: 9e08bc79 Fixes to run PIR flow REVERT: 9034799f bug fixes REVERT: 0882c5f3 added support for CC2755 and PIR_Detection Task REVERT: cda48064 Bug fixes REVERT: 1d175b36 added support for CC2755 and PIR_Detection Task REVERT: fac1dc51 Bug fixes REVERT: 95ef6cc5 added support for CC2755 and PIR_Detection Task REVERT: 1b73ae9b Bug fixes REVERT: c39b8d34 added support for CC2755 and PIR_Detection Task REVERT: 28238666 bug fixes REVERT: 6f008652 added support for CC2755 and PIR_Detection Task REVERT: 8afa87b0 Bug fixes REVERT: b04471f7 added support for CC2755 and PIR_Detection Task REVERT: f9ae44e7 Bug fixes REVERT: 5eb48234 added support for CC2755 and PIR_Detection Task REVERT: 747a7381 Bug fixes REVERT: ac5696af added support for CC2755 and PIR_Detection Task REVERT: 9e78e130 Updated devices for respective applications REVERT: fd4b5c14 removed cc2755 presets from arc fault REVERT: a9ee363e Added a newer model 'TimeSeries_Generic_100_t' REVERT: 2b39eb5e Pull request #48: Added more examples for anomaly detection flow REVERT: 27a4f34f TINYML_ALGO-468 REVERT: c5a87b49 TINYML_ALGO-485 REVERT: 6cad81fb MSPM0 SDK version updates REVERT: 5ef62a91 TINYML_ALGO-484 REVERT: 52c448a6 TINYML_ALGO-468 REVERT: 60de168e TINYML_ALGO-483 REVERT: 2eb650b7 TINYML_ALGO-482 REVERT: ba1a4d2c TINYML_ALGO-468 REVERT: eefc1857 Added more examples for anomaly detection flow REVERT: e9116181 TINYML_ALGO-468 REVERT: aeee0d28 Minor cleanup REVERT: c4383006 Pull request #49: Added my name to the readme's i contributed to REVERT: ac52599a TINYML_ALGO-466 REVERT: 68358eab Added my name to the readme's i contributed to REVERT: ed142051 Bug fix REVERT: f033ccca Version changes REVERT: 464ded9d Pull request #47: changes in washing machine readme file and config REVERT: dea92b50 Readme bug fix REVERT: 72a88893 changes in washing machine readme file and config REVERT: d9aeac51 CC2755 compiler options updated REVERT: 04c074af CC2755 compilation bug fix REVERT: 6d3d7efd Default inference_time, flash and sram setting is "TBD" instead of null REVERT: 013667bb TINYML_ALGO-477 REVERT: 07270325 TINYML_ALGO-477 REVERT: 89c2965e Bug fixes REVERT: c7c2be9a TINYML_ALGO-468 REVERT: 514a4e25 Minor update REVERT: dabf7c2a file permission update REVERT: c7b08a30 Updated REVERT: 5584815b Minor typo REVERT: c92e970b Minor update REVERT: 49d09a75 Upgraded versions of C2000ware and cgt-f28 tools REVERT: 1ace045a Pull request #46: 2025/rahul tmp REVERT: f2ba7149 added device run info for CC2755 + hello world config for CC2755 REVERT: 96f27b4e added CC2755 in description.py REVERT: c994a698 added support for CC2755 and PIR_Detection Task REVERT: f82cc99b Pull request #45: adding readme.md to washing_machine example, removing Generic_13K_regression model, as it's redundant REVERT: 6f4db212 adding readme.md to washing_machine example, removing Generic_13K_regression model, as it's redundant REVERT: ce7c3856 TINYML_ALGO-461 REVERT: d8e95789 Pull request #44: COMPILER PATH VARIABLE NAME FOR MSPM0 REVERT: 9319b9c7 Pull request #42: 2025/abhijeet REVERT: 28eedf7a relevant changes in regression flow, removing unnecessary projects REVERT: 6c97f359 Based on discussions with MCE team, the environment variable for MSPM0's compiler is renamed from MSPM0_CGT_PATH to ARM_LLVM_CGT_PATH. This maintains consistency with other MCEs as well as CCS REVERT: b71075a6 washing machine example and regression flow REVERT: 2efc945d Changes 29th Sept REVERT: 4bb51db1 TINYML_ALGO-423, TINYML_ALGO-441 : Battery RUL Example, path issue resolved for regression REVERT: 74bcdaab Moved F29 to additional devices REVERT: 370a7c71 Updated the correct json files based on MSPM0 commit REVERT: f8353a80 Updated json REVERT: 8602af47 Pull request #37: Added anomlay detection flow REVERT: df3643ee Pull request #39: MSPM0-fixes REVERT: b76310c6 Merge branch 'main-dev' of ssh://bitbucket.itg.ti.com/tinyml-algo/tinyml-modelmaker into MSPM0 REVERT: e6962bc1 no message REVERT: 188477be no message REVERT: 51b0cd52 no message REVERT: bdce7c8e Fixed the issues in PR comments REVERT: 275b55ed Pull request #38: TINYML_ALGO-460: Fixed `within_files` dataset splitting error, Completed documentation of running float model pmsm example ondevice REVERT: 6045d78b Added zip link REVERT: 1604d828 added description about msp specfic feature extraction transforms in readme, added ac arc fault dataset to constants.py and gave descriptive names to presets(MSPM0) REVERT: ff1e83ba deleted zip file REVERT: 4728fb2d documentation: running float model pmsm example ondevice REVERT: e1c24ad1 Dataset Splitting: within_files not working for applications other than Classification REVERT: 161d6f58 Added anomlay detection flow REVERT: dae378ba Merge branch 'main-dev' of ssh://bitbucket.itg.ti.com/tinyml-algo/tinyml-modelmaker into 2025/fasna REVERT: 41280226 Modified pmsm readme to only include float training REVERT: 296e4af7 TINYML_ALGO-454 REVERT: df8a95d8 Pull request #36: TINYML_ALGO-433: File-Level Classification Summary Readme REVERT: e0b9e83c Merge branch 'main-dev' of ssh://bitbucket.itg.ti.com/tinyml-algo/tinyml-modelmaker into 2025/fasna REVERT: 5b95222e file_level_classification_summary: updated file_path REVERT: 5c4d0c46 File level classification log is now packaged exception handling around test_suite import REVERT: 7009181d Minor update REVERT: 92cfad3e File-Level Classification Summary Readme REVERT: fc578374 Pull request #34: TINYML_ALGO-453 Modelmaker: Integration of device inference from test suite REVERT: b87b276b Pull request #35: 2025/fasna REVERT: 736d759b Corrected table layout of nilm classification readme REVERT: fb81191c Training process to provide feedback on which data files caused false alarms REVERT: 4e5939cc TINYML_ALGO-453 Modelmaker: Integration of device inference from test suite REVERT: 3849ed59 Pull request #33: correction made to MSPM0 feature extraction for latest Hello_world dataset REVERT: 76bf48c2 Merge branch 'main-dev' of ssh://bitbucket.itg.ti.com/tinyml-algo/tinyml-modelmaker into MSPM0 REVERT: a05aae31 corrected feature extraction steps for the new hello world dataset + corrected the garbage change i accidentally made to readme.md of post training analysis REVERT: 747777d3 TINYML_ALGO-447, TINYML_ALGO-448 REVERT: 993a300c TINYML_AGO-448 REVERT: 1d7eef8e Changed sampling rate and frame size default to 1 from arbitrary values REVERT: f54fd531 Changed http to https in dataset links REVERT: eef89ae6 Minor typo REVERT: 7c2dadb0 Release prep for 1.2 REVERT: e20a349f Pull request #31: Added support for two MSPM0 Devices and made appropriate changes for that REVERT: b412b93f no message REVERT: aa753612 no message REVERT: 2936d29c no message REVERT: 7c112ebe no message REVERT: cc430bfb no message REVERT: 29dd4158 no message REVERT: 4a04a657 no message REVERT: b3bd4cfa normalize line ends to LF REVERT: 5fce2c9a no message REVERT: 735410d4 no message REVERT: b2794987 no message REVERT: d8a5bf01 changed the order of msp devices to be at the trailing end REVERT: 95a65647 no message REVERT: ed9533c6 no message REVERT: dd72670b Merge branch 'main-dev' of ssh://bitbucket.itg.ti.com/tinyml-algo/tinyml-modelmaker into MSPM0 REVERT: 49618f7a added empty data_proc_transforms REVERT: b1e7013e correct indentation and mnist yaml has correct dataset_name=mnist_image_classification REVERT: c98ca795 added suppport for motor fault, arc_fault and generic TS FOR 3507 and 5187. Removed unncessary info about zenodo dataset REVERT: c4bf77b0 renamed the example motorfault yaml for msp to config_mspm0.yaml REVERT: 3180aa32 added details about mnist_dataset_creation.py, and made the yaml more comprehensive REVERT: 631c9eae added support for vision module REVERT: fa7fa6f8 added vision module REVERT: 381e8792 commented out unncessary line REVERT: 679d6e18 removed image_classification from timeseries REVERT: a7225e3c added vision application REVERT: 3833b1e4 removed lenet5 from timeseries REVERT: bd745e60 no message REVERT: 4bc689a6 issue with indentation resolved REVERT: 5f3dd3cc ac arc fault yaml REVERT: 3dd9438b no message REVERT: 1c760e23 deleted unncessary files REVERT: dfac4938 added hello world mspm0 yaml in hello world example folder REVERT: af898622 added vision module(corrected spacing and empty lines) REVERT: a5b2857a added vision module(corrected spacing and empty lines) REVERT: f13cb97e added vision module REVERT: fcaf9539 corrected yaml for motor fault app for mspm0 REVERT: 850ee445 Pull request #32: TINYML_ALGO-444: Training process to provide feedback on which data files caused false alarms REVERT: 26277b9a Training process to provide feedback on which data files caused false alarms REVERT: eda3b803 no message REVERT: 4fd8bc84 no message REVERT: 8e3f0279 added yaml for mnist REVERT: f8c3f411 removed unwanted arc.zip REVERT: 37ca5293 Merge branch 'main-dev' of ssh://bitbucket.itg.ti.com/tinyml-algo/tinyml-modelmaker into MSPM0 REVERT: b7917126 no message REVERT: 7ae01f2a no message REVERT: 45ff34fb Merge branch 'mspm0-lenet5-mnist' into MSPM0 REVERT: 668fe5b9 no message REVERT: fc79a57b no message REVERT: 6382321b Minor update REVERT: 7b582f5f Pull request #30: TINYML_ALGO-311 August App Example: Tushar REVERT: 1e73a39b no message REVERT: c52fc9e7 temp changes for mnist REVERT: cbff3804 fixes for the PR REVERT: 14dbf3f0 fixes REVERT: f87b7880 added changes in yaml and constants.py to enable support for ac arc fault, motor fault and wave_form classification for mspm0 REVERT: 74f7812c support added for preset for mspm0 hello world REVERT: fd59428b fix for pytoml to not download from github as we have observed some issues there+ reduced ac arc epochs to 14 REVERT: c1fd31ce no message REVERT: bc1dd45a lenet 5 basic support added REVERT: 99b76fa3 fixes for latest arc_fault REVERT: cc42d721 added descriptio for mspm0 devices REVERT: 9143696a TINYML_ALGO-443 ModelMaker: Modelmaker prints model compiled, even though when it is not REVERT: a4b93d9c Shifting and refactoring example REVERT: 4ccad872 Shifting and refactoring example REVERT: 5cc89a1c added skip normalize and output int flags for mspm0 hard and soft tinie compilation REVERT: 48a8fdb0 added device support in every required script for mspm0g3507 and mspm0g5187 REVERT: d26167f6 readme update REVERT: 18933c15 Improvements in readme REVERT: 3630114d TINYML_ALGO-442 REVERT: 883eca38 TINYML_ALGO-442 REVERT: 3df14a3d TINYML_ALGO-311 August App Example: Tushar REVERT: a4419fc3 Updated readme REVERT: f3947a83 TINYML_ALGO-442: Gain variations for different classes in a classification task REVERT: 1116cd5f Best numbers for w8a8 are 92.01 for 700t model-Zenodo dataset REVERT: 33764eb6 Pull request #29: App Examples REVERT: be9cf275 Removed August example for merge with main-dev REVERT: 49ab01f6 modified constants.py with relevant new details for mspm0 REVERT: 50d70ecf TINYML_ALGO-311 August App Example: Tushar REVERT: 1c1cb2d3 TINYML_ALGO-307 July App Example: Tushar REVERT: c153fa54 TINYML_ALGO-305 June App Example: Tushar REVERT: ce0a2ae7 getting test accuracy with w8a8 of : 93.18% REVERT: 48c4b145 final changes for zenodo dataset: getting test accuracy with w8a8 of 90.59% REVERT: a0f11fcf Merge branch 'MSPM0' of ssh://bitbucket.itg.ti.com/tinyml-algo/tinyml-modelmaker into MSPM0 REVERT: f644a174 added ac arc fault Zenodo dataset REVERT: c8fea166 bug fix REVERT: 7390a606 Added example yaml's to run fixed point fft based feature extraction REVERT: 75edfcd8 Pull request #28: quantization set to 2 in pmsm example REVERT: 0c8beaf7 changed dataset path REVERT: 63864c62 changed dataset path REVERT: 95df5ece Forecasting Readme REVERT: 6c9d7773 set compilation:True REVERT: 86d28fa9 Merge branch 'main-dev' of ssh://bitbucket.itg.ti.com/tinyml-algo/tinyml-modelmaker into 2025/fasna REVERT: 405d0bc6 quantization set to 2 REVERT: 20fc560c Defaulted num_gpus to 0 to allow Windows users to run off the shelf REVERT: 58ac54b0 TINYML_ALGO-306: Overhaul of Modelmaker structure & Documentation REVERT: 5fc928be Updated battery_dataset link REVERT: 326c60d7 Pull request #27: TINYML_ALGO-372: Timeseries Forecasting (ModelMaker) REVERT: 956a8120 TINYML_ALGO-409 REVERT: 69d6f628 minor REVERT: c84f8601 minor REVERT: ba6479ba minor REVERT: efdc2ad2 Merge branch 'main-dev' of ssh://bitbucket.itg.ti.com/tinyml-algo/tinyml-modelmaker into 2025/fasna REVERT: 69daae30 minor REVERT: 4ea87f0f minor REVERT: e677ccc4 minor REVERT: daa8642e minor REVERT: e210d327 minor REVERT: 40a90c1a Updated C2000Ware RC5 to RC8 REVERT: 798431a2 minor REVERT: c2e856c3 minor REVERT: 6da7a8c4 minor REVERT: 870974df deleted nilm test files REVERT: d5c3441c Merge branch 'main-dev' of ssh://bitbucket.itg.ti.com/tinyml-algo/tinyml-modelmaker into 2025/fasna REVERT: 3ea971bb deleted some test files REVERT: b93d088d test_files modified REVERT: 072bc744 TINYML_ALGO-409: Updated model performance numbers REVERT: f05b0db4 Deleted test_files REVERT: 69260b3b Merge branch 'main-dev' of ssh://bitbucket.itg.ti.com/tinyml-algo/tinyml-modelmaker into 2025/fasna REVERT: 46e689f0 removed rnn models REVERT: 1cc5b724 Deleted examples/sem and examples/timeseries_forecasting REVERT: cd80dfc8 Updated performance data REVERT: db529d63 Model Selection Factor starts with 0 instead of 1 REVERT: e5e2e58e Merge branch 'main-dev' REVERT: a7213b15 TINYML_ALGO-407: model_selection_factor has null values for Motor Fault and Blower Imbalance Models REVERT: 9ff75b00 Merge branch 'main-dev' of ssh://bitbucket.itg.ti.com/tinyml-algo/tinyml-modelmaker into backup/fasna-04-07-2025 REVERT: c9781d21 minor changes REVERT: 2d97b256 Changed submodules to pip install from specific version instead of main REVERT: 2af44534 Changed submodules to pip install from specific version instead of main REVERT: 31122b80 Pull request #26: C2000Ware update REVERT: 469aaf6e C2000Ware update REVERT: 7cb1a119 Pull request #25: Main dev merge to main. Prep for 1.1 release REVERT: 8b7d3174 Updated description.json REVERT: 8796bf6d commit REVERT: f899347f Backup REVERT: 5ff18818 initial commit:Forecasting REVERT: 3478a454 TINYML_ALGO-364: Removed unnecessary dependencies & cross platform initiative REVERT: 0c27a0e6 Updated dataset links from 1.0 to 1.1 REVERT: 10e9a5cf Dataset directory updated to 01_01_00 REVERT: 15b08a09 Minor update to README REVERT: fb49b524 TINYML_ALGO-308: Dataset Format Standard for Classification REVERT: 8446b061 TINYML_ALGO-397-Evaluate TimeSeries_Generic_6k model REVERT: b3fc7227 TINYML_ALGO-396: Each model to have a model_details section under common REVERT: e85c0cec Pull request #24: 2025/tushar REVERT: 715ed8e0 Correction REVERT: 8e602ff7 Correction REVERT: 52bf9f2d Correction REVERT: e3df73a0 Correction: REVERT: d62c7108 Merge branch '2025/tushar' of ssh://bitbucket.itg.ti.com/tinyml-algo/tinyml-modelmaker into 2025/tushar REVERT: de7cdee8 Correction in timeseries regression REVERT: 385fb34c TINYML_ALGO-243 TINYML_ALGO-305 June App Example: Regression REVERT: 4cf53493 TINYML_ALGO-243 TINYML_ALGO-305 June App Example: Regression REVERT: 28bc32d0 Get_from_nas changed to NAS REVERT: ae3841ef Update description files REVERT: f6400f74 Merge branch '2025/tushar' of ssh://bitbucket.itg.ti.com/tinyml-algo/tinyml-modelmaker into 2025/tushar REVERT: 06f0e3c1 Correction in timeseries regression REVERT: 12f9d9ec TINYML_ALGO-393-Dataset split 'within_files' doesnt retain header for val & test split REVERT: d751b28f TINYML_ALGO-394, TINYML_ALGO-395 : Support for F29, SDK dependency removed from MSPM0 REVERT: 96bebfdc TINYML_ALGO-392-Use CCS-consistent variables to locate C2000 SDKs REVERT: a5aa9597 Minor update to dsk.yaml REVERT: 3e6f776f Pull request #23: Added params for NAS REVERT: 736bb9fe Merge branch '2025/soum' of ssh://bitbucket.itg.ti.com/tinyml-algo/tinyml-modelmaker into 2025/soum REVERT: 299ef51d Correction in timeseries regression REVERT: f345efc5 Added params for NAS REVERT: 2acba181 Added params for NAS REVERT: c017b600 TINYML_ALGO-383: Exposed opt for space as a compilation_preset- compress_npu_layer_data REVERT: e8657d0e Removed obsolete models REVERT: ec7f52e6 TINYML_ALGO-382, TINYML_ALGO-384 - Update Model Cycle & Inference time numbers with NNC 2.0.0 & Support for F280013x REVERT: 260f5228 TINYML_ALGO-385, TINYML_ALGO-386 - Version upgrade to 1.1 & C2000Ware 6.0 REVERT: d7c5e1a0 Unimportant doc fix REVERT: 39012ca2 TINYML_ALGO-380: Modelmaker to be compatible with ti-mcu-nnc-2.0.0 REVERT: 23f774ab TINYML_ALGO-381: Moving away from requirements.txt REVERT: b5de0df8 Merge branch '2025/tushar' of ssh://bitbucket.itg.ti.com/tinyml-algo/tinyml-modelmaker into 2025/tushar REVERT: c778329b TINYML_ALGO-243 TINYML_ALGO-305 June App Example: Regression REVERT: 2375d190 TINYML_ALGO-243 TINYML_ALGO-305 June App Example: Regression REVERT: 897a4722 added ac arc fault Zenodo dataset REVERT: 009a67a7 bug fix REVERT: 0e9ed109 Added example yaml's to run fixed point fft based feature extraction REVERT: 3c763f39 TINYML_ALGO-339 REVERT: c4abfb2d TINYML_ALGO-339: Simplifying "timeseries_*.py" for model addition REVERT: a87e2d9a Fixed typo REVERT: 92640c2a TINYML_ALGO-290: Updated toml with python versions REVERT: 4663d944 TINYML_ALGO-290: Python package version updated REVERT: db4de19c TINYML_ALGO-366: tinyml-modelmaker upgrade to C2000Ware 5.05 REVERT: e34f2653 Pull request #20: Tushar march example REVERT: 8c0233ca Merge branch 'tushar_march_example' of ssh://bitbucket.itg.ti.com/tinyml-algo/tinyml-modelmaker into tushar_march_example REVERT: 4d99d3e2 Added information for test_vector.c REVERT: 380450e5 updated path of data_processing_feature_extraction example in readme REVERT: d8ed16fd Added output_dequantize param default to False REVERT: 0848c974 TINYML_ALGO-303 May App Example: Tushar REVERT: b18cc5b2 Pull request #21: modified sdk version to the latest sdk 2.05.00.05 REVERT: 2572a19a Merge branch 'tushar_march_example' of ssh://bitbucket.itg.ti.com/tinyml-algo/tinyml-modelmaker into tushar_march_example REVERT: 228a0b9b added path to latest sdk 2.05.00.05 REVERT: ee2d5352 Added information for test_vector.c REVERT: 7cceee38 updated path of data_processing_feature_extraction example in readme REVERT: de8d25b8 Added output_dequantize param default to False REVERT: 9e8c72df TINYML_ALGO-303 May App Example: Tushar REVERT: 7c73e58a Shallow cloning in git REVERT: 62c1a4bf Minor typo REVERT: 7d074385 Minor typo REVERT: 5ec4ca4d TINYML_ALGO-359 REVERT: 750faaf4 Pull request #19: MSPM0 REVERT: 60261e50 Changed target device name to M0G3507 REVERT: 1bf9035d replaced msp0 target device name to the appropriate device name 'm0g3507' REVERT: bf137830 Merge branch 'MSPM0' of ssh://bitbucket.itg.ti.com/tinyml-algo/tinyml-modelmaker into MSPM0 REVERT: 4cd598de added additional details for mspm0 REVERT: b9c9a271 Added support for MSPM0 REVERT: f78a1a81 TINYML_ALGO-358: Model Selection Factor Updated REVERT: fa0eda62 TINYML_ALGO-357: Changed dataset links from https to https, removed unsupported models from appearing in Model Composer REVERT: 762e9fca TINYML_ALGO-356 REVERT: 4be3f392 Minor update REVERT: 8c3307ff TINYML_ALGO-345: Docker Image Size Reduction REVERT: f6b9bea0 Minor bug fix REVERT: ec731435 Fix for TINYML_ALGO-344 REVERT: 82446c97 Added information for test_vector.c REVERT: 5b0f900a updated path of data_processing_feature_extraction example in readme REVERT: 553e9077 Added output_dequantize param default to False REVERT: 13a34635 TINYML_ALGO-303 May App Example: Tushar REVERT: 084ad89b Added support for MSPM0 REVERT: 2ac1ad73 Pull request #17: NILM: April Example REVERT: aa205098 Removed zip file REVERT: bd8d55ee NILM: April Example REVERT: 4f30e60a Changed Default value from None to integer REVERT: 539de286 NILM: April Example REVERT: 8a14ded8 Updated hello world dataset REVERT: 69811405 Pull request #15: TINYML_ALGO-343 Added argument to get quantized/dequantized output from model REVERT: 09b640f0 TINYML_ALGO-343 Added argument to get quantized/dequantized output from model REVERT: a882f6ca Minor bug REVERT: dcdef9f3 Updated config REVERT: 6c76b52d TINYML_ALGO-329: Updated config yaml for hello world REVERT: d99d50c2 TINYML_ALGO-337, TINYML_ALGO-329 REVERT: 24bfd4b4 Dataset path updates REVERT: ca5177a7 Pull request #14: combined feature extraction and data processing REVERT: 14ec3877 combined feature extraction and data processing REVERT: 0b62cca7 Merge branch 'main' of ssh://bitbucket.itg.ti.com/tinyml-algo/tinyml-modelmaker into 2025/fasna REVERT: 4b35c83c combined feature extraction and data processing REVERT: b960c791 Fix for bug: TINYML_ALGO-331 REVERT: 2bdb2acb Pull request #13: Tushar march example REVERT: bd7a3982 readme update REVERT: 9ea0995b identation REVERT: f145ae10 correcting feat ext REVERT: bd3b5ab8 Merge branch 'tushar_march_example' of ssh://bitbucket.itg.ti.com/tinyml-algo/tinyml-modelmaker into tushar_march_example REVERT: e7b245fb added paper for grid stability, removed downsample from data_processing REVERT: 31db5766 added paper for grid stability, removed downsample from data_processing REVERT: 7128000d Dataset path update REVERT: f8cf56d4 TINYML_ALGO-328: Upload tinyml-datasets on Software-dl REVERT: bbdc3870 TINYML_ALGO-330: OOB- Hello World - Modelmaker Support REVERT: 6817289a TINYML_ALGO-329, TINYML_ALGO-330, TINYML_ALGO-324: OOB Example: Hello world REVERT: de64c54c Updated json REVERT: b77a0444 Minor update REVERT: 17a3a0ee Minor update REVERT: 2c117c6a Minor bug REVERT: 83c33d41 TINYML_ALGO-324 : OOB Example for HelloWorld Dataset. REVERT: dbc66ebb Pull request #11: TINYML_ALGO-281: Completed Goodness of Fit README : March Example REVERT: e1ef9be5 changed input_data_path REVERT: 2bee1d0b Changed input_data_path REVERT: f0d572e5 Removed zip file REVERT: 2efb3afd changed input_data_path REVERT: 2a01635a Updated readme REVERT: 703ea158 minor REVERT: 0009d3ff merged feature_extraction and data_processing REVERT: 9bc1d056 Bug fix for TINYML_ALGO-318 REVERT: e61ad410 Updated for TINYML_ALGO-318, TINYML_ALGO-319 REVERT: 88a16a6e Minor update for ArcFault_1400_t model addition REVERT: e3de6251 Setup GPU version of tinyverse by default REVERT: 640f75ee updated YAML structure REVERT: 0c1fe23a Merge branch 'main' of ssh://bitbucket.itg.ti.com/tinyml-algo/tinyml-modelmaker into 2025/fasna REVERT: a4d66db0 Updated pyproject.toml REVERT: 6a07dfc5 Updated description.json REVERT: 7015423b Readme updates REVERT: f0938110 Readme update REVERT: 9fb14804 Minor update to readme REVERT: 02fc42e2 Minor update REVERT: 538ce624 Minor update REVERT: 77e95e61 Minor Update REVERT: c98016c1 TINYML_ALGO-295: May App Example: Fan Blade Fault Dataset REVERT: 0700e0ab Pull request #12: name and heading changed for wisdm REVERT: df46f6c3 link correction REVERT: 2617e9f9 rename features to out_channel_layer and num_splits=5 as 4 was giving accuracy problem REVERT: b712c100 spelling correction REVERT: bc3a04d7 name and heading changed for wisdm REVERT: 9e35e372 Merge branch 'main' of ssh://bitbucket.itg.ti.com/tinyml-algo/tinyml-modelmaker into 2025/fasna REVERT: 83abd5b3 Completed Goodness of Fit README- March Example REVERT: 602213ca TINYML_ALGO-289 - TinyML Modelmaker on Windows REVERT: e686a09f Merge branch 'main' of ssh://bitbucket.itg.ti.com/tinyml-algo/tinyml-modelmaker into 2025/fasna REVERT: 6917b27d Initial commit : GoF README REVERT: 0b40a26c TINYML_ALGO-287: Overview for Examples and docs REVERT: e7e02602 Readme updates REVERT: 08c62bbb Updated file names REVERT: b1abd958 Changed name of file REVERT: a68d9ec6 TINYML_ALGO-279 : Explanation for PCA on Feature Extraction REVERT: 97183362 TINYML_ALGO-270: Post Training Analysis Explanation REVERT: da8cf0f7 Pull request #9: TINYML_ALGO-286 TINYML_ALGO-280 March-April App Example REVERT: 0bbca69f consistency in folder structure REVERT: e42be9b3 readme update for grid stability addition of model in timeseries_classification REVERT: b37d4535 TINYML_ALGO-286 TINYML_ALGO-280 March-April App Example REVERT: cdbbd04c Pull request #8: TINYML_ALGO-239: Goodness of Fit Test Integration REVERT: eb3dbb03 Goodness of Fit Test Integration REVERT: eb45cefc Updated readme REVERT: f7de17fd TINYML_ALGO-284 - Dataset Split to be done per file REVERT: 8f514a65 TINYML_ALGO-277 : Default Custom Feature Extraction REVERT: 2cb37046 TINYML_ALGO-283, TINYML_ALGO-285: Re-enable ArcFault_model_1400_tRe REVERT: 01fdb1c2 Pull request #6: 2025/adithya autoencoder REVERT: 532b3d6c Feature Update for Anomaly Detection: TINYML_ALGO-265, TINYML_ALGO-266, TINYML_ALGO-267, TINYML_ALGO-268 REVERT: cebed704 More models, updated documentation REVERT: 45df29ee TINYML_ALGO-265, TINYML_ALGO-266, TINYML_ALGO-267, TINYML_ALGO-268 REVERT: 46530de1 Draft commit REVERT: f691ac72 Initial commit REVERT: 0ccb48b7 Pull request #3: 2025/tushar REVERT: b212de1a removing zip file REVERT: aa3d7343 fixes REVERT: 9d7256ff Pull request #5: README for Motor Fault dsk dataset: Feature Extraction and Data Processing REVERT: 4586b32b Updated readme REVERT: 27eb1346 Updated readme REVERT: ebbec8ba Cleanup and readme updated REVERT: 5981048c README for Motor Fault dsk dataset: Feature Extraction and Data Processing REVERT: 11f98991 Updated config file REVERT: cf509476 Pull request #4: 2025/adithya cnn preprocessing REVERT: 07dcf2ae readme.MD for wisdm REVERT: c8be8b9c TINYML_ALGO-271 WISDM example showcasing residual connections REVERT: 7dcdad7c Added wisdm example REVERT: 4898b2a5 updated feature extraction model REVERT: 8f4a7c19 changed config params REVERT: 897d67c3 Updated descriptions.json REVERT: e203c0d3 Draft commit REVERT: 1a6b7323 Draft commit REVERT: 704788f5 TINYML_ALGO-250, TINYML_ALGO-251 - Torch mps backend support REVERT: 19a63043 PTQ and QAT support in toolchain, Ternary and 4 bit support in Toolchain: TINYML_ALGO-253, TINYML_ALGO-254, TINYML_ALGO-255, TINYML_ALGO-256, TINYML_ALGO-257 REVERT: 33d6ced8 Pull request #2: 2025/tushar REVERT: 41af6e9f correction in naming convention REVERT: d177449a working towards support for regression REVERT: 90de53a6 General Code Cleanup REVERT: a066f5d6 Minor changes REVERT: af399f3a Updated descriptions.json REVERT: 460c4c87 Feature Support for Timeseries Regression. TINYML_ALGO-234, TINYML_ALGO-233 REVERT: 6b6f2fb7 Minor readme update REVERT: b94907c3 Preparation for v1.0 release REVERT: f153ba1b Updates for internal installation through pip REVERT: 569114b5 TINYML_ALGO-230 REVERT: e562460e TINYML_ALGO-228, TINYML_ALGO-230 REVERT: c39d861e TINYML_ALGO-221 REVERT: df70a091 Minor comment REVERT: f5bb2a46 Modified description.json REVERT: 06b16bcc TINYML_ALGO-140: Data Augmentation Feature REVERT: af613648 Added post_training_analysis in packaged directories REVERT: c6de80d4 Minor update REVERT: 1cc7107e Additional Config YAML comments REVERT: e69d7719 Updated description to pick model_spec from the right path in docker images REVERT: b8020dd2 Code cleanups by using str2bool REVERT: 215ee8dc Pull request #1: 2024/tushar concat TS Dataset REVERT: 3b46ec13 removed dont-train-just-feat-ext from config REVERT: b49b4845 disabled dont-train-just-feat-ext from config REVERT: 7951cdae getpass to get the user instead of hardcoded user REVERT: 1875e448 updated description timeseries REVERT: 44edaffc using dont-train-just-feat-ext instead of test-bench REVERT: da19b71f empty transform in config REVERT: e8b820e3 correction REVERT: 2072d17d added data-proc params in configs REVERT: b94cb586 added test_bench for tinyml-firmware REVERT: db0d6245 checked difference btw basic_binning and dataloader binning, removed basic binning and bin_size REVERT: ed9a8c84 TINYML_ALGO-221, TINYML_ALGO-222 REVERT: df67c818 Removed unused FFTBIN from transform array REVERT: 787844db added fft cycle transformation REVERT: 21294d6c adding offset and scaling for GenericTSDataset REVERT: bbcefbc1 changing frame-size-bt to sequence_window REVERT: a01e92da code cleanup REVERT: 69858526 Merge branch 'main' into 2024/tushar_concat_TS_Dataset REVERT: 3d1ceab2 changed simple timeseries parameters REVERT: 021ab83c only values that are required will be present in feat-ext REVERT: 65a48d6b Updated README REVERT: fb5e21e7 Increased QAT epochs default to 10 REVERT: 9657869f files changed to run the GenericTSDataset REVERT: 0f8bd59b Updated configs to have generic models so that it can be used OOB REVERT: 9115d19e Updated from C2000WARE 5.04 RC2 to RC4 REVERT: 455cb119 Updated description w.r.t newer generic models REVERT: 472f446a TINYML_ALGO-160: additional generic models REVERT: b6a5821c TINYML_ALGO-63, TINYML_ALGO-210 REVERT: 57194ab0 TINYML_ALGO-213 REVERT: 966db890 TINYML_ALGO-211 REVERT: 82a891fb TINYML_ALGO-208 REVERT: 3bbeb507 Updated setup_C2000Ware.sh with newer version REVERT: 57480c3e Updated C2000Ware version to 5.04 REVERT: 98d79b5f Updated model performance numbers, changed c2000ware setup file permissions REVERT: c6296afb Separated C2000Ware setup which requires sudo permissions REVERT: dea9ba2a Removed some stray comments REVERT: 95dff63d TINYML_ALGO-202 : Stratified split of dataset TINYML_ALGo-203 : Leave no datafile unused REVERT: 186746aa TINYML_ALGO-200 REVERT: 7b18f427 TINYML_ALGO-200 : Optimiser and Lr scheduler can be chosen from the main config yaml REVERT: 84ad401b Updated docs REVERT: 25edee27 Updated cgt version and link in setup_cg_tools.sh REVERT: c3d732f2 Preparation for 0.9 release REVERT: 1d25ccc8 TINYML_ALGO-192: Integrate with ti_mcu_nnc 1.3.0rc4 REVERT: 8dc28702 TINYML_ALGO-189 Part fix to speed up exit after success message REVERT: e0282d05 Lazy imports in runner.py to speed up in Windows REVERT: 085ac74b Removed more unused imports REVERT: 1d9bd0b9 Removed unused imports REVERT: 2d8b6418 Preparation for 0.9 release, TINYML_ALGO-186, added support for dual_op, TINYML_ALGO-187 : added new motor fault model REVERT: 0c99dc93 TINYML_ALGO-183: Dataset auto Split excludes files REVERT: 70123473 Updated description.json REVERT: 04909d87 TINYML_ALGO-171: IP Protection for TI-developed arc-fault and motor-fault models on desktop REVERT: 8623bc4b TINYML_ALGO-180: confusion matrix regex generated at end of training needs to be corrected for windows \r\n REVERT: 824aca3d Just a formatting update. REVERT: 3e8675c4 Added License for proprietary models REVERT: e9026dd5 Updated derivation of path of model_file for compilation REVERT: ee1536f9 Support for custom tools paths: C2000_CGT_PATH, C2000WARE_PATH Reverted C2000Ware to 5.02, CGT to 22.6.0 REVERT: 7b18e09f Total elimination of forward slashes, updated to cgt 22.6.1 and C2000Ware 5.03 REVERT: 4c5710d6 Moved scripts/run_tinyml_modelmaker.py inside the package tinyml_modelmaker REVERT: 39a16a43 Changed proprietary_models to tinyml_proprietary_models REVERT: 6350ddbb Update in descriptions and README REVERT: 66ebf7b4 Updates to enable Pyinstaller REVERT: 4d6d3ebb Added support for Custom_ArcFault and Custom_MotorFault preprocessing options REVERT: e5484e2c Fixed a typo REVERT: d2199f62 Better handling of junctions for windows REVERT: 2b4fcc5f Used pep517 to remove a deprecated warning during pip REVERT: 02a893e8 Updated README REVERT: fb84f37a v0.8 release prep REVERT: a8dbb7b9 Figured a bug in feature extraction names in constants.py REVERT: b653c262 Updated a stray 3.10 to 3.12 REVERT: c10c76f4 Updated a stray 3.10 to 3.12 REVERT: b2b5cce8 Dynamic Preprocessing Updates REVERT: c40e9755 Dynamic Preprocessing updates REVERT: a7b6caf7 TINYML_ALGO-169, TINYML_ALGO-170 : Moved to Python3.12 REVERT: 8edacbe5 TINYML_ALGO-164: Used subprocess to make a junction in windows as an alternate to symlinks REVERT: 6a206ee2 Replaced forward slashes for cross OS compatibility REVERT: 7024e6cc Updated constants.py for TINYML_ALGO-168 Updated confusion matrix regex name REVERT: ca5610d4 TINYML_ALGO-161- Changes for preprocessing handoff REVERT: e2598543 Updated documentation REVERT: ee7238c6 Added documentation updates REVERT: 8ad6274e TINYML_ALGO-159: Integrate Modelmaker with TI MCU NNC 1.3.0 REVERT: a67a0f6d TINYML_ALGO-158 Ability to let the user choose to keep the libc files for compilation or not. params has a temporary revert of 'properties' because MCE wasn't ready yet REVERT: ce70878b TINYML_ALGO-155: Support for Preprocessing Options for RTM - Arc Fault TINYML_ALGO-157: Revert feature extraction preset precedence over config REVERT: c0bce913 Update for Motor Fault: New Preprocessing config: MotorFault_256Input_FFT_128Feature_8Frame_3InputChannel_removeDC_2D1 REVERT: 18b0674a Dynamic Train Properties for Model Composer Extension REVERT: b775305c Updated model_description.json REVERT: eda11e3b TINYML_ALGO-154: BYOM for testing an external model REVERT: c3a02a9d Working code of BYOM for testing. (Not without training) REVERT: 122a18fc Removed TI internal proxies info REVERT: a5393ff0 Minor typo fix in WSL doc REVERT: 1bb83801 TINYML_ALGO-153: Enabled Docker image usage on WSL (+documentation) REVERT: 7566ef46 Hidden TI proxies REVERT: 9b3f45cf Updated Readme REVERT: c99343ed Updated WSL documentation REVERT: 2e63da42 TINYML_ALGO-150 . WSL documentation for Tiny ML Modelmaker REVERT: 442d971f Addressing EDGEST-954 REVERT: 3ee9837a README edit REVERT: 0b34b1b3 Documentation added for BYOM for Compilation. TINYML_ALGO-117. Added smoother flow for BYOM for compilation REVERT: 6a2227fa Added BYOM for compilation only. TINYML_ALGO-118 REVERT: 64fb0715 Updated confusion matrix regex REVERT: 78ff1895 Version update from 0.6.0 to 0.7.0. Regex added for Best Epochs REVERT: 1a416bad ArcFault and MotorFault Models are tied to dataloaders REVERT: c7210008 Bug fix for TINYML_ALGO-144 REVERT: f81a6142 Added ArcFaultDataset, MotorFaultDataset. TINYML_ALGO-136 REVERT: d6ab1d55 TINYML_ALGO-131, TINYML_ALGO-141: Ability to verify a test set either separately/alongwith the dataset on CLI REVERT: 9dad3aec Minor update to setup_all.sh REVERT: be3f6c76 Preparation for v0.6 release REVERT: 92c2b6e5 Model Selection Factor update for ArcFault Models TINYML_ALGO-95 REVERT: 4d476f4b Revert "Additional models for sungrow (sungrow_arc_model_5CNN_t,sungrow_arc_model_4CNN_t,sungrow_arc_model_3CNN_t)" REVERT: f16cfd91 Additional models for sungrow (sungrow_arc_model_5CNN_t,sungrow_arc_model_4CNN_t,sungrow_arc_model_3CNN_t) REVERT: 8592fd78 TINYML_ALGO-115: Remove Quantized Run option from GUI REVERT: 360e2a7c Added default model_spec to all model descriptions. TINYML_ALGO-114 REVERT: d7638a9f Changed f2837x to f2837xd. TINYML_ALGO-111 REVERT: 8a35c937 TINYML_ALGO-110: Device support for F2800157 REVERT: 613ad4f7 TINYML_ALGO-98 -- Archive downloadable artifacts in a zip file for a better user experience on Windows REVERT: fdfbfd86 Removed arc_fault_classification_dsi dataset from SAMPLE_DATASET_DESCRIPTIONS. Cant be used in EdgeAI Studio anymore. Can only be used in Tiny ML Modelmaker. TINYML_ALGO-109 REVERT: ebb66486 Readme updated with software-dl link REVERT: 8adca29e TINYML_ALGO-104 REVERT: 8ab82658 Changed C2000Ware installer to release version. REVERT: 427f2e41 For Arc Fault Models: Default batch Size is now 32, Default Learning Rate is now 0.04 For Motor Fault Models: Default batch Size is now 256, Default Learning Rate is now 0.01 Directly Run Quant Only Training Defaults to False REVERT: 08bea2e9 Updated input_data path to a software-dl link REVERT: 7b5bb4a3 Updated default epochs to 50, learning rate to 0.04 REVERT: 0334f1d3 Batch size changed to 32, erroneous bug caused 1D feature extraction to not be in json-> fixed REVERT: 3e23371b dataset links updated REVERT: 35424da8 Version number update v0.2 to "0.5.0" REVERT: 833ef537 Updated description with model selection factor and device selection factor REVERT: 1d9f913e Added 1D feature extraction based on Thomas request despite knowing it will error out on compilation. REVERT: a7350db1 Removed few more 1D stacking existences, updated description.json REVERT: f043bd5d MotorFault_model_3_t removed, Feature extraction with 1D stacking removed REVERT: 448b7b68 preset descriptions an target divices fix REVERT: 8d384b4f TINYML_ALGO-96, minor cleanup REVERT: c8da0a21 TINYML_ALGO-89 REVERT: 38aaefff TINYML_ALGO-90 , TINYML_ALGO-93, TINYML_ALGO-94 REVERT: 9d02298d Added TimeSeries_Generic_AF/MF_7k/3k(+_t) models for specific tasks. Updated description json for feature extraction specific tasks. Addresses TINYML_ALGO-87, TINYML_ALGO-88. REVERT: bd64824f LICENSE updated REVERT: 8a6078bd TI…

b8838b5b TINYML_ALGO-820 REVERT: 8b1beff0 Pull request #53: Main dev REVERT: 66c8a258 updated REVERT: c176b560 minor update REVERT: 10ef7599 Pull request #52: Adding preset in induction_motor_speed_prediction config.yaml REVERT: 194cca42 adding preset in induction_motor_speed_prediction config.yaml REVERT: 671df6cc Pull request #50: TINYML_ALGO-735: Removed Model Support for Regression, Anamoly Detection, Forecasting as Tasks does not exist for it. REVERT: 9f911c91 TINYML_ALGO-735: Removed Model Support for Regression, Anamoly Detection, Forecasting as Tasks does not exist for it. REVERT: bdc77319 Pull request #47: Dev mspm0 REVERT: 6286dfcd Pull request #49: Updated feature extraction preset REVERT: 9936792e no message REVERT: b5db6f86 Updated feature extraction preset REVERT: 5a4752cf corrected the task type in yaml file REVERT: 8b002130 updated task type in configuration file of hand gesture recognition REVERT: 9140e13c Pull request #48: Dev mspm0 REVERT: 62dd5683 Conflict resolved REVERT: b096f1eb Pull request #41: Bearing fault REVERT: 9e097b9b TINYML_ALGO-724 REVERT: 14ea17ac TINYML_ALGO-724 REVERT: 983ee8fe Pull request #46: TINYML_ALGO-722: Added CC1314 PIR config file REVERT: e720867d Merge branch 'dev_mspm0' of ssh://bitbucket.itg.ti.com/tinyml-algo/tinyml-modelzoo into dev_mspm0 REVERT: 29dbdd1a config file for hand gesture recognition and its readme is added REVERT: 914f2322 TINYML_ALGO-722: Added CC1314 PIR config file REVERT: 0e5a4ba3 PR comments from Laavanya resolved REVERT: de8af16d Pull request #45: https://jira.itg.ti.com/browse/TINYML_ALGO-698 REVERT: 37def77b no message REVERT: 8d19528c https://jira.itg.ti.com/browse/TINYML_ALGO-698 Resolved NPU compliance issues in 20K, 40K, and 55K models by fixing layers that violated the conservative accumulator-depth rule:kernel_height × kernel_width × input_channels <= 256 20K: added 1x1 bottleneck before final 3x1 conv to avoid 3x1 over 128 channels 40K: added 1x1 bottleneck before 7x1 conv to reduce input channels from 40 to 36 55K: added 1x1 bottleneck before 5x1 conv to reduce input channels from 64 to 48 REVERT: 075bb03a Pull request #44: Changing quantization of hvac_indoor_forecasting example from 2 to 1 REVERT: 3496133b Changing quantization of hvac_indoor_forecasting example from 2 to 1 REVERT: 173a78c0 Pull request #43: Added NPU compliant variant of MobileNet_v2 REVERT: 9fbf9195 no message REVERT: 4bc3cae1 Conflict resolved REVERT: 2da3d194 no message REVERT: 301f718c Anomaly detection yaml file changed REVERT: 59ad5bc8 no message REVERT: de1121ab Pull request #42: Google speech command audio example REVERT: 97c0672e no message REVERT: d4e7de63 no message REVERT: 1efa83c5 Merge branch 'main-dev' of ssh://bitbucket.itg.ti.com/tinyml-algo/tinyml-modelzoo into dev_mspm0 REVERT: 1c1de7e9 no message REVERT: 81225092 Merge branch 'dev_mspm0' of ssh://bitbucket.itg.ti.com/tinyml-algo/tinyml-modelzoo into dev_mspm0 REVERT: 7e60867d support for audio REVERT: b88d82c5 Pull request #23: Added export_samples_per_class option in the config file and added ondevice learning documentation REVERT: 3bdb7dfc Pull request #40: Moved the Config_MSPM0.yaml to fan blade fault REVERT: dd6c8a8a Anomaly detection yaml changed REVERT: 013d0eb7 Dataset for anomal detection added REVERT: 9767dc87 Bearing fault model for M0 REVERT: c29472f9 Moved the Config_MSPM0.yaml to fan blade fault REVERT: c4c185f2 fixed broken links REVERT: de59d6d7 Pull request #38: Quantization change for forecasting models, variable name change to auto_quantization REVERT: 6493d8b8 Pull request #36: Added fall detection application & fixed a documentation error [MSPML-162] REVERT: 697c6b5b Pull request #35: Fixed minor naming/Doxygen issues REVERT: 116d0de0 changing quantization for forecasting models to 2, variable name changed from partial_quantization to auto_quantization REVERT: e43c4571 changing quantization for forecasting models to 2, variable name changed from partial_quantization to auto_quantization REVERT: 7c62999d changing quantization for forecasting models to 2, variable name changed from partial_quantization to auto_quantization REVERT: 1903ca16 minor REVERT: 61ac66fa Pull request #37: TINYML_ALGO-714: Removed redundant operation REVERT: dda17dda TINYML_ALGO-714: Removed redundant operation REVERT: ecc844fa Added fall detection application & fixed a documentation error REVERT: 41031b8e Added fall detection application & fixed a documentation error REVERT: 1de499cd Pull request #34: Added two new image classification examples REVERT: eba54b30 Fixed errors pointed by Qodo REVERT: 588d3ab8 Added two new image classification examples: coffee bean classification and machine readable code classification https://jira.itg.ti.com/browse/MSPML-149 REVERT: 7a936b55 TINYML_ALGO-706 REVERT: 7c79d80d updated REVERT: fd0815a1 TINYML_ALGO-705 REVERT: 442deb8d Pull request #33: Updated dataset names and removed redundant lines from config REVERT: 9de8a1f0 Updated dataset names and removed redundant lines from config REVERT: 61be623e Pull request #32: Feature/SL EDGEAI-45 enable cc2755xxx device support cls 4k npu model and documentation in ccstudio REVERT: 93057540 SL_EDGEAI-52 - Enable CC13xx devices for Fan Blade REVERT: 33043973 SL_EDGEAI-45, SL_EDGEAI-59: Add CC2755 and CC35X1 configs for fan blade fault classification REVERT: b5c6ac42 Pull request #31: Added 9 classification models and 1 new application (gearbox fault) REVERT: 6d9594f4 Added error handling and fixed linting issue REVERT: 7ee77925 Added 9 classification models and 1 new application (gearbox fault) REVERT: ab301c33 Pull request #30: SL_EDGEAI-43: Add CC1312 PIR detection configs REVERT: 41c7e5bc TINYML_ALGO-706 REVERT: 2de4f335 TINYML_ALGO-706 REVERT: 841ad3fd SL_EDGEAI-43: Add CC1312 PIR detection configs REVERT: 574d0a75 Pull request #29: Updated the configs with num_gpus=0 and updated old models with proper inputs from config REVERT: 7c5e3ae7 Updated the configs with num_gpus=0 and updated old models with proper inputs from config REVERT: 40fe2e0a Pull request #28: added example for forecasting for mspm0 REVERT: 65eb177a added example for forecasting for mspm0 REVERT: 929c3632 Pull request #27: bug fix for https://jira.itg.ti.com/browse/TINYML_ALGO-690 REVERT: d6d51a8f bug fix for https://jira.itg.ti.com/browse/TINYML_ALGO-690: having learning rate as just 1e-5 gives an error REVERT: dce1f452 TINYML_ALGO-670 REVERT: d136bea0 TINYML_ALGO-663 REVERT: ec62234a Bug fix REVERT: 25d50b2c TINYML_ALGO-137 , TINYML_ALGO-649 - Created documentation for on device learning REVERT: 3ea0abeb Fixed some formating issues in the anomaly detection compilation readme REVERT: 89e225d4 TINYML_ALGO-559: Added export_samples_per_class option in the config file. It enables the export of training data REVERT: c30000aa TINYML_ALGO-652 REVERT: b1f8eece pytorch export of models with output size 4,1 is not supported. Changed to 1,1 REVERT: fc4f7679 Pull request #26: TINYML_ALGO-648 Remove artifacts from modelzoo examples REVERT: c2acb944 Minor changes in doc REVERT: ba686e70 Remove artifacts from modelzoo examples REVERT: 43f79b9f Renamed modelmaker.sh instances to modelzoo.h REVERT: ae68ce32 Pull request #25: README's for ECG,PIR, Character reco and AFCI REVERT: 3be9755f no message REVERT: 7f4c720a no message REVERT: 90f5716e no message REVERT: 446d55a2 no message REVERT: 34078430 no message REVERT: 85006d80 no message REVERT: 614de69f no message REVERT: 2cfb2cc8 Merge branch 'main-dev' of ssh://bitbucket.itg.ti.com/tinyml-algo/tinyml-modelzoo into dev_mspm0 REVERT: fdb696ac Updated REVERT: fa548af2 no message REVERT: 7e814981 updated REVERT: 9fe81a98 no message REVERT: 635af11a added readme for pir, ecg, mnist classification, ac arc fault REVERT: 338ec7a3 updated path for user_guide REVERT: 8fad7291 typo fix REVERT: 34cecff8 Pull request #24: MSPM0 config files and readme changes REVERT: 19c8b620 am13 separated out REVERT: 904a5a9c no message REVERT: 34c6d5fa no message REVERT: c750992b no message REVERT: fd7a6d99 Merge branch 'main-dev' of ssh://bitbucket.itg.ti.com/tinyml-algo/tinyml-modelzoo into dev_mspm0 REVERT: d3e121cb no message REVERT: e217fbfc no message REVERT: 4bb66f84 no message REVERT: 4b626467 Updated with Link for User Guide REVERT: bd22fdde Pull request #16: Changes in generic_timeseries_regression REVERT: 0f67f1a2 no message REVERT: 8315fe73 no message REVERT: fe972c94 updated dataset path REVERT: 485c93b7 Merge branch 'main-dev' of ssh://bitbucket.itg.ti.com/tinyml-algo/tinyml-modelzoo into dev_mspm0 REVERT: 8378c056 no message REVERT: 522b633b minor change REVERT: 244fa59c minor changes REVERT: 968bb444 Adding 2k regression model, changing generc_timeseries_regression example with good results for fully quantized and partially quantized REVERT: 0bd7244a Removed keep_libc_files REVERT: 9f672a9d Fixed two buggy models REVERT: 9dafb065 Pull request #14: Updating versions to latest sdk versions in forecasting compilation guide REVERT: 46c71880 removed zone identifier files REVERT: 1931ea6f TINYML_ALGO-639 REVERT: 2b76f2a2 updated REVERT: cb19e655 TINYML_ALGO-636, TINYML_ALGO-621, TINYML_ALGO-620, TINYML_ALGO-619, TINYML_ALGO-616 REVERT: c6c5357d Typos fixed REVERT: a8338725 Pull request #21: Add CC1354 device support and update PIR detection configs REVERT: 48ac2cc4 Move CC1354 hello world config to generic_timeseries_classification directory REVERT: 1a20cb14 Add CC1354 device support and update PIR detection REVERT: 758c6a8c Pull request #22: Added CC35X1 device support for PIR detection REVERT: 115b98f0 Added CC35X1 device support for PIR detection REVERT: 17a37402 minor REVERT: bbd7a39b Pull request #20: TINYML_ALGO-632 REVERT: d8a083d4 TINYML_ALGO-632 REVERT: 14e05e7b Pull request #19: temp prediction update REVERT: 7e043f55 removed feature_size_per_frame in config REVERT: bf01e5a9 fixed variables range in config REVERT: 81e81c73 fixed config dataset_name REVERT: b13578e0 change example name to mosfet_temp_prediction and updated example config file REVERT: 5f65dc1f Fixed typos and bugs REVERT: 347525a6 Updated REVERT: efbcfd51 Pull request #18: Dev btv REVERT: 2ac10cef TINYML_ALGO-630 REVERT: c9488005 TINYML_ALGO-630 REVERT: 4d16de7f fixed grid_fault_detection readme REVERT: 1c620ccf added grid_fault_detection, fet junc temp projects. Grid fault detection is updated. Temp prediction is placeholder REVERT: 3c2bba24 Pull request #17: Bug fixes for edgeai release + added tensorlab only example for forecasting-mspm0 REVERT: 7bc7de41 Merge branch 'main-dev' of ssh://bitbucket.itg.ti.com/tinyml-algo/tinyml-modelzoo into dev_mspm0 REVERT: 39514e1c no message REVERT: ce2d46a3 no message REVERT: 5e101cb1 1. Added tensorlab only example for pmsm forecasting for mspm0 2. corrected the labelling script aswell as updated the labelling script readme REVERT: 4684566a Bug fixes in regression models REVERT: 4d1f0585 Pull request #13: Correcting sdk versions and adding regression compilation doc link at end of each regression example REVERT: f697a0cf Pull request #15: Updated the sdk versions and added compilation readme to other examples for anomaly detection. REVERT: 0b37b49c Updated the sdk versions and added compilation readme to other examples for anomaly detection. REVERT: bd8ccaa4 Updating versions to latest sdk versions in forecasting compilation guide REVERT: 6d77757c correcting sdk versions, adding compilation guide link at end of regression examples REVERT: 1b1260c2 Pull request #12: Linking classification on-device model inference guide at the end of two NILM examples REVERT: 3f7130f0 Linking classification on-device model inference guide at the end of two NILM examples REVERT: ce0ed2ae Pull request #10: TINYML_ALGO-606 REVERT: bdfaccb0 Updates REVERT: e0c0edc0 Pull request #11: Added generic timeseries anomaly detection example and created readme for running the model and deploying it to the device REVERT: 51d3d48c Pull request #8: [TINYML_ALGO-580: Hello World Example] [TINYML_ALGO-610: Guide for deploying forecasting models from ModelMaker to device] REVERT: e70541ef Pull request #9: TINYML_ALGO-592, TINYML_ALGO-587 : Hello world example for regression and running on device documentation REVERT: 0195a77f path changes in generic_timeseries_regression readme REVERT: 500ca77a path changes in generic_timeseries_regression readme REVERT: 4fc44678 Linking running model inference ondevice doc to other forecasting examples REVERT: 587fe36e Minor fix REVERT: 8f377f19 Modified supported devices REVERT: ca5a291a Modified pmsm example REVERT: 7c773be9 Changed input data path, Added forecasting support for these target devices: F29x, AM26x and M33 REVERT: 752a0077 Updated dataset links in generic timeseries anomaly detection REVERT: b75c2d0f Added hello world example assets REVERT: ed6c6c9a Modified hello world readme to comply with latest changesin modelzoo REVERT: cd34ca11 TINYML_ALGO-607 Training options for ECG classification task does not have an option to enter number of epochs REVERT: f0d24bd5 Add comprehensive documentation for deploying time series forecasting models to TI MCUs REVERT: a4d8820b readme correction REVERT: 07600f3b name change REVERT: 7ef91aa9 Spell check and naming convention REVERT: bd49a448 Added from other docs REVERT: fb971e77 image correction REVERT: a1608738 Added generic timeseries anomaly detection example and created readme for running the model and deploying it to the device TINYML_ALGO-605 TINYML_ALGO-432 REVERT: faadabc8 Updates REVERT: 99295144 TINYML_ALGO-606 Modelzoo: Added compilation guide for classification examples REVERT: d9c46371 changing torque_measurement_regression example readme to include deployment on device document REVERT: e6a5dd1e changing washing machine example readme to include deploying on device REVERT: 91d3fea0 regression hello world, and deploying on device REVERT: fb2f8ea9 regression hello world, and deploying on device REVERT: e44d6cf8 Simulated Thermostat Dataset as Generic Timeseries Forecasting example: Initial Commit REVERT: dc1624c8 TINYML_ALGO-591 REVERT: 073f0848 Content Updates REVERT: c2d83fca Updated to an existing model REVERT: b9b6206d Pull request #7: fixes for EAI Studio REVERT: 4fd51e18 no message REVERT: 333a1083 resolved merge conflict REVERT: 2aa3e053 added msp devices to ecg and pir classification aswell as make the cls 55k model specfic to ecg classification application REVERT: 807e74d9 TINYML_ALGO-589 REVERT: 0c30971b TINYML_ALGO-589 REVERT: 6e9ea519 Pull request #6: corrections in the yaml file REVERT: c3e23945 corrections in the yaml file REVERT: 091b4ba6 Added dataset path REVERT: 2fc09387 Pull request #4: TINYML_ALGO-585 : Adding plots in washing machine readme.md REVERT: 3324caf3 Pull request #5: MSPM0 REVERT: 6663c3ae corrected the model names for the msp config yaml files REVERT: 830b37a1 bug fix REVERT: 3c25f461 Added ac arc fault, ecg, motor fault and pir config files for mspm0. added ecg as a task type REVERT: 3ade6642 Typos Fixed REVERT: b7eb4103 NPU opt models for regression REVERT: 88786d98 run_info update for regression models REVERT: e82d42ed added support for MSPM0G3519, and regression for MSPM0 REVERT: 2e1a7fb7 TINYML_ALGO-585: Washing machine weight loading readme adding plots REVERT: 135dc7db TINYML_ALGO-585: Washing machine weight loading readme adding plots REVERT: a756a9e4 TINYML_ALGO-585: Washing machine weight loading readme adding plots REVERT: 047e3096 Minor REVERT: 6041d298 updated REVERT: 6d9a53f4 Merge branch 'main' into main-dev REVERT: 90d8c9d3 Pull request #3: 2026/adithya/modelzoo REVERT: c64a128c Changed file name REVERT: 6860ebdb TINYML_ALGO-578, TINYML_ALGO-365, TINYML_ALGO-491, TINYML_ALGO-576, TINYML_ALGO-577 REVERT: b8f40a40 TINYML_ALGO-576 REVERT: 440d70c3 TINYML_ALGO-576 REVERT: ab73eeec TINYML_ALGO-457 REVERT: 6d839ad3 TINYML_ALGO-457 REVERT: bcf22643 README update REVERT: f851e5e6 minor typo REVERT: 1b045f9d Minor update REVERT: 5aa8f709 Removed files REVERT: 013d590b Added performance comparison of Motor Fault GUI models REVERT: c99db977 Pull request #1: Model Zoo Readme REVERT: 6cc4deef minor REVERT: c6d9694c removed non _t models REVERT: d945b394 updated REVERT: 84fd2022 removed REVERT: 284d4213 removed REVERT: 047f191c FEP_vs_accuracy plots REVERT: 925085f0 removed flash_vs_sram plots REVERT: 7ddcb320 Model_zoo readme draft REVERT: 36cb61e1 Model Zoo Readme REVERT: 245a355b Model Zoo Readme REVERT: c8116c00 Updated info according to TINYML_ALGO-112 REVERT: 2597e7bb Updated README REVERT: 37bf95b1 Updated readme with more models REVERT: 217e9623 Minor documentation change REVERT: 0aedce0d Updated with more models REVERT: 1f57d05e First Commit git-subtree-dir: tinyml-modelzoo git-subtree-split: b8838b5baa7ec49f29d3bc0402f8e8964aa1c85d

t5fkg8d44d-beep and others added 3 commits August 13, 2026 12:43

fix: radar_classification run() was dispatching to main_debug, not main

088e680

This was referenced Aug 14, 2026

feat: wire compile_model_if_enabled into radar, image, and audio classification #35

Open

fix: remove dead --sample-rate flag from audio_classification scripts #36

Open

feat: wire compile_model into modelmaker (explicit opt-in) + 4 review follow-ups #37

Open

t5fkg8d44d-beep added 2 commits August 14, 2026 09:09

docs: clean up plan-doc presentation for the open PR

f874793

Stripped the 'For agentic workers: REQUIRED SUB-SKILL...' header and normalized checkboxes from - [ ] to - [x] -- every task described is done.

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fix: radar_classification's run() dispatched to a dead debug function, not main() - #34

fix: radar_classification's run() dispatched to a dead debug function, not main()#34
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musicalplatypus commented Aug 14, 2026 •

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