fix: vision/audio argv builders silently drop or duplicate transform flags by musicalplatypus · Pull Request #30 · TexasInstruments/tinyml-tensorlab

musicalplatypus · 2026-08-04T22:34:35Z

Summary

Two independent bugs in the vision/audio ai_modules' train/test argv builders — both variations of the same underlying defect: the train-time and test-time argv construction for the same parameter disagreeing with each other.

`image_base.py`: train/test disagree on `data_proc_transforms`'s wire format

Train argv rendered it through an f-string (stringified list, e.g. "['BINARIZE']"), while test argv passed the real list object.

prepare_transforms() (tinyml-tinyverse's train_base.py) only combines data_proc_transforms into args.transforms when isinstance(args.data_proc_transforms, list) is true, with no else branch — so the stringified form silently skipped it during training while testing still applied it. Pure train/test skew for anyone customizing this parameter, with no error or warning.

timeseries_base.py already passes the raw list on both sides correctly; image_base.py's train side now matches it. feat_ext_transform/augmentation_transform don't have this defect — they're parsed via _normalize_transform_list's literal_eval fallback, which tolerates both string and list forms — and were left untouched (not a real bug, no need to change working code).

`audio_base.py`: `--data-proc-transforms`/`--feat-ext-transform` declared twice

Both the train and test argv builders declared these two flags twice: once correctly as a raw list, and again later as a stringified f-string. argparse's last-occurrence-wins semantics meant the later, stringified declaration always won — making the earlier, correct declaration dead code. Same underlying defect as above, just duplicated instead of split across two methods.

Removed the dead duplicate declarations in both _build_common_train_argv and _build_common_test_argv, keeping the single correct raw-list version each already had.

Verification

Unit tests against the argv-building methods directly (constructed via unittest.mock.MagicMock for self — these methods only read self.params, no full ModelRunner instance needed). All 4 tests fail on the unmodified code with the exact symptoms described above (stringified list where a real list was expected; --data-proc-transforms appearing twice in the argv) and pass after the fix.

🤖 Generated with Claude Code

…flags Two independent bugs in the vision/audio ai_modules' train/test argv builders: 1. image_base.py's train argv rendered data_proc_transforms through an f-string (stringified list, e.g. "['BINARIZE']"), while test argv passed the real list object -- the two builders disagreed on the wire format for the same parameter. prepare_transforms() (tinyml-tinyverse's train_base.py) only combines data_proc_transforms into args.transforms when isinstance(args.data_proc_transforms, list) is true, with no else branch, so the stringified form silently skipped it during training while testing still applied it -- pure train/test skew for anyone customizing this parameter, with no error or warning. timeseries_base.py already passes the raw list on both sides correctly; image_base.py's train side now matches it. feat_ext_transform/augmentation_transform don't have this defect (parsed via _normalize_transform_list's literal_eval fallback, which tolerates both forms) and were left untouched. 2. audio_base.py's train and test argv builders each declared --data-proc-transforms/--feat-ext-transform twice: once correctly as a raw list, and again later as a stringified f-string. argparse's last-occurrence-wins semantics meant the later, stringified declaration always won, making the earlier, correct one dead code -- the same underlying defect as (1), just duplicated instead of split across two methods. Removed the dead duplicate declarations in both methods, keeping the single correct raw-list version each already had. Verified with unit tests against the argv-building methods directly (no full ModelRunner instance needed -- these only read self.params). All 4 tests fail on the unmodified code with the exact symptoms described above (stringified list where a real list was expected; --data-proc-transforms appearing twice in the argv) and pass after the fix. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>

An independent Opus peer review caught that fixing --data-proc-transforms (making it a raw list, matching test-time argv) introduced a new crash: prepare_transforms() (tinyml-tinyverse/references/common/train_base.py) does args.transforms = args.data_proc_transforms + args.feat_ext_transform whenever args.data_proc_transforms is a list. image_base.py's train argv builder still stringified --feat-ext-transform (and --augmentation-transform), so once --data-proc-transforms became a real list, this became `list + str`, raising: TypeError: can only concatenate list (not "str") to list on every image-classification training run (the vision default for data_proc_transforms is [], and even an empty list still enters this branch, so this wasn't conditional on the user setting anything). An earlier comment in this file claimed feat_ext_transform "doesn't have this defect: it's parsed via _normalize_transform_list's literal_eval fallback, which tolerates both string and list forms" -- that's true of a different consumer (image_dataset.py's Dataset construction, later in the pipeline) but not of prepare_transforms(), which runs first and reads feat_ext_transform directly with no such tolerance. Fixed by passing --feat-ext-transform and --augmentation-transform as raw lists too, matching _build_common_test_argv (which already did this) and timeseries_base.py's reference implementation. Adds a test that drives the REAL prepare_transforms() against the argv builder's actual output, rather than only asserting argv shape (which is exactly why the previous test suite didn't catch this -- MagicMock-based shape checks never fed the argv through the function that actually crashes). Verified to fail on the pre-this-commit code with the exact TypeError above and pass post-fix. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>

musicalplatypus · 2026-08-05T00:00:09Z

An independent peer review caught that this PR's own fix broke every image-classification training run. Pushed a follow-up commit (72196d6):

Making --data-proc-transforms a raw list (correctly, per the original fix) exposed a latent issue: prepare_transforms() in tinyml-tinyverse does args.data_proc_transforms + args.feat_ext_transform whenever data_proc_transforms is a list. --feat-ext-transform (and --augmentation-transform) were still stringified in the train argv builder, so this became list + str, raising TypeError: can only concatenate list (not "str") to list on every training run -- not conditional on any user setting, since the default data_proc_transforms=[] still enters that branch.

My earlier comment claiming feat_ext_transform "tolerates both string and list forms via _normalize_transform_list" was true of a different consumer (image_dataset.py's Dataset construction, later in the pipeline) but not of prepare_transforms(), which reads it directly with no such tolerance and runs first.

Fixed by passing both flags as raw lists too, matching _build_common_test_argv (already correct) and timeseries_base.py.

Added a test that drives the real prepare_transforms() against the argv builder's actual output rather than only checking argv shape -- confirmed to fail pre-fix with the exact TypeError above and pass post-fix.

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 2 commits August 4, 2026 18:34

Adithya-Thonse merged commit 56e77dc into TexasInstruments:main Aug 5, 2026
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fix: vision/audio argv builders silently drop or duplicate transform flags - #30

fix: vision/audio argv builders silently drop or duplicate transform flags#30
Adithya-Thonse merged 2 commits into
TexasInstruments:mainfrom
musicalplatypus:pr/vision-audio-argv-builder-bugs

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musicalplatypus commented Aug 4, 2026

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image_base.py: train/test disagree on data_proc_transforms's wire format

audio_base.py: --data-proc-transforms/--feat-ext-transform declared twice

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`image_base.py`: train/test disagree on `data_proc_transforms`'s wire format

`audio_base.py`: `--data-proc-transforms`/`--feat-ext-transform` declared twice