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path: root/src/mlia/nn/tensorflow
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2022-07-26MLIA-551 Rework remains of AIET architectureBenjamin Klimczak
Re-factoring the code base to further merge the old AIET code into MLIA. - Remove last traces of the backend type 'tool' - Controlled systems removed, including SSH protocol, controller, RunningCommand, locks etc. - Build command / build dir and deploy functionality removed from Applications and Systems - Moving working_dir() - Replace module 'output_parser' with new module 'output_consumer' and merge Base64 parsing into it - Change the output consumption to optionally remove (i.e. actually consume) lines - Use Base64 parsing in GenericInferenceOutputParser, replacing the regex-based parsing and remove the now unused regex parsing - Remove AIET reporting - Pre-install applications by moving them to src/mlia/resources/backends - Rename aiet-config.json to backend-config.json - Move tests from tests/mlia/ to tests/ - Adapt unit tests to code changes - Dependencies removed: paramiko, filelock, psutil - Fix bug in corstone.py: The wrong resource directory was used which broke the functionality to download backends. - Use f-string formatting. - Use logging instead of print. Change-Id: I768bc3bb6b2eda57d219ad01be4a8e0a74167d76
2022-07-22MLIA-569 Update TensorFlow to version 2.8Raul Farkas
- Update TensorFlow to version 2.8 (now supported by Vela 3.4) - Adapt existing codebase to preserve intermediary tensors in the interpreter in order to avoid errors when trying to print all of them in the future. - Ignore types for numpy methods that do not have typing annotations in their definitions. This is needed because otherwise mypy would consider the calling function to also be untyped. Change-Id: I943ac196fd4e378f5238949b15c23a2d628c8b5e
2022-07-22MLIA-507 Upgrade Vela versionRaul Farkas
Upgrade Vela version from 3.3.0 to 3.4.0. - Adapt code to use new typing notation by replacing `numpy.array` with `numpy.ndarray` where necessary. Change-Id: I035e9564d448652aa09a52d79c71ef09663ea776
2022-06-23MLIA-545 Make quantization non-strictBenjamin Klimczak
Use TFLITE_BUILTINS instead of TFLITE_BUILTINS_INT8 to make the quantization non-strict. Note: De facto this does not change the behavior of MLIA because the TFLITE_BUILTINS_INT8 is not correctly applied with the new quantizer. See: https://github.com/tensorflow/tensorflow/issues/56535 Change-Id: Ia0782ba22c5e9223fa10fec71c16aee60b79bb57
2022-05-30Add MLIA codebase0.3.0-rc.1Diego Russo
Add MLIA codebase including sources and tests. Change-Id: Id41707559bd721edd114793618d12ccd188d8dbd