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Resolves: MLIA-1055, MLIA-1056, MLIA-1057
Signed-off-by: Nathan Bailey <nathan.bailey@arm.com>
Change-Id: Id573cec94e4a69117051dcd5175f383c0955d890
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- List available rewrites
- Refactor/rename 'Rewrite' class to 'RewritingOptimizer'
- Introduce a registry for rewrite functions
- Refactor 'Rewriter' to use the registry to look up rewrite functions
- Remove mentions of hardcoded "fully_connected" from CLI help and
error messages, using the registry instead
- Add unit tests
- Enable rewrites for all targets:
Extract optimization (including rewrite specific code) from the
Ethos-U-specific data collector into OptimizingDataCollector.
This is reused in other targets' collectors, such as TOSA
and Cortex-A.
- Add more logging for rewrite
- add display of MAE and NRMSE values for the trained result
- add total model MAE and NRMSE metric
Resolves: MLIA-891, MLIA-899, MLIA-906
Change-Id: Ie798749e1ed60cab14fdb6d9c2271c833960e93f
Signed-off-by: Benjamin Klimczak <benjamin.klimczak@arm.com>
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- Fix input shape of rewrite replacement:
During and after training of the replacement model for a rewrite the
Keras model is converted and saved in TensorFlow Lite format. If the
input shape does not match the teacher model exactly, e.g. if the
batch size is undefined, the TFLiteConverter adds extra operators
during conversion.
- Fix rewritten model output
- Save the model output with the rewritten operator in the output dir
- Log MAE and NRMSE of the rewrite
- Remove 'verbose' flag from rewrite module and rely on the logging
mechanism to control verbose output.
- Re-factor utility classes for rewrites
- Merge the two TFLiteModel classes
- Move functionality to load/save TensorFlow Lite flatbuffers to
nn/tensorflow/tflite_graph
- Fix issue with unknown shape in datasets
After upgrading to TensorFlow 2.12 the unknown shape of the
TFRecordDataset is causing problems when training the replacement models
for rewrites. By explicitly setting the right shape of the tensors we
can work around the issue.
- Adapt default parameters for rewrites. The training steps especially
had to be increased significantly to be effective.
Resolves: MLIA-895, MLIA-907, MLIA-946, MLIA-979
Signed-off-by: Benjamin Klimczak <benjamin.klimczak@arm.com>
Change-Id: I887ad165aed0f2c6e5a0041f64cec5e6c5ab5c5c
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* Define replacement function fully_connected layer
* Define RewriteConfiguration and Rewriter to integrate
rewrite module into mlia optimize command
* Fix a bug in the ethos_u/data_collection.py file
* Fix a bug in join.py
* Remove diff_stats and use diff instead, added related
changes around this to ensure e2e tests passing
* Add unit tests for all changes
* Fix bug in diff_stats function
* The bug was caused by a dividing by numpy array
of all zeros. The previous way of handling it
did not consider the all zeros case but only
dealt with partially zeros
* unit tests added.
* Fix the bug in rewrite/core/graph_edit/join.py
* Remove the possibility of passing None to append_relabel
function because it is immutable
* The bug happened when empty dictionary was passed in the
append_relabel function and the function overwrites the
reference of operator_map which caused the dictionary
was not updated after the function call
Resolves: MLIA-749, MLIA-864, MLIA-866
Change-Id: I1ab426996232f182345e6e98033d5dcb32aea08c
Signed-off-by: Benjamin Klimczak <benjamin.klimczak@arm.com>
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* Add flags for rewrite (--rewrite, --rewrite-start,
--rewrite-end, --rewrite-target)
* Refactor CLI interfaces to accept tflite models with optimize for
rewrite, keras models with optimize for clustering and pruning
* Refactor and move common.py and select.py out of the folder
nn/tensorflow/optimizations
* Add file nn/rewrite/core/rewrite.py as placeholder
* Update/add unit tests
* Refactor OptimizeModel in ethos_u/data_collection.py
for accepting tflite model case
* Extend the logic so that if "--rewrite" is specified, we don't add
pruning to also accept TFLite models.
* Update README.md
Resolves: MLIA-750, MLIA-854, MLIA-865
Signed-off-by: Benjamin Klimczak <benjamin.klimczak@arm.com>
Change-Id: I67d85f71fa253d2bad4efe304ad8225970b9622c
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- Update version dependencies in the tox.ini
- Fix linter issues
Change-Id: I04c3a841ee2646a865dab037701d66c28792f2a4
Signed-off-by: Benjamin Klimczak <benjamin.klimczak@arm.com>
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- Remove unused silencing of typing
- Amend None type hints where it is default
Change-Id: Id972b56dcdce865bf6c9d6aea88bc76baf39133e
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- Unify the TensorFlow Lite compatibility check across Cortex-A, TOSA
and Ethos-U targets
- Display tables/messages with parsed information
- Do not display raw TensorFlow Lite errors, and return with exit code 0
Change-Id: I9333fdb6cbe592f1ed7395d392412168492a1479
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Change-Id: I68fb8c4e51046e9fc2d91ad8338718ba545209cd
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- Provide "pretty names" to print information for targets and backends.
- Use 'target_config' instead of 'target' if a target profile is
used.
- Fix minor issue in output regarding the output directory.
Change-Id: Ib38231f30b4d609a0d1e8f9c52b2fb547c69cb6a
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Term 'device' can be ambiguous and is replaced with 'target'.
Change-Id: I5e5108d033a13b98e4c2997713e1c32bce63ae62
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- Use the target/backend registries to avoid hard-coded names.
- Cache target profiles to avoid re-loading them
Change-Id: I474b7c9ef23894e1d8a3ea06d13a37652054c62e
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- Remove old backend configuration code
- Install backends into directory ~/.mlia
- Rename targets/backends in registry to make it consistent
across codebase.
Change-Id: I9c8b012fe863280f1c692940c0dcad3ef638aaae
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- Rely on target and backend registry for support information
- Make above information less Ethos(TM)-U specific
Change-Id: I8dbfb84401016412a3d719a84eb592f21d79c46b
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New class 'TargetProfile' is used to load and verify target profiles.
Change-Id: I76373a923e2e5f55c4e95860635afe9fc5627a5d
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- Start using TOML format for target profile
- Add support for loading custom target profile files
Change-Id: I6be019d4341e93115440ccdbdb6dafdc1c85b966
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* Remove --output parameter from argument parser
* Remove FormattedFilePath class and its presence across the codebase
* Move logging module from cli to core
* The output format is now injected in the execution context and used
across MLIA
* Depending on the output format, TextReporter and JSONReporter have
been created and used accordingly.
* The whole output to standard output and/or logfile is driven via the
logging module: the only case where the print is used is when the
--json parameter is specified. This is needed becase all output
(including third party application as well) needs to be disabled
otherwise it might corrupt the json output in the standard output.
* Debug information is logged into the log file and printed to stdout
when the output format is plain_text.
* Update E2E test and config to cope with the new mechanism of
outputting json data to standard output.
Change-Id: I4395800b0b1af4d24406a828d780bdeef98cd413
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Breaking change in the CLI and API: Sub-commands "optimization",
"operators", and "performance" were replaced by "check", which
incorporates compatibility and performance checks, and "optimize" which
is used for optimization. "get_advice" API was adapted to these CLI
changes.
API changes:
* Remove previous advice category "all" that would perform all three
operations (when possible). Replace them with the ability to pass a
set of the advice categories.
* Update api.get_advice method docstring to reflect new changes.
* Set default advice category to COMPATIBILITY
* Update core.common.AdviceCategory by changing the "OPERATORS" advice
category to "COMPATIBILITY" and removing "ALL" enum type.
Update all subsequent methods that previously used "OPERATORS" to use
"COMPATIBILITY".
* Update core.context.ExecutionContext to have "COMPATIBILITY" as
default advice_category instead of "ALL".
* Remove api.generate_supported_operators_report and all related
functions from cli.commands, cli.helpers, cli.main, cli.options,
core.helpers
* Update tests to reflect new API changes.
CLI changes:
* Update README.md to contain information on the new CLI
* Remove the ability to generate supported operators support from MLIA
CLI
* Replace `mlia ops` and `mlia perf` with the new `mlia check` command
that can be used to perform both operations.
* Replace `mlia opt` with the new `mlia optimize` command.
* Replace `--evaluate-on` flag with `--backend` flag
* Replace `--verbose` flag with `--debug` flag (no behaviour change).
* Remove the ability for the user to select MLIA working directory.
Create and use a temporary directory in /temp instead.
* Change behaviour of `--output` flag to not format the content
automatically based on file extension anymore. Instead it will simply
redirect to a file.
* Add the `--json` flag to specfy that the format of the output should
be json.
* Add command validators that are used to validate inter-dependent
flags (e.g. backend validation based on target_profile).
* Add support for selecting built-in backends for both `check` and
`optimize` commands.
* Add new unit tests and update old ones to test the new CLI changes.
* Update RELEASES.md
* Update copyright notice
Change-Id: Ia6340797c7bee3acbbd26601950e5a16ad5602db
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Change-Id: Ieeaa9188ea1e29e2ccaad7475d457bce71e3140d
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- Rename module "mlia.devices" into "mlia.target"
- Rename module "mlia.target.ethosu" into "mlia.target.ethos_u"
- Rename module "mlia.target.cortexa" into "mlia.target.cortex_a"
- Rename and update tests
Change-Id: I6dca7c8646d881f739fb6b5914d1cc7e45e63dc2
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