diff options
| author | Annie Tallund <annie.tallund@arm.com> | 2023-01-26 09:31:11 +0100 |
|---|---|---|
| committer | Diego Russo <diego.russo@arm.com> | 2023-02-10 12:20:10 +0000 |
| commit | 50271dee0a84bfc481ce798184f07b5b0b4bc64d (patch) | |
| tree | bd8d7177d03cce50f9ad77ace5de2f1910a1e284 | |
| parent | b863f8eaf0b2e2627fa9c5d2a51004fd8133cc68 (diff) | |
| download | mlia-50271dee0a84bfc481ce798184f07b5b0b4bc64d.tar.gz | |
MLIA-592 Add documentation for using custom target profiles
Change-Id: I7dda9c2b99a1464d9682074245584d8c518a9c13
| -rw-r--r-- | README.md | 22 |
1 files changed, 20 insertions, 2 deletions
@@ -193,8 +193,11 @@ mlia optimize --help # Target profiles -All sub-commands require the name of a target profile as input parameter. The -profiles currently available are described in the following sections. +The targets currently supported are described in the sections below. +All MLIA sub-commands require a target profile as input parameter. +That target profile can be either a name of a built-in target profile +or a custom file. MLIA saves the target profile that was used for a run +in the output directory. The support of the above sub-commands for different targets is provided via backends that need to be installed separately, see @@ -248,6 +251,21 @@ For more information, see TOSA Checker's: * [repository](https://review.mlplatform.org/plugins/gitiles/tosa/tosa_checker/+/refs/heads/main) * [pypi.org page](https://pypi.org/project/tosa-checker/) +## Custom target profiles + +For the _custom target profiles_, the configuration file for a custom +target profile is passed as path and needs to conform to the TOML file format. +Each target in MLIA has a pre-defined set of parameters which need to be present +in the config file. The built-in target profiles (in `src/mlia/resources/target_profiles`) +can be used to understand what parameters apply for each target. + +*Example:* + +``` bash +# for custom profiles +mlia ops --target-profile ~/my_custom_profile.toml sample_model.tflite +``` + # Backend installation The ML Inference Advisor is designed to use backends to provide different |