Docs for statistics caching #3052
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docs/usage/post_training_compression/weights_compression/Usage.md
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ljaljushkin
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Oct 31, 2024
| @@ -180,6 +180,20 @@ from nncf import compress_weights, CompressWeightsMode | |||
| compressed_model = compress_weights(model, mode=CompressWeightsMode.E2M1, group_size=32, all_layers=True) | |||
| ``` | |||
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| #### Caching Statistics | |||
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Caching stats are the only bullet in usage guide. Looks confusing. I'd add one more for previous bullets.
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Do we really need bullets at all?
| @@ -180,6 +180,20 @@ from nncf import compress_weights, CompressWeightsMode | |||
| compressed_model = compress_weights(model, mode=CompressWeightsMode.E2M1, group_size=32, all_layers=True) | |||
| ``` | |||
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| #### Caching Statistics | |||
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| To optimize performance and reuse statistics data across multiple configurations, the `statistics_path` option can be used. This feature allows caching of computed statistics, so they can be loaded from a specified file path rather than being recalculated with each configuration. This can significantly reduce the setup time for models that require extensive statistical computations. | |||
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performance is really ambiguous word. could you clarify what exactly is optimized - e.g. compression time, memory footprint..
| @@ -180,6 +180,20 @@ from nncf import compress_weights, CompressWeightsMode | |||
| compressed_model = compress_weights(model, mode=CompressWeightsMode.E2M1, group_size=32, all_layers=True) | |||
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I'd add a table of content for this file, since it's easy to skip this feature in the long description.
It would be great to format some big sections as a "spoiler" for better navigation:
-
Example
long console output here
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Changes
Add section regarding statistics caching for WeightCompression