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Dev compress refactor #1690
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Dev compress refactor #1690
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liuzhe-lz
reviewed
Nov 4, 2019
| @@ -9,13 +9,13 @@ You can easily compress a model with NNI compression. Take pruning for example, | |||
| ```python | |||
| from nni.compression.torch import LevelPruner | |||
| config_list = [{ 'sparsity': 0.8, 'op_types': ['default'] }] | |||
| pruner = LevelPruner(config_list) | |||
| pruner(model) | |||
| pruner = LevelPruner(model, config_list) | |||
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Logically a pruner should be a standalone component. It should not need a model to "create" a pruner. So this looks strange.
But I known we don't have a better solution yet.
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yes, let's keep it for now
liuzhe-lz
reviewed
Nov 4, 2019
docs/en_US/Compressor/Overview.md
Outdated
| """ | ||
| Pruners should overload this method to provide mask for weight tensors. | ||
| The mask must have the same shape and type comparing to the weight. | ||
| It will be applied with `mul()` operation on the weight. |
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numpy/pandas use ``inline code``
liuzhe-lz
reviewed
Nov 4, 2019
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| Parameters | ||
| ---------- | ||
| layer: LayerInfo |
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There should be a space before colon. My bad.
liuzhe-lz
approved these changes
Nov 4, 2019
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