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Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/42602 In this diff, clearer semantics and namings for are introduced by splitting the original `init_dynamic_qrange` into 2 separate `Optional[int]` types `qmin` and `qmax` to avoid the confusion of the parameters with dynamic quantization. The `qmin` and `qmax` parameters allow customers to specify their own customary quantization range and enables specific use cases for lower bit quantization. Test Plan: To assert the correctness and compatibility of the changes with existing observers, on a devvm, execute the following command to run the unit tests: `buck test //caffe2/test:quantization -- observer` Reviewed By: vkuzo, raghuramank100 Differential Revision: D22948334 fbshipit-source-id: 275bc8c9b5db4ba76fc2e79ed938376ea4f5a37c |
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| .. | ||
| __init__.py | ||
| _equalize.py | ||
| _learnable_fake_quantize.py | ||
| _numeric_suite.py | ||
| default_mappings.py | ||
| fake_quantize.py | ||
| fuse_modules.py | ||
| observer.py | ||
| qconfig.py | ||
| quantize_jit.py | ||
| quantize.py | ||
| stubs.py | ||