pytorch

ebb7f20a - quant: make various configs printable (#91419)

quant: make various configs printable (#91419) Summary: Makes various quantization configs print out human readable values instead of just the class name. This is useful when printing these configs out when debugging. Test plan: test script ``` conf_1 = torch.ao.quantization.backend_config.backend_config.DTypeConfig() print(conf_1) conf_2 = torch.ao.quantization.backend_config.backend_config.BackendConfig() print(conf_2) conf_3 = torch.ao.quantization.backend_config.backend_config.BackendPatternConfig() print(conf_3) conf_4 = torch.ao.quantization.fx.custom_config.PrepareCustomConfig()\ .set_input_quantized_indexes([0]) print(conf_4) conf_5 = torch.ao.quantization.fx.custom_config.ConvertCustomConfig()\ .set_preserved_attributes(['foo']) print(conf_5) conf_6 = torch.ao.quantization.fx.custom_config.FuseCustomConfig()\ .set_preserved_attributes(['foo']) print(conf_6) ``` test script output ``` DTypeConfig(input_dtype_with_constraints=DTypeWithConstraints(dtype=None, quant_min_lower_bound=None, quant_max_ upper_bound=None, scale_min_lower_bound=None, scale_max_upper_bound=None, scale_exact_match=None, zero_point_exa ct_match=None), output_dtype_with_constraints=DTypeWithConstraints(dtype=None, quant_min_lower_bound=None, quant _max_upper_bound=None, scale_min_lower_bound=None, scale_max_upper_bound=None, scale_exact_match=None, zero_poin t_exact_match=None), weight_dtype_with_constraints=DTypeWithConstraints(dtype=None, quant_min_lower_bound=None, quant_max_upper_bound=None, scale_min_lower_bound=None, scale_max_upper_bound=None, scale_exact_match=None, zero _point_exact_match=None), bias_dtype=None, is_dynamic=None) BackendConfig({'name': '', '_pattern_complex_format_to_config': {}}) BackendPatternConfig({'observation_type': <ObservationType.OUTPUT_USE_DIFFERENT_OBSERVER_AS_INPUT: 0>}) PrepareCustomConfig({'input_quantized_indexes': [0]}) ConvertCustomConfig({'preserved_attributes': ['foo']}) FuseCustomConfig({'preserved_attributes': ['foo']}) ``` Pull Request resolved: https://github.com/pytorch/pytorch/pull/91419 Approved by: https://github.com/andrewor14