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1ca9d43d4e
Summary: made _register_activation_post_process_hook, _add_observer, _get_unique_devices_, _get_observer_dict private Test Plan: python test/test_public_bindings.py Reviewers: Subscribers: Tasks: Tags: Differential Revision: [D40709277](https://our.internmc.facebook.com/intern/diff/D40709277) Pull Request resolved: https://github.com/pytorch/pytorch/pull/87521 Approved by: https://github.com/jerryzh168
64 lines
2.6 KiB
Python
64 lines
2.6 KiB
Python
from .quantize import * # noqa: F403
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from .observer import * # noqa: F403
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from .qconfig import * # noqa: F403
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from .fake_quantize import * # noqa: F403
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from .fuse_modules import fuse_modules
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from .stubs import * # noqa: F403
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from .quant_type import * # noqa: F403
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from .quantize_jit import * # noqa: F403
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# from .quantize_fx import *
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from .quantization_mappings import * # noqa: F403
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from .fuser_method_mappings import * # noqa: F403
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def default_eval_fn(model, calib_data):
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r"""
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Default evaluation function takes a torch.utils.data.Dataset or a list of
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input Tensors and run the model on the dataset
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"""
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for data, target in calib_data:
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model(data)
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# TODO(future PR): fix the typo, should be `__all__`
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_all__ = [
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'QuantWrapper', 'QuantStub', 'DeQuantStub',
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# Top level API for eager mode quantization
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'quantize', 'quantize_dynamic', 'quantize_qat',
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'prepare', 'convert', 'prepare_qat',
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# Top level API for graph mode quantization on TorchScript
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'quantize_jit', 'quantize_dynamic_jit', '_prepare_ondevice_dynamic_jit',
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'_convert_ondevice_dynamic_jit', '_quantize_ondevice_dynamic_jit',
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# Top level API for graph mode quantization on GraphModule(torch.fx)
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# 'fuse_fx', 'quantize_fx', # TODO: add quantize_dynamic_fx
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# 'prepare_fx', 'prepare_dynamic_fx', 'convert_fx',
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'QuantType', # quantization type
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# custom module APIs
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'get_default_static_quant_module_mappings', 'get_static_quant_module_class',
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'get_default_dynamic_quant_module_mappings',
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'get_default_qat_module_mappings',
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'get_default_qconfig_propagation_list',
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'get_default_compare_output_module_list',
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'get_quantized_operator',
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'get_fuser_method',
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# Sub functions for `prepare` and `swap_module`
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'propagate_qconfig_', 'add_quant_dequant', 'swap_module',
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'default_eval_fn',
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# Observers
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'ObserverBase', 'WeightObserver', 'HistogramObserver',
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'observer', 'default_observer',
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'default_weight_observer', 'default_placeholder_observer',
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'default_per_channel_weight_observer',
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# FakeQuantize (for qat)
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'default_fake_quant', 'default_weight_fake_quant',
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'default_fixed_qparams_range_neg1to1_fake_quant',
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'default_fixed_qparams_range_0to1_fake_quant',
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'default_per_channel_weight_fake_quant',
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'default_histogram_fake_quant',
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# QConfig
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'QConfig', 'default_qconfig', 'default_dynamic_qconfig', 'float16_dynamic_qconfig',
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'float_qparams_weight_only_qconfig',
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# QAT utilities
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'default_qat_qconfig', 'prepare_qat', 'quantize_qat',
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# module transformations
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'fuse_modules',
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]
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