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Source code for torch.quantization

from .quantize import *
from .observer import *
from .qconfig import *
from .fake_quantize import *
from .fuse_modules import fuse_modules
from .stubs import *
from .quant_type import *
from .quantize_jit import *
# from .quantize_fx import *
from .quantization_mappings import *
from .fuser_method_mappings import *

[docs]def default_eval_fn(model, calib_data): r""" Default evaluation function takes a torch.utils.data.Dataset or a list of input Tensors and run the model on the dataset """ for data, target in calib_data: model(data)
_all__ = [ 'QuantWrapper', 'QuantStub', 'DeQuantStub', # Top level API for eager mode quantization 'quantize', 'quantize_dynamic', 'quantize_qat', 'prepare', 'convert', 'prepare_qat', # Top level API for graph mode quantization on TorchScript 'quantize_jit', 'quantize_dynamic_jit', # Top level API for graph mode quantization on GraphModule(torch.fx) # 'fuse_fx', 'quantize_fx', # TODO: add quantize_dynamic_fx # 'prepare_fx', 'prepare_dynamic_fx', 'convert_fx', 'QuantType', 'quant_type_to_str', # quantization type # custom module APIs 'get_default_static_quant_module_mappings', 'get_static_quant_module_class', 'get_default_dynamic_quant_module_mappings', 'get_default_qat_module_mappings', 'get_default_qconfig_propagation_list', 'get_default_compare_output_module_list', 'get_quantized_operator', 'get_fuser_method', # Sub functions for `prepare` and `swap_module` 'propagate_qconfig_', 'add_quant_dequant', 'add_observer_', 'swap_module', 'default_eval_fn', 'get_observer_dict', 'register_activation_post_process_hook', # Observers 'ObserverBase', 'WeightObserver', 'observer', 'default_observer', 'default_weight_observer', 'default_placeholder_observer', # FakeQuantize (for qat) 'default_fake_quant', 'default_weight_fake_quant', 'default_symmetric_fixed_qparams_fake_quant', 'default_affine_fixed_qparams_fake_quant', 'default_per_channel_weight_fake_quant', 'default_histogram_fake_quant', # QConfig 'QConfig', 'default_qconfig', 'default_dynamic_qconfig', 'float16_dynamic_qconfig', 'float_qparams_weight_only_qconfig', # QAT utilities 'default_qat_qconfig', 'prepare_qat', 'quantize_qat', # module transformations 'fuse_modules', ]

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