Spaces:
Runtime error
Runtime error
File size: 2,743 Bytes
b2659ad |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 |
from .quantize import * # noqa: F403
from .observer import * # noqa: F403
from .qconfig import * # noqa: F403
from .fake_quantize import * # noqa: F403
from .fuse_modules import fuse_modules
from .stubs import * # noqa: F403
from .quant_type import * # noqa: F403
from .quantize_jit import * # noqa: F403
# from .quantize_fx import *
from .quantization_mappings import * # noqa: F403
from .fuser_method_mappings import * # noqa: F403
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",
"_prepare_ondevice_dynamic_jit",
"_convert_ondevice_dynamic_jit",
"_quantize_ondevice_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", # 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",
"swap_module",
"default_eval_fn",
# Observers
"ObserverBase",
"WeightObserver",
"HistogramObserver",
"observer",
"default_observer",
"default_weight_observer",
"default_placeholder_observer",
"default_per_channel_weight_observer",
# FakeQuantize (for qat)
"default_fake_quant",
"default_weight_fake_quant",
"default_fixed_qparams_range_neg1to1_fake_quant",
"default_fixed_qparams_range_0to1_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",
]
|