o h66@sUddlZddlZddlmZddlmmZddlmmmZ ddl mmmm Z ddl mmmm mZddlmmmmZddlmmm Zddlmmm mZddlmmm mZddlmmmZddlmmmmZddlmZm Z m!Z!m"Z"m#Z#m$Z$ddl%Zddl&mmZ'ddl(m)Z)m*Z*ddl+m,Z,m-Z-ddl.m/Z/ddl0m1Z1gdZ2e)ej3e*ej4ej5ej5ej6ej6ej7ej7ej8ej8ej9ej9ej:ej:ej;ej;ejej>ej?ej?ej@ej@ejAejAiZBe!e#e$feCd <ie)ej3e*ej4ejDejDejEejEejFejFej6ej6ej7ej7ej8ej8ej9ej9ej:ej:ej;ej;ejGejGejej>ej5ej5ej5ej5ejOjPjQej5ejAejAejiejiej?ej?ej@ej@e j]ej]ej=ej=ejN)nn)OptionalUnionDictSetCallableAny) QuantStub DeQuantStub)+default_fixed_qparams_range_0to1_fake_quant.default_fixed_qparams_range_neg1to1_fake_quant)get_combined_dict)type_before_parametrizations).DEFAULT_REFERENCE_STATIC_QUANT_MODULE_MAPPINGS$DEFAULT_STATIC_QUANT_MODULE_MAPPINGSDEFAULT_QAT_MODULE_MAPPINGS%DEFAULT_DYNAMIC_QUANT_MODULE_MAPPINGS,DEFAULT_FLOAT_TO_QUANTIZED_OPERATOR_MAPPINGS"DEFAULT_MODULE_TO_ACT_POST_PROCESS+DEFAULT_STATIC_SPARSE_QUANT_MODULE_MAPPINGS,DEFAULT_DYNAMIC_SPARSE_QUANT_MODULE_MAPPINGSno_observer_set(get_default_static_quant_module_mappings2get_default_static_quant_reference_module_mappings*get_embedding_static_quant_module_mappings/get_default_static_sparse_quant_module_mappingsget_static_quant_module_classget_dynamic_quant_module_classget_default_qat_module_mappings!get_embedding_qat_module_mappings)get_default_dynamic_quant_module_mappings0get_default_dynamic_sparse_quant_module_mappings$get_default_qconfig_propagation_list&get_default_compare_output_module_list0get_default_float_to_quantized_operator_mappingsget_quantized_operatorrrrr_INCLUDE_QCONFIG_PROPAGATE_LISTrrrrreturncCstjjtjjh}|S)z8These modules cannot have observers inserted by default.)r quantizableLSTMMultiheadAttention) no_observersr,a/var/www/html/ai/venv/lib/python3.10/site-packages/torch/ao/quantization/quantization_mappings.pyrsrcC ttS)z> Get module mapping for post training static quantization )copydeepcopyrr,r,r,r-r rcCr.)zH Get reference module mapping for post training static quantization )r/r0rr,r,r,r-rr1rcC&tt}tj|tj<tj|tj<|S)z= Get module mapping, including mapping for embedding QAT )r/r0rnnq EmbeddingBagnnqat Embeddingmappingr,r,r-rs   rcCr.)zE Get module mapping for post training static sparse quantization )r/r0rr,r,r,r-rr1rFfloat_module_classadditional_static_quant_mapping is_referencecCsR|duri}t|r tnt|}||d}|dus$Jdt|dt|S)zen Get the statically quantized module class corresponding to the floating point module class NFloating point module class 5 does not have a corresponding quantized module class)r rrgetstrr/r0)r9r:r; all_mappingsstatic_quant_module_classr,r,r-rs    r additional_dynamic_quant_mappingcCsJ|duri}tt|}||d}|dus Jdt|dt|S)zfn Get the dynamically quantized module class corresponding to the floating point module class Nr<r=)r rr>r?r/r0)r9rBr@dynamic_quant_module_classr,r,r-rs     rcCr.)z@ Get default module mapping for quantization aware training )r/r0rr,r,r,r-rr1rcCr2)z Get module mapping for quantization aware training This is includes default values in addition to enabling qat for embeddings. )r/r0rr5r4rr6r7r,r,r-rs   rcCtS)z? Get module mapping for post training dynamic quantization )rr,r,r,r-r r cCrD)zF Get module mapping for post training dynamic sparse quantization )rr,r,r,r-r!%rEr!cCs2ttttBttBtB}t|S)z` Get the default list of module types that we'll attach qconfig attribute to in prepare )setrkeysrrr&r/r0)#QCONFIG_PROPAGATE_MODULE_CLASS_LISTr,r,r-r"*s    r"cCsVttttBttBttBttBttBtB}t|S)zT Get list of module class types that we will record output in numeric suite ) rFrvaluesrrrGr&r/r0).NUMERIC_SUITE_COMPARE_MODEL_OUTPUT_MODULE_LISTr,r,r-r#6s       r#cCr.N)r/r0rr,r,r,r-r$Es r$float_opcCs,t|d}|dusJdt|d|S)zD Get the quantized operator corresponding to the float operator Nz Operator z) does not have corresponding quantized op)rr>r?)rL quantized_opr,r,r-r%Js  r%modulecCstt|dS)z Get the special activation post process for `module`, this has higher priority than the activation post process in `qconfig` e.g. input: torch.nn.Sigmoid output: default_affine_fixed_qparam_fake_quant N)rr>rrNr,r,r-_get_special_act_post_processRsrPcCs|jot|tvSrK)trainingtyperrOr,r,r-_has_special_act_post_process[srS)NFrK)r/torchrtorch.nn.functional functionalFtorch.ao.nn.intrinsicao intrinsicnnitorch.ao.nn.intrinsic.quantized quantizednniq'torch.ao.nn.intrinsic.quantized.dynamicdynamicnniqdtorch.ao.nn.intrinsic.qatqatnniqattorch.ao.nn.quantizedr3torch.ao.nn.quantized.reference referencennqrtorch.ao.nn.quantized.dynamicnnqdtorch.ao.nn.qatr5torch.ao.nn.qat.dynamicnnqatdtypingrrrrrrtorch.ao.nn.sparse torch.ao.nnao_nntorch.ao.quantization.stubsr r #torch.ao.quantization.fake_quantizer r torch.ao.quantization.utilsr torch.nn.utils.parametrizer__all__Quantize DeQuantizeLinearConv1dConv2dConv3dConvTranspose1dConvTranspose2dConvTranspose3dr6r4GRUCellLSTMCellRNNCellr)r__annotations__ BatchNorm2d BatchNorm3dDropoutELU GroupNorm HardswishInstanceNorm1dInstanceNorm2dInstanceNorm3d LayerNorm LeakyReLUmoduleslinearNonDynamicallyQuantizableLinearReLU6PReLUFloatFunctional QFunctionalBNReLU2dBNReLU3d ConvReLU1d ConvReLU2d ConvReLU3d ConvAdd2d ConvAddReLU2d LinearReLULinearLeakyReLU LinearTanhConvBn1dConvBn2dConvBn3d ConvBnReLU1d ConvBnReLU2d ConvBnReLU3d LinearBn1drrGRUr Sequentialr&eluops hardswish instance_norm layer_norm leaky_reludropoutrr? HardsigmoidSigmoidSoftmaxTanhrsparserrrrrrrboolrrrrr r!r"r#r$r%ModulerPrSr,r,r,r-s  $          !"#$%&'()*+,-./01345: