קg9UddlmZddlmZddlmZmZmZmZm Z m Z ddl Z ddl m Z mZddlmZmZmZmZmZddlmZmZmZmZmZmZmZmZgd Zd Zd Z d Z!d Z"dZ#e j$j%ee j$j&j'ededee j$j(ee j)ededee j$j*ee j$j+ee j,ededei Z-de.d<d,dZ/d-d.d!Z0d/d.d"Z1d.d#Z2d.d$Z3d0d'Z4gd(Z5d)e.d*<Gd+dZ6dS)1) annotations) OrderedDict)AnyCallableDictListTupleUnionN)default_weight_fake_quantFixedQParamsFakeQuantize)_PartialWrapper)default_fixed_qparams_range_0to1_observer,default_fixed_qparams_range_neg1to1_observerdefault_placeholder_observerdefault_weight_observer)default_quint8_weight_qconfigdefault_reuse_input_qconfig%default_symmetric_qnnpack_qat_qconfig!default_symmetric_qnnpack_qconfigget_default_qat_qconfigget_default_qconfigQConfig QConfigAny)get_default_qconfig_mappingget_default_qat_qconfig_mappingQConfigMapping object_typemodule_name_regex module_namemodule_name_object_type_order hardsigmoid hardsigmoid_sigmoidsigmoid_tanhtanh_z+Dict[Union[Callable, str], _PartialWrapper]_FIXED_QPARAMS_OP_TO_OBSERVERis_qatboolbackendstrversionintreturnrc|rt||}nt||}|rtnt}|dvrt |j|}n|}t |jt }t| dt tj j | tj j| tj j| tj jj| tj jj| tj jj| tj jj| tj j| tj jt.}i}t0D]X\} } | |vr || } n0|rt5j| } n| } t | |} | || <| | | Y|S)zX Return the default QConfigMapping for the given quantization type and backend. )fbgemmx86) activationweightreshape)observer)rrr rrr4rr set_globalset_object_typertorchnnConvTranspose1dConvTranspose2dConvTranspose3d functionalconv_transpose1dconv_transpose2dconv_transpose3d layer_norm LayerNormPReLUrr)itemsr with_args) r*r,r.qconfigdefault_weightqconfig_transposeqconfig_layernormqconfig_mapping!fixed_qparams_observer_to_qconfigfixed_qparams_opr7fixed_qparams_qconfigr4s a/var/www/html/ai-engine/env/lib/python3.11/site-packages/torch/ao/quantization/qconfig_mapping.py_get_default_qconfig_mappingrQ=s< 8)'7;;%gw7728U..>UN ####).   $ %.J  G   $? @ @ 13D E E 13D E E 13D E E ,=?P Q Q ,=?P Q Q ,=?P Q Q ,79J K K +-> ? ? )F G G@B%&C&I&I&K&K Q Q"( 8 8 8$Eh$O ! ! &5?RRR % $+%n%%% !;P -h 7''(8:OPPPP r3c$td||S)a? Return the default QConfigMapping for post training quantization. Args: * ``backend`` (str) : the quantization backend for the default qconfig mapping, should be one of ["x86" (default), "fbgemm", "qnnpack", "onednn"] * ``version`` (int) : the version for the default qconfig mapping FrQr,r.s rPrr~s (w @ @@rRc$td||S)a@ Return the default QConfigMapping for quantization aware training. Args: * ``backend`` (str) : the quantization backend for the default qconfig mapping, should be one of ["x86" (default), "fbgemm", "qnnpack", "onednn"] * ``version`` (int) : the version for the default qconfig mapping TrTrUs rPrrs (gw ? ??rRc2t}tdd|S)z Return a QConfigMapping that uses `torch.ao.quantization.default_symmetric_qnnpack_qconfig` as the default QConfig. Fqnnpack)r1_get_default_qconfig_mapping_with_default_qconfigdefault_qconfigs rP&_get_symmetric_qnnpack_qconfig_mappingr\s" 8O < y/  rRc2t}tdd|S)z Return a QConfigMapping that uses `torch.ao.quantization.default_symmetric_qnnpack_qat_qconfig` as the default QConfig. TrX)rrYrZs rP*_get_symmetric_qnnpack_qat_qconfig_mappingr^s" >///"7<<>>FF 7 7 7  + +G_ E E E rR)global_qconfigr`module_name_regex_qconfigsmodule_name_qconfigs&module_name_object_type_order_qconfigsz List[str]_QCONFIG_STYLE_ORDERcjeZdZdZddZddZdd ZddZddZd dZ d!dZ d"dZ e d#dZ dS)$ra Mapping from model ops to :class:`torch.ao.quantization.QConfig` s. The user can specify QConfigs using the following methods (in increasing match priority): ``set_global`` : sets the global (default) QConfig ``set_object_type`` : sets the QConfig for a given module type, function, or method name ``set_module_name_regex`` : sets the QConfig for modules matching the given regex string ``set_module_name`` : sets the QConfig for modules matching the given module name ``set_module_name_object_type_order`` : sets the QConfig for modules matching a combination of the given module name, object type, and the index at which the module appears Example usage:: qconfig_mapping = QConfigMapping() .set_global(global_qconfig) .set_object_type(torch.nn.Linear, qconfig1) .set_object_type(torch.nn.ReLU, qconfig1) .set_module_name_regex("foo.*bar.*conv[0-9]+", qconfig1) .set_module_name_regex("foo.*", qconfig2) .set_module_name("module1", qconfig1) .set_module_name("module2", qconfig2) .set_module_name_object_type_order("foo.bar", torch.nn.functional.linear, 0, qconfig3) r0Nonecd|_t|_t|_t|_t|_dS)N)rcrr`rdrerfselfs rP__init__zQConfigMapping.__init__sN*. MM !IT 'BM--! MM 333rRrcrc||_|S)z3 Set the global (default) QConfig. )rc)rlrcs rPr8zQConfigMapping.set_globals- rRrUnion[Callable, str]rHc||j|<|S)z Set the QConfig for a given module type, function, or method name. If the QConfig for an existing object type was already set, the new QConfig will override the old one. )r`)rlrrHs rPr9zQConfigMapping.set_object_types29!+. rRr r-c||j|<|S)aO Set the QConfig for modules matching the given regex string. Regexes will be matched in the order in which they are registered through this method. Thus, the caller should register more specific patterns first, e.g.:: qconfig_mapping = QConfigMapping() .set_module_name_regex("foo.*bar.*conv[0-9]+", qconfig1) .set_module_name_regex("foo.*bar.*", qconfig2) .set_module_name_regex("foo.*", qconfig3) In this example, "foo.bar.conv0" would match qconfig1, "foo.bar.linear" would match qconfig2, and "foo.baz.relu" would match qconfig3. If the QConfig for an existing module name regex was already set, the new QConfig will override the old one while preserving the order in which the regexes were originally registered. )rd)rlr rHs rPset_module_name_regexz$QConfigMapping.set_module_name_regexs(>E'(9: rRr!c||j|<|S)z Set the QConfig for modules matching the given module name. If the QConfig for an existing module name was already set, the new QConfig will override the old one. )re)rlr!rHs rPset_module_namezQConfigMapping.set_module_names 29!+. rRrindexr/c ||j|||f<|S)a- Set the QConfig for modules matching a combination of the given module name, object type, and the index at which the module appears. If the QConfig for an existing (module name, object type, index) was already set, the new QConfig will override the old one. )rf)rlr!rrurHs rP!set_module_name_object_type_orderz0QConfigMapping.set_module_name_object_type_order$s%  3 +u -  rRc|jjdz}tD]p}|d|z }t||}t |t r9t |dkr&|D]\}}|d|d|z }h|d|z }q|dzS)Nz (z rz z: z )) __class____name__rggetattr isinstancerlenrF)rloutput style_nameqconfigskeyrHs rP__repr__zQConfigMapping.__repr__3s(4/. , ,J (J(( (FtZ00H(K00 ,S]]Q5F5F$,NN$4$466LC5S55G555FF6++++~rRDict[str, Any]c pt|jtt|jt t|jtt|j td|j DiS)a? Convert this ``QConfigMapping`` to a dictionary with the following keys: "" (for global QConfig) "object_type" "module_name_regex" "module_name" "module_name_object_type_order" The values of this dictionary are lists of tuples. c"g|] \}}g||R Sr).0kvs rP z*QConfigMapping.to_dict..Us3666 Aq!Q666rR) _GLOBAL_DICT_KEYrc_OBJECT_TYPE_DICT_KEYlistr`rF_MODULE_NAME_REGEX_DICT_KEYrd_MODULE_NAME_DICT_KEYre'_MODULE_NAME_OBJECT_TYPE_ORDER_DICT_KEYrfrks rPto_dictzQConfigMapping.to_dict@s" d1 !4(A(G(G(I(I#J#J 'd.M.S.S.U.U)V)V !4(A(G(G(I(I#J#J 366$($O$U$U$W$W666   rR qconfig_dictc,|}t|vr ||t|tgD]\}}||||t gD]\}}||||tgD]\}}||||tgD]\}}}}| |||| |S)a[ Create a ``QConfigMapping`` from a dictionary with the following keys (all optional): "" (for global QConfig) "object_type" "module_name_regex" "module_name" "module_name_object_type_order" The values of this dictionary are expected to be lists of tuples. ) rr8getrr9rrrrrtrrw)clsrconfrrHr r!rus rP from_dictzQConfigMapping.from_dict[sR"suu | + + OOL)9: ; ; ;$0$4$45JB$O$O 7 7 K  g 6 6 6 6*6*:*: '+ +  C C & w  & &'8' B B B B$0$4$45JB$O$O 7 7 K  g 6 6 6 68D8H8H 3R9 9    4KeW  2 2[%     rRN)r0ri)rcrr0r)rrorHrr0r)r r-rHrr0r)r!r-rHrr0r) r!r-rrrur/rHrr0r)r0r-)r0r)rrr0r)rz __module__ __qualname____doc__rmr8r9rrrtrwrr classmethodrrrRrPrrs<    .            6!!![!!!rR)r*r+r,r-r.r/r0r)r3r)r0r)r3r )r*r+r,r-r[rr0r)7 __future__r collectionsrtypingrrrrr r r: fake_quantizer r r7rrrrrrHrrrrrrrr__all__rrrrrr; Hardsigmoidr?r#Sigmoidr%SoftmaxTanhr'r)__annotations__rQrrr\r^rYrgrrrRrPrs"""""""######:::::::::::::::: NNNNNNNN                       %1%*I' HC H#%N<= H? 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