U KcK2@sDUddlmZddlmZddlmZmZmZmZm Z ddl Z ddl m Z m Z ddlmZmZmZmZmZddlmZmZmZmZmZd d d gZd Zd ZdZdZdZe j j!ee j j"j#ededee j j$ee j%ededee j j&ee j j'ee j(ededei Z)de*d<dddd dddZ+d$d d d!d Z,d%d d d"d Z-Gd#d d Z.dS)&) annotations) OrderedDict)AnyCallableDictTupleUnionN)default_weight_fake_quantFixedQParamsFakeQuantize)_PartialWrapper)default_fixed_qparams_range_0to1_observer,default_fixed_qparams_range_neg1to1_observerdefault_placeholder_observerdefault_weight_observer)default_reuse_input_qconfigget_default_qconfigget_default_qat_qconfigQConfig QConfigAnyget_default_qconfig_mappingget_default_qat_qconfig_mappingQConfigMapping object_typemodule_name_regex module_nameZmodule_name_object_type_order hardsigmoidZ hardsigmoid_sigmoidZsigmoid_tanhZtanh_z+Dict[Union[Callable, str], _PartialWrapper]_FIXED_QPARAMS_OP_TO_OBSERVERboolstrint)is_qatbackendversionreturnc Cs|rt||}n t||}|r"tnt}|dkr>t|j|d}n|}t|jtd}t| dt  t j j | t j j| t j j| t j j| t j j| t j j| t j j| t j jj| t j jj| t j jj| t j jj| t j jj| t j jj| t j jj| t j j| t j jj| t j| t j j| t j j| t j j | t j jj!| t j j"|}i}t#$D]V\} } | |kr|| } n,|rt%j&| d} n| } t| |d} | || <| | | q|S)zX Return the default QConfigMapping for the given quantization type and backend. )fbgemmx86) activationZweightZreshape)observer)'rrr rrr*rr set_globalset_object_typertorchnnZConv1dZConv2dZConv3dZConvTranspose1dZConvTranspose2dZConvTranspose3dZLinear functionalZconv1dZconv2dZconv3dZconv_transpose1dZconv_transpose2dZconv_transpose3dZlinearZReLUZreluZ BatchNorm1dZ BatchNorm2dZ BatchNorm3dZ layer_normZ LayerNormr itemsr Z with_args) r$r%r&qconfigZdefault_weightZqconfig_transposeZqconfig_layernormZqconfig_mappingZ!fixed_qparams_observer_to_qconfigZfixed_qparams_opr+Zfixed_qparams_qconfigr*r3I/tmp/pip-unpacked-wheel-gikjz4vx/torch/ao/quantization/qconfig_mapping.py_get_default_qconfig_mapping:s           r5r(r'cCs td||S)a3 Return the default QConfigMapping for post training quantization. Args: * ``backend`` : the quantization backend for the default qconfig mapping, should be one of ["x86", "fbgemm" (default), "qnnpack", "onednn"] * ``version`` : the version for the default qconfig mapping Fr5r%r&r3r3r4r{s cCs td||S)a4 Return the default QConfigMapping for quantization aware training. Args: * ``backend`` : the quantization backend for the default qconfig mapping, should be one of ["x86", "fbgemm" (default), "qnnpack", "onednn"] * ``version`` : the version for the default qconfig mapping Tr7r8r3r3r4rs c@seZdZdZddZdddddZdddd d d Zd ddd ddZd dddddZd dddddddZ ddddZ e dddddZ 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) cCs*d|_t|_t|_t|_t|_dS)N)global_qconfigrobject_type_qconfigsmodule_name_regex_qconfigsmodule_name_qconfigs&module_name_object_type_order_qconfigsselfr3r3r4__init__s zQConfigMapping.__init__r)r9r'cCs ||_|S)z3 Set the global (default) QConfig. )r9)r?r9r3r3r4r,szQConfigMapping.set_globalzUnion[Callable, str])rr2r'cCs||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:)r?rr2r3r3r4r-s zQConfigMapping.set_object_typer")rr2r'cCs||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. )r;)r?rr2r3r3r4set_module_name_regexs z$QConfigMapping.set_module_name_regex)rr2r'cCs||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. )r<)r?rr2r3r3r4set_module_names zQConfigMapping.set_module_namerr#)rrindexr2r'cCs||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. )r=)r?rrrCr2r3r3r4!set_module_name_object_type_orders z0QConfigMapping.set_module_name_object_type_orderzDict[str, Any]r6c CsHt|jtt|jtt|jtt|j t dd|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. cSsg|]\}}||fqSr3r3).0kvr3r3r4 sz*QConfigMapping.to_dict..) GLOBAL_DICT_KEYr9OBJECT_TYPE_DICT_KEYlistr:r1MODULE_NAME_REGEX_DICT_KEYr;MODULE_NAME_DICT_KEYr<&MODULE_NAME_OBJECT_TYPE_ORDER_DICT_KEYr=r>r3r3r4to_dicts   zQConfigMapping.to_dict) qconfig_dictr'cCs|}t|kr||t|tgD]\}}|||q(|tgD]\}}|||qJ|tgD]\}}|||ql|t gD]\}}}}| ||||q|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. ) rIr,getrJr-rLrArMrBrNrD)clsrPconfrr2rrrCr3r3r4 from_dictszQConfigMapping.from_dictN) __name__ __module__ __qualname____doc__r@r,r-rArBrDrO classmethodrTr3r3r3r4rs )r(r)r(r )/ __future__r collectionsrtypingrrrrrr.Z fake_quantizer r r+r r rrrr2rrrrr__all__rIrJrLrMrNr/Z Hardsigmoidr0rZSigmoidrZSoftmaxZTanhrr __annotations__r5rrrr3r3r3r4s^    A