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Please try to make things (e.g. kernel sizes) static if possible.cSsg|]}tt|dqSr2)r4 _node_getnoder5r3r3r7r8rszbONNX symbolic does not know how to unpack the ListConstruct node that is not a list of integers: ''z*Expected node type 'onnx::Constant', got 'z2Expected node type 'onnx::Constant' for argument 'z ' of node 'z', got ') _is_valuer> mustBeNonekindr=r4r9boolstrrSymbolicValueErrorinputs)r2r.r/r0r>Znode_valr$Z element_noder3r3r7 _parse_argAsd     rGz_C.NoderD)r>keycCs(t|tjst||}t|||S)z@Gets attributes of a node which is polymorphic over return type.) isinstancer NodeAssertionErrorZkindOfgetattr)r>rHselr3r3r7r=s r=z_C.Valuer<cCs|dkS)z$Whether a Value is an ONNX constant.r1r>rBr<r3r3r7_is_onnx_constantsrOz9Optional[Union[_C.Value, torch.Tensor, Number, Sequence]]r2 descriptorcCs"t|tjrt|rt||S|SN)rIr ValuerOrGrPr3r3r7_maybe_get_consts rTcCs(t|d}t|tjr$|jdkr$|S|S)Nr+r3)rTrItorchTensorshape)r2value_tr3r3r7_maybe_get_scalars rYcCs,t|s"td|d|d|t||S)Nz0ONNX symbolic expected a constant value of the 'z' argument, got 'r?) _is_constantrrErG)r2r.r/r3r3r7 _get_consts r[zList[_C.Value]) list_valuereturncCs4|}|dkr(td|d|t|S)Nr;z;ONNX symbolic expected node type prim::ListConstruct, got 'r:)r>rBrrElistrF)r\Z list_noder3r3r7 _unpack_lists  r_zTuple[_C.Value, ...]) tuple_valuer]cCs4|}t|s(td|d|t|S)Nz>ONNX symbolic expected node type 'prim::TupleConstruct', got 'r:)r>_is_tuple_constructrrErBtuplerF)r` tuple_noder3r3r7 _unpack_tuplesrdcCs`|}t|s4td|d|dtj|t|}t |dks\t |dks\t |S)zUnpacks a quantized tensor into a tuple of tensor and scale/zero_point. Args: tuple_value: A tuple of tensor, scale, zero_point, and optionally axis. Returns: A tuple of tensor, scale, zero_point, and optionally axis. z&ONNX symbolic expected the output of `zQ` to be a quantized tensor. Is this likely due to missing support for quantized `z`. Please create an issue on ) r>rarrErBrPYTORCH_GITHUB_ISSUES_URLrbrFlenrK)r`rcunpackedr3r3r7_unpack_quantized_tensors rjrrCcCst|o|dkS)Nr;r@r>rB)r\r3r3r7_is_packed_listsrlarg_descriptorscsfdd}|S)aA decorator which converts args from torch._C.Value to built-in types. For example: ``` @parse_args('v', 'i', 'fs') foo(g, a, b, c): assert isinstance(a, torch._C.Value) assert isinstance(b, int) assert isinstance(c, list) assert isinstance(c[0], float) ``` Args: arg_descriptors: list of str, where each element is a string that specifies the type to convert to. Valid descriptors: "v": no conversion, keep torch._C.Value. "i": int "is": list of int "f": float "fs": list of float "b": bool "s": str "t": torch.Tensor "none": the variable is unused cs"_tfdd}|S)Nc sd}tt|ks>tdt|dtdjd|z*t}t|jdd}jWn&tk rdgt|}dYnXfddt ||D}t|dkstd jd |t|dkrd |kstd jd ||f||S) NzIf you believe this is not due to custom symbolic implementation within your code or an external library, please file an issue at https://github.com/pytorch/pytorch/issues/new?template=bug-report.yml to report this bug.z,A mismatch between the number of arguments (z) and their descriptors (z") was found at symbolic function 'z'. cs g|]\}}}t|||qSr3)rG)r6argZarg_descr/fn_namer3r7r8!szBparse_args..decorator..wrapper..zSymbolic function z4's '**kwargs' can contain a single key/value entry. _outputsz='s '**kwargs' can only contain '_outputs' key at '**kwargs'. ) rhrK__name__inspect signaturer^ parameterskeys Exceptionzip)gargskwargsZ FILE_BUG_MSGsig arg_names)rnfnrqr7wrapper s.$       z.parse_args..decorator..wrapper)Z_arg_descriptors functoolswrapsrrrmrr7 decorators)zparse_args..decoratorr3)rnrr3rmr7rs /T)scale zero_pointquantize_outputzOptional[float]z Optional[int])arg_q_descriptorsrrrcsfdd}|S)aA decorator which extends support for quantized version of the base operator. 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Default is True cs"tfdd}|S)Ncsdk r|jdtd}nd}dk r@|jdtd}nd}dt|t}tt||}dd}t}|D]D\} } t| r|  D]} | || | qq|| || | q|t |sڈ|f||Sg} |D]\} } || | r0t || \} }}}| | |dkr |}|dkr|}qt| r|  D]J} || | rFt || \} }}}|dkrv|}|dkr|}| | qF| | q| | q|f| |}|dk std|dk stdrt||||S|S)NConstantrX)FcSs|ot|ot|SrR)r@ra)rQrpr3r3r7_is_arg_quantized}szMquantized_args..decorator..wrapper.._is_arg_quantizedz-Bug: Scale must be set for quantized operatorz2Bug: Zero point must be set for quantized operator)oprUtensorrhrbrzr^rlr>rFappendanyrZreplaceAllUsesWithrKr)r{r|r}Z_scaleZ _zero_pointZarg_q_descriptors_extendedZdescriptor_argsrZ is_quantizedrQrpZ arg_inputZnon_quantized_argsZdequantized_argZ arg_scaleZarg_zero_point_output)rrrrrr3r7rjsp             z2quantized_args..decorator..wrapper)rrrrrrrrr7risRz!quantized_args..decoratorr3)rrrrrr3rr7r9s0VzOptional[Number])xr]cCs"t|tjr|jdkr|SdS)z,Convert a scalar tensor into a Python value.r3N)rIrUrVrWitemrr3r3r7_scalarsrcCsJt|tjr|Stj|tjj}|tjjkrF|}t ||S|S)z Convert self into the same type of tensor, as necessary. 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