g^(hsP tddlZddlZddlmZmZmZddlZddlmcm cm cm Z ddl mcm cm Zddlm Z ddlmZmZddlmZddlmZddlmZddlmZdd lmZmZej<jZGd d ej@Z!d ed edede"e#e$efde%e!e!ff dZ&d ed ede"e#e$efdee%eejNe(feejNe)fffdZ*d ed edefdZ+d ed ede)fdZ,d ede-e)fdZ.d ed ede#fdZ/dede#defdZ0deddfdZ1dZ2e2dejNdejNdejNfdZ3e2dejNdejNdejNfdZ4e2dejNdejNdejNfd Z5d ede6fd!Z7d ed ed"e)defd#Z8y)$N)CallableOptionalUnion)FakeQuantizeBase ObserverBase)_is_activation_post_process)getattr_from_fqn) GraphModule)Node)NSNodeTargetType NSResultsTypeceZdZejZejZejZejZejZ y)NodeInputOrOutputTypeN) __name__ __module__ __qualname__enumautoFP32INT8FP16UNKNOWN FP32_OR_INT8R/var/www/skyplay_api_hub/venv/lib/python3.12/site-packages/torch/ao/ns/fx/utils.pyrrsE 499;D 499;D 499;DdiikG 499;Lrrnodegm logger_clsnode_type_to_io_type_mapreturnc|d}|d}|d}|d}|d}|d} |d} |d} |jd k(r|j|vr tjtjfS|j|vr tjtjfS|j|vr tj tj fS|j|vr4t ||d } t| tsJt| |||\} }||fStjtjfS|jd k(r0|jd k(sJt|jtsJt||jtfd | D}t|ttfs|r4t ||d } t| tsJt| |||\} }||fStfd |D}tfd| D}|r tjtjfS|r tj tj fStjtjfS|jdk(r-|jdk(rBt ||d }t|tsJt||||\} }|tjfS|jdk(rkt ||d }t|tsJt||||\} }t ||d}|t j"us J|d|tjfS|j| vr4t ||d } t| tsJt| |||\} }||fStjtjfStjtjfS)Nfuns_io_type_fp32funs_io_type_fp16funs_io_type_int8funs_io_type_fp32_or_int8mods_io_type_fp32mods_io_type_int8mods_io_type_fp32_or_int8meths_io_type_fp32_or_int8 call_functionr call_modulec36K|]}t|ywN isinstance.0 target_typemods r z7get_node_first_input_and_output_type..Ns1 -8JsK (1 c36K|]}t|ywr/r0r2s rr6z7get_node_first_input_and_output_type..`) -8JsK () r7c36K|]}t|ywr/r0r2s rr6z7get_node_first_input_and_output_type..cr9r7 call_method dequantizetor z handling needs to be added)optargetrrrrget_normalized_nth_inputr1r $get_node_first_input_and_output_typerstrr anyrrtorchfloat16)rrr r!FUNS_IO_TYPE_FP32FUNS_IO_TYPE_FP16FUNS_IO_TYPE_INT8FUNS_IO_TYPE_FP32_OR_INT8MODS_IO_TYPE_FP32MODS_IO_TYPE_INT8MODS_IO_TYPE_FP32_OR_INT8METHS_IO_TYPE_FP32_OR_INT8 first_arg_prev_node_input_typeprev_node_output_type"is_known_fp32_or_int8_input_moduleis_known_fp32_input_moduleis_known_int8_input_module prev_nodecur_node_dtype_targetr5s @rrArA&s11DE01DE01DE 89T U01DE01DE 89T U!9:V!W ww/! ;;+ +)..0E0J0JK K ;;+ +)..0E0J0JK K [[- -)..0E0J0JK K [[5 50r1=Ii. ..52z+C %%*+@A A)113H3P3PQ Q M !ww-'''$++s+++r4;;/-01 tj@tjBt$jDt$jFt$jHt$j&t$jJt$jLfrjNjPfStSfd |D}|r tU|||Sy) z{ Returns the qparams (scale, zero_point) of the first input to `node`, if they can be inferred from the graph. rNr*cFt|||}t|||}t|trt|jtsJt|trt|jtsJt ||j}t ||j}||fSr/)r@r1r r?rBr )rr scale_arg_idx zp_arg_idx scale_nodezp_node scale_objzp_objs r _get_scale_zp_from_function_argsz@get_node_input_qparams.._get_scale_zp_from_function_argss-dB F *4Z@*d+ :;L;Lc0RRR'4(Z-LLL$R):):; !"gnn56""rr,r r-c36K|]}t|ywr/r0)r3r4 module_objs rr6z)get_node_input_qparams..s1 4?Jz; /1 r7)+r@r1r r>r?rDquantize_per_tensortoqaddadd_relumulmul_relurBr nnqLinearConv1dConv2dnniq ConvReLU2dConv3d BatchNorm2d BatchNorm3dConvTranspose1dConvTranspose2dELU GroupNormInstanceNorm1dInstanceNorm2dInstanceNorm3d LayerNorm Hardswish LeakyReLUReLU6BNReLU2dBNReLU3d ConvReLU1d ConvReLU3d LinearReLUscale zero_pointrCget_node_input_qparams)rrr!rTrLr^rQrbs @rrrs)r15I i & 89T U#||&   u88 83Ir1aH H   #''3<<#,,!O O3Ir1aH H  &)**C000%b)*:*:;      #### """"""      1  :$$j&;&;< <-01 C\1 . * .))R9QR R rc|jdk(rt||j}t|rt |j dk(sJt |j dtsJ|j d}t |jtsJt||j}t|rHt |j dk(sJt |j dtsJ|j d}|S)a If node is not an observer, returns it. If node is an observer, navigates up the graph and returns the first parent which is not an observer. For example, graph: (node_non_obs), node = node_non_obs : returns node_non_obs graph: (node_non_obs -> obs0), node = obs0 : returns node_non_obs graph: (node_non_obs -> obs0 -> fq0), node = fq0 : returns node_non_obs r-r r) r>r r?rlenargsr1r rBrrnode_objs rreturn_first_non_observer_noders ww-#B 4 &x 0tyy>Q& &&diilD1 1199Qr r?r1nnLSTMrs rget_number_of_non_param_argsrs6" ww-#B 4 h ( rct|jdk(rgS|jdk(r|jtj tj jj tj fvsO|jtjtj jjtjfvr:tdDcgc]$}t|j|tk(s#|&}}|SdgScc}w)a- Returns the indices of args of the node which we should attach loggers to, if input logging is enabled. For example, * for (x + y), returns [0, 1] * for (1 + y), returns [1] * for (x + 1), returns [0] * for (linear(x, w, b)) returns [0] * by default, returns [0] rr,r_) rrr>r?rDreops quantizedoperatorrgrangetyper )riresults r get_arg_indices_of_inputs_to_logr(s 499~  ww/!  599#6#6#:#:HLLII ;;599eii&9&9&=&=x||L L"1XDdiil);t)C!DD 3JEs $D:Dcd}|jdvr!tj|j}|S|jdk(rGt |jt sJt ||j}tj|}|S)z Returns a string representation of the type of the function or module pointed to by this node, or '' for other node types. )r,r;r-)r>rDtypenamer?r1rBr )rrr4 target_mods rget_target_type_strr@sv K ww22nnT[[1  M !$++s+++%b$++6 nnZ0 rresults model_nameci}|jD]\\}}d}|jD]5}|jD] \}}||k(rt|sJ|dd}!"7||||<X|||<^|S)a  Rekeys the layer name of a results dictionary to use node names from `model_name`. For example, transforms {'base_op_1_0': {'node_output': {'model_a': [{'ref_node_name': 'linear1', ...}]}}} into {'linear1': {'node_output': {'model_a': [{'ref_node_name': 'linear1', ...}]}}} Note: we cannot use these node names directly because they are not guaranteed to be consistent across models. This is why we extract the results first and rekey afterwards. Nr ref_node_name)itemsvaluesr) rr new_resultsold_layer_nameresult_type_to_resultsnew_layer_namemodel_name_to_resultscur_model_namelist_of_resultss r'rekey_logger_info_on_node_name_of_modelrOs,K29--/ A..%;%B%B%D  !3H3N3N3P /!Z////%4Q%7%HN     %*@K '*@K ' A rcd}|jD]L}|jD]6}|jD] \}}t|dkDs|dd|}nnn|rw|jD]c}|jD]N}||}|jD]4\}}||k(r tt|D]}||d}|||d<6Peyy)ay If `fqn` entries are filled in for one of the models in `results`, copies them over to any models which do not have them filled out. A common use case benefitting from this is comparing a model prepared by quantization to a quantized model. In this case, the model prepared by quantization would have `fqn` entries, and the quantized model would not. Nrfqn)rrrr) rmodel_name_with_fqnsrrr model_resultsref_model_resultsrrs rmaybe_add_missing_fqnsrvs- ").."2%;%B%B%D  !-B-H-H-J ) M}%)$Q'.:/9,      &-nn&6 6 ")?)F)F)H 6%$9:N$O!1F1L1L1N6-J !%99 "3}#566/25925 a(/66 6 6rcfdS)Ncf|^}}}t|trt|ts t|trFt|tr6g}t||D]#\}}||g|}|j  |i|%|St|t j rRt|t j r8|jr|j}|jr|j}|jt jk7s|jt jk7ry||g|} |i|Sr/) r1tuplelistzipappendrDTensor is_quantizedr<dtypefloat) rkwargsa0a1a_otherrel0el1new_argsfinners rrzGmaybe_dequantize_first_two_tensor_args_and_handle_tuples..innersB r5 !jU&; r4 ZD%9GBK ;S/w/uh9&9: ;N ELL )jU\\.J]]_]]_ 88u{{ "bhh%++&=%W%(%f%%rr)rrs`@r8maybe_dequantize_first_two_tensor_args_and_handle_tuplesrs&2 Lrxyctj|}tj||z }dtj||z zS)z Computes the SQNR between `x` and `y`. Args: x: Tensor or tuple of tensors y: Tensor or tuple of tensors Return: float or tuple of floats )rDnormlog10)rrPsPns r compute_sqnrrs; AB AE B  BG$ $$rc|tj||z dzj|dzjz S)z Computes the normalized L2 error between `x` and `y`. Args: x: Tensor or tuple of tensors y: Tensor or tuple of tensors Return: float or tuple of floats r_)rDsqrtsumrrs rcompute_normalized_l2_errorrs3 ::A!|((*adZZ\9 ::rc|jdd}|jdd}tjjj ||S)z Computes the cosine similarity between `x` and `y`. Args: x: Tensor or tuple of tensors y: Tensor or tuple of tensors Return: float or tuple of floats r )reshaperDr functionalcosine_similarityrs rcompute_cosine_similarityrsA !RA !RA 88   0 0A 66rc|jdk(ri|jtjtjt jt jtj tjfvryy)Nr,FT)r>r?rDrergrcatstack)rs rop_type_supports_shadowingrsQ ww/! ;; II II LL LL II KK    ridxcD |j|d}|P|\}}t|t|z|kDsJ|t|kr||St|j|St|jt|j z|kDsJ|t|jkr|j|S|t|jz}t|j j|S#t $rt|jt|j z|kDsJ|t|jkr|j|cYS|t|jz}t|j j|cYSwxYw)zu Given a node, gets the n'th input to that node, normalizing args and kwargs to the best of its ability. T)normalize_to_only_use_kwargs)normalized_argumentsrrrrr RuntimeError)rrrnorm_args_and_kwargs norm_args norm_kwargs kwargs_idxs rr@r@st :#88 T 9  +%9 "I{y>C $44s: ::S^# ~%K..01#66tyy>C $44s: ::S^#yy~% 3tyy>1 DKK..01*==  :499~DKK 003666 TYY 99S> !s499~-J **,-j9 9 :s,AC< C<'AC<>=C<FF)9rrtypingrrrrDtorch.ao.nn.intrinsic.quantizedaor intrinsicrrmtorch.ao.nn.quantizedritorch.nntorch.ao.quantizationrrtorch.ao.quantization.observerrtorch.ao.quantization.utilsr torch.fxr torch.fx.graphr ns_typesr rrrdEnumrdictrBsetrrArrintrrrrrrrrrrrrboolrr@rrrrs ,, ..##@F8 5 ii DII xN xNxNxN#3,<(=#=> xN  "7 78 xNvM MM#3,<(=#=>MeE%,,-.ellC6G0HHIJ M`  :     44DI0 d   $ $$$N6M6d6D:: %ELL %U\\ %ell %: % : ;5<< ;ELL ;U\\ ;: ;:77%,,75<<7:7& T d !:4!:[!:s!:t!:r