sgP ddlZddlZddlmZmZmZmZmZmZm Z ddl Z ddl m cm cmcmZddlm cm cmZddlm Z ddlmZmZddlmZddlmZddlmZddlmZdd lm Z m!Z!e jDjZ#Gd d ejHZ%d ed ededee&ee fdee%e%ff dZ'd ed edee&ee fdeee e jPe)fe e jPe*fffdZ+d ed edefdZ,d ed ede*fdZ-d edee*fdZ.d ed ede&fdZ/de!de&de!fdZ0de!ddfdZ1dZ2e2de jPde jPde jPfdZ3e2de jPde jPde jPfdZ4e2de jPde jPde jPfd Z5d ede6fd!Z7d ed ed"e*defd#Z8y)$N)CallableDictListOptionalSetTupleUnion)FakeQuantizeBase ObserverBase)_is_activation_post_process)getattr_from_fqn) GraphModule)Node)NSNodeTargetType NSResultsTypeceZdZejZejZejZejZejZ y)NodeInputOrOutputTypeN) __name__ __module__ __qualname__enumautoFP32INT8FP16UNKNOWN FP32_OR_INT8G/var/www/html/venv/lib/python3.12/site-packages/torch/ao/ns/fx/utils.pyrrsE 499;D 499;D 499;DdiikG 499;Lr rnodegm logger_clsnode_type_to_io_type_mapreturnc|d}|d}|d}|d}|d}|d} |d} |d} |jd k(r|j|vr tjtjfS|j|vr tjtjfS|j|vr tj tj fS|j|vr4t ||d } t| tsJt| |||\} }||fStjtjfS|jd k(r0|jd k(sJt|jtsJt||jtfd | D}t|ttfs|r4t ||d } t| tsJt| |||\} }||fStfd |D}tfd| D}|r tjtjfS|r tj tj fStjtjfS|jdk(r-|jdk(rBt ||d }t|tsJt||||\} }|tjfS|jdk(rkt ||d }t|tsJt||||\} }t ||d}|t j"us J|d|tjfS|j| vr4t ||d } t| tsJt| |||\} }||fStjtjfStjtjfS)Nfuns_io_type_fp32funs_io_type_fp16funs_io_type_int8funs_io_type_fp32_or_int8mods_io_type_fp32mods_io_type_int8mods_io_type_fp32_or_int8meths_io_type_fp32_or_int8 call_functionr call_modulec36K|]}t|ywN isinstance.0 target_typemods r! z7get_node_first_input_and_output_type..Ns1 -8JsK (1 c36K|]}t|ywr3r4r6s r!r:z7get_node_first_input_and_output_type..`) -8JsK () r;c36K|]}t|ywr3r4r6s r!r:z7get_node_first_input_and_output_type..cr=r; call_method dequantizetorz handling needs to be added)optargetrrrrget_normalized_nth_inputr5r$get_node_first_input_and_output_typerstrr anyr r torchfloat16)r"r#r$r%FUNS_IO_TYPE_FP32FUNS_IO_TYPE_FP16FUNS_IO_TYPE_INT8FUNS_IO_TYPE_FP32_OR_INT8MODS_IO_TYPE_FP32MODS_IO_TYPE_INT8MODS_IO_TYPE_FP32_OR_INT8METHS_IO_TYPE_FP32_OR_INT8 first_arg_prev_node_input_typeprev_node_output_type"is_known_fp32_or_int8_input_moduleis_known_fp32_input_moduleis_known_int8_input_module prev_nodecur_node_dtype_targetr9s @r!rErE&s11DE01DE01DE 89T U01DE01DE 89T U!9:V!W ww/! ;;+ +)..0E0J0JK K ;;+ +)..0E0J0JK K [[- -)..0E0J0JK K [[5 50r1=Ii. ..52z+C %%*+@A A)113H3P3PQ Q M !ww-'''$++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}||fSr3)rDr5rrCrFr )r"r# 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""r r0rr1c36K|]}t|ywr3r4)r7r8 module_objs r!r:z)get_node_input_qparams..s1 4?Jz; /1 r;)+rDr5rrBrCrHquantize_per_tensortoqaddadd_relumulmul_relurFr nnqLinearConv1dConv2dnniq ConvReLU2dConv3d BatchNorm2d BatchNorm3dConvTranspose1dConvTranspose2dELU GroupNormInstanceNorm1dInstanceNorm2dInstanceNorm3d LayerNorm Hardswish LeakyReLUReLU6BNReLU2dBNReLU3d ConvReLU1d ConvReLU3d LinearReLUscale zero_pointrGget_node_input_qparams)r"r#r%rXrPrbrUrfs @r!rrs)r15I i & 89T U#||&   u88 83Ir1aH H   #''3<<#,,!O O3Ir1aH H  &)**C000%b)*:*:;      #### """"""      1  :$$j&;&;< <-01 C\1 . * .))R9QR R r c|jdk(rt||j}t|rt |j dk(sJt |j dtsJ|j d}t |jtsJt||j}t|rHt |j dk(sJt |j dtsJ|j d}|S)a If node is not an observer, returns it. If node is an observer, navigates up the graph and returns the first parent which is not an observer. For example, graph: (node_non_obs), node = node_non_obs : returns node_non_obs graph: (node_non_obs -> obs0), node = obs0 : returns node_non_obs graph: (node_non_obs -> obs0 -> fq0), node = fq0 : returns node_non_obs r1rr) rBr rCr lenargsr5rrFr"r#node_objs r!return_first_non_observer_noders ww-#B 4 &x 0tyy>Q& &&diilD1 1199Q.innersB r5 !jU&; r4 ZD%9GBK ;S/w/uh9&9: ;N ELL )jU\\.J]]_]]_ 88u{{ "bhh%++&=%W%(%f%%r r)rrs`@r!8maybe_dequantize_first_two_tensor_args_and_handle_tuplesrs&2 Lr xyctj|}tj||z }dtj||z zS)z Computes the SQNR between `x` and `y`. Args: x: Tensor or tuple of tensors y: Tensor or tuple of tensors Return: float or tuple of floats )rHnormlog10)rrPsPns r! compute_sqnrrs; AB AE B  BG$ $$r c|tj||z dzj|dzjz S)z Computes the normalized L2 error between `x` and `y`. 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