Χg|dZddlZddlmZmZddlZddlmZddlmZm Z m Z ddl m Z m Z gdZeje jd Zed e jd d d d d dde jdejdeedejdejdedefdZedde jfdZdZede jd dddd ddd d(de jdejded eed!eed"eejd#ed$eed%eed&ejfd'ZdS))aThis file exports ONNX ops for opset 17. Note [ONNX Operators that are added/updated in opset 17] ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ https://github.com/onnx/onnx/blob/main/docs/Changelog.md#version-17-of-the-default-onnx-operator-set New operators: BlackmanWindow DFT HammingWindow HannWindow LayerNormalization MelWeightMatrix STFT SequenceMap N)OptionalSequence)_C) _type_utilserrorssymbolic_helper) jit_utils registration) layer_normstftquantized_layer_norm)opsetzaten::layer_normvisfnoneginputnormalized_shapeweightbiaseps cudnn_enablect| }tj|tjj}|} t j|r-tj || } | d| }t j|r-tj || } | d| }| d|||||S)NdtypeConstantvalue_tLayerNormalization) epsilon_faxis_i) lenr JitScalarType from_valueFLOATrr_is_nonetorchonesopzeros) rrrrrrraxis scalar_typer weight_value bias_values W/var/www/html/ai-engine/env/lib/python3.11/site-packages/torch/onnx/symbolic_opset17.pyr r %s  ! ! !D+66 {(.K     E''8z"2%@@@ j,77%%4[!1??? ttJ t33 44     zquantized::layer_normc tj||\}}}}t||||||d} tj|| ||S)NF)rdequantize_helperr quantize_helper) rxrrrrop_scale op_zero_point_outputs r1r r IsO!21a88JAq!Q 1.c5 I IF  *1fh N NNr2c*||z dz}||z |z }||fS)zuHelper function to compute the sizes of the edges (left and right) of a given window centered within an FFT size.)n_fft window_sizeleftrights r1_compute_edge_sizesrB[s+ K A %D DL; &E ;r2z aten::stftibFTr> hop_length win_lengthwindow normalizedonesidedreturn_complexreturnc |rtjd|||n|dz} |dtj| tj} |dtj|tj} |} t j| } | dkrL|d | |dtjd gtj} n"| | d krtjd | d |t j|d }||r|n|}||ksJd|df||krt||\}}|dtj |}|dtj |}|d|||d }t j |r|r||krtjd|d|d|t||\}}tj tj |tj |tj |f}ntj |}|jd |ksJ|d|}|d|tj| }|d| | || ||rdnd }|d|gd}| dkrK|d||dtjd gtj}|rxtjtj|| }|d||d|}|S)aAssociates `torch.stft` with the `STFT` ONNX operator. Note that torch.stft calls _VF.stft, without centering or padding options. Hence, this function does not contain these two arguments. See torch.stft source code for more info. Args: g: Graph to write the ONNX representation into input: Input tensor for the transformation n_fft: FFT size hop_length: Size of the hop. Defaults to `floot(n_fft // 4)` win_length: Size of the analysis window. Defaults to `n_fft` window: Analysis window. Defaults to a window of all ones normalized: Whether to return a normalized STFT onesided: Whether to return only half (+1) of the results, given the symmetry of the STFT return_complex: Whether to return the complex value (Note: Must be `False` or `None`) Returns: op: Operator for torch.stft associated with STFT (ONNX) z-STFT does not currently support complex types)msgvalueNrrr Unsqueezerr<zcSTFT can only take inputs of 1 [signal] or 2 [batch, signal] dimensions. Current rank of signal is z, please reduce it.)dimzuAnalysis window size must equal `win_length` or `n_fft`. Please, set `win_length` or `n_fft` to match `window` size ()Concat)r#zWThe analysis window can't be longer than the size of the FFT. Please set `win_length` (z) to `n_fft` (z ) or less.Cast)to_iSTFT) onesided_i Transpose)rr<rP)perm_iSqueezeDiv)rSymbolicValueErrorr+r)tensorint64r_get_tensor_rank_get_tensor_dim_sizerBr,r(hstackr*shaperr%r& onnx_typesqrttyper)rrr>rErFrGrHrIrJframe_step_valueframe_step_constframe_length_constsignal signal_rankn_winwin_length_defaultr@rAleft_win right_win torch_windowresult sqrt_nffts r1r r cslF '?u    &0%;zz!ttEL)9MMMELekBBB F!26::Ka   DDU\1#U[%I%I%ID J J     a'J)4JJJ      0Q ? ? ?E +5@ZZ5**** TKP T T T- *** 5==-eU;;KD%ttJ D0A0AtBBHZU1C1CDDITT(HfiTJJF''8  -E!!/\0:\\JO\\\.eZ@@KD% <T""EJz$:$:EKrs"%%%%%%%% ;;;;;;;;;;88888888 9 8 8""<#=RHHH"##CsCf== 8sm H  (   >=$#D'((OOOO)(O" Cc3S#sCC !% $!%#%*BBB 8B B B  B RX  BBtnBTNBXBBBDCBBBr2