U 1þjgþã@s<dZddlZddlmZmZddlZddlmZddlmZm Z m Z ddl m Z m Z mZddd gZejejd d Zed ƒe  d dd d dd¡e jejeeejejeedœdd„ƒƒZedƒe jdœdd „ƒZdd„Zedƒe  d dddd ddd¡e jde jejeeeeeeejeeeeeejdœ dd„ƒƒƒZdS) a‘This 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 éN)ÚOptionalÚSequence)Ú_C)Ú _type_utilsÚerrorsÚsymbolic_helper)Ú _beartypeÚ jit_utilsÚ registrationÚ layer_normÚstftÚquantized_layer_normé)Zopsetzaten::layer_normÚvÚisÚfÚnone)ÚgÚinputÚnormalized_shapeÚweightÚbiasÚepsÚ cudnn_enablec Cs†t|ƒ }tj |tjj¡}| ¡} t |¡rJtj || d} |j d| d}t |¡rptj || d} |j d| d}|j d|||||dS)N©ÚdtypeÚConstant©Zvalue_tZLayerNormalization)Z epsilon_fÚaxis_i) ÚlenrÚ JitScalarTypeÚ from_valueÚFLOATrrÚ_is_noneÚtorchÚonesÚopÚzeros) rrrrrrrZaxisZ scalar_typerZ weight_valueZ bias_value©r(ú?/tmp/pip-unpacked-wheel-ttp2cnii/torch/onnx/symbolic_opset17.pyr #s( ÿ  úzquantized::layer_norm)rc Cs8t ||¡\}}}}t||||||dƒ} t || ||¡S)NF)rZdequantize_helperr Zquantize_helper) rÚxrrrrZop_scaleZ op_zero_pointÚ_Úoutputr(r(r)r Gs cCs ||d}|||}||fS)zuHelper function to compute the sizes of the edges (left and right) of a given window centered within an FFT size.ér()Ún_fftZ window_sizeÚleftÚrightr(r(r)Ú_compute_edge_sizesYs  r1z aten::stftÚiÚbFT) rrr.Ú hop_lengthÚ win_lengthÚwindowÚ normalizedÚonesidedÚreturn_complexÚreturnc  Csª|rtjd|d‚|dk r|n|d} |jdtj| tjdd} |jdtj|tjdd} |} t | ¡} | dkr˜| d | |jdtjd gtjdd¡} n| d kr¶tjd | ›d |d‚tj|d d}|dk rH|rÖ|n|}||ksôt d|›dfƒ‚||krHt ||ƒ\}}|jdt  |¡d}|jdt  |¡d}|jd|||d d}t  |¡rÞ|r²||kr€tjd|›d|›d|d‚t ||ƒ\}}t  t  |¡t |¡t  |¡f¡}n t |¡}|jd |ksÐt ‚|jd|d}|jd|tj | ¡ ¡d}|jd| | || |dks|rdnd d}|jd|d d ddgd}| dkrl| d||jdtjd gtjdd¡}|r¦t tj||  ¡ ¡d¡}| d||jd|d¡}|S)a®Associates `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)ÚmsgÚvalueNérrréZ Unsqueezerr-zcSTFT can only take inputs of 1 [signal] or 2 [batch, signal] dimensions. Current rank of signal is z, please reduce it.)ZdimzuAnalysis window size must equal `win_length` or `n_fft`. Please, set `win_length` or `n_fft` to match `window` size (ú)ZConcat)rzWThe analysis window can't be longer than the size of the FFT. Please set `win_length` (z) to `n_fft` (z ) or less.ZCast)Zto_iZSTFT)Z onesided_iZ Transposeé)Zperm_iZSqueezeZDiv)rZSymbolicValueErrorr&r$ZtensorZint64rZ_get_tensor_rankZ_get_tensor_dim_sizeÚAssertionErrorr1r'r#Zhstackr%Úshaperr r!Z onnx_typeÚsqrtÚtyper)rrr.r4r5r6r7r8r9Zframe_step_valueZframe_step_constZframe_length_constÚsignalZ signal_rankZn_winZwin_length_defaultr/r0Zleft_winZ right_winZ torch_windowÚresultZ sqrt_nfftr(r(r)r as˜$ÿÿÿ ý ý    ÿ   ýÿ ÿú  ý)NNNFTF)Ú__doc__Ú functoolsÚtypingrrr$rZ torch.onnxrrrZtorch.onnx._internalrr r Ú__all__ÚpartialZ onnx_symbolicZ_onnx_symbolicÚ parse_argsZ GraphContextÚValueÚintÚfloatÚboolr r r1Zbeartyper r(r(r(r)ÚsV  ù"ÿ÷ö