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dGddZe$de1d4d4dMd5dGddZe$ddGddZe$ddGddZe$ddGddZe$ddGddZe$ddGddZe$ddGd d!Ze$d"dGd#d$Ze$d%dGd&d'Ze$d(e1d4d4dGd)d*Ze$d+e1d4d4dGd,d-Ze$d.dYdGd/d0Ze$d1e)dddGd2d3Ze$d4dYdGd5d6Ze$d7e)dddGd8d9Ze$d:e)de1d4ddMdGd;d<Ze$d=e)de1d4ddMdGd>d?Ze$d@e)de1d4d4dMdGdAdBZe$dCdGdDdEZe$dFe$dGe1d4d5dMdGdHdIZe$dJeOdJgde$dKeOdKgde$dLeOdLgde$dMeOdMgde$dNeOdNgde$dOeOdOgddFdPdQZe$dRe1d4d`ddMd4dHdGdSdTZe$dUe1d4d4d4dMdGdVdWZe$dXe1d4dMdMdGdYdZZe$d[e1d4dMdMdMdGd\d]Ze$d^ed_dGd`daZe$dbed_dGdcddZe$deed_dGdfdgZe$dhed_dGdidjZe$dked_dGdldmZe$dned_dGdodpZe$dqed_dGdrdsZe$dted_dGdudvZe$dwed_dGdxdyZe$dze1d4dMd4d4d4d4		dZdGd{d|Ze$d}e1d4dMd4d4d4d4					d[dGd~dZe$d	dMdGddZe$ddGddZe$d	d\dGddZe$ddYdGddZe$de1d4dMd4d4d4dMdGddZe$de1d4dMd4d4d4d4					d[dGddZe$d	dMdGddZe$ddGddZe$de1d4dMd4d4d4dMdGddZe$de1d4dMd4d4d4d4					d[dGddZe$d	dMdGddZe$d	dMdGddZe$d					d[dGddZe$d	dMdGddZe$ddGddZe$ddGddZe$de)de1d4d5d5d]ddZe$de)de1d4dGddZe$dej)ddddoe1d4dGddZe$de1d4dGddZe$de1d4d5dGddZe$de1d4d5dGdÐdĄZe$dŃdGdƐdǄZe$dȃe1d4dMdGdɐdʄZe$d˃e1d4dMdMddHdGd̐d̈́Ze$d΃dGdϐdЄZe$dуe1d4dMdMdMdMddHdGdҐdӄZe$dԃdGdՐdքZe$d׃dGdؐdلZe$dڃdGdېd܄Ze$d݃	dYdGdސd߄Ze$de1d4dMdGddZe$de1d4dMdGddZ		dYdGddZ e1d4d4d4dMdMd5dMdMdM	dGddZe1d4d4d4d4dMdMd5dMdM	dGddZe$ddGddZe$ddGddZe$deOde%dgde$deOde%dgde$deOde%dgdd^ddZe$de1d4dMdGdd Ze$ddGddZe$de1d4dMdGddZe$de1d4d4dMdGdd	Z	e$d
e1d4d4dMd`d4dGddZ
e$ddGddZe$ddGddZe$ddGddZe$ddGddZe$d				d_dGddZe$d				d_dGddZe$de1d4d5d5dMddGd d!Ze$d"dTdGd#d$Ze$d%e1d4dGd&d'Ze$d(e1d4dGd)d*Ze$d+e)ddde1d4dMdMdGd,d-Ze$d.e1d4dGd/d0Ze$d1dHdGd2d3Ze$d4e1d4dGd5d6Ze$d7dGd8d9Ze$d:dGd;d<Ze$d=e1d4dMdMdMdGd>d?Ze$d@e1d4d4dd`dCdDZe$dEe1d4d4dd`dFdGZe$dHe1d4dMd4d4dGdIdJZe$dKe1d4dMd4d4dGdLdMZe$dNdGdOdPZ e$dQdGdRdSZ!e$dTdGdUdVZ"e$dWedGdXdYZ#e$dZdGd[d\Z$e$d]e1d4dMd4d4dMdGd^d_Z%e1d4ddMdMdGd`daZ&e$dbdGdcddZ'e$dedGdfdgZ(e$dhdGdidjZ)e$dkdGdldmZ*e$dne1d4ddMdGdodpZ+e$dqdGdrdsZ,e$dtdGdudvZ-e$dwdGdxdyZ.e$dzdGd{d|Z/e$d}dGd~dZ0e$ddGddZ1e$de1d4d4ddd4daddZ2e$de1d4d5ddd4dbddZ3e$de1d4d4ddd4dcddZ4e$de1d4d4dMdddGddZ5e$de1d4dddedGddZ6e$de1d4dMdd4	dZdGddZ7e$ddGddZ8e$de1d4d9dHdfddZ9e$ddGddZ:e$de1d4d9dgdhddZ;e$de)dddde1d4dMd4d4d5dMdGddZ<e$de1d4d4dMdGddZ=e$ddGddEZ>e$ddGddZ?e$ddGddZ@e$ddGddZAe$ddGddZBdGddZCdGddZDe$de1d4d4dMddGddÄZEe$dăe1d4d4dMdGdŐdƄZFe$dǃe)de1d4d4ddMdHdGdȐdɄZGe$dʃdGdːd̄ZHe$d̓dGdΐdτZIe$dЃdGdѐdjZJe$d҃e1d4ddMd4d4d4d4						didjdԐdՄZKe$dփdGdאd؄ZLe$dكdGdڐdۄZMe$d܃e1d4d`d`dGdݐdބZNe$d߃e1d4d4dGddZOe$ddHdGddZPe$de1d4ddȡdGddZQe$de1d4d4dMdHdGddZRe$d		dkdGddZSdGddZTe$ddGddZUe$ddGddZVe$ddHdGddZWe$ddGddZXe$ddGdd ZYe$ddGddZZe$ddGddZ[e$ddHdGdd	Z\e$d
dGddZ]e$ddGddZ^e$ddGddZ_e$ddlddZ`e$ddGddZae$ddGddZbe$ddGddZce$d dGd!d"Zde$d#dGd$d%Zee$d&dmd(d)Zfe$d*dnd,d-Zge$d.dnd/d0Zhe$d1dGd2d3Zie$d4dod6d7Zje$d8dGd9d:Zke$d;e$d<dpd=d>Zle$d?e$d@dpdAdBZme$dCdqdDdEZndS (r  zhThis file exports ONNX ops for opset 9.

Opset 9 is supported by ONNX release 1.4.1
release on 01/23/19
    )annotationsN)CallableTYPE_CHECKING)
deprecated)_C)
_constants_type_utilserrorssymbolic_helper)GLOBALS)	jit_utilsregistration)Sequence)Number(  absacosaddaddcmuladdmmaliasamaxaminaminmaxarangeargmaxargmin
as_strided	as_tensorasinatanatan2baddbmm
batch_norm	bernoullibitwise_not
bitwise_orbmmbroadcast_tensorsbroadcast_to	bucketizecatcdistceil	clamp_max	clamp_minclampcloneconstant_pad_nd
contiguousconv_tbcconv_transpose1dconv_transpose2dconv_transpose3dconv1dconv2dconv3dconvert_element_typeconvolutioncoscosine_similaritycrosscumsumdetachdimdivdotdropouteluembedding_bag	embedding
empty_likeemptyeqerfexp	expand_asexpandeyefillflattenfloor_dividefloorfloordivfrobenius_norm	full_likefullgathergegeluget_pool_ceil_paddingglu
group_normgthann_window
hardshrinkhardsigmoid	hardswishhardtanh	index_add
index_copy
index_fill	index_putindex_selectindexinstance_normis_floating_point	is_pinnedisnanitemkl_div
layer_normle
leaky_relulerpliftlinalg_crosslinalg_matrix_normlinalg_normlinalg_vector_normlinearlinspacelog_sigmoidlog_softmaxloglog10log1plog2logical_andlogical_not
logical_orlogical_xorlogit	logsumexp	lstm_celllstmltmasked_fillmasked_fill_matmulmax_pool1d_with_indicesmax_pool2d_with_indicesmax_pool3d_with_indicesmaxmaximummeshgridminminimummishmmmovedimmse_lossmulmultinomialmvnarrownative_layer_normneneg	new_emptynew_fullnew_ones	new_zerosnonzero_numpynonzeronormnumelnumpy_Tone_hot	ones_likeonesonnx_placeholderpadpairwise_distancepermutepixel_shufflepixel_unshufflepowpreluprim_constant_chunkprim_constant_splitprim_constant	prim_dataprim_device
prim_dtypeprim_ifprim_layoutprim_list_constructprim_list_unpack	prim_loopprim_maxprim_min
prim_shapeprim_tolistprim_tuple_construct	prim_typeprim_unchecked_castprim_uninitialized	rand_likerandrandint_likerandint
randn_likerandn
reciprocalreflection_padrelurelu6	remainderrepeat_interleaverepeatreplication_pad
reshape_asreshaperollrrelursqrtrsubscalar_tensorscatter_addscatterselectselusigmoidsignsilusinsizeslicesoftmaxsoftplus
softshrinksortsplit_with_sizessplitsqrtsquaresqueezestackstd_meanstdsubttaketantanh
tanhshrinktensor	thresholdtotopk	transposetrue_dividetype_asunbindunfoldunsafe_chunkunsafe_split_with_sizesunsafe_split	unsqueezeunsupported_complex_operatorsnoop_complex_operatorsunusedvar_meanvarview_asviewwherewrap_logical_op_with_cast_towrap_logical_op_with_negation
zeros_likezeroszero	   )opsetnamestrc                       fdd}|S )z5Exports the function in the current global namespace.c                   s   | t   < t  | S N)globals__all__appendfuncr   n/var/www/html/construction_image-detection-poc/venv/lib/python3.10/site-packages/torch/onnx/symbolic_opset9.pywrapper4  s   

z_export.<locals>.wrapperr  )r  r   r  r  r  _export1  s   r!  c                 C  s   |  d}|tj  |S )z%Represents "missing" optional inputs.prim::Constant)opsetTyper   OptionalTypeofTensor)gnr  r  r  r  <  s   
r  zaten::_shape_as_tensorr'  jit_utils.GraphContextc                 C     |  d|S NShaper#  r'  inputr  r  r  _shape_as_tensorC     r0  zaten::_reshape_from_tensorc                 C  s.   t |tr| jdg|R ddi}t| ||S )NConcataxis_ir   )
isinstancelistr#  r   )r'  r/  shaper  r  r  _reshape_from_tensorH  s   
r7  zaten::reshapeTc                 C     t | ||S r  )r
   _reshape_helperr'  selfr6  r  r  r  r   O     r   zaten::reshape_asc                 C     |  d|}t| ||S r+  r#  r   r'  r;  otherr6  r  r  r  r   U     r   z	aten::addc                 C  sZ   t |rt |rt dddd|S |r&t t |dkr&| d||}| d||S )a  
    This function takes the add function and returns the corresponding ONNX operator.

    This function is not meant to be called directly by the user.

    Args:
        g (GraphContext): The graph context.
        self (Tensor): The first operand.
        other (Tensor): The second operand.
        alpha (float, optional): The scaling factor for the second operand. Defaults to None.

    Returns:
        ONNX operator.
    Addr     z)Add between list of tensors not supported   Mul)r
   	_is_value_is_tensor_list _onnx_opset_unsupported_detailed_scalar_maybe_get_scalarr#  r'  r;  r@  alphar  r  r  r   \  s   
r   z	aten::subc                 C  s4   |rt t |dkr| d||}| d||S )a  
    Consumes sub function and returns the corresponding ONNX operator.

    This function is not meant to be called directly by the user.

    Args:
        g (GraphContext): The graph context.
        self (Tensor): The first operand.
        other (Tensor): The second operand.
        alpha (Optional[Tensor]): A scaling factor to apply to the second operand.
            If `alpha` is not provided, it defaults to 1.

    Returns:
        ONNX operator
    rD  rE  Sub)r
   rI  rJ  r#  rK  r  r  r  r   u  s   r   z
aten::rsubc                 C  s   t | |||dS )N)rL  )r   rK  r  r  r  r     s   r   z	aten::mulc                 C  s0   t |rt |r| d||S | d||S )NAndrE  )r
   _is_boolr#  r'  r;  r@  r  r  r  r     s   r   z	aten::divc                 G  s,   t |dkrt| ||S t| ||g|R  S Nr   )lenr   _div_rounding_mode)r'  r;  r@  argsr  r  r  rB     s   rB   zaten::addcmulvf      ?c              	   C  s2   | j dt|gd}t| |t| t| |||S NConstantvalue_t)r#  torchr   r   r   )r'  r;  tensor1tensor2value
value_tensr  r  r  r     s   r   sc                 C  sP   |d u r
t | ||S |dkrt| ||S |dkrt| ||S td| d|)NrS   trunczUnsupported rounding mode: "z$". Expected None, "floor" or "trunc")r   _floor_divide_trunc_divider	   SymbolicValueError)r'  r;  r@  rounding_moder  r  r  rS    s   
rS  c                 C  s   |  d||}| j d|tjjd}tj|tjj}|tjjkrBt	|s6t	|r6| j d|tjj
d}|S | j d|| d}|S | j d|tjj
d}|S )NDivCastto_i)r#  _C_onnxTensorProtoDataTypeINT64r   JitScalarType
from_value	UNDEFINEDr
   _is_fpFLOAT	onnx_type)r'  r;  r@  outscalar_typer  r  r  rd    s"   	rd  c                 C  s   t |s
t |rt| ||}| d|S | d||}| jdtjdtjdd}| dt | ||t | ||}| d|| d	||}| d
|| d| d||}| jdtjdtjdd}	| d	||	}
| d||
S )NFloorrg  rY  r   dtyperZ  XorrM  rE  rN  NotEqualrD  )r
   rq  r   r#  r\  r   int64
_lt_helper)r'  r;  r@  rt  rB   r  negativemod
fixup_maskonefixupr  r  r  rc    s    rc  zaten::floor_dividec                 C     t | ||S r  )rd  rP  r  r  r  rR        rR   zaten::floordivc                 C  r  r  )rR   rP  r  r  r  rT     r1  rT   zaten::true_dividec                 C  s   t |s
t |r| d||S t }tjj}|tju s%|tj	u s%J t tj	u r0tjj
}| jd||d}| jd||d}| d||S )a  Division where both inputs are cast to floating types

    If both inputs are floating, performs div as usual
    If only one input is a floating type, the other input is cast to its type
    If neither input is a floating type, both inputs are cast to the default scalar type
    rg  rh  ri  )r
   rq  r#  r\  get_default_dtyperk  rl  rr  floatdoubleDOUBLE)r'  r;  r@  ru  onnx_scalar_typer  r  r  r     s   r   zaten::reciprocalc                 C  s*   t |s| jd|tjjd}| d|S )Nrh  ri  
Reciprocal)r
   rq  r#  rk  rl  rr  r'  r;  r  r  r  r     s   
r   z	aten::catic                   s   t |}g  |D ]}t |rt |dsq	 | q	t dks%J t fdd D s2J |    D ]	}| 	| q:t |}| j
dg|R d|iS )a{  Implement concatenation of pytorch tensors in ONNX along the specified `dim` dimension.

    Parameters:
        g (jit_utils.GraphContext): Graph context.
        tensor_list (List[torch.Tensor]): List of tensors to concatenate.
        dim (int): Dimension along which to concatenate the tensors.

    Returns:
        ONNX graph node representing the concatenated tensor.
    r   c                 3  sH    | ]}t  d  du pt |du pt |t  d  kV  qdS r   N)r
   _get_tensor_rank.0r   nonempty_tensorsr  r  	<genexpr>6  s    
zcat.<locals>.<genexpr>r2  r3  )r
   _unpack_list_is_constant_get_tensor_dim_sizer  rR  allnoderemoveAllInputsaddInputr#  )r'  tensor_listrA   tensorsr   r  r  r  r*     s"   

r*   zaten::stackc                   s2    fddt |D }jdg|R d iS )Nc                      g | ]
}t | gqS r  r
   _unsqueeze_helperr  rA   r'  r  r  
<listcomp>H      zstack.<locals>.<listcomp>r2  r3  )r
   r  r#  )r'  r  rA   
unsqueezedr  r  r  r   E  s   r   z
aten::listc                 C     |S r  r  r  r  r  r  _listO     r  zaten::mmc                 C  s,   | j dtdgd}| j d|||dddS )NrY  rD  rZ  Gemm        rW  beta_falpha_fr#  r\  r   )r'  r;  r@  Cr  r  r  r   T  s   r   z	aten::bmmc                 C     |  d||S NMatMulr-  rP  r  r  r  r&   \     r&   zaten::matmulc                 C  r  r  r-  rP  r  r  r  r   a  r  r   zaten::addmmr   c              	   C  sB  d }t |}t |}t |}	|d ur|}n|d ur|}n|	d ur%|	}t |}
t |}dd }|d ur||
dsA||dr| d||}|}t |}t |}|dkrm| jdtj|| dd}| d	||}|dkr| jdtjt || dd}| d	||}| d
||S | jd|||t |t |dS )Nc                 S  s   | d uo| |kS r  r  )rU  ur  r  r  is_not_none_norw  s   zaddmm.<locals>.is_not_none_nor   r  rD  rY  rw  rZ  rE  rB  r  r  )r
   _try_get_scalar_typer  r#  rI  r\  r   rx  )r'  r;  mat1mat2betarL  ru  self_scalar_typemat1_scalar_typemat2_scalar_type	mat1_rank	mat2_rankr  res1res2r  r  r  r   f  sX   






r   z	aten::negc                 C  r*  )NNegr-  r  r  r  r  r     r1  r   z
aten::sqrtc                 C  sT   t j|t jjt jjt jjt jjt jjt jjhv r$| j	d|t
jjd}| 	d|S )Nrh  ri  Sqrt)r   rn  ro  rp  UINT8INT8INT16INTrm  r#  rk  rl  rr  r  r  r  r  r     s   
r   zaten::rsqrtc                 C  s"   |  dttd|t| |S )Nrg  rD  )r#  r
   _if_scalar_type_asr\  r   r   r  r  r  r  r     s   r   z
aten::tanhg      ?   )scale
zero_pointc                 C  r*  )NTanhr-  r  r  r  r  r        r   z	aten::sinc                 C  r*  )NSinr-  r  r  r  r  r     r1  r   z	aten::cosc                 C  r*  )NCosr-  r  r  r  r  r<     r1  r<   z	aten::tanc                 C  r*  )NTanr-  r  r  r  r  r     r1  r   z
aten::asinc                 C  r*  )NAsinr-  r  r  r  r  r     r1  r   z
aten::acosc                 C  r*  )NAcosr-  r  r  r  r  r     r1  r   z
aten::atanc                 C  r*  )NAtanr-  r  r  r  r  r     r1  r   zaten::atan2c              
   C  s   |  d||}|  d|}| j dtdd}| j dttjd}|  d||}|  d||  d|||  d	||}|  d
||}	|  d|	||}
|
S )Nrg  r  rY  r   rZ  GreaterWhererB  rM  Less)r#  r\  r   mathpi)r'  r;  r@  sloper   
const_zeroconst_pi"condition_second_or_third_quadrantsecond_third_quadrantcondition_14_or_23_quadrantresultr  r  r  r      s   r    zaten::sigmoidg      p?c                 C  r*  )a  Converts the corresponding PyTorch function into ONNX operators.

    It is not meant to be called directly by a user.

    Args:
        g (jit_utils.GraphContext): Graph context.
        self (Tensor): the input tensor.
    Returns:
        ONNX operator
    Sigmoidr-  r  r  r  r  r     s   r   z
aten::signc                 C  r*  )NSignr-  r  r  r  r  r     r1  r   c                 C  sR   t |t |ks
J t |dkr|d dkr|d tjkr|S | jd||||dS )NrD  r   Slice)axes_istarts_iends_i)rR  r   	INT64_MAXr#  )r'  r/  axesstartsendsr  r  r  _slice  s   &r  z	aten::sum	ReduceSumsum)decoratez
aten::mean
ReduceMeanmeanz
aten::prod
ReduceProdprodF)allow_multi_dim_supportonnx_opr  boolc                 C  r8  r  )r
   _reduce_with_dtype_helper)r  r  r  r  r  r  _reduce_with_dtype  s   r  zaten::cumsumnonec                 C     t ddd| d S )Nr?   r  rC  r
   _onnx_opset_unsupported)r'  r/  rA   rx  r  r  r  r?   (     r?   zaten::_sample_dirichletc                 C     t d|S )N_sample_dirichletr
   _onnx_unsupportedr'  r;  	generatorr  r  r  r  .  r1  r  zaten::_standard_gammac                 C  r  )N_standard_gammar  r  r  r  r  r   3  r1  r   zaten::tc                 C  s6   t |}|d u s|dk r| d|S | jd|ddS )Nr  Identity	Transpose)rD  r   perm_i)r
   r  r#  )r'  r;  rankr  r  r  r   8  s   
zaten::numpy_Tc                 C  s8   t |}|d usJ tttd|}| jd||dS Nr   r  r  )r
   r  r5  reversedranger#  )r'  r/  ndimpermr  r  r  r   C  s   
r   zaten::expandc              	   C  s   t |d}t |s| jdt|d}nt |r/t | t| |d| jdt	dgd}t
jj}t| ||}t| || jdt	dd}t| | d||||}| d||S )zXImplement the expand function for a pytorch tensor in ONNX according to specified `size`isrY  rZ  r   r{  Expandr
   _maybe_get_constrF  r#  r\  
LongTensor_is_packed_listr9  r   r   r   rn  rm  r   r   r  )r'  r;  r   implicitrx  r   neg_onesr  r  r  rN   L  s   

 rN   zaten::broadcast_toc              	   C  s   t |d}t |s| jdt|d}nt |r/t | t| |d| jdt	dgd}t
jj}t| ||}t| || jdt	dd}t| | d||||}| d||S )Nr  rY  rZ  r   r  r{  r  r  )r'  r;  r   rx  r   r  r  r  r  r(   a  s   

 r(   zaten::expand_asc                 C  s   t |d}t|tjrC|j}|tj}g }t|	 D ]%}t
|||||rB|| | jd|j|dd|d}q| d|}| d||S )Nr   rY  T)keepdimrZ  r,  r  )r
   r  r4  r\  Tensorrx  r   r  r  rA   equalr  r  rM   r  r#  )r'  r;  r@  self_t	orig_typedimsdr6  r  r  r  rM   u  s   
rM   zaten::embeddingbc                 C  s<   |rt jrtd||dkrt jrtd | d||S )NzUnsupported: ONNX export of embedding with scale_grad_by_freq=True for training mode. ONNX does not support scaling the gradients.r   zWarning: ONNX export of embedding with padding_idx >= 0 for training mode. ONNX does not support not updating the embedding vector at padding_idx during training.Gather)r   export_trainingr	   re  warningswarnr#  )r'  weightindicespadding_idxscale_grad_by_freqsparser  r  r  rG     s   
rG   zaten::embedding_bagc
           
      C  s    t |s
t dS t d|S )Nz%embedding_bag with per_sample_weightsrF   )r
   _is_noner  )
r'  embedding_matrixr!  offsetsr#  moder$  per_sample_weightsinclude_last_offsetr"  r  r  r  rF     s
   
rF   z
aten::size)quantize_outputc                 C  sh   |d u r
|  d|S t|ddk r-t|}|d ur-t|d| }| j dt|d}t| ||S )Nr,  r  r   rY  rZ  )r#  r
   r  r  r\  r   _size_helperr'  r;  rA   r  r  r  r  r     s   
r   zaten::transposec                 C  s`   ||kr|S t |}|d ur*tt|}|| || ||< ||< | jd||dS td|)Nr  r  zAUnsupported: ONNX export of transpose for tensor of unknown rank.)r
   r  r5  r  r#  r	   re  )r'  r;  dim0dim1r  r  r  r  r  r     s   
r   zaten::permuter  c                 C  s*   |t tdt|kr|S | jd||dS r  )r5  r  rR  r#  )r'  r;  r  r  r  r  r     s   r   z
aten::viewc                 C  r  r  )r   )r'  r;  r   r  r  r  r    r  r  zaten::view_asc                 C  r=  r+  r>  r?  r  r  r  r
    s   r
  zaten::unsafe_chunkc           	      C  s   |d u rt dddd|S t ||}|d u rt dd|S || d | }|g||  }|| }|r8|| | jd||||dS )	Nr  r  rC  'Dynamic number of outputs not supportedunknown dimension sizerD  Splitsplit_ir3  outputs)r
   rH  r  _unimplementedr  r#  )	r'  r;  chunksrA   _outputsr   
split_sizesplitsleftoverr  r  r  r    s   

r  zaten::splitc           
      C  s   t ||st dddd|S t | d}| dkr%t| ||||S t |dd}t ||}|d u rH|d ur?|| }n	t dddd	|S |g||  }|| }	|	rZ|	|	 | j
d
||||dS )Nr   r  rC  r0  r_  r   r  r9  z$Unknown dimension size not supportedr2  r3  )r
   _is_split_staticrH  	_node_getr  rA   r   
_get_constr  r  r#  )
r'  r;  split_size_or_sizesrA   r8  	split_valr9  r   r:  r;  r  r  r  r     s(   



r   zaten::unsafe_splitc                 C     t | ||||S r  )r   )r'  r;  r?  rA   r8  r  r  r  r       r  zaten::split_with_sizesc                 C  s2   t ||st dddd|S | jd||||dS )Nr   r  rC  r0  r2  r3  )r
   r<  rH  r#  r'  r;  split_sizesrA   r8  r  r  r  r   %  s
   
r   zaten::unsafe_split_with_sizesc                 C  rA  r  )r   rC  r  r  r  r  /  rB  r  zaten::unbindc                   s^   |d u rt dddd|S jd|dg|  |d}|dkr!|gn|} fdd	|D }|S )
Nr   r  rC  r0  r2  rD  r3  c                   r  r  )r
   _squeeze_helper)r  rt  r  r  r  r  @  s    zunbind.<locals>.<listcomp>)r
   rH  r#  )r'  r;  rA   r8  r5  squeezed_outputsr  r  r  r   6  s   
r   zaten::selectc                 C  sp   t |}t |s/|dk r/|dkrtj}n|d }t j| ||g|g|gd}t | ||gS | jd|||dS )zImplement the select functionality for a pytorch tensor in ONNX.

    Selects elements from the input tensor along the specified `dim` dimension based on the `index` tensor.
    r   r  rD  r  r  r  r  r3  )r
   rJ  rF  r   r  _slice_helperrE  r#  )r'  r;  rA   ri   	end_index
slice_noder  r  r  r   F  s   
r   zaten::squarec                 C  s   |  d||S NrE  r-  r  r  r  r  r   ]  r  r   zaten::squeezec                 C  sH  |d u r
|  d|S t|dd}|dk rCt|}|d ur<tdt| d d d t||  d	 d
  ||7 }ntdd|S t||}|d u rotdt| d d t| d d d d  tj	| ||gdS |dkrtdt| d d t| d d d d  |S tdt| d d  tj	| ||gdS )NSqueezer  rA   r   z'ONNX export squeeze with negative axis - might cause the onnx model to be incorrect. (Negative axis is not supported in ONNX. Axis is converted to & based on input shape at export time. CPassing an tensor of different rank in execution will be incorrect.r   %negative axis with unknown input rankz5This model contains a squeeze operation on dimension z on an input z7with unknown shape. Note that if the size of dimension z of the input zVis not 1, the ONNX model will return an error. Opset version 11 supports squeezing on zMnon-singleton dimensions, it is recommended to export this model using opset zversion 11 or higher.r  rD  z. The size of z%this dimension in the given input is z. The model will zWbe exported without the squeeze node. If the model is intended to be used with dynamic z-input shapes, please use opset version 11 to zexport the model.z. If the model is z_intended to be used with dynamic input shapes, please use opset version 11 to export the model.)
r#  r
   r>  r  r  r  r  r6  r  rE  )r'  r;  rA   squeeze_dimr  dim_sizer  r  r  r   b  s   



r   zaten::preluc              	   C  s   t |}t |}t|}|d ur8|dkr%t | |ttd|d }n|dkr8|dgkr8t | |dg}d}|d urN|d urN||ksNJ d| d| | d||S )Nr  rD  r   z)rank(x) should be >= rank(slope) but got z < PRelu)	r
   r  _get_tensor_sizesrR  r  r5  r  rE  r#  )r'  r;  r   	self_rankweight_sizesweight_rankr  r  r  r     s    


r   z
aten::siluc                 C  s   |  d||  d|S )NrE  r  r-  r.  r  r  r  r     s   r   z
aten::mishc                 C  s   |  d||  d|  d|S )NrE  r  Softplusr-  r.  r  r  r  r     s   r   z
aten::reluc                 C  s   t j| d|ddS )NRelu   opset_beforer
   _op_with_optional_float_castr.  r  r  r  r     s   r   zaten::relu6c                 C  s   t | |ddS )Nr      )r/   r.  r  r  r  r     r<  r   z
aten::ceilc                 C  r*  )NCeilr-  r.  r  r  r  r,     r1  r,   zaten::floorc                 C  r*  )Nrv  r-  r.  r  r  r  rS     r1  rS   z	aten::lenc                 C  s.   t | || jdtdgd}t| |dgS NrY  r   rZ  )r   r#  r\  r  r
   rE  )r'  r;  sz_0r  r  r  _len  s   rg  zaten::thresholdc                 C  sD   t |dkrt dd|S t |dkrt dd|S | d|S )Nr   r   znon-zero thresholdznon-zero valuer]  )r
   rI  r6  r#  )r'  r;  r   r_  r  r  r  r     s
   r   zaten::leaky_relur/  _C.Valuenegative_sloper  inplacec                 C  s   | j d||dS )N	LeakyRelur  r-  )r'  r/  ri  rj  r  r  r  rr     s   
rr   z	aten::gluc                 C  sP   t ||}|d ur|d dksJ | jd||dd\}}| d|| d|S )Nr  r   r2  )r3  r5  rE  r  )r
   r  r#  )r'  r/  rA   rV  firstsecondr  r  r  r\     s
   r\   zaten::softmaxc              
   C  s^  t |}|d urj|dk r|| }||d k}|r8tt|}|d || ||< |d< | jd||d}|d }| jd||d}|r^|  dkr^t |d	d
}| jd|t	|
 d}|rh| jd||d}|S | d|| jd||gdd}| d|}	t j| |	|gd}
| d|	|
}|r|  dkrt |d	d
}| jd|t	|
 d}|S )Nr   rD  r  r  r  SoftmaxrH  r"  r  rx  rh  ri  rM  	ReduceMaxr  
keepdims_iExprT  rg  )r
   r  r5  r  r#  r  kindr>  r   rn  rs  _reducesum_helper)r'  r/  rA   rx  	input_dimis_transpose_requiredr  r   parsed_dtyperL   r  r  r  r  r     s>   
r   zaten::softplusc                 C  s@   t |d}|dkr| d| d| d|||S | d|S )NrV  rD  rg  r\  rE  )r
   r  r#  )r'  r;  r  r   
beta_constr  r  r  r   C  s    r   zaten::get_pool_ceil_paddingc                   s   t | }|d ur|t d  nd d u s!tdd D r(t dd| S fddtdtD   fddtdt D   fd	dtdtD fd
dtdtD S )Nc                 s      | ]}|d u V  qd S r  r  r  r  r  r  r  r  P      z(get_pool_ceil_padding.<locals>.<genexpr>r[   input size not accessiblec              	     sB   g | ]}t t | d |   |  t|  d qS r  rD  )intr  r,   r  r{  )rA   kernel_sizepaddingstrider  r  r  T  s    0z)get_pool_ceil_padding.<locals>.<listcomp>r   c                   sD   g | ]} | d  |  | |  kr | d  n | qS rD  r  r{  )ceiled_output_dimrA   r  r  r  r  r  Z  s    $c                   sP   g | ]$}| d krdn| | d|    | d  |  d    qS rD  r   r  r  r{  )r  rA   r  r  r  r  r  r  b  s    
c                   sd   g | ].}| d |    | kr*|  | d k r"t | nt  | d nt | qS r~  r  r{  )r  r  padding_ceilr  r  r  r  s    

)r
   rX  rR  anyr6  r  )r/  r  r  r  sizesr  )r  rA   r  r  r  r  r  r[   K  s&   

r[   zaten::max_pool1d
max_pool1drD  )return_indiceszaten::max_pool2d
max_pool2dr  zaten::max_pool3d
max_pool3d   c              	     s>   t ddddddt dddddd fdd}|S )NTFrU  r  r  c                   s6  t |dhkrt d|S |s|}t|}|r2t||||}|tdd t||D  }n|d }|||d}r| jd|fddi|\}	}
| jd|dd	d
 tD dd
 tD d\}}tj| |dd
 tD t	dt	dd}t
| |
|}
|	|
fS | jd|fddi|}	|	S )NrD  dilationc                 s      | ]	\}}|| V  qd S r  r  r  ar  r  r  r  r    s    z1_max_pool.<locals>.symbolic_fn.<locals>.<genexpr>r  )kernel_shape_ipads_i	strides_iMaxPoolr5  c                 S     g | ]}d qS r  r  r  _r  r  r  r        z2_max_pool.<locals>.symbolic_fn.<locals>.<listcomp>c                 S  r  r  r  r  r  r  r  r    r  )r5  r  r  c                 S  s   g | ]}d | qS )r  r  r{  r  r  r  r        r   rG  )setr
   r6  tupler[   zipr#  r  rI  r5  r   )r'  r/  r  r  r  r  	ceil_moder  kwargsrr!  r  flattened_indicesra  r  ndimsr  tuple_fnr  r  symbolic_fn  sB   


z_max_pool.<locals>.symbolic_fnr
   quantized_args
parse_args)r  r  r  r  r  r  r  r  	_max_pool  s   4r  zaten::max_pool1d_with_indicesr   zaten::max_pool2d_with_indicesr   zaten::max_pool3d_with_indicesr   zaten::avg_pool1d
avg_pool1dzaten::avg_pool2d
avg_pool2dzaten::avg_pool3d
avg_pool3dc              
     s8   t dt ddddddd	 dd fdd}|S )NTrU  r  r  r  r/  rh  r  Sequence[int]r  r  int | Sequence[int]r  r  count_include_padc              	     s   |s|}t |||| }t|tsJ |}|r/t j| d|d| d dddd}dt| }|rGt||||}	|td	d
 t|	|D  }n|d }| jd||||d}
|
S )NPad)r   r   r  constantr  rC  r  mode_svalue_fr`  r   c                 s  r  r  r  r  r  r  r  r  +  s    
z1_avg_pool.<locals>.symbolic_fn.<locals>.<genexpr>AveragePool)r  r  r  )	r
   _avgpool_helperr4  r  rb  rR  r[   r  r#  )r'  r/  r  r  r  r  r  divisor_overrideadjusted_paddingr  outputr  r  r  r  r    s@   
	
z_avg_pool.<locals>.symbolic_fnr  )r/  rh  r  r  r  r  r  r  r  r  r  r  r  )r  r  r  r  r  r  	_avg_pool  s
   	1r  zaten::adaptive_avg_pool1dadaptive_avg_pool1dr  zaten::adaptive_avg_pool2dadaptive_avg_pool2dzaten::adaptive_avg_pool3dadaptive_avg_pool3dzaten::adaptive_max_pool1dadaptive_max_pool1dr  zaten::adaptive_max_pool2dadaptive_max_pool2dzaten::adaptive_max_pool3dadaptive_max_pool3dc                   s"   t dd fdd}|S )NTFc              	     s  }zt dW n ty   t d| Y S w dgt kr-dkr-| d|S t |}z|dd   W n tyE   d  Y nw  d u sStdd  D rkdgt krd| d	|d fS t d
|S  fddt	dt D }|dgt| krdgt kr| d	|d fS t d|S  fddt	dt D }dkr| |||dt  dt  dS | j|||d}|S )Nr  z4adaptive pooling, since output_size is not constant.rD  r  GlobalAveragePoolr  c                 s  rz  r  r  r{  r  r  r  r    r|  z6_adaptive_pool.<locals>.symbolic_fn.<locals>.<genexpr>GlobalMaxPoolr}  c                   s   g | ]
} | |  qS r  r  r{  rA   output_sizer  r  r        z7_adaptive_pool.<locals>.symbolic_fn.<locals>.<listcomp>r   z-output size that are not factor of input sizec                   s    g | ]}t  | |  qS r  r  r{  r  r  r  r    s     r  r  r  F)r  r  )
r
   
_parse_arg	Exceptionr  rR  r#  rX  r  r6  r  )r'  r/  r  output_size_valuer  r  kr  fnr  r  typer  r  r  |  sD   
$z#_adaptive_pool.<locals>.symbolic_fn)r
   r  )r  r  r  r  r  r  r  r  _adaptive_pool<  s   
@1r  rA   r  c                 C  sF   t |dd dg| d t|   }|ddd |ddd  }|S )zGenerate paddings in ONNX order based on pad in pytorch.
    Args:
        dim: the dimension of the tensor.
        pad: the paddings in pytorch.
            The order is dim_n_begin, dim_n_end, dim_n-1_begin, dim_n-1_end, ...
    Nr   r  r  )r5  rR  )rA   r   paddingsr  r  r  _prepare_onnx_paddings  s   &r  c              
   C  sh   t | d}t |r2t |r2t |}z
dd |D }W |S  ty1   t dddd|  Y S w |S )Nr  c                 S  s   g | ]	}t |d dqS )r  r  )r
   r>  )r  rU  r  r  r  r    s    z)_convert_padding_node.<locals>.<listcomp>r  r  rC  z)The sizes of the padding must be constant)r
   r  rF  r  r  r  rH  )r/  r  
input_listr  r  r  _convert_padding_node  s   
	
r  zaten::constant_pad_ndc              
   C  sl   d}z	t |dd}W n ty   t dddd| Y S w t|}tt ||}t j| d||||ddS )	Nr  rV  r_  r  r  rC  z*The value for the padding must be constantr  )r
   r>  r  rH  r  r  r  rb  )r'  r/  r  r_  r(  r  r  r  r  r1     s   
r1   r   c                 C  sH  t |}t|d dksJ t|d }|}t|D ]}|d| d   }|d| d   }g }	|dkrJtj| |d| g| gtjgd}
|	|
 |dk sR|dk rvt	d| }t	d|  }tj| |d| g|g|gd}|	| n|	| |dkrtj| |d| gdg|gd}|	| | j
dg|	R dd| i}q|S )Nr  r   rD  rG  r2  r3  )r  rR  r  r
   rI  r   r  r  builtinsr   r#  )r'  r/  r   r  r	  curidxpad_rpad_lr  leftstartendmiddlerightr  r  r  _pad_circular  s@   


r  zaten::reflection_pad1dzaten::reflection_pad2dzaten::reflection_pad3dc                 C  2   d}t |}tt||}tj| d|||ddS )Nreflectr  rC  r  r  r`  r  r  r
   r  rb  r'  r/  r  r(  r  r  r  r  r        r   zaten::replication_pad1dzaten::replication_pad2dzaten::replication_pad3dc                 C  r  )Nedger  rC  r  r  r  r  r  r  r     r  r   z	aten::padr(  r_  c                 C  sp   t |d}|dkrt| ||S |dkrt| ||S |dkr%t| |||S |dkr/t| ||S td| |)Nra  	replicater  r  circularzUnrecognized padding mode )r
   r  r   r   r1   r  r	   re  )r'  r/  r   r(  r_  r  r  r  r   '  s   zaten::upsample_nearest1dupsample_nearest1dnearestzaten::upsample_nearest2dupsample_nearest2d   zaten::upsample_nearest3dupsample_nearest3d   zaten::upsample_linear1dupsample_linear1dry   zaten::upsample_bilinear2dupsample_bilinear2dzaten::upsample_trilinear3dupsample_trilinear3dinterpolate_modec                   s    fdd}|S )Nc                   sb   t | |\}}t  t |}|rt d|S |d u r(t | || }| jd||dS )Nzalign_corners == TrueUpsampler  )r
   _get_interpolate_attributes_interpolate_warningrJ  r6  _interpolate_size_to_scalesr#  )r'  r/  r  rT  scalesalign_cornersrA   r  r  r  r  r  g  s   

z!_interpolate.<locals>.symbolic_fnr  )r  rA   r  r  r  r  r  _interpolate<  s   +r  zaten::__interpolatec           	      C  s*   t | |||||\}}| jd|||dS )Nr  r  )r
    _interpolate_get_scales_and_moder#  )	r'  r/  r   scale_factorr(  r  recompute_scale_factor	antialiasr  r  r  r  __interpolatex  s   r  zaten::bitwise_notc                 C  "   t |std|| d|S NzOONNX export does NOT support exporting bitwise Not for non-boolean input valuesrz  r
   rO  r	   re  r#  r.  r  r  r  r$        
r$   zaten::bitwise_orc                 C  s:   t |std|t |std|| d||S )NzVONNX export does NOT support exporting bitwise OR for non-boolean input values. self: zWONNX export does NOT support exporting bitwise OR for non-boolean input values. other: Orr  rP  r  r  r  r%        

r%   c                   r  )Nc                   s   t   fdd}|S )Nc                   s,   t  d  } | || |d|| |dS )N_cast_F)r  )r'  r/  r@  to_cast_func)r  to_typer  r  wrap_with_cast  s   zGwrap_logical_op_with_cast_to.<locals>.decorator.<locals>.wrap_with_cast	functoolswraps)r  r  r
  )r  r  	decorator  s   z/wrap_logical_op_with_cast_to.<locals>.decoratorr  )r
  r  r  r  r  r    s   r  r  r   returnc                   s   t   fdd}|S )Nc                   s   |  d | ||S )Nrz  r-  r'  r/  r@  r  r  r  wrap_with_not  s   z4wrap_logical_op_with_negation.<locals>.wrap_with_notr  )r  r  r  r  r  r    s   r  zaten::__not_c                 C  r  r  r  r  r  r  r  __not_  r  r  zaten::eqc                 C  s   t | tjrt | tjr| jdtjdtjddS | }| }|	 |	   kr3dkr\n n'|
d|
d  krEdkr\n n| jdtj|d|dktjddS | d||S )	NrY  Trw  rZ  onnx::Constantr_  ra  r{  )r4  r  r   DeviceObjTyper#  r\  r   r  r  rt  kindOfra  )r'  r;  r@  	self_node
other_noder  r  r  rJ     s    
 $rJ   zaten::nec                 C  r  r  )rJ   rP  r  r  r  r     r  r   zaten::gtc                 C  r  r  _gt_implr  r  r  r  r^     r  r^   c                 C  J   t |rt |r| jd|tjjd}| jd|tjjd}| d||S )Nrh  ri  r  r
   rO  r#  rk  rl  INT32r  r  r  r  r       r  zaten::ltc                 C  r  r  _lt_implr  r  r  r  r     r  r   c                 C  r  )Nrh  ri  r  r  r  r  r  r  r!    r  r!  zaten::gec                 C  r  r  r   r  r  r  r  rY      r  rY   zaten::lec                 C  r  r  r  r  r  r  r  rq     r  rq   zaten::__and_c                 C  :   t |std|t |std|| d||S )NzOONNX export does NOT support exporting bitwise AND for non-boolean input valuesrN  r  r  r  r  r  __and_  r  r#  zaten::__or_c                 C  r"  )NzNONNX export does NOT support exporting bitwise OR for non-boolean input valuesr  r  r  r  r  r  __or_  r  r$  zaten::__xor_c                 C  r"  )NzOONNX export does NOT support exporting bitwise XOR for non-boolean input valuesry  r  r  r  r  r  __xor_0  r  r%  zaten::logical_andBoolc                 C  r  )NrN  r-  r  r  r  r  r   A  r<  r   zaten::logical_orc                 C  r  )Nr  r-  r  r  r  r  r   G  r<  r   zaten::logical_xorc                 C  r  )Nry  r-  r  r  r  r  r   M  r<  r   zaten::logical_notc                 C  s   |  d| j d|tjjdS )Nrz  rh  ri  r#  rk  rl  BOOLr.  r  r  r  r   S  s   r   zaten::__rshift_c                 C     t j|}t j|t jj|kr| jd|| d}| jdtjdtjdd}t	
|s7| jd|tjjd}| d||}| jd|| d}| d||}|S )	Nrh  ri  rY  r  rw  rZ  Powrg  r   rn  ro  rp  r#  rs  r\  r   float32r
   rq  rk  rl  rr  )r'  r;  r@  r  twotwo_powrshiftr  r  r  	__rshift_X  (   
r0  zaten::__lshift_c                 C  r)  )	Nrh  ri  rY  r  rw  rZ  r*  rE  r+  )r'  r;  r@  r  r-  r.  lshiftr  r  r  	__lshift_u  r1  r3  zaten::wherec              	   C  s`   t |s| jd|tjjd}|d u r(t| |}t | || jdt	dd|S | d|||S )Nrh  ri  rY  rD  rZ  r  )
r
   rO  r#  rk  rl  r(  r   _unbind_helperr\  r   )r'  	conditionr;  r@  r8  r  r  r  r    s   

r  zaten::log_softmaxc           	      C  s   t |}|d u rt ddS |dk r|| }||d k}|r>tt|}|d || ||< |d< | jd||d}|d }| jd||d	}|rd|  d
krdt |dd}| jd|t	
| d}|rn| jd||d}|S )NrA   fONNX and PyTorch use different strategies to split the input. Input rank must be known at export time.r   rD  r  r  r  
LogSoftmaxrH  r"  r  rx  rh  ri  )r
   r  r6  r5  r  r#  r  rt  r>  r   rn  rs  )	r'  r/  rA   rx  rv  rw  r  	return_oprx  r  r  r  r|     s.   
r|   zaten::_log_softmaxc                 C  s>   |rt j|t jjt jjkr| jd|tjjd}t	| ||S Nrh  ri  )
r   rn  ro  rp  HALFr#  rk  rl  rr  r|   )r'  r/  rA   half_to_floatr  r  r  _log_softmax  s   r<  zaten::_convolutionc                 C  s  t |}z|dd  }W n ty   d }Y nw |d u s&tdd |D r,td|||g}t |sAt |dkrA|| |dd  ||| ||	d}tdd |D rj|s\J t	|t	|ksfJ ||d< | j
|rpd	nd
g|R i |}t |st |dkr| 
d||S |S )Nr  c                 s  rz  r  r  r{  r  r  r  r    r|  z_convolution.<locals>.<genexpr>DUnsupported: ONNX export of convolution for kernel of unknown shape.rD  )r  r  r  dilations_igroup_ic                 s  s    | ]}|d kV  qdS r  r  )r  or  r  r  r  	  r|  output_padding_iConvTransposeConvrB  )r
   rX  r  r  r	   re  r%  r  r  rR  r#  )r'  r/  r   biasr  r  r  
transposedoutput_paddinggroups	benchmarkdeterministiccudnn_enabled
allow_tf32weight_sizekernel_shaperT  r  r(  r  r  r  _convolution  s@   



 rN  zaten::_convolution_modec                 C  s   t |}z|dd  }	W n ty   d }	Y nw |	d u s&tdd |	D r,td|||g}
t |sAt |dkrA|
| |dkrHd}n|dkrNd	}|dd  ||||d
}| j	dg|
R i |}t |syt |dkry| 	d||S |S )Nr  c                 s  rz  r  r  r{  r  r  r  r  2	  r|  z$_convolution_mode.<locals>.<genexpr>r=  rD  validVALIDsame
SAME_UPPER)r  r  
auto_pad_sr>  r?  rC  rB  )
r
   rX  r  r  r	   re  r%  r  r  r#  )r'  r/  r   rD  r  r  r  rG  rL  rM  rT  r  r(  r  r  r  _convolution_mode	  s@   


rT  zaten::convolutionc
           
      C  s"   t | |||||||||	d d d d S r  rN  )
r'  r/  r   rD  r  r  r  rE  rF  rG  r  r  r  r;   W	  s    r;   zaten::conv1dc           	      C  X   t |d}|dv rt| |||||||S t |d}t| ||||||dd|d d d d S Nra  )rO  rQ  r  Fr  r
   r  rT  rN  	r'  r/  r   rD  r  r  r  rG  str_paddingr  r  r  r7   w	  :   r7   zaten::conv2dc           	      C  rV  rW  rX  rY  r  r  r  r8   	  r[  r8   zaten::conv3dc           	      C  rV  rW  rX  rY  r  r  r  r9   	  r[  r9   zaten::conv_transpose1dc	           	      C  "   t | ||||||d||d d d d S NTrU  	r'  r/  r   rD  r  r  rF  rG  r  r  r  r  r4   	      r4   zaten::conv_transpose2dc	           	      C  r\  r]  rU  r^  r  r  r  r5   
  r_  r5   zaten::conv_transpose3dc	           	      C  r\  r]  rU  r^  r  r  r  r6   $
  r_  r6   zaten::batch_normc
                 C  s   t |d t r"t |||||gs"tjdk r"t dddd|S t | |||||\}}}}| j	d||||||d| |s@dndd	}
|sH|
S |
\}}}}}|
|  |
|  |d	|   |d	|   |S )
Nr"      BatchNormalizationr  zaAll input tensors must have the same `dtype`. Turn off Autocast or export using opset version 15.rD  r  )	epsilon_f
momentum_fr5  zbatch_norm_dead_output-)r
   check_training_moder\  is_autocast_enabledargs_have_same_dtyper   export_onnx_opset_versionrH  _batchnorm_helperr#  r$  r  setDebugName	debugName)r'  r/  r   rD  running_meanrunning_vartrainingmomentumepsrJ  rt  resnew_running_meannew_running_var
saved_mean	saved_varr  r  r  r"   C
  sJ   
	
r"   zaten::native_layer_normnormalized_shaper  r   rD  ro  #tuple[_C.Value, _C.Value, _C.Value]c              
   C  s  dd t t|ddD }t| d}t| |}| jdk r'| jd||d}	n| d|| jd	tj|tjd
d}	t	| ||	}
t
j|
t
jjk}|r^t
j|}| jd|
t
| d}
| jdk rp| jdt| |
||d}n| dt| |
|| jd	tj|tjd
d}t| | d||}| d|
|}|rt
j|}| jd|t
| d}|d u st|st| ||}|d u st|st| ||}|r| jd|t
| d}| d|}nt| |}||	|fS )Nc                 S  s   g | ]}| qS r  r  r{  r  r  r  r  
  s    z%native_layer_norm.<locals>.<listcomp>r   r         @   r  rT  rY  rw  rZ  rh  ri  rB  rg  r  )r  rR  r
   _generate_wrapped_numberr  r#  r\  r   longr   r   rn  ro  r:  rs  r   r   r%  r   r   r   )r'  r/  ru  r   rD  ro  r  two_csteps_cstr  	numeratoris_type_half	eps_dtypevariancedenominator
normalizedinput_dtyperdenominatorr  r  r  r   |
  s^   





r   zaten::layer_normcudnn_enablec           	      C  s   t | |||||\}}}|S r  )r   )	r'  r/  ru  r   rD  ro  r  r  r  r  r  r  rp   
  s   rp   zaten::instance_normuse_input_statsrn  r   rJ  c
                 C  s&  t |d t |d}
|d u st |r6|
d u rtd|tjdg|
 tj	
| d}| jd|d}|d u s?t |r`|
d u rItd|tjdg|
 tj	
| d}| jd|d}|d u srt |sr|d u srt |r|| jd	||||d
S t |}| }|d }|d u rtd||d }d|d< || |d< t| || jdtj|gtjdd}t| || jdtj|gtjdd}t| || jdtj|gtjdd}t| || jdtj|gtjdd}| d|| jdt|d}t| |||||||||	
}t| || jdt|dS )Nrj   rD  zCUnsupported: ONNX export of instance_norm for unknown channel size.rW  rw  rY  rZ  r  InstanceNormalizationrb  r   zJUnsupported: ONNX export of instance_norm training for unknown batch size.Reshape)r
   rd  r  r%  r	   re  r\  r   r   rn  ro  rx  r#  rX  copyr   r|  r  r"   r  )r'  r/  r   rD  rk  rl  r  rn  ro  rJ  channel_sizeweight_value
bias_value
input_sizeinput_size_reshaper(  cweight_bias_running_mean_running_var_input_reshapedrt  r  r  r  rj   
  s   
rj   zaten::unfoldc                   s   t }z|  }W n ty   d }Y nw |d uratd||}t||d |} fddt||D }	t|}
ttd|
   fdd|	D }j	dg|R d iS t 
dd	S )
Nr   rD  c              	     s*   g | ]\}}t j g|g|gd qS )rG  r
   rI  )r  lowhi)	dimensionr'  r/  r  r  r  J  s    zunfold.<locals>.<listcomp>c              
     s(   g | ]}t jd |d gqS )r  r  )r
   r  r#  r  )r  r'  r
  r  r  r  S  s    r2  r3  Unfoldr}  )r
   rX  r  r  r  rR  r5  r  popr#  r6  )r'  r/  r  r   stepr  sizedimlow_indices
hi_indicesr   r	  r  r  )r  r'  r/  r
  r  r   <  s,   
r   z	aten::eluc                 C  sJ   |r|dkrt dd|S |r|dkrt dd|S | jd|t |dS )NrW  r  zdoes not support scale in Eluinput_scalez#does not support input_scale in EluElurl  )r
   r6  r#  rI  )r'  r/  rL  r  r  r  r  r  rE   `  s   rE   z
aten::seluc                 C  r*  )NSelur-  r.  r  r  r  r   p  r  r   zaten::index_selectc                 C     t | |||S r  )r
   _select_helper)r'  r;  rA   ri   r  r  r  rh   v  s   rh   zaten::index_putc                 C  s\   t |rt |}n|g}t |d}t|dkr$|r"t| ||S |S t ddd| d S )Nr  r   rg   r  rC  )r
   r  r  r  rR  r   r  )r'  r;  indices_list_valuevalues
accumulateindices_listr  r  r  rg     s   
rg   zaten::index_fillc                 C  sH   t | |||\}}t |}t ||}t| ||d }t| ||||S r  )r
   _index_fill_reshape_helperrJ  r  rN   r   )r'  r;  rA   ri   r_  expanded_index_shapeexpanded_indexexpanded_valuer  r  r  rf     s   
rf   zaten::index_copyc                 C  s$   t | |||\}}t| ||||S r  )r
   r  r   )r'  r;  rA   ri   source_expanded_index_shaper  r  r  r  re     s   re   zaten::bucketizec                 C  s   t jj}|r
t jj}| jd| d|| d|dd}t|}|d us&J ttd|d }t	| t
| |||d }	|rDt| ||	}
nt| ||	}
| jd|
|d}tj| |dgddS )	Nr2  r,  r   rH  rD  rh  ri  rq  )rk  rl  rm  r  r#  r
   r  r5  r  rN   r  rY   r^   ru  )r'  r;  
boundaries	out_int32r  out_type	new_shapetensor_rankunsqueeze_axesexpanded_boundariescondcond_outr  r  r  r)     s$   "

r)   zaten::type_asc                 C  sP   t |}t |}||kr|d ur|S |d ur"| jd|| dS td|)Nrh  ri  zUnsupported: ONNX export of type_as for tensor of unknown dtype. Please check if the dtype of the parameter passed to the type_as function is correct.)r
   r  r#  rs  r	   re  )r'  r;  r@  
self_dtypeother_dtyper  r  r  r     s   

r   zaten::cosine_similarityc           	      C  s   t j| t| |||gdd}t j| t| |||gdd}t j| t| |||gdd}t| t| t| ||| jdt|gd}t| ||S )Nr   rq  rY  rZ  )	r
   ru  r   r   r   r#  r\  r   rB   )	r'  x1x2rA   ro  r>   x1_l2x2_l2div_tensr  r  r  r=     s   &r=   zaten::pairwise_distancec                 C  s   t |s| jdt|gd}t| | jdtjdgtjddt| ||}t j| t	| t
| |||dgt |dd}t	| ||S )NrY  rZ  rD  rw  r  r  rq  )r
   rF  r#  r\  r   rB   r  r   ru  r   r   r  )r'  input1input2pro  r  inv_p	summationr  r  r  r     s   


r   zaten::clonec                 C  r  r  r  )r'  r/  unused_memory_formatr  r  r  r0        r0   z	aten::absc                 C  r*  )NAbsr-  r  r  r  r  r     r1  r   z	aten::logc                 C  r*  )NLogr-  r  r  r  r  r}     r1  r}   zaten::log1pc              	   C  s    t | t| ttd||S )NrD  )r}   r   r
   r  r\  r   r  r  r  r  r         r   zaten::log10c              	   C  s*   d}|  dt| || j dt|gdS )NgUk@rg  rY  rZ  r#  r}   r\  r   )r'  r;  _ln10r  r  r  r~     s   &r~   z	aten::powc                 C  sb   t j|}t|st jj}| jd|| d}t|s(| jd|| d}| d||}|S )Nrh  ri  r*  )r   rn  ro  r
   rq  rr  r#  rs  )r'  r;  exponentf_dtyper   r  r  r  r     s   

r   zaten::clampc              	   C  sz   t |rt| ||S t |rt| ||S t |r3t |r3t j| d|t |dt |dddS t| t| |||S )NCliprV     min_fmax_fr`  )r
   r%  r-   r.   r  rb  r  )r'  r;  r   r   r  r  r  r/   ,  s   



	r/   zaten::clamp_minc                 C  Z   t |rt j| d|t |dddS tj|}| jd|| d}t j| d||ddS )	Nr  rV  r  )r  r`  rh  ri  Maxr_  	r
   r  rb  r  r   rn  ro  r#  rs  )r'  r;  r   rx  r  r  r  r.   B     

r.   zaten::clamp_maxc                 C  r  )	Nr  rV  r  )r  r`  rh  ri  Minr_  r  )r'  r;  r   rx  r  r  r  r-   Q  r  r-   z	aten::maxc                 C  r  r  )r
   _max_helperr'  r;  dim_or_yr  r  r  r  r   `  s   r   zaten::maximumc                 C     t | ||dS N)r  )r   r  r  r  r  r   h  r<  r   z	aten::minc                 C  r  r  )r
   _min_helperr  r  r  r  r   n  s   r   zaten::minimumc                 C  r  r  )r   r  r  r  r  r   t  r<  r   z
aten::amaxc                 C     | j d|||dS )Nrp  rq  r-  r'  r;  rA   r  r  r  r  r   z     r   z
aten::aminc                 C  r  )N	ReduceMinrq  r-  r  r  r  r  r     r  r   zaten::aminmaxc                 C  sR   d|i}t |st |dd}|g|d< | jd|fi || jd|fi |fS )Nrr  r  rA   r  r  rp  )r
   r%  r>  r#  )r'  r;  rA   r  reduce_kwargsr  r  r  r     s   

r   z	aten::expc                 C  r*  )Nrs  r-  r  r  r  r  rL     r1  rL   zaten::dropout_zaten::dropoutc                 C  s.   t |d |s
|S | jd||dd\}}|S )NrD   Dropoutr  )ratio_fr5  )r
   rd  r#  )r'  r/  r  trainr  r  r  r  r  rD     s
   rD   zaten::alpha_dropout_zaten::feature_alpha_dropout_zaten::feature_dropout_zaten::feature_alpha_dropoutzaten::alpha_dropoutzaten::feature_dropoutc                   s   t ddd fdd}|S )NrU  r  r  c                   s   |r	t  d|S |S )Nztraining mode)r
   r6  )r'  r/  r  r  r  r  r  feature_dropout  s   z-_unsupported_dropout.<locals>.feature_dropoutr
   r  )r  r  r  r  r  _unsupported_dropout  s   r  z
aten::normc                 C  sx   |dkr
t d}n|dkrt d}ntd||| |||d}|d ur:t |dd}| jd	|t| d
}|S )NrD  ReduceL1r  ReduceL2z)ONNX export only p-norms with p of 1 or 2)rA   r  r  rx  rh  ri  )	r
   _reduce_op_symbolic_helperr	   re  r>  r#  r   rn  rs  )r'  r;  r  rA   r  rx  rV  r  r  r  r  r     s   r   zaten::conv_tbcc              	   C  sX   | j d|g dd}| j d|g dd}t| |||dg|gdgd}| j d|g ddS )Nr  )rD  r  r   r  )r  rD  r   rD  )r  r   rD  )r#  r7   )r'  r/  r   rD  r   convr  r  r  r3     s   r3   zaten::_uniquec                 C  r  )N_uniquer  )r'  r/  sortedreturn_inverser  r  r  r    r  r  zaten::_unique2c                 C  r  )N_unique2r  rC  r  )r'  r/  r  r  return_countsr  r  r  r    r  r  zaten::_cast_Bytez8Avoid using this function and create a Cast node insteadc                 C     | j d|tjjdS r9  )r#  rk  rl  r  r'  r/  non_blockingr  r  r  
_cast_Byte  r  r  zaten::_cast_Charc                 C  r  r9  )r#  rk  rl  r  r  r  r  r  
_cast_Char  r  r  zaten::_cast_Shortc                 C  r  r9  )r#  rk  rl  r  r  r  r  r  _cast_Short  r  r  zaten::_cast_Intc                 C  r  r9  )r#  rk  rl  r  r  r  r  r  	_cast_Int  r  r  zaten::_cast_Longc                 C  r  r9  )r#  rk  rl  rm  r  r  r  r  
_cast_Long  r  r  zaten::_cast_Halfc                 C  r  r9  )r#  rk  rl  FLOAT16r  r  r  r  
_cast_Half  r  r  zaten::_cast_Floatc                 C  r  r9  )r#  rk  rl  rr  r  r  r  r  _cast_Float  r  r  zaten::_cast_Doublec                 C  r  r9  )r#  rk  rl  r  r  r  r  r  _cast_Double   r  r  zaten::_cast_Boolc                 C  r  r9  r'  r  r  r  r  
_cast_Bool&  r  r  zaten::emptyc                 C     t | |||||S r  )r  )r'  r  rx  layoutdevice
pin_memorymemory_formatr  r  r  rI   ,     rI   zaten::empty_likec                 C  r  r  )r  )r'  r/  rx  r  r   r  r  r  r  r  rH   :  r  rH   zaten::new_emptyc                 C  2   t |}t |r|d ur|}t| |||||S r  )r
   r  r%  rI   r'  r;  r  rx  r  r   r  r  r  r  r  r   H     
r   zaten::scalar_tensorc                 G  s<   t |dd}|d u rtjj}| jd|t| d}|S )Nr  rx  rh  ri  )r
   r>  r   rn  rr  r#  rs  )r'  scalarrx  optionsr  r  r  r   R  s
   r   zaten::tensorc                 C  s  t |dd}t |rU|d u rtjt |d }g }t |D ]&}| jdt	dgd}t 
| ||}| jd|t| d}|| q"| jd	g|R d
diS |d u r_tj|}t |rwt |snt |rw| jd|ddd}| jd|t| dS )Nr  rx  r   rY  rD  rZ  rh  ri  r2  r3  ConcatFromSequence)r3  
new_axis_i)r
   r>  r  r   rn  ro  r  r#  r\  r  r9  rs  r  _is_listrG  _is_scalar_list)r'  datarx  r   requires_gradr  r   shape_referencer  r  r  r   [  s,   

r   zaten::as_tensorc                 C     t | |||S r  )r   )r'  r  rx  r   r  r  r  r   w  r  r   zaten::zerosc                 C  sz   |d u r	t jj}nt |}t|d}t|tr-t|dkr-| jdt	
g t	jd}| jd|t	j
dg| ddS )Nr  r   rY  rZ  ConstantOfShaperw  r   rn  rr  r
   r  r4  r5  rR  r#  r\  r   r   r|  rx  r'  r  rx  r  r   r  ru  sizes_r  r  r  r  |  s   

r  zaten::zeros_likec           	      C  T   |  d|}t|rtj|tjj}nt|}| j d|tjdg|	 ddS )Nr,  r  r   rw  rZ  
r#  r
   r%  r   rn  ro  rr  r\  r   rx  	r'  r/  rx  r  r   r  r  r6  ru  r  r  r  r       

r  zaten::new_zerosc                 C  r  r  )r
   r  r%  r  r  r  r  r  r     s   
r   z
aten::zeroc                 C  s   t |}t| ||S r  )r
   r  r  )r'  r;  r  r  r  r  r    s   
r  z
aten::onesc                 C  sz   |d u r	t jj}nt |}t|d}t|tr-t|dkr-| jdt	
g t	jd}| jd|t	j
dg| ddS )Nr  r   rY  rZ  r  rD  rw  r  r  r  r  r  r     s   

r   zaten::ones_likec           	      C  r  )Nr,  r  rD  rw  rZ  r  r  r  r  r  r     r  r   zaten::new_onesc                 C  r  r  )r
   r  r%  r   r  r  r  r  r     r  r   z
aten::fullc              	   C  s   t |d}t |r,|d u rtjjn|}t| ||||}t| ||| jdt	
ddS t |dd}|d u r<tjj}	nt|}	t |d}
t|
tr`t|
dkr`| jdt	
g t	jd}| jd	||d|	 dS )
Nr   rY  rD  rZ  r  rx  r  r   r  )r
   r  rF  r   rn  rr  r  r   r#  r\  r   r>  r4  r5  rR  r   r|  r  rx  )r'  r  r_  rx  r  r   r  const_valuetmpru  r  r  r  r  rW     s"   


rW   zaten::full_likec              	   C  s   t |d}t |dd}|d u rtj|tjj}nt|}t |rFt| ||||}	| j	d||
 d}t| |	|| j	dtddS | 	d	|}
| j	d
|
tj|g| ddS )NrV  r  rx  rh  ri  rY  rD  rZ  r,  r  rw  )r
   r  r>  r   rn  ro  rr  rF  r  r#  rs  r   r\  r   rx  )r'  r/  
fill_valuerx  r  r   r  r  ru  r  r6  r  r  r  rV     s"   

rV   zaten::new_fullc           	      C  s4   t |}t |r|d ur|}t| ||||||S r  )r
   r  r%  rW   )	r'  r;  r   r  rx  r  r   r  r  r  r  r  r   %  s   
r   	aten::eyec                 G  s   t |dkr,|\}}}}}t| |dg}| jd||dd}t| ||||}	| d|	S t |dkr]|\}}
}}}}| jdt| |dgt| |
dgdd}t| ||||}	| d|	S tddt | d	S )
Nr  r   r2  rH  EyeLikerc  r  with 
 arguments)rR  r
   r  r#  r  r6  )r'  rT  r(  rx  r  r   _pin_memoryrV  r6  r   mr  r  r  rO   6  s"   rO   aten::slicec                 G  s  t |dkr|\}}}}t|d}|dkrtd||  dko+t| t	j
}|  dko;t| t	j
}|  dk}	|  dk}
|sP|	r\|sT|
r\|  dkrtjtjjkritd|t| |dg}t| |dg}t| |dg}| d	||||S |rdnt|d}|rtjnt|d}t|d}tj| ||g|g|gd
S t |dkr|\}}}d}|  dkot| t	j
}|  dkot| t	j
}|rdnt|d}|rtjnt|d}tj| ||g|g|gd
S tddt | dS )Nr  r  rD  z"step!=1 is currently not supportedr"  r  zUnsupported: ONNX export of Slice with dynamic inputs. DynamicSlice is a deprecated experimental op. Please use statically allocated variables or export to a higher opset version.r   DynamicSlicerG  r  r"  r  r  )rR  r
   r  r	   re  r  rt  r4  r  r   NoneTyper   operator_export_typerk  OperatorExportTypesONNXr  r#  r   r  rI  r6  )r'  r;  rT  rA   r  r  r  is_start_noneis_end_noneis_start_onnx_constis_end_onnx_conststart_unsqueezedend_unsqueezeddim_unsqueezedr  r  r  r   N  s   






r   zaten::hardtanhr;  min_valmax_valc                 C  s   t j| d|||ddS )Nr  r  r  ra  )r'  r;  r/  r0  r  r  r  rc     s   rc   zaten::hardswishc                 C  s   t | |}| d||S rL  )ra   r#  )r'  r;  hsr  r  r  rb     s   
rb   zaten::hardsigmoidc                 C  s   | j d|ddS )NHardSigmoidgUUUUUU?rl  r-  r  r  r  r  ra     s   ra   zaten::tanhshrinkc                 C  s   |  d|t| |S )NrM  )r#  r   r  r  r  r  r     r  r   zaten::hardshrinkc                 C  sx   t j|t jj}| jdtj|| dd}t| t	| ||t
| |t| |}| d||| jdtjd| ddS NrY  rw  rZ  r  r   )r   rn  ro  rr  r#  r\  r   rx  r   r^   r   r   )r'  r;  lambdru  lambd_opr  r  r  r  r`     s"   "r`   zaten::softshrinkc           	      C  s   t j|t jj}| jdtj|| dd}t| ||}| d|t	| ||| jdtjd| dd}t
| |t| |}| d|t| ||| jdtjd| dd}t| ||S r3  )r   rn  ro  rr  r#  r\  r   rx  r^   r   r   r   r   )	r'  r;  r4  ru  r5  gt_condgt_outlt_condlt_outr  r  r  r     s8   
	
	r   zaten::aliasc                 C  r  r  r  r  r  r  r  r     r  r   zaten::unsqueezec                 C  s~   |dk r6t |}|dur/tdt| d d d t|| d  d d	  || d }nt d
d|S t j| ||gdS )zbImplement unsqueezing a pytorch tensor in ONNX by inserting a new dimension at the specified `dim`r   Nz)ONNX export unsqueeze with negative axis rN  rO  rP  rD  rQ  rR  r  rS  rT  )r
   r  r  r  r  r6  r  r-  r  r  r  r    s2   

r  z
aten::sortc                 C  sn   |d urt dd| t |}z|| }W n ty!   d }Y nw |d u r-t dd|S | jd|||ddS )NSortz'Out parameter is not supported for sortr}  TopKr  k_ir3  r5  )r
   r6  rX  r  r#  )r'  r;  rA   	decendingrt  
self_sizesrV  r  r  r  r     s   
r   zaten::numelc                 C  s   t | |S r  )r
   _numel_helperr  r  r  r  r   %  r1  r   z
aten::topkc                 C  s<   |d urt dd| |st dd| | jd|||ddS )Nr;  z'Out parameter is not supported for topkzAscending TopK is not supportedr  r<  )r
   r6  r#  )r'  r;  r  rA   largestr  rt  r  r  r  r   *  s   r   zprim::convert_element_typec                 G  s,   t |d dd}| jd|t| dS )Nr   r  rx  rh  ri  )r
   r>  r#  r   rn  rs  )r'  r;  rT  rx  r  r  r  r:   8  s   r:   zaten::toc                 G  s  dd }||r
|S t |dkrq|d }t|d rG|d   dkrGt|d  d}t|tjrGt |j	dkrE|
 }t|}n|}t|sRt|tjrdtj|d }| jd|| dS | jd|t| dS t |d	krt|d
 dd}| jd|t| dS t |dkrt|d dd}| jd|t| dS t |dkrt|d dd}| jd|t| dS td|S )Nc                 S  s   t | dkr&| d   dkp%| d  tj p%t| d  tj	S t | dkr9t
| d dd}|d u S t | dv rLt
| d dd}|d u S d	S )
Nr  r   prim::devicer  rD  r  rx  )rc     F)rR  r  rt  r  isSubtypeOfr   ListTypeofIntsr4  r  r
   r>  )rT  rx  r  r  r  is_aten_to_device_only@  s   z"to.<locals>.is_aten_to_device_onlyr  r   r  r_  rh  ri  r  rD  r  rx  rc  rC  zUnknown aten::to signature)rR  r
   rF  r  rt  r=  r4  r\  r  r6  rn   r  r   rn  ro  r#  rs  r>  r  )r'  r;  rT  rG  rx  tvalr  r  r  r   >  s@   
r   zaten::repeatc                 C  s0   t jj}t| ||}| d||}| d||S )Nr  Tile)r   rn  rm  r   r#  )r'  r;  repeatsrx  shape_r  r  r  r     s   r   zaten::repeat_interleavec              
   C  s  t |}t |}t |}|d u rtd||d u r#td||d u r-td|t |rKt | || jdt	dgd}tj	dtj
d}nt |}|dk rZ|t|7 }| }t|D ]\}	}
|
d u rrd	\||	< ||	< qb|dks|d
kr|d d
kr|| dkrt dddd|S t | |||S |d
kr|| dkrt dddd|S |d d u rt dddd|S |d || ksJ d|d }ntd|g }t | ||d}t | |||}d\||< ||< t|D ]X\}	}t| ||	 |d
 }| jdt|d |d
  d|| jdt||d
 d  dg}| jdg|R ddi}t| ||d }t j| || jdt|ddd}|| q| jdg|R d|iS )NzGUnsupported: ONNX export of repeat_interleave for unknown repeats rank.zGUnsupported: ONNX export of repeat_interleave for unknown repeats size.zEUnsupported: ONNX export of repeat_interleave for unknown input size.rY  r  rZ  r   rw  )r   r  rD  r   r     z3Unsupported along dimension with unknown input sizez*Unsupported for cases with dynamic repeatsz2repeats must have the same size as input along dimz%repeats must be 0-dim or 1-dim tensor)r  rD  r2  r3  	allowzero)r
   r  rX  r	   re  r%  r9  r#  r\  r   r|  rJ  rR  r  	enumeraterH  -_repeat_interleave_single_value_repeat_helper_repeat_interleave_split_helperr  r  rN   r  )r'  r;  rJ  rA   r  repeats_dimrepeats_sizesinput_sizesinput_sizes_tempr  r  repsfinal_splitsr_splitsi_splitsr_spliti_splitr_concatr  r  r  r     s   





r   zaten::pixel_shufflec           	      C  s  t |}t|dkrt dd|S tdd |dd  D rvt j| t | |ddg| jd	t	d
d||d
d
gdd
d}| jd|g dd}t j| || jd	t	g ddd
d}t j| || jd	t	g ddd
d}t 
| |ddgS |d | | }t j| || jd	t	d||||d |d gdd
d}| jd|g dd}t j| || jd	t	d||d | |d | gdd
dS )Nr  r   only support 4d inputc                 s  rz  r  r  r{  r  r  r  r    r|  z pixel_shuffle.<locals>.<genexpr>rD  r  r  rY  r   r  rZ  rM  r  )r   rD  r  r  r  r  r  )r   r   r  rD  r   r   )r   r   r   r   r  rD  r  r
   rX  rR  r6  r  r9  r  r#  r\  r   rE  )	r'  r;  upscale_factorr  
after_viewafter_transpose	reshape_h	reshape_woutput_channelr  r  r  r     s~   
	

r   zaten::pixel_unshufflec           
      C  s  t |}t|dkrt dd|S tdd |dd  D rxt j| t | |dg| jdt	d	d	d
|d	gdd	d}t j| || jdt	d	d	d	d	d
|gdd	d}| jd|g dd}t j| || jdt	g ddd	d}t 
| |ddgS |d | | }t j| || jdt	d
|d |d | ||d | |gdd	d}	| jd|	g dd}t j| || jdt	d
||d | |d | gdd	dS )Nr  r   r]  c                 s  rz  r  r  r{  r  r  r  r  I  r|  z"pixel_unshuffle.<locals>.<genexpr>rD  r  rY  r   r  rZ  rM  r  )r   rD  r  r  r  r  r  )r   r  rD  rD  r   r   r  r^  )
r'  r;  downscale_factorr  rb  rc  ra  final_reshaperd  r`  r  r  r  r   A  sx   




r   c           *   
     s  t d d d d d  g d}ttdd |D |}|r#d	nd
dkr<t  d|	  kr<tdd|S t  d|	  ksJJ  fddtdt D |
rfjd|g dd}|rq|rqtdd|S 	dr|d	d  
  }d d }t|dd u rtdd|S |	 }|}g }dksdkr|}n
dkr|\}}g }|d u rtn|}dkrg dndkrg ddd fdd}fdd}fd d!}tD ]-}|rd	kr||\}}}n
||\}}t}||d f}nUd	kr:|d
| \}} }!|d
| d \}"}#}$jd"|!|$dd#}n|d
| \}} |d
| d \}"}#t}jd"||"dd#}jd"| |#dd#}d
| d
| d
 f}|||||g}%|%||g|R   dkr|%||g|R   |ri nd$d%i}&dkr|	r||g}'n|g}'jdg|%R d
|'d&|&\}}(n/dkr҈jdg|%R d
dd'|&\}}(ndkrjdg|%R d(d)|&\}}(})|	r
jd|g d*d}tj|jd+tg d,d-dd.}nt|dg}||( dkr!||) q|
r/jd|g dd}dkr6|(njd"g|R d/di}dksLdkrP||fS dkrmdkr\|)njd"g|R d/di}|||fS d S )0NzVExporting a model to ONNX with a batch_size other than 1, with a variable length with z can cause an error z9when running the ONNX model with a different batch size. z4Make sure to save the model with a batch size of 1, z=or define the initial states (h0/c0) as inputs of the model. )r]  r  r  Affinerk  ThresholdedRelu
ScaledTanhr2  r  Softsignr\  c                 S  s   g | ]}|  qS r  )lower)r  act_funr  r  r  r    r  z _generic_rnn.<locals>.<listcomp>r  r  LSTMrD  zLSTMs with projectionsc                   s   g | ]
} ||  qS r  r  r{  )all_weightsweights_per_layerr  r  r    r  r   r  r  r  zRNN/GRU/LSTMzdropout in training modeRNNzunknown hidden sizeGRU))rD  r  r   rD  )r  r  )rr  )r  r  )rD  r  c                   s.    fdd|D } j dg|R ddiS )Nc              	     s2   g | ]\}}t j d g| g| gdqS )r   rG  r  )r  xyr'  r(  wr  r  r    s     z8_generic_rnn.<locals>.reform_weights.<locals>.<listcomp>r2  r3  r   r-  )r'  rv  r(  	intervalsslicesr  ru  r  reform_weights  s   z$_generic_rnn.<locals>.reform_weightsc                   s`   |  }dkr|\}}ndksdkr# fdd|D \}}t  fdd||fD S )Nrp  rq  rm  c                 3      | ]
} |V  qd S r  r  r  rv  r'  hidden_sizereform_permutationry  r  r  r        
zB_generic_rnn.<locals>.transform_weights_no_bias.<locals>.<genexpr>c                 3       | ]}t  |d gV  qdS r  r  r  rs  r'  r  r  r    
    
)r  )layer_indexweights	weight_ih	weight_hhr'  r}  layer_weightsr~  ry  variantr  r  transform_weights_no_bias  s   

z/_generic_rnn.<locals>.transform_weights_no_biasc                   s|   |  }dkr|\}}}}ndksdkr' fdd|D \}}}} j d||dd}t fd	d|||fD S )
Nrp  rq  rm  c                 3  rz  r  r  r{  r|  r  r  r    r  z:_generic_rnn.<locals>.transform_weights.<locals>.<genexpr>r2  r   rH  c                 3  r  r  r  r  r  r  r  r    r  )r#  r  )r  r  r  r  bias_ihbias_hhbias_concatr  r  r  transform_weights  s   z'_generic_rnn.<locals>.transform_weightsc                   s&   dkr| S t j | dg|g|gdS )NrD  r   rG  r  )rs  r  r  )r'  
num_layersr  r  retrieve_state  s   z$_generic_rnn.<locals>.retrieve_stater2  rH  direction_sbidirectional)r5  hidden_size_iactivations_s)r5  r  linear_before_reset_ir  )r5  r  )r   r  rD  r  rY  )r   r   r  rZ  rM  r3  )r  r  dictr  rR  r
   r6  r  r#  
startswithrk  r  r  r  r9  r\  r  rE  )*r'  r  r/  initial_statesrn  
has_biasesr  rD   r  r  batch_firstbatch_sizesonnxActivationsvariantToOnnxActivationMapnonlinearityw_hhunidirectionalprev_outputh_outsh0c0c_outssequence_lensr  r  r  r  r  r  r  state_indicesweight_ih_fweight_hh_fbias_fweight_ih_bweight_hh_bbias_binputsextra_kwargs
activationh_outc_outr  )	rn  r'  r}  r  r  r~  ry  r  ro  r  _generic_rnn  s  


	









&
&
r  c
                 C  s2   t |t |}
}t| d||
|||||||	S )Nrm  r
   r  r  )r'  r/  hidden_vweight_vr  r  rD   r  r  r  hiddenr   r  r  r  
_lstm_fullh  s    r  c
                 C  s4   t |t |}
}t| d||
||||||	|dS )Nrm  r  r  )r'  r/  r  r  r  r  r  rD   r  r  r  r   r  r  r  _lstm_packed  s    r  z
aten::lstmc                 G  s.   t |d rt| g|R  S t| g|R  S Nr  )r
   rG  r  r  r'  rT  r  r  r  r     s   r   zaten::lstm_cellc                   s   t  |dg}t |} fdd|D }t |r!||||fn||f}t |r,dnd}	t d||||	dddddd\}
}}t  |dgt  |dgfS )	Nr   c                   s   g | ]
}t  |d gqS r  r  r  r  r  r  r    r  zlstm_cell.<locals>.<listcomp>TFrm  rD  )r  rD   r  r  r  )r
   r  r  
_is_tensorr  rE  )r'  r;  r  w_ihr  b_ihb_hhr/  r   r  r  r  r  r  r  r  r     s0   
r   z	aten::grurq  gruzaten::rnn_tanhRNN_TANHrnn_tanhzaten::rnn_reluRNN_RELUrnn_relurt  c                   s^   t ddddddddd	fdd t ddddddddd	fdd fdd	}|S )
NrU  r  rV  c
                   s&   t |}
t|  |||
||||||	S r  r  )r'  r/  r  r  r  r  rD   r  r  r  r   rt  r  r  	_rnn_full  s   
z"_one_hidden_rnn.<locals>._rnn_fullc
                   s(   t |}
t|  |||
|||||	|dS )Nr  r  )r'  r/  r  r  r  r  r  rD   r  r  r   r  r  r  _rnn_packed  s   
z$_one_hidden_rnn.<locals>._rnn_packedc                   s.   t |d r| g|R  S  | g|R  S r  )r
   rG  r  )r  r  r  r  symbolic  s   z!_one_hidden_rnn.<locals>.symbolicr  )rt  r  r  )r  r  rt  r  _one_hidden_rnn  s   r  zaten::_dim_arangec                 C  s@   |  d|}| j d|| j dt|ddd}t| |dd d d S )Nr,  r  rY  rZ  r   rH  r  )r#  r\  r   r   )r'  likerA   
like_shapestopr  r  r  _dim_arange  s
   r  zaten::detachc                 C  r  r  r  r.  r  r  r  r@   #  r  r@   zaten::contiguousc                 C  s   |dkr
t d||S )Nr  z-onnx memory_format support is not implemented)r	   re  )r'  r/  r  r  r  r  r2   )  s
   r2   zaten::_pack_padded_sequencec                 C  sz   |r| j d|g dd}| tjj std|t	j
|t	j
jt	j
jkr4| j d|tjjd}| j d||dd	S )
Nr  r  r  z*'lengths' must be a Tensor for ONNX exportrh  ri  zprim::PackPaddedr  r5  )r#  r  rD  r\  r   
TensorTypegetr	   re  r   rn  ro  rp  r  rk  rl  r  )r'  r/  lengthsr  r  r  r  _pack_padded_sequence3  s   r  zaten::_pad_packed_sequencec                 C  s6   | j d||dd\}}|r| j d|g dd}||fS )Nzprim::PadPackedr  r  r  r  r  r-  )r'  r  r  r  padding_valuetotal_lengthr  r  r  r  _pad_packed_sequenceL  s   r  zaten::randintc                 G  s  t |dd}t |dd}t |dd}|d u rtjj}nt|}|d u r-t d||d u r7t d|t |d}	t |	r[| jd|t	j
dgt	jd	d
}
| jd|
||d}n	| jd|	||d}tjj}| jd|| d}||kr| jd|| d}|S )Nr  rx  r  highr   r  r  r   rw  rZ  RandomUniformLikelow_fhigh_fRandomUniform)shape_ir  r  rh  ri  )r
   r>  r   rn  rm  r  r  rF  r#  r\  r   r  rs  )r'  r  r  shapesrx  r  low_ihigh_iru  r6  shape_constr   	int_dtyper   r  r  r  r   _  sD   


r   zaten::randint_likec                 G  s   t |dd}t |dd}t |dd}|d u rtjj}nt|}|d u r-t d||d u r7t d|| jd|||d}	tjj}
| jd|	|
 d	}|
|kr\| jd|| d	}|S )
Nr  rx  r  r  r   r  r  rh  ri  )r
   r>  r   rn  rm  r  r#  rs  )r'  r;  r  r  rx  r  r  r  ru  r   r  r   r  r  r  r     s*   

r   zaten::randnc                 G     t |dd}|d u rtjj}nt|}t |d}t |r9| jd|tj	dgtj
dd}| jd|| d	S | jd
|| dS )Nr  rx  r  r  r   rw  rZ  RandomNormalLikedtype_iRandomNormalr  r  r
   r>  r   rn  rr  r  rF  r#  r\  r   r  rs  r'  r  rx  r  ru  r6  r  r  r  r  r     *   


r   z
aten::randc                 G  r  )Nr  rx  r  r  r   rw  rZ  r  r  r  r  r  r  r  r  r  r     r  r   zaten::randn_likec                 C  sH   t |dd}|d u rtj|tjj}nt|}| jd|| dS )Nr  rx  r  r  r
   r>  r   rn  ro  rr  r#  rs  )r'  r;  rx  r  r   r  r  ru  r  r  r  r     s   

r   zaten::rand_likec                 C  sB   t |dd}|d u rtj|tjj}| jd|t| dS )Nr  rx  r  r  r  )r'  r;  rx  r  r   r  r  r  r  r  r     s   
r   zaten::rreluc                 C  s@   |s|| d }| j d||dS | j d|||d}|  d||S )Nrw  rk  rl  r  )r  r  rW  r-  )r'  r/  rk  upperrm  r  r  r  r  r  r  r     s
   r   zaten::bernoullic           	      C  s   |d urt |st dd| |d ur t |s t dd| tj|tjj}|tjjkr6t dd|S | jd|dd| d}|d urMt |sM|n|}| d	||}| jd
|| dS )N	Bernoulliz,out parameter is not supported for bernoulliz(generator is not supported for bernoulliinput dtype not accessibler  rW  r  )r  r  r  r  rh  ri  )	r
   r%  r6  r   rn  ro  rp  r#  rs  )	r'  r/  r  r  rt  rx  randsprobr  r  r  r  r#     s2   r#   zaten::log_sigmoidc                 C     |  d|}|  d|S )Nr  r  r-  )r'  r/  r  r  r  r  r{   ,  rA  r{   z	aten::erfc                 C  r*  )NErfr-  r.  r  r  r  rK   3  r  rK   zaten::flattenc                 C  s   t |}|d u rt dd|S |dkrt | |dgS |dkr&| d|S |dk r.|| }|dkr@||d kr@| jd||dS |dkrT||d krT| jd||d dS t | ||||S )	NrA   r6  r   rD  r  FlattenrH  r  )r
   r  r6  r9  r#  _flatten_helper)r'  r/  	start_dimend_dimrA   r  r  r  rQ   9  s$   
rQ   zaten::nonzeroc                 C  s   t | | d|S )z/Emitted from `torch.nonzero(x, as_tuple=False)`NonZero)r   r#  r.  r  r  r  r   V  r  r   zaten::nonzero_numpyc                 C  s   t | t| |d|dS )NrD  )r8  )r   r   )r'  r/  r8  r  r  r  r   ]  s   r   zaten::isnanc                 C  s   |  d|}|S )NIsNaNr-  )r'  r/  r  r  r  r  rm   c  s   rm   z	aten::anyc              	   G  s   t |dkr|d }d\}}n|\}}}t|d}dd |dD }t|d}| jd	|tjjd
}tj| |||d}t	| || jdt
jdt
jddS )NrD  r   rQ  r   c                 S  s   g | ]}t |qS r  r  )r  r  r  r  r  r  u  r  z_any.<locals>.<listcomp>r  r  rh  ri  rq  rY  rw  rZ  )rR  r
   r  r  r#  rk  rl  rm  ru  r^   r\  r   rz  )r'  rT  r/  rA   r  	input_sumr  r  r  _anyj  s   

"r  z	aten::allc              	   G  sL   |  d|d }t|dkr|  dt| |S |  dt| ||d |d S )Nrz  r   rD  r  )r#  rR  r  )r'  rT  r/  r  r  r  _all~  s   r  zaten::narrowc                 C  s   t j| ||g|g|| gdS )NrG  r  )r'  r/  rA   r  lengthr  r  r  r     s   r   zaten::argmaxtorch._C.Valuer  c                 C     t | |||dS )NArgMaxr
   _argmin_argmax_helperr'  r/  rA   r  r  r  r  r        r   zaten::argminc                 C  r   )NArgMinr  r  r  r  r  r     r  r   zaten::scatterc                 C  s~   t j|t jj}t|}t|r| jd||||dS t j|}||kr1| jd|| d}| jd||t	| |||dS )NScatterrH  rh  ri  )
r   rn  ro  rp  r
   rJ  rF  r#  rs  rM   )r'  r;  rA   ri   srcsrc_typer  r  r  r  r     s   

r   zaten::scatter_addc                 C  sz   t |}|d u rt dd|S t j|dd}|r(| jdtj|| dd}nt| ||}t 	| ||||}t
| ||S )Nr   r  F)allow_nonstaticrY  rw  rZ  )r
   r  r6  rX  r#  r\  r  rx  r  _scatter_helperr   )r'  r;  rA   ri   r  ru  r  to_addr  r  r  r     s   
r   z
aten::log2c              	   C  s(   d}|  dt| || j dt|dS )Ng9B.?rg  rY  rZ  r  )r'  r;  _ln2r  r  r  r     s   $r   zaten::is_floating_pointc                 C  s6   t |r| jdtdgdS | jdtdgdS NrY  rD  rZ  r   )r
   rq  r#  r\  
BoolTensorr  r  r  r  rk     s   
rk   zaten::__is_c                 C  sL   t |r t |r| jdtdgdS | jdtdgdS t| ||S r  )r
   r%  r#  r\  r  rJ   rP  r  r  r  __is_  s
   

r  zaten::__isnot_c                 C  r  r  )r  rP  r  r  r  __isnot_  r  r  zaten::one_hotc                 C  sn   | j dtddgd}tj|tjjtjjtjjtjj	tjj
hv r-| j d|tjjd}| j d|||dd	S )
NrY  r   rD  rZ  rh  ri  OneHotr  rH  )r#  r\  r  r   rn  ro  rp  r  r  r  r  rk  rl  rm  )r'  r;  num_classesr  r  r  r  r     s   r   zaten::gatherc           	   	   C  s   t |drt dd|S tj|}| jdtddgd}t	| || jdt|gd}| jd| jd	||||d
|
 d}| dt | ||d g|}t j| ||gddS )Nr  rX   zsparse_grad == TruerY  r   rD  rZ  rh  r  rH  ri  rE  rq  )r
   r  r6  r   rn  ro  r#  r\  r  r   rs  r  ru  )	r'  r;  rA   ri   sparse_gradru  r  depthr   r  r  r  rX     s   rX   c                 C  s   t | ||||S r  )r
   _var_mean_helper)r'  r/  rA   
correctionr  r  r  r  	_var_mean	  s   r  z	aten::stdc                 G  s"   t | |g|R  \}}| d|S Nr  r  r#  r'  r/  rT  r	  r  r  r  r  r     s   r   z	aten::varc                 G  s   t | |g|R  \}}|S r  )r  r  r  r  r  r	    s   r	  zaten::var_meanc                 G  s2   t |dkrt| |d |d d S t| |g|R  S )NrD  r   )rR  r  )r'  r/  rT  r  r  r  r    s   r  zaten::std_meanc                 G  s&   t | |g|R  \}}| d||fS r  r  )r'  r/  rT  r	  r  r  r  r  r   "  s   r   zaten::logsumexpc                 C  r  )NReduceLogSumExprq  r-  r  r  r  r  r   (  s   r   aten::arangec           
        s  dd } fdd}t |dkst |dkr]t |dkrd }n||d }tj |d |d	\}}}}t |dg}||}t t t ||d d dg}	 jd
|	t	|
 dS t |dksit |dkrt |dkrrd }n||d }tj |d |d |d |d\}}}}t |dg}t |dg}t |dg}| d d|||}t t t |d d d dg}	 d d|	||}	 jd
|	t	|
 dS t |dkr<||d }tj |d |d |d\}}}}t |dg}t |dg}| d||} dt t t ||g|dd  R  dg|}	 jd
|	t	|
 dS tddt | dS )Nc                 S  s   t | d} | S )Nr  )r
   r  rw  r  r  r  _get_arange_dtype0  s   z!arange.<locals>._get_arange_dtypec                   s.   t | r jd d| tjj d} | S )Nrh  rd  ri  )r
   rq  r#  r   rn  rm  rs  )range_tensorr  r  r  _float_step_convert4  s   


z#arange.<locals>._float_step_convertr  r  rD  r   )r  rx  rh  ri  r  rC  r  )r  r  r  rx  rg  rM  rB  rE  rc  )r  r  rx  r  r  r  )rR  r
   _arange_cast_helperr  rE  r   r   r#  r   rn  rs  r6  )
r'  rT  r  r   rx  r  r  r  r  arange_tensorr  r  r  r   .  sl   	
&r   zaten::linspacec           
      C  sT   t | |d }t| t| ||t| || jdtjdtjdd}	t| t	| ||	|S )NrY  rD  rw  rZ  )
r
   _arange_helperrB   r   r#  r\  r   r|  r   r   )
r'  r  r  stepsrx  r  r   r  r  r  r  r  r  rz   {  s   
 rz   z
aten::liftc                 C  r  r  r  r  r  r  r  rt     r  rt   zaten::masked_fillc                 C  s6   | j d|tjjd}t|}|  d|t|||S )zImplement the masked_fill functionality available for a pytorch tensor in ONNX.

    Fills elements of the input tensor with `value` where `mask` is True.
    rh  ri  r  )r#  rk  rl  r(  r
   rJ  r  r'  r;  maskr_  r  r  r  r     s   
r   zaten::masked_fill_c                 C  r  r  )r   r%  r  r  r  r     r  r   aten::indexc                   s  t |rt |}n|g}fddfdd|D }t|dkr0t jd|d ddS d	d t|D  t dkrAS t dkrTt d | d  S t }|d u rdt d
dS t	
dtj d t }tfddt|D jd  fddt|D  djd|d| d  } d  }t|d ddD ]}d| |  |}	d||	}d| |  }qtd|t|}
 tt d  d d krjjdtdgdg fddt|D  }jdg|R ddi}t |ttd d d dg tt d d || d  }jd|dfddt d D |
g  fddt d |D  }jdg|R ddi}njd|
g fddt|D R ddi}t |S ) Nc                   sh   t | s2tj| tjjtjjkst | r2 jdk r"t	
dtd t  t | dg} | S )Nr  z?Exporting masked indices are only supported after ONNX opset 9.zExporting aten::index operator with indices of type Byte. Only 1-D indices are supported. In any other case, this will produce an incorrect ONNX graph.rD  )r
   r%  r   rn  ro  rp  r  rO  r  r	   re  r  r  rE  r   )ri   r  r  r  try_mask_to_index  s$   

z index.<locals>.try_mask_to_indexc                   s   g | ]} |qS r  r  )r  r  )r(  r  r  r    r  zindex.<locals>.<listcomp>rD  r   F)apply_reshapec                 S  s   g | ]\}}t |s|qS r  )r
   r%  )r  r  r  r  r  r  r    s
    r'  z9operator of advanced indexing on tensor of unknown rank. z=Exporting aten::index operator of advanced indexing in opset z is achieved by combination of multiple ONNX operators, including Reshape, Transpose, Concat, and Gather. If indices include negative values, the exported graph will produce incorrect results.c              
     s0   g | ]} j d  j dt|gdddqS )r  rY  rZ  r   rH  )r#  r\  r  r  rA   )r'  shape_tensorr  r  r    s    r  c                   s   g | ]}| vr|qS r  r  r{  )adv_idx_indicesr  r  r        r  r  rH  r  r  rE  rB  rY  rZ  c                      g | ]
}| vr| qS r  r  r{  r,  dim_tensor_listr  r  r    s    r2  r3  c                   s   g | ]} | qS r  r  r{  )r0  r  r  r  *  r  c                   r.  r  r  r{  r/  r  r  r  ,  
    c                   r.  r  r  r{  r/  r  r  r  7  r1  )r
   r  r  rR  r  rO  rh   r  r6  r  r  r   rg  r0  r  r#  r5  r\  r  r9  )r'  r;  ri   r!  r  adv_idx_countcum_adv_index
multiplierr  	adv_indexcum_adv_index_shape_tensorfolded_adv_idx_shape_listfolded_adv_idx_shapeadv_idx_permutefinal_shape_listfinal_shaper  )r,  r0  r'  r;  r+  r(  r  ri     s   




	ri   zaten::linalg_normordSequence[int] | Nonerx  c                 C  s   d }|d u r>t |rt | |dg}| jdtdgd}t |}|d u r.t dd|S |dkr9t |d}n!d	dg}nt	|dkrZt |rT| jdtdgd}t |d}|ret
| |||||S t| |||||S )
Nr  rY  r  rZ  rA   (Input rank must be known at export time.rD  rV  r   )r
   r%  r9  r#  r\  r  r  r6  r  rR  rx   rv   )r'  r;  r<  rA   r  rx  	ord_valueself_dimr  r  r  rw   B  s(   



rw   zaten::linalg_vector_normc                 C  s   t | |||||S r  )r
   _linalg_vector_norm_helper)r'  r;  r<  rA   r  rx  r  r  r  rx   e  s   
rx   zaten::linalg_matrix_norm	list[int]c              	   C  s  t |d}|dkrt| |||S |dkrt dd|S t |d}|d u r-t| |||S |dks5|dkr<t dd	|S t |}|d u rLt dd
|S |d dk rZ|d  |7  < |d dk rh|d  |7  < |tjkss|tj kr|d |d |d< |d< |d |d kr|s|d  d8  < t j| | d||d g|d}|dkrt	| || jdt
|d gd|d\}	}
|	S t| || jdt
|d gd|d\}	}
|	S )Nra  fronuczlinalg.matrix_normzord==nucrV  r  r  zord==2r>  r   rD  r  rq  rY  rZ  )r  r  )r
   r  rU   r6  r  r  infru  r#  r   r\  r  r   )r'  r;  r<  rA   r  rx  r?  r@  r  r  _indicesr  r  r  rv   r  sR   


rv   zaten::linalg_crossr  c                 C  r  r  )r>   )r'  r/  r@  rA   r  r  r  ru     r<  ru   zaten::frobenius_normc                 C  s,   |  d||}tj| |||d}|  d|S )NrE  rq  r  )r#  r
   ru  )r'  r;  rA   r  sqrsumsqrr  r  r  rU     s   rU   zaten::multinomialc                 C  sZ   |d urt |st dd| |s|dkrt dd| t| |}| jd|tjj|dS )NMultinomialz*generator is not supported for multinomialrD  zGreplacement=False when num_samples > 1 is not supported for multinomial)r  sample_size_i)r
   r%  r6  r}   r#  rk  rl  rm  )r'  r/  num_samplesreplacementr  	log_inputr  r  r  r     s"   
r   zaten::baddbmmc           
      C  s\   t j|}t| ||}t| || jd|| d}t| || jd|| d}	t| ||	S r9  )r   rn  ro  r   r   r#  rs  r   )
r'  r;  batch1batch2r  rL  ru  	batch_mulmul_amul_br  r  r  r!     s   r!   zaten::meshgridindexing
str | Nonec                   s:  |d u rd}n|dvrt d| |t|}|dkr(|dd d |d d<  fdd	|D } fd
d	|D } jdg|R ddi}g }t|D ]6\}}	 jdtjdtjddgt	| }
|| |
|< t
 |	 jdg|
R ddi}| d|| qL|dkr|d |d |d< |d<  jdg|R  S )Nij>   rU  xyzUnsupported indexing: rV  rD  r  r  c                   s,   g | ]}t  | jd tdgdqS )rY  r  rZ  )r
   r9  r#  r\  r  r  r  r  r  r    s    zmeshgrid.<locals>.<listcomp>c                   s   g | ]}  d |qS )r,  r-  r  r  r  r  r    r-  r2  r3  r   rY  rw  rZ  r  prim::ListConstruct)r	   re  r
   r  r#  rO  r\  r   r|  rR  r7  r  )r'  r  rS  unpacked_tensor_listr  tensors_shape	out_shapert  r  r   r  
t_reshapedr  r  r  r     s2   


 r   zaten::remainderc                 C  s(   t | ||}| d||}| d||S )NrE  rM  )rc  r#  )r'  r/  r@  rB   quor  r  r  r     s   r   z
aten::geluapproximatec                 C  s"  |dkrXt dt j }d}tj|tjd}tj|tjd}tjdtjd}tjdtjd}t| |t| ||}	t| |t| |t| ||	}
t| |t| |t| || d|
S d}| d	| d
|tj|tjd}t| || jdtjdtjdd}t| t| ||| jdtjdtjddS )Nr   r  gHm?rw  rW        ?r  g;f?r  rg  rY  rD  rZ  )	r  r   r  r\  r   r  r   r   r#  )r'  r;  r]  kBetakKappar  kappar  half	self_cubeinner_sqrt2rK   erf_plusoner  r  r  rZ     s(   $"
rZ   zaten::group_normc              
   C  s  t |d}|d ur|| dksJ t |}|d u r"t dd|S d|dg}	t | || jdt|	d}
| jdtjdg| t	j
| d	d}| jdtjd
g| t	j
| d	d}| jd|
|||d}t | || d|}|d u s|  rtjdgt	j
| d	}| jd|d}|d u s|  rtjd
gt	j
| d	}| jd|d}ttd|d }t| t| |t | ||t | ||S )NrD  r   r]   zunknown input rankr  rY  rZ  rW  rw  r  r  r  r,  )r
   r  r  r6  r9  r#  r\  r  r   r   rn  ro  rx  r  
mustBeNoner5  r  r   r   r  )r'  r/  
num_groupsr   rD  ro  rJ  r  
input_rankr6  r  r  r  norm_reshapedr   r  r  r  r  r  r  r]   +  sX   


r]   zaten::_weight_normc                 C  s   t |}|d ur:tt|}|d ur$|dk r||7 }|dkr$|| t| |d|d}| d||}| d||S td|)Nr  r  rD  rg  rE  zDUnsupported: ONNX export of _weight_norm for tensor of unknown rank.)	r
   r  r5  r  remover   r#  r	   re  )r'  r  weight_grA   r  r  norm_vrB   r  r  r  _weight_normh  s   

rn  z	aten::dimc                 C  r  )zFImplement the dim functionality available for a pytorch tensor in ONNXr,  Sizer-  r:  r  r  r  rA     s   zaten::__contains_c                 C  s`   t |}tdd |D r*t |r*| jdtt | ddd |D v dS t	
d|)Nc                 s  s    | ]}t |V  qd S r  )r
   r  r  r  r  r  r    s    

z__contains_.<locals>.<genexpr>rY  r_  c                 s  s     | ]}t | d V  qdS )r_  N)r
   r=  r  r  r  r  r  r    s    rZ  zJUnsupported: ONNX export of __contains__ for non-constant list or element.)r
   r  r  r  r#  r\  r   r=  r  r	   re  )r'  r;  elementunpacked_listr  r  r  __contains_  s$   
rr  zaten::__getitem_c                 C  s    t | || jdtdgd|S re  )r   r#  r\  r   )r'  r;  r  r  r  r  
__getitem_  r  rs  z
aten::itemc                 C  r  r  r  r  r  r  r  rn     r  rn   z
aten::takec              
   C  sD   t | || jdtjdgtjdd}t| |d|}t| ||}|S )NrY  r  rw  rZ  r   )r
   r9  r#  r\  r   r|  rh   r   )r'  r;  ri   self_flattenedrt  r  r  r  r     s   r   c                 C  s&   t | ||}t| |}t| ||}|S r  )r   rL   r   )r'  r/  targetdiff_exp_r  r  r  r  _kl_div_log_target_impl  s   
rx  c           	      C  sZ   t | |}t| ||}t| ||}t| |}t| || jdtdd}t| |||}|S re  )	r}   r   r   r  r^   r#  r\  r   r  )	r'  r/  ru  log_rv  
output_poszeros_mask_r  r  r  r  _kl_div_non_log_target_impl  s   

r}  zaten::kl_divc                 C  sf   |r	t | ||}nt| ||}|dkr|S |dkr!| jd|ddS |dkr-tj| |ddS td|S )Nr   rD  r  rr  r  z4kl_div with reduction other than none, mean, or sum.)rx  r}  r#  r
   ru  r  )r'  r/  ru  	reduction
log_targetr  r  r  r  ro     s   ro   zaten::mse_lossc                 C  sd   t | t| ||t| ||}|dkr|S |dkr | jd|ddS |dkr,tj| |ddS td|S )Nr   rD  r  r~  r  z6mse_loss with reduction other than none, mean, or sum.)r   r   r#  r
   ru  r  )r'  r/  ru  r  r  r  r  r  r     s   r   zaten::as_stridedc                 C  s  t |d}t|}t | || jdtjdgtjdd}t |s`tjdgtj	d}t
t||D ]\}\}	}
dg| }d||< |t|	||
  }q2|rT|| }| d|| jd|dS d }t
|D ]Y\}}
dg| }d||< t| || jdtdgd| jdt|d}	t | t| |	d	d d d | jdt|d}| d
|| jdt|
gd}|d u r|}qf| d||}qf|r| d|| dt|g}| d||S )Nr  rY  r  rw  rZ  r   rD  r  r  rE  rB  )r
   r  rR  r9  r#  r\  r   r|  rF  rz  rO  r  r   r  r   )r'  r;  r  stridesoffsetr  self_1dindr  r   r  r_sizetmp_indr  r  r  r     sL   


r   zaten::__derive_indexc              	   C  s   |  d||  d||S )NrB  rE  r-  )r'  ri   r  r  r  r  r  __derive_index  s   r  zaten::__range_lengthc                 C  s6   |  d||}|  dt| ||}| j d|tjjdS )NrM  rd  rh  ri  )r#  r   rk  rl  rm  )r'  lor  r  r   rB   r  r  r  __range_length  s   
r  zaten::linearc                 C  s   t |}t| |}|dkr9|  s9| jdtjdtjdd}| jdtjdtjdd}t	| |||||}|S t
| ||}|  sKt| ||}|S )Nr  rY  rD  rw  rZ  )r
   r  r   r  rg  r#  r\  r   r|  r   r   r   )r'  r/  r   rD  r  rL  r  r  r  r  r  ry   )  s   

zaten::hann_window
int | Nonec              	   C  s   |d u rt  }|r|jst j}tj|}	nt|}	t| |dd d d }
| jd|
t	j
jd}t| | jdt jtjt jdd|}|du rVt| || jdt jdt jdd}t| ||}| jdt| t| ||	 d}|S )	Nr  rh  ri  rY  rw  rZ  FrD  )r\  r  rk   r  r   rn  
from_dtyper   r#  rk  rl  rr  r   r   r  r  r   r  rB   r   r   rs  )r'  window_lengthperiodicrx  r  r   r  r  dtype_ru  n_arrayr  r  r  r  r_   9  s,   

r_   zaten::mvc                 C  r  r  r   )r'  r;  vecr  r  r  r   a  r1  r   z	aten::dotc                 C  r  r  r  rP  r  r  r  rC   f  r1  rC   zaten::movedimc           
      C  s   | d}| d}| | ksJ ||k r|S t|}|d us'J tt|}| }| }t|	 |	 D ]\}}	|||	< d||< d||	< q>dd |D }dd |D }t||D ]\}}	|||	< qb| j
d||dS )Nr  c                 S     g | ]}|d kr|qS r  r  r*  r  r  r  r    r-  zmovedim.<locals>.<listcomp>c                 S  r  r  r  r*  r  r  r  r    r-  r  r  )r  r   r  r
   r  r5  r  r  r  tolistr#  )
r'  r;  r  destinationrY  r
  src_dimsdst_dimsr  dstr  r  r  r   k  s&   




r   z
aten::fillc                 C  s    t j|t jj}t| |||S r  )r   rn  ro  rr  rV   )r'  r;  r_  ru  r  r  r  rP     s   rP   zaten::index_addc                   s  t d |rtt|dkrtdd|S t d  d u r(td|t	|}t	|}|d u s:|d u r@td|||krZ|| }t
|D ]}	t| |t	|g}qLt| }
t| }|
d urx|d urx|
|krxtd|tt
|}d	d
 t
|D } fdd
t
|D }tj| ||||d}t| ||}t
 D ]
}	t| |dg}qt
|  d D ]}	t| |t	|g}qt| | t| |||S )NzyWarning: ONNX export does not support duplicated values in 'index' field, this will cause the ONNX model to be incorrect.rD  rd   z
alpha != 1r  zXONNX export does NOT support exporting 'index_add_()' function with unknown 'dim' value.z~ONNX export does NOT support exporting 'index_add_()' function while the rank of self tensor or tensor to be added is unknown.zoONNX export does not support exporting 'index_add_()' function with duplicated values in 'index' parameter yet.c                 S  r  r  r  r{  r  r  r  r    r  zindex_add.<locals>.<listcomp>c                   s   g | ]}| krt jnd qS r  )sysmaxsizer{  rA   r  r  r    s    rG  r   )r  r  r
   rI  rJ  r6  r  r	   re  r  r  r  r  r5  rI  rM   r   )r'  r;  rA   ri   r@  rL  self_dim_rankother_dim_rankdeltar  other_dim_sizeself_dim_sizenew_shape_axesnew_shape_startsnew_shape_endsr  r  r  r  rd     s\   


rd   z
aten::rollc                 C  s   t |t |ks
J |}tt |D ]A}g }tj| ||| g||  gtjgd}|| tj| ||| gdg||  gd}|| | jdg|R d|| i}q|S )NrG  r   r2  r3  )rR  r  r
   rI  r  r  r  r#  )r'  r;  shiftsr  r  r  r  r6  r  r  r  r     s   

r   zaten::crossc                 C  sp   t ||}t| |dg|g}t| |dg|g}t| |dg|g}t| |dg|g}t| t| ||t| ||S )Nr  rD  )r
   _get_dim_for_crossr   r   r   )r'  r/  r@  rA   roll_x_1roll_y_1roll_x_2roll_y_2r  r  r  r>     s   r>   zaten::cdistrw  #use_mm_for_euclid_dist_if_necessaryc                 C  s   t |d}t |d}|d usJ |d usJ t |d}t |d}|dkr>|dks8|d u r>|dkr>|dkr>t| ||S t |}|d usIJ t | ||d g}	t | ||d g}
t| |	|
|dd	d
S )Nr  rV  r  rw  rD     r  gư>F)ro  r  )r
   r  r  _euclidean_distr  r  r   )r'  r  r  r  compute_moderow_size_x1row_size_x2p_floatr  broadcasted_x1broadcasted_x2r  r  r  r+     s"   
r+   c              	   C  s  t |}|d usJ t j| t| |t | ddgdd}t| |}t j| t| |t | ddgdd}t| |}| jdgt| t | d|||gR ddi}| jdg|||gR ddi}	t| |t	| |	dd}
t
j|
}| jd	t | d
| d}t j| d|
|dd}
t| |
}
|
S )Nrw  r  Trq  r2  g       r3  r  rh  r  ri  r  r  r_  )r
   r  ru  r   ry  r   r#  r   r   r   r   rn  ro  rs  rb  r   )r'  r  r  r  x1_normx1_padx2_normx2_padx1_x2_r  rx  r   r  r  r  r  $  sJ   


	

r  z
aten::lerpc                 C  sx   |  d||}t| |  d|| j dtdd|  d||  d|||  d||  d||  d| j dtdd|S )	NrM  r  rY  r^  rZ  rB  rE  rW  )r#  r  r\  r   )r'  r;  r  r   diffr  r  r  rs   N  s   rs   zaten::broadcast_tensorsc                   sT   t |}t |d |D ]}t |q fdd|D } jdg|R  S )Nr   c                   s   g | ]}t  |qS r  )rM   r  r'  t_with_final_shaper  r  r  m  r-  z%broadcast_tensors.<locals>.<listcomp>rW  )r
   r  r  r   r#  )r'  r;  all_tensorsr   t_listr  r  r  r'   c  s   
r'   zaten::is_pinnedc                 C     d S r  r  )r'  r;  r   r  r  r  rl   q  r  rl   prim::ConstantSplitc                 C  s^   t ||}|d u rt dd|S |g||  }|| }|r#|| | jd|||t|dS )Nr  r1  r2  r3  )r
   r  r6  r  r#  rR  )r'  r;  r9  rA   r   r:  r;  r  r  r  r   w  s   
r   prim::ConstantChunkc                 C  s@   t ||}|d u rt dd|S || d | }t| |||S )Nr  r1  rD  )r
   r  r6  r   )r'  r;  r7  rA   rV  r9  r  r  r  r     s   r   zprim::shapec                 C  r*  r+  r-  r  r  r  r  r     r1  r   z	prim::maxc                 C  s   t j| d||ddS )Nr  r  r_  ra  rP  r  r  r  r     s   
r   z	prim::minc                 C  sB   |st |rt| || jdtdgd}t| |S t| ||S re  )r
   r  r   r#  r\  r   r   rP  r  r  r  r     s
   

r   z
prim::datac                 C  r  r  r  r  r  r  r  r     r  r   zprim::layoutc                 C  s   | j dtddS re  r  r  r  r  r  r     s   r   rW  c                 O  r  r  r  r'  r  r  r  r  r  r     r  r   zprim::ListUnpacklist[_C.Value] | Nonec                 O  s2   t |dkr|d   dkrt|d S d S )NrD  r   rW  )rR  r  rt  r
   r  r  r  r  r  r     s    r   zprim::TupleConstructc                 O  r  r  r  r  r  r  r  r     r  r   zprim::Uninitializedc                 O  r  r  r  r  r  r  r  r     r  r   zprim::unchecked_castc                 C  r  r  r  r  r  r  r  r     r  r   zprim::dtypec                 C  s.   t |}|d u rtjj}| jdt|dS rX  )r
   r  r   rn  rr  r#  r\  r   )r'  r;  ru  r  r  r  r     s   
r   prim::tolistc                 C  s&   t |d}|dkrt dd|S |S )ztolist is currently supported only for 1D input tensors.

    dim_val and elem_ty_val represent dimension and type annotations
    that need to match dimension and type of the input tensor.
    r  rD  r  zdim_val > 1)r
   r  r6  )r'  r/  dim_valelem_ty_valrA   r  r  r  r     s   r   rB  Nonec                 O  s>   | j   }t|tjrd S tdd|  d| j  S )NrB  z,output type should be 'DeviceObjType', not '')	original_noder  r  r4  r   r  r
   r6  rt  )r'  r  r  output_typer  r  r  r     s   r   z
prim::Looplist[_C.Value]c              	   O  s(  | j }| j}| j}| j}tj}tj}t| }	t	j
| dg|R | t|	d\}
}}t|	|D ]M\}}t| D ]6\}}|dkrS|t|k rS|||   |dkrr|d t|k rrt| tjsr|||d    q<tj||j|||d q2tj||}tjrtj||| |S )NLoopr5  n_blocksr   rD  F)r  envvalues_in_envparams_dictr   r%  rg  r  blocksr   add_op_with_blocksoutputsSizerR  r  rO  r  r$  r  r4  r   r%  r\  _jit_pass_onnx_blockblock%_jit_pass_fixup_onnx_controlflow_nodeonnx_shape_inference(_jit_pass_onnx_node_shape_type_inference)r'  r  attrsr  r  r  r  r%  opset_version
old_blocks_new_op_outputsnew_block_contextsnew_node	old_blocknew_block_contextr  b_infixed_outputsr  r  r  r     sP   r   zprim::Ifc              	   O  s  | j }| j}| j}| j}| j}tj}tj}	|d  	 dk}
|
rt
|d  d }t|tr6t|nt|}|r>dnd}t| | }tj|||||d}t| }t| }g }tt|D ]!}|| |vr}td||  d|| |||  }|| qg|S t| }tj| dg|R | t|d	\}}}t||D ]\}}tj||j|||d
 qtj ||	}tj!rtj"|||	 |S )Nr   r  r_  rD  TzThe sub block ATen output z is not in env.Ifr  F)#r  r  r  r  r  r   r%  rg  r  rt  r
   r=  r  r4  r5  r  r  r  r\  r   r  r5  r  rR  r	   re  r  r  r   r  r  r  r  r  r  )r'  r  r  r(  r  r  r  r  r%  r  	static_if
input_flagr  	block_idx	current_bif_output_listcurrent_b_listfinal_b_listr  onnx_br  r  r  r  r  r  r  r  r  r  r   4  sv   r   r"  c                   s(   j }| r	d S t|  tjrd S |ddkr' jdt	
|ddS |ddkr9 jdt	
|ddS |  tj sQ|  tj r_ jdtt	
|ddS |  tj r fddt	
|dD } jd	g|R  S td
|d dtj d| )Nr_  r   rY  rZ  ra  value_sc                   s   g | ]	} j d |dqS )rY  r  r-  )r  ra  r  r  r  r    s    z!prim_constant.<locals>.<listcomp>rW  z"Unsupported prim::Constant kind: 'z'. Please send a bug report at .)r  rg  r4  r  r  r   r  r  r#  r
   r=  rD  rE  rF  ofFloatsr\  r   	ofStringsr	   re  r   PYTORCH_GITHUB_ISSUES_URL)r'  r  r  r  str_constantsr  r  r  r     s8   

r   
prim::typedevice_valuec                 O  sJ   |   dkrt|   }|d ur| jdt|dS tdd|S )NrB  rY  r  r  z,Device type cannot be statically determined.)	r  rt  r   get_device_from_valuer/  r#  r  r
   r6  )r'  r  rT  r  r   r  r  r  r     s   r   zonnx::Placeholderc                 O  s*   | j }| j}| j}| j}tj||||S r  )r  r  r  r  r\  r   '_jit_onnx_convert_pattern_from_subblock)r'  r  r  r  r  r  r  r  r  r  r     s   r   zaten::resolve_conjzaten::resolve_negc                 C  r  r  r  r.  r  r  r  r    s   r  zaten::_conjzaten::conj_physicalc                 C  s    t |rt d|S t| |S )Nz aten::_conj, aten::conj_physical)r
   is_complex_valuer  r  r.  r  r  r  r    s   

r  zaten::logitc                 C  s   | j dtdd}t|sC| j d|tj| d}|  d||}|  d||}|  d|||}|  d	||}|  d|||}n|}|  d||}	|  d
||	}
|  d|
S )NrY  rW  rZ  rh  ri  rM  r  r  r  rg  r  )	r#  r\  r   r
   r%  r   rn  ro  rs  )r'  r;  ro  r  one_sub_epsself_less_equal_one_sub_epstemporary_selftemporary_self_less_epszr   rB   r  r  r  r     s   
r   )r  r  )r'  r)  r  )rW  )T)r  r  r  r  r  r  r  )F)r'  r)  r/  rh  ri  r  rj  r  )rA   r  )r'  r)  r/  rh  r   rh  )
r'  r)  r/  rh  r   rh  r(  rh  r_  rh  )r  r  rA   r  r  r  )r  r   r  r   )NNN)r'  r)  r/  rh  ru  r  r   rh  rD  rh  ro  r  r  rv  )r'  r)  r/  rh  ru  r  r   rh  rD  rh  ro  r  r  r  r  rh  )
r'  r)  r  r  rn  r   ro  r   rJ  r  )FF)NN)FN)NNNFN)NNF)r'  r)  r;  rh  r/  r  r0  r  )rt  r  )NNFN)r'  r)  r/  r  rA   r  r  r  )r'  r)  r;  r  r<  r  rA   r=  r  r  rx  r  )r'  r)  r;  r  r<  r  rA   r=  r  r  rx  r  )r'  r)  r;  r  r<  r  rA   rB  r  r  rx  r  r  )NF)r'  r)  rS  rT  )r  )r'  r)  r;  r  r]  r  )TNNNNF)r'  r)  rx  r  )rw  r  )r'  r)  r  r  )r'  r)  r  r  )r'  r)  r  r  )r'  r)  r  rh  )r'  r)  r/  rh  )r'  r)  r;  r  ro  r  (o  __doc__
__future__r   r  r  r  r  r  typingr   r   typing_extensionsr   r\  torch._C._onnxr   _onnxrk  torch.nn.modules.utils
torch.onnxr   r   r	   r
   torch.onnx._globalsr   torch.onnx._internalr   r   collections.abcr   torch.typesr   r  partialonnx_symbolic_onnx_symbolicr!  r  r0  r7  r  r   r   r   r   r   r   rB   r  r   rS  rd  rc  rR   rT   r   r   r*   r   r  r   r&   r   r   r   r   r   r   r   r<   r   r   r   r   r    r   r   r  _apply_paramsr  r?   r  r   r   r   rN   r(   rM   rG   rF   r   r   r   r  r
  r  r   r  r   r  r   r   r   r   r   r   r   r   r   r,   rS   rg  r   rr   r\   r   r   r[   nnmodulesutils_single_pair_tripler  r   r   r   r  r  r  r  r1   r  r   r   r   r  r  r$   r%   r  r  r  rJ   r   r^   r  r   r!  rY   rq   r#  r$  r%  r   r   r   r   r0  r3  r  r|   r<  rN  rT  r;   r7   r8   r9   r4   r5   r6   r"   r   rp   rj   r   rE   r   rh   rg   rf   re   r)   r   r=   r   r0   r   r}   r   r~   r   r/   r.   r-   r   r   r   r   r   r   r   rL   rD   r  r   r3   r  r  r  r  r  r  r  r  r  r  r  rI   rH   r   r   r   r   r  r  r   r  r   r   r   rW   rV   r   rO   r   rc   rb   ra   r   r`   r   r   r  r   r   r   r:   r   r   r   r   r   r  r  r  r   r   r  r  r@   r2   r  r  r   r   r   r   r   r   r   r#   r{   rK   rQ   r   r   rm   r  r  r   r   r   r   r   r   rk   r  r  r   rX   r  r   r	  r  r   r   r   rz   rt   r   r   ri   rw   rx   rv   ru   rU   r   r!   r   r   rZ   r]   rn  rA   rr  rs  rn   r   rx  r}  ro   r   r   r  r  ry   r_   r   rC   r   rP   rd   r   r>   r+   r  rs   r'   rl   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r   r  r  r   r  r  r  r  <module>   s`    
&
5


>	

	>5			:



7			


6)		







C	7###7L_"#



		
		H


Jg
F
N cB
	
*
		L
 $!;

:	
,	& 
E*
4Z"	