
    #Ki                       S r SSKrSSKrSSKrSSKrSSKrSSKrSSKrSSKJ	r	J
r
  SSKJr  SSKJrJr  SSKJr  SSKrSSKJrJrJrJrJrJrJrJrJr  / SQr\" S	5      r\" S
5      r  S.S\	\\4   S\S\S\	\\4   4S jjr \RB                  \ S\"\	   4S j5       5       r#\RB                  S\"\	   4S j5       r$\RB                  \ S\%\	\	4   4S j5       5       r&S\	4S jr' S/S\
\   S\	\/\(4   S-  S\)\   4S jjr*S\	S\
\   S\4S jr+\" \S5      r,\" \S5      r-\" \S5      r.\RB                  S\/\%\\)\	   4   \%\	\4   4   4S j5       r0\ S\%\\)\	   4   4S j5       r1\ S 5       r2\RB                  S\"\	   4S  j5       r3\ S\	S\44S! j5       r5S" r6 " S# S$5      r7S% r8S& r9S' r:S( r;\Rx                  S) 5       r= " S* S+\75      r>\Rx                  S, 5       r?\Rx                  S- 5       r@g)0aE  
Python implementation of ``__torch_function__``

While most of the torch API and handling for ``__torch_function__`` happens
at the C++ level, some of the torch API is written in Python so we need
python-level handling for ``__torch_function__`` overrides as well. The main
developer-facing functionality in this file are handle_torch_function and
has_torch_function. See torch/functional.py and test/test_overrides.py
for usage examples.

Note
----
heavily inspired by NumPy's ``__array_function__`` (see:
https://github.com/pytorch/pytorch/issues/24015 and
https://www.numpy.org/neps/nep-0018-array-function-protocol.html
)

If changing this file in a way that can affect ``__torch_function__`` overhead,
please report the benchmarks in ``benchmarks/overrides_benchmark``. See the
instructions in the ``README.md`` in that directory.
    N)CallableIterable)wraps)AnyTypeVar)	ParamSpec)	_add_docstr_get_function_stack_at_has_torch_function_has_torch_function_unary_has_torch_function_variadic_is_torch_function_mode_enabled_len_torch_function_stack_pop_torch_function_stack_push_on_torch_function_stack)
get_ignored_functionsget_overridable_functionsget_testing_overrideshandle_torch_functionhas_torch_functionresolve_nameis_tensor_likeis_tensor_method_or_propertywrap_torch_functionenable_reentrant_dispatch_P_Rfuncregexmodulereturnc                    ^ ^^ [        T 5      S[        R                  S[        R                  S[        4U UU4S jj5       nU$ )a  
Decorator that temporarily disables ``UserWarning``s for the given ``module`` if the warning message matches the
given ``regex`` pattern.

Arguments
---------
func : function
    Function to disable the warnings for.
regex : str
    A regex pattern compilable by ``re.compile``. This is used to match the ``UserWarning`` message.
module : str
    The python module to which the filtering should be restricted.

Returns
-------
function
    The wrapped function.
argskwargsr!   c                     > [         R                  " 5          [         R                  " S[        TTS9  T" U 0 UD6sS S S 5        $ ! , (       d  f       g = f)Nignore)categorymessager    )warningscatch_warningsfilterwarningsUserWarning)r#   r$   r   r    r   s     Q/var/www/html/dynamic-report/venv/lib/python3.13/site-packages/torch/overrides.pywrapper'_disable_user_warnings.<locals>.wrapper[   sA    $$&##;f ((	 '&&s   #A
A)r   r   r#   r$   r   )r   r   r    r.   s   ``` r-   _disable_user_warningsr0   C   sD    0 4[)rww )")) ) ) ) ) N    c                  %   [         R                  n 1 [         R                  i[         R                  i[         R                  i[         R
                  i[         R                  i[         R                  i[         R                  i[         R                  i[         R                  i[         R                  i[         R                  i[         R                  i[         R                  i[         R                  i[         R                   i[         R"                  i[         R$                  i[         R&                  i[         R(                  i[         R*                  i[         R,                  i[         R.                  i[         R0                  i[         R2                  i[         R4                  i[         R6                  i[         R8                  i[         R:                  i[         R<                  i[         R>                  i[         R@                  i[         RB                  i[         RD                  i[         RF                  i[         RH                  i[         RJ                  i[         RL                  i[         RN                  i[         RP                  i[         RR                  i[         RT                  i[         RV                  i[         RX                  i[         RZ                  i[         R\                  i[         R^                  i[         R`                  i[         Rb                  i[         Rd                  i[         Rf                  i[         Rh                  i[         Rj                  i[         Rl                  i[         Rn                  i[         Rp                  i[         Rr                  i[         Rt                  i[         Rv                  i[         Rx                  i[         Rz                  i[         R|                  i[         R~                  i[         R                  i[         R                  i[         R                  i[         R                  i[         R                  i[         R                  i[         R                  i[         R                  i[         R                  i[         R                  i[         R                  i[         R                  i[         R                  i[         R                  i[         R                  R                  i[         R                  R                  i[         R                  R                  i[         R                  R                  i[         R                  i[         R                  R                  i[         R                  R                  i[         R                  i[         R                  i[         R                  i[         R                  i[         R                  i[         R                  i[         R                  i[         R                  i[         R                  i[         R                  i[         R                  i[         R                  i[         R                  i[         R                  i[         R                  i[         R                  i[         R                  i[         R                  i[         R                  i[         R                  i[         R                  i[         R                  i[         R                  i[         R                  i[         R                  i[         R                  i[         R                  i[         R                  i[         R                  i[         R                  i[         R                  i[         R                  i[         R                  i[         R                  i[         R                  i[         R                  i[         R                  i[         R                  i[         R                  i[         R                  i[         R                  R                  i[         R                  R                  GR                   i[         R                  R                  GR                  i[         R                  R                  GR                  i[         R                  R                  GR                  i[         R                  R                  GR                  i[         R                  R                  GR
                  i[         R                  R                  GR                  i[         R                  R                  GR                  i[         R                  R                  GR                  i[         R                  R                  GR                  i[         R                  R                  GR                  i[         R                  R                  GR                  i[         R                  R                  GR                  i[         R                  R                  GR                  i[         R                  R                  GR                  i[         R                  R                  GR                  i[         R                  GR                   GR"                  i[         R                  GR                   GR$                  i[         R                  GR                   R                  i[         R                  GR                   GR&                  i[         R                  GR                   R                  i[         R                  GR                   GR(                  i[         R                  GR                   GR*                  i[         R                  GR                   GR,                  i[         R                  GR                   GR.                  i[         R                  GR                   GR0                  i[         R                  GR                   GR2                  i[         R                  GR                   GR4                  i[         GR6                  GR8                  iG[        iG[        i[         GR:                  i[         GR<                  i[         GR>                  i[         GR@                  i[         GRB                  i[         GRD                  i[         GRF                  i[         GRH                  i[         GRJ                  i[         GRL                  i[         GRN                  i[         GRP                  i[         GRR                  i[         GRT                  i[         GRV                  i[         GRX                  i[         GRZ                  i[         GR\                  i[         GR^                  i[         GR`                  i[         GRb                  i[         GRd                  i[         GRf                  i[         R                  R                  GRh                  i[         GRj                  i[         GRl                  i[         GRn                  i[         GRp                  i[         GRr                  i[         GRt                  i[         GRv                  i[         GRx                  i[         GRz                  i[         GR|                  i[         GR~                  i[         GR                  i[         GR                  i[         GR                  i[         GR                  i[         GR                  i[         GR                  i[         GR                  i[         GR                  i[         GR                  i[         GR                  iU GR                  iU GR                  iU GR                  iU GR                  iU GR                  iU GR                  iU GR                  iU GR                  iU GR                  iU GR                  iU GR                  iU GR                  iU GR                  iU GR                  iU GR                  iU GR                  iU GR                  iU GR                  iU GR                  iU GR                  iU GR                  iU GR                  iU GR                  iU GR                  iU GR                  iU GR                  iU GR                  iU GR                  iU GR                  iU GR                  iU GR                  iU GR                  iU GR                  iU GR                  iU GR                  iU GR                  iU GR                  iU GR                  iU GR                  iU GR                  iU GR                  iU GR                  iU GR                  iU GR                  iU GR                  iU GR                  iU GR                  iU GR                  iU GR                  GR                  iU GR                  GR                  iU GR                  iU GR                  iU GR                  iU GR                   iU GR                  iU GR                  iU GR                  iU GR                  iU GR8                  iU GR
                  inG[        GR                  S:  a  UGR                  U GR                  5        U$ )a  
Return public functions that cannot be overridden by ``__torch_function__``.

Returns
-------
set[Callable]
    A tuple of functions that are publicly available in the torch API but cannot
    be overridden with ``__torch_function__``. Mostly this is because none of the
    arguments of these functions are tensors or tensor-likes.

Examples
--------
>>> torch.Tensor.as_subclass in torch.overrides.get_ignored_functions()
True
>>> torch.add in torch.overrides.get_ignored_functions()
False
)      (
  torchTensortypename	is_tensor
is_storageset_default_tensor_typeset_default_deviceget_default_deviceset_rng_stateget_rng_statemanual_seedinitial_seedseedsaveloadset_printoptionsforkget_default_dtypeget_num_interop_threadsget_num_threadsinit_num_threadsimport_ir_moduleimport_ir_module_from_bufferis_anomaly_enabledis_anomaly_check_nan_enabledis_grad_enabledmerge_type_from_type_commentparse_irparse_schemaparse_type_commentset_anomaly_enabledset_flush_denormalset_num_interop_threadsset_num_threadswait	as_tensor
from_numpytensordefault_generatorhas_cuda	has_cudnn
has_lapackdevicedtypefinfohas_mklhas_mps
has_mkldnn
has_openmpiinfomemory_formatqschemeset_grad_enabledno_gradenable_gradinference_modeis_inference_mode_enabledlayoutalign_tensorsarange
as_stridedbartlett_windowblackman_windowbroadcast_shapescan_castcompilecudnn_affine_grid_generatorcudnn_batch_normcudnn_convolutioncudnn_convolution_transposecudnn_convolution_relucudnn_convolution_add_relucudnn_grid_samplercudnn_is_acceptableemptyempty_permutedempty_stridedempty_quantizedexportregister_dataclasseyefftfftfreqrfftfreq	from_filefullfillhamming_windowhann_windowkaiser_windowlinspacelogspacemkldnn_adaptive_avg_pool2dmkldnn_convolutionmkldnn_max_pool2dmkldnn_max_pool3dmkldnn_linear_backward_weightsmkldnn_rnn_layernormalonespromote_typesrand	rand_likerandn
randn_likerandintrandint_likerandpermrangeresult_typescalar_tensorsparse_coo_tensorsparse_compressed_tensorsparse_csr_tensorsparse_csc_tensorsparse_bsr_tensorsparse_bsc_tensorsym_constrain_rangesym_constrain_range_for_sizesym_fresh_sizetril_indicestriu_indicesvanderzeros_jit_internalboolean_dispatchnn
functionalassert_int_or_pairupsampleupsample_bilinearupsample_nearestr   has_torch_function_unaryhas_torch_function_variadicr   
grouped_mmscaled_grouped_mm	scaled_mmsigmoidhardsigmoidtanh_canonical_mask_none_or_dtypeinitcalculate_gainuniformconstantdiracxavier_uniformxavier_normalkaiming_uniformkaiming_normal
orthogonalsparsenestedto_padded_tensorset_autocast_enabledis_autocast_enabledset_autocast_dtypeget_autocast_dtypeclear_autocast_cacheset_autocast_cpu_enabledis_autocast_cpu_enabledset_autocast_xla_enabledis_autocast_xla_enabledset_autocast_ipu_enabledis_autocast_ipu_enabledset_autocast_cpu_dtypeget_autocast_cpu_dtypeset_autocast_ipu_dtypeget_autocast_ipu_dtypeget_autocast_gpu_dtypeset_autocast_gpu_dtypeget_autocast_xla_dtypeset_autocast_xla_dtypeautocast_increment_nestingautocast_decrement_nestingis_autocast_cache_enabledset_autocast_cache_enabled	hardswishis_vulkan_available$are_deterministic_algorithms_enableduse_deterministic_algorithms-is_deterministic_algorithms_warn_only_enabledset_deterministic_debug_modeget_device_moduleget_deterministic_debug_modeset_float32_matmul_precisionget_float32_matmul_precisionunify_type_listis_warn_always_enabledset_warn_alwaysvitals_enabled	set_vitalread_vitalsvmapcond
frombufferasarray_functional_sym_constrain_range_make_dep_token__delitem____dir____getattribute____init____iter____init_subclass____delattr____setattr____torch_function____torch_dispatch____new__	__class____subclasshook____hash__as_subclasseiglstsq	reinforcenew
new_tensor	new_emptynew_empty_strided	new_zerosnew_onesnew_full_make_subclasssolvesymeigstride	unflattento_sparse_cooto_sparse_csrto_sparse_cscto_sparse_bsrto_sparse_bsc
_to_sparse_to_sparse_csr_to_sparse_csc_to_sparse_bsr_to_sparse_bsc_typed_storage_reduce_ex_internal_fix_weakref
_view_func_view_func_unsafe_rev_view_func_unsafe_dtensor__new___make_wrapper_subclass_python_dispatch__get___has_symbolic_sizes_strides_conj_conj_physical_lazy_clone	_neg_view_is_zerotensor_is_all_true_is_any_true_addmm_activation
_use_countsysversion_infoadd__annotate__)r6   	functionss     r-   r   r   f   s   ( \\FGGG 	G 	%%	G
 	  G 	  G 	G 	G 	G 	G 	

G 	

G 	

G 	G 	

G  	!G" 	%%#G$ 	%G& 	'G( 	)G* 	**+G, 	  -G. 	**/G0 	1G2 	**3G4 	5G6 	7G8 	  9G: 	!!;G< 	  =G> 	%%?G@ 	AGB 	

CGD 	EGF 	GGH 	IGJ 	KGL 	MGN 	OGP 	QGR 	SGT 	UGV 	WGX 	YGZ 	[G\ 	]G^ 	_G` 	aGb 	cGd 	eGf 	gGh 	iGj 	kGl 	mGn 	''oGp 	qGr 	sGt 	uGv 	wGx 	yGz 	{G| 	}G~ 	G@ 	AGB 	))CGD 	EGF 	GGH 	))IGJ 	$$KGL 	((MGN 	  OGP 	!!QGR 	SGT 	UGV 	WGX 	YGZ 	[G\ 	]G^ 	''_G` 	aGb 			cGd 			eGf 			gGh 	iGj 	

kGl 	

mGn 	oGp 	qGr 	sGt 	uGv 	wGx 	((yGz 	  {G| 	}G~ 	G@ 	,,AGB 	CGD 	EGF 	

GGH 	IGJ 	

KGL 	MGN 	OGP 	QGR 	SGT 	UGV 	WGX 	YGZ 	[G\ 	]G^ 	_G` 	&&aGb 	cGd 	eGf 	gGh 	iGj 	!!kGl 	**mGn 	oGp 	qGr 	sGt 	uGv 	wGx 	,,yGz 	..{G| 	$$}G~ 	--G@ 	,,AGB 	..CGD 	44EGF 	77GGH 	11IGJ 	&&KGL 	--MGN 	%%OGP 	##QGR 	''SGT 	  UGV 	++WGX 	**YG\ 	$$]G` 	aGb 	cGd 	eGf 	gGh 	iGj 	$$kGl 	##mGn 	%%oGp 	$$qGr 	  sGt 	uGv 	%%wGx 	yGz 	{G| 	""}G~ 	!!G@ 	  AGB 	  CGD 	""EGF 	&&GGH 	%%IGJ 	&&KGL 	%%MGN 	&&OGP 	%%QGR 	$$SGT 	$$UGV 	$$WGX 	$$YGZ 	$$[G\ 	$$]G^ 	$$_G` 	$$aGb 	((cGd 	((eGf 	''gGh 	((iGj 	%%kGl 	!!mGn 	22oGp 	**qGr 	;;sGt 	**uGv 	wGx 	**yGz 	**{G| 	**}G~ 	G@ 	$$AGB 	CGD 	EGF 	GGH 	IGJ 	

KGL 	

MGN 	OGP 	QGR 	--SGT 	UGV 	WGX 	YGZ 	[G\ 	]G^ 	_G` 	  aGb 	cGd 	eGf 	!!gGh 	!!iGj 	kGl 	mGn 	oGp 	qGr 	sGt 	

uGv 	wGx 	yGz 	

{G| 	}G~ 	G@ 	  AGB 	CGD 	EGF 	GGH 	IGJ 	KGL 	MGN 	OGP 	QGR 	SGT 	UGV 	WGX 	YGZ 	[G\ 	]G^ 	_G` 	aGb 	cGd 	eGf 	gGh 	""iGj 	kGl 	mGn 	  oGp 	$$qGr 	sGt 	%%uGv 	''wGx 	**22yGz 	{G| 	}G~ 	G@ 	AGB 	CGD 	EGF 	GGH 	  IGJ 	KGL 	MGIR 7"f))*r1   c                      [         R                  n U R                  R                  U R                  R                  U R
                  R                  1$ )a  
Return public functions that do not wrap in a subclass when invoked by
the default ``Tensor.__torch_function__`` that preserves subclasses.  Typically,
these functions represent field accesses (i.e., retrieving a Tensor that
is stored somewhere on the Tensor) as opposed to computation.  Users of
these functions expect object identity to be preserved over multiple accesses
(e.g., ``a.grad is a.grad``) which cannot be upheld if we're wrapping on
the fly every time (furthermore, the tensor stored here might already be
the subclass, in which case wrapping really ought not to happen).

Not ALL property accessors have this property; for example ``Tensor.T`` actually
just creates a new transposed tensor on the fly, and so we SHOULD interpose on
these calls (you need to check the implementation of the function to see if
this is the case or not).  Additionally, if a property accessor doesn't return a Tensor,
it doesn't have to be on this list (though it is harmless if it is).
)r5   r6   _baser.  grad_grad)r6   s    r-   get_default_nowrap_functionsrB    s>    $ \\F r1   c                     [         R                  n 0 [         R                  GSS j_[         R                  GSS j_[         R                  S _[         R
                  S _[         R                  GSS j_[         R                  S _[         R                  GSS j_[         R                  GSS	 j_[         R                  GSS
 j_[         R                  GSS j_[         R                  GSS j_[         R                  GSS j_[         R                  GSS j_[         R                  GSS j_[         R                   GSS j_[         R"                  GSS j_[         R$                  S _0 [         R&                  GSS j_[         R(                  GSS j_[         R*                  GSS j_[         R,                  GSS j_[         R.                  GSS j_[         R0                  GSS j_[         R2                  GSS j_[         R4                  GSS j_[         R6                  S _[         R8                  S _[         R:                  GSS j_[         R<                  GSS j_[         R>                  S  _[         R@                  GSS! j_[         RB                  GSS" j_[         RD                  GSS# j_[         RF                  GSS$ j_E0 [         RH                  GSS% j_[         RJ                  GSS& j_[         RL                  GSS' j_[         RN                  GSS( j_[         RP                  GSS) j_[         RR                  S* _[         RT                  S+ _[         RV                  S, _[         RX                  GSS- j_[         RZ                  GSS. j_[         R\                  S/ _[         R^                  S0 _[         R`                  S1 _[         Rb                  S2 _[         Rd                  S3 _[         Rf                  S4 _[         Rh                  S5 _E0 [         Rj                  S6 _[         Rl                  GSS7 j_[         Rn                  S8 _[         Rp                  GSS: j_[         Rr                  GSS; j_[         Rt                  GSS< j_[         Rv                  GSS= j_[         Rx                  GSS> j_[         Rz                  GSS? j_[         R|                  GSS@ j_[         R~                  GSSA j_[         R                  GSSB j_[         R                  SC _[         R                  GSSD j_[         R                  SE _[         R                  SF _[         R                  GSSG j_E0 [         R                  SH _[         R                  GSSI j_[         R                  GSSJ j_[         R                  GSSK j_[         R                  GSSL j_[         R                  GSSM j_[         R                  GSSO j_[         R                  SSP.SQ j_[         R                  SR _[         R                  GSSS j_[         R                  R                  GSST j_[         R                  R                  GSSU j_[         R                  GSSV j_[         R                  GSSW j_[         R                  SX _[         R                  GSSY j_[         R                  GSSZ j_E0 [         R                  GSS[ j_[         R                  GSS\ j_[         R                  GSS] j_[         R                  GSS^ j_[         R                  GSS_ j_[         R                  S` _[         R                  GSSa j_[         R                  Sb _[         R                  GSSc j_[         R                  Sd _[         R                  R                  GSSe j_[         R                  GSSf j_[         R                  GSSg j_[         R                  GSSh j_[         R                  GSSi j_[         R                  GSSj j_[         R                  GSSk j_E0 [         R                  GSSl j_[         R                  GSSm j_[         R                  Sn _[         R                  GSSo j_[         R                  GSSp j_[         R                  GSSq j_[         R                  GSSr j_[         R                  Ss _[         R                  GSSt j_[         R                  GSSu j_[         R                  GSSv j_[         R                  GSSw j_[         R                  Sx _[         R                  GSSy j_[         R                  R                  GSS{ j_[         R                  GSS| j_[         R                  GSS} j_E0 [         R                  GSS~ j_[         R                  GSS j_[         R                  GSS j_[         R                  GSS j_[         R                  GSS j_[         R                  GSS j_[         R                  S _[         R                  S _[         R                  R                  S _[         GR                   S _[         GR                  GSS j_[         GR                  GSS j_[         GR                  GSS j_[         GR                  GSS j_[         GR
                  GSS j_[         R                  GR
                  GSS j_[         GR                  GSS j_E0 [         GR                  GSS j_[         GR                  GSS j_[         GR                  GSS j_[         GR                  GSS j_[         GR                  GSS j_[         GR                  GSS j_[         GR                  GSS j_[         GR                  GSS j_[         GR                  S _[         GR                   S _[         GR"                  GSS j_[         R                  GR$                  GSS j_[         R                  GR&                  GSS j_[         R                  GR(                  GSS j_[         R                  GR*                  GSS j_[         GR,                  S _[         GR.                  GSS j_E0 [         GR0                  GSS j_[         GR2                  GSS j_[         GR4                  GSS j_[         GR6                  S _[         GR8                  GSS j_[         GR:                  GSS j_[         GR<                  GSS j_[         GR>                  GSS j_[         GR@                  GSS j_[         GRB                  GSS j_[         GRD                  S _[         GRF                  S _[         GRH                  GSS j_[         GRJ                  S _[         GRL                  S _[         GRN                  S _[         GRP                  S _E0 [         GRR                  S _[         GRT                  S _[         GRV                  S _[         GRX                  S _[         GRZ                  S _[         GR\                  GR^                  GSS j_[         GR\                  GR`                  GSS j_[         GR\                  GRb                  GSS j_[         GR\                  GRd                  GSS j_[         GR\                  GRf                  GSS j_[         GR\                  GRh                  GSS j_[         GR\                  GRj                  GSS j_[         GR\                  GRl                  GSS j_[         GR\                  GRn                  GSS j_[         GR\                  GRp                  GSS j_[         GR\                  GRr                  GSS j_[         GR\                  GRt                  GSS j_E0 [         GR\                  GRv                  GSS j_[         GR\                  GRx                  GSS j_[         GR\                  GRz                  GSS j_[         GR\                  GR|                  GSS j_[         GR\                  GR~                  GSS j_[         GR\                  GR                  GSS j_[         GR\                  GR                  GSS j_[         GR\                  GR\                  GSS j_[         GR                  GSS j_[         GR                  GSS j_[         GR                  S _[         GR                  S _[         GR                  S _[         GR                  GSS j_[         GR                  GSS j_[         GR                  S _[         GR                  GSS j_E0 [         GR                  GSS j_[         GR                  GSS j_[         GR                  GSS j_[         GR                  SS[         GR                  SS4S j_[         GR                  S _[         GR                  GSS j_[         GR                  GSS j_[         GR                  GSS j_[         GR                  GSS j_[         GR                  S _[         GR                  GSS j_[         GR                  GSS j_[         GR                  GSS j_[         GR                  GSS j_[         GR                  GSS j_[         GR                  GSS j_[         GR                  GS S j_E0 [         GR                  S _[         GR                  S _[         GR                  S _[         GR                  GSS j_[         GR                  S _[         GR                  GSS j_[         GR                  GSS j_[         GR                  GSS j_[         GR                  GSS j_[         GR                  GSS j_[         GR                  GSS j_[         GR                  GSS j_[         GR                  GSS j_[         GR                  GSS j_[         GR                  GSS j_[         R                  GR                  S _[         GR                  GSS j_E0 [         GR                  S _[         GR                  GSS j_[         GR                  GSS j_[         GR                  GSS j_[         GR                  GSS j_[         GR                  GSS j_[         GR                  S _[         GR                  S _[         GR                  GSS j_[         GR                  GSS j_[         GR                  S _[         GR                  GSGS  j_[         GR                  GS _[         GR                  GSGS j_[         GR                  GS _[         GR                  GS _[         GR                  GSGS j_E0 [         GR                  GSGS j_[         GR                   GS _[         GR                  GS _[         GR                  GSGS	 j_[         R                  GR                  GSGS
 j_[         R                  GR                  GSGS j_[         GR
                  GS _[         GR                  GS _[         GR                  GS _[         GR                  GS _[         GR                  GS _[         GR                  GS _[         GR                  GS _[         GR                  GS _[         GR                  GS _[         GR                  GSGS j_[         GR                  GS _E0 [         GR                   GS	GS j_[         GR"                  GS
GS j_[         GR$                  GS _[         GR&                  GSGS j_[         R                  GR(                  GSGS j_[         R                  GR*                  GSGS j_[         R                  GR,                  GSGS j_[         GR.                  GSGS j_[         GR0                  GSGS j_[         GR2                  GSGS  j_[         GR4                  GSGS! j_[         GR6                  GSGS" j_[         GR8                  GSGS# j_[         GR:                  GSGS$ j_[         GR<                  GSGS% j_[         GR>                  GSGS& j_[         GR@                  GSGS' j_E0 [         GRB                  GSGS( j_[         GRD                  GSGS) j_[         GRF                  GSGS* j_[         GRH                  GSGS+ j_[         GRJ                  GSGS, j_[         GRL                  GS- _[         GRN                  GSGS. j_[         GRP                  GSGS/ j_[         GRR                  GSGS0 j_[         GRT                  GSGS1 j_[         GRV                  GSGS2 j_[         GRX                  GSGS3 j_[         GRZ                  GSGS4 j_[         GR\                  GS5 _[         GR^                  GSGS6 j_[         GR`                  GSGS7 j_[         GRb                  GSGS8 j_E0 [         GRd                  GSGS9 j_[         GRf                  GSGS: j_[         GRh                  GSGS; j_[         GRj                  GS< _[         GRl                  GS= _[         GRn                  GSGS> j_[         GRp                  GSGS? j_[         R                  GRd                  GSGS@ j_[         R                  GRr                  GSGSA j_[         R                  GRt                  GSGSB j_[         R                  GRf                  GSGSC j_[         R                  GRp                  GSGSD j_[         GRv                  GSE _[         R                  GRv                  GSGSF j_[         R                  GRx                  GSGSG j_[         R                  GRz                  GSGSH j_[         GR|                  GSI _E0 [         R                  GR|                  GSJ _[         GR~                  GSGSK j_[         GR                  GSGSL j_[         GR                  GSGSM j_[         GR                  GSGSN j_[         GR                  GSGSO j_[         GR                  GSGSP j_[         GR                  GSGSQ j_[         GR                  GSGSR j_[         GR                  GSGSS j_[         GR                  GSGST j_[         GR                  GSGSU j_[         GR                  GSV _[         GR                  GSGSW j_[         GR                  GSGSX j_[         GR                  GSGSY j_[         GR                  GSZ _E0 [         GR                  GS[ _[         GR                  GS\ _[         GR                  GS] _[         GR                  GS^ _[         GR                  GS_ _[         GR                  GS` _[         GR                  GSGSa j_[         GR                  GSGSb j_[         GR                  GSc _[         GR                  GSd _[         GR                  GSGSe j_[         GR                  GSGSf j_[         GR                  GSGSg j_[         GR                  GSGSh j_[         GR                  GSGSi j_[         GR                  GSj _[         GR                  GSk _E0 [         GR                  GSGSl j_[         GR                  GSm _[         GR                  GSn _[         GR                  GSo _[         GR                  GSGSp j_[         GR                  GSGSq j_[         GR                  GSr _[         GR                  GSGSs j_[         GR                  GSt _[         GR                  GSGSu j_[         GR                  GSGSv j_[         GR                  GSGSw j_[         GR                  GSGSx j_[         GR                  GSGSy j_[         GR                  GR                  GR                  GSz _[         GR                  GR                  GR                  GS{ _[         GR                  GR                  R
                  GSGS| j_E0 [         GR                  GR                  GR                  GSGS} j_[         GR                  GR                  GR                  GSGS~ j_[         GR                  GR                  GR                  GSGS j_[         GR                  GR                  GR                  GSGS j_[         GR                  GR                  GR                  GSGS j_[         GR                  GR                  GR                  GSGS j_[         GR                  GR                  R*                  GSGS j_[         GR                  GR                  GR                  GSGS j_[         GR                  GR                  GR                  GSGS j_[         GR                  GR                  R\                  GSGS j_[         GR                  GR                  Rn                  GSGS j_[         GR                  GR                  GR                  GSGS j_[         GR                  GR                  Rp                  GSGS j_[         GR                  GR                  R                  GSGS j_[         GR                  GR                  R                  GSGS j_[         GR                  GR                  GR                  GSGS j_[         GR                  GR                  R                  GSGS j_E0 [         GR                  GR                  GR                  GSGS j_[         GR                  GR                  GR                  GSGS j_[         GR                  GR                  GR                  GSGS j_[         GR                  GR                  GR                  GSGS j_[         GR                  GR                  GR                  GSGS j_[         GR                  GR                  GR.                  GSGS j_[         GR                  GR                  GR0                  GSGS j_[         GR                  GR                  GRX                  GSGS j_[         GR                  GR                  GR                   GSGS j_[         GR                  GR                  GR                  GSGS j_[         GR                  GR                  GR                  GSGS j_[         GR                  GR                  GR                  GSGS j_[         GR                  GR                  GR                  GSGS j_[         GR                  GR                  GR
                  GSGS j_[         GR                  GR                  GR                  GS GS j_[         GR                  GR                  GR                  GS!GS j_[         GR                  GR                  GR                  GS"GS j_E0 [         GR                  GR                  GR                  GSGS j_[         GR                  GR                  GR                  GS#GS j_[         GR                  GR                  GR                  GSGS j_[         GR                  GR                  GR                  GS$GS j_[         GR                  GR                  GR                  GSGS j_[         GR                  GR                  GR                   GS%GS j_[         GR                  GR                  GR                  GS&GS j_[         GR                  GR                  GR"                  GS
GS j_[         GR                  GR                  GR                  GS'GS j_[         GR                  GR                  GR.                  GSGS j_[         GR                  GR                  GR                  GS(GS j_[         GR                  GR                  GR                  GSGS j_[         GR                  GR                  GR                  GS)GS j_[         GR                  GR                  GR@                  GS*GS j_[         GR                  GR                  GR                   GS _[         GR                  GR                  GR"                  GSGS j_[         GR                  GR                  GR$                  GSGS j_E0 [         GR                  GR                  GR&                  GSGS j_[         GR                  GR                  GRh                  GSGS j_[         GR                  GR                  GR                  GSGS j_[         GR                  GR                  GR                  GSGS j_[         GR                  GR                  GR                  GSGS j_[         GR                  GR                  GR(                  GSGS j_[         GR                  GR                  GR                  GSGS j_[         GR                  GR                  GR*                  GSGS j_[         GR                  GR                  GR,                  GS+GS j_[         GR                  GR                  GR.                  GS+GS j_[         GR                  GR                  GR0                  GS+GS j_[         GR                  GR                  GR2                  GS'GS j_[         GR                  GR                  GR4                  GS,GS j_[         GR                  GR                  GR6                  GS-GS j_[         GR                  GR                  GR8                  GS.GS j_[         GR                  GR                  GR:                  GSGS j_[         GR                  GR                  GR<                  GS/GS j_E0 [         GR                  GR                  GR>                  GS0GS j_[         GR                  GR                  GR@                  GS!GS j_[         GR                  GR                  GRB                  GS1GS j_[         GR                  GR                  GRD                  GS2GS j_[         GR                  GR                  GRF                  GS3GS j_[         GR                  GR                  GRH                  GS _[         GR                  GR                  GRJ                  GSGS j_[         GR                  GR                  GRL                  GSGS j_[         GR                  GR                  GRN                  GS4GS j_[         GR                  GR                  GRP                  GS5GS j_[         GR                  GR                  GRR                  GSGS j_[         GR                  GR                  GRT                  GSGS j_[         GR                  GR                  GRV                  GSGS j_[         GR                  GR                  GRX                  GS6GS j_[         GR                  GR                  GRZ                  GS7GS j_[         GR                  GR                  GR\                  GS8GS j_[         GR                  GR                  GR^                  GS.GS j_E0 [         GR                  GR                  GR`                  GS*GS j_[         GR                  GR                  GRb                  GS*GS j_[         GR                  GR                  GRd                  GS9GS j_[         GR                  GR                  GRf                  GSGS j_[         GR                  GR                  GRh                  GS _[         GR                  GR                  GRj                  GS _[         GR                  GR                  GRl                  GSGS j_[         GR                  GR                  GRn                  GS:GS j_[         GR                  GR                  GRp                  SSNSS9GS.GS j_[         GR                  GR                  GRr                  GSGS j_[         GR                  GRt                  GRv                  GS;GS j_[         GR                  GRt                  GRx                  GS;GS j_[         GR                  GRt                  GRz                  GS _[         GR                  GRt                  GR|                  GS<GS j_[         GR~                  GSGS j_[         GR                  SzGS.GS j_[         GR                  GS _E0 [         GR                  GS=GS j_[         R                  GR                  GS>GS j_[         R                  GR                  GS?GS j_[         R                  GR                   GS@GS j_[         GR                  GSAGS j_[         GR                  GS=GS j_[         GR                  GS _[         GR                  GS _[         GR                  GSBGS j_[         GRD                  GS2GS j_[         GR                  GS _[         GR                  GSCGS j_[         GR                  GSGS j_[         GR                  GSDGS j_[         R                  GR                  GSEGS j_[         GR                  GS _[         GR                  GS _E0 [         GR                  GSGS j_[         GRF                  GS _[         GR                  GSGS j_[         GR                  GSGS j_[         GRH                  GS _[         GR                  GSGS j_[         GR                  GSGS j_[         GR                  GSGS j_[         GR                  GSGS j_[         GR                  GS _[         GR                  GS  _[         GR                  GS _[         GR                  GS _[         GR                  GS _[         GR                  GSGS j_[         R                  GR                  GSFGS j_[         GR                  GSGGS j_E0 [         GR                  GSGGS j_[         GR                  GS _[         GR                  GS	 _[         GR                  GS
 _[         GR                  GS _[         GR                  GS _[         GR                  GS _[         GR                    GSHGS j_[         GR                    GSIGS j_[         GR                    GSJGS j_[         GR                  GS _[         GR                  GS _[         GR                  GSGS j_[         GR                  GS _[         GR                  GSGS j_[         GR                  GSGS j_[         R                  GR                  GSGS j_E0 [         GR                  GS _[         GR                  GS _[         GR                  GSGS j_[         GRJ                  GSGS j_[         GR                  GSGS j_[         GR                  GSGS j_[         GR                  GSGS  j_[         GR                  GS! _[         GRN                  GS4GS" j_[         GR                  GS# _[         GR                  GSGS$ j_[         GR                  GS% _[         GR                  GSGS& j_[         GR                  GSGS' j_[         GR                  GSKGS) j_[         GR                  GSGS* j_[         GR                  GSGS+ j_E0 [         GR                  GS, _[         GRP                  GS5GS- j_[         GR                   GSGS. j_[         GR                  GSGS/ j_[         GR                  GSGS0 j_[         GR                  GS1 _[         GR                  GS2 _[         GR
                  GSGS3 j_[         GR                  GSGS4 j_[         GR                  GSLGS5 j_[         GR                  GS6 _[         GR                  GS7 _[         GR                  GSMGS8 j_[         GR                  GSMGS9 j_[         GRR                  GSGS: j_[         GR                  GSGS; j_[         GR                  GSGS< j_E0 [         GR                  GSGS= j_[         GR                  GSGS> j_[         GR                   GSGS? j_[         GR"                  GSGS@ j_[         GR$                  GSGSA j_[         GR&                  GSB _[         R                  GR&                  GSC _[         GR(                  GSGSD j_[         GR*                  GSGSE j_[         GR`                  GSGSF j_[         R                  GR,                  GSGSG j_[         R                  GR.                  GSGSH j_[         GR0                  GSNSSGSI.GSJ jj_[         GR2                  GSGSK j_[         GR4                  GSGSL j_[         GR6                  GSGSM j_[         GR8                  GSGSN j_E0 [         GR:                  GSGSO j_[         GR<                  GSGSP j_[         GR>                  GSGSQ j_[         GR@                  GSGSR j_[         GRB                  GSGSS j_[         GRD                  GSOGST j_[         GRF                  GSGSU j_[         GRH                  GSGSV j_[         GRJ                  GSGSW j_[         GRL                  GSX _[         GRN                  GSY _[         GRP                  GSZ _[         GRR                  GS[ _[         GRT                  GS\ _[         GRV                  GS] _[         GRX                  GS^ _[         GRZ                  GS_ _E0 [         GR\                  GS` _[         GR^                  GSa _[         GR`                  GSb _[         GRb                  GSc _[         GRd                  GSd _[         GRf                  GSe _[         GRh                  GSf _[         GRj                  GSg _[         GRl                  GSh _[         GRn                  GSGSi j_[         GRp                  GSPGSj j_[         GRr                  GSQGSk j_[         R                  GRp                  GSGSl j_[         R                  GRt                  GSGSm j_[         GRv                  GSn _[         GRx                  GSo _[         GRz                  GR|                  GSp _E0 [         GRz                  GR~                  GSq _[         GRz                  GR                  GSr _[         GRz                  GR                  GSs _[         GRz                  GR                  GSt _[         GRz                  GR                  GSGSu j_[         GRz                  GR                  GSGSv j_[         GRz                  GR                  GSGSw j_[         GRz                  GR                  GSGSx j_[         GRz                  GR                  GSy _[         GRz                  GR                  GSz _[         GRz                  GR8                  GS{ _[         GRz                  GR:                  GS| _[         GRz                  GR                  GS} _[         GRz                  GR<                  GS~ _[         GRz                  GR@                  GS _[         GRz                  GR                  GS _[         GRz                  GRB                  GS _E0 [         GRz                  GR                  GSGS j_[         GRz                  GR                  GSGS j_[         GRz                  GR                  GS _[         GRz                  GR                  GSGS j_[         GRz                  GR                  GSGS j_[         GRz                  GR                  GS _[         GRz                  GR                  GS _[         GRz                  GR                  GS _[         GRz                  GR                  GS _[         GRz                  GR                  GSGS j_[         GRz                  GR                  GSGS j_[         GRz                  GRD                  GS _[         GRz                  GR                  GS _[         GRz                  GR@                  GSGS j_[         GRz                  GRX                  GS _[         GRz                  GRZ                  GSGS j_[         GRz                  GR                  GS _E0 [         GRz                  GR                  GS _[         GRz                  GR                  GS _[         GRz                  GR                  GS _[         GRz                  GR                  GS _[         GRz                  GR                  GS _[         GRz                  GR                  GS _[         GRz                  GR                  GSGS j_[         GRz                  GR                  GS _[         GRz                  GR                  GS _[         GRz                  GR                  GS _[         GRz                  GR                  GS _[         GRz                  GR                  GSGS j_[         GRz                  GR                  GSGS j_[         GRz                  GR                  GSGS j_[         GRz                  GR                  GSGS j_[         GRz                  GR"                  GS _[         GRz                  GR`                  GSGS j_E0 [         GRz                  GR                  GS _[         GRz                  GR                  GSGS j_[         GRz                  GRN                  GSGS j_[         GRz                  GR                  GSGS j_[         GR                  GS _[         GR                  GS _[         GR                  GSGS j_[         GR                  GSGS j_[         GR                  GSGS j_[         R                  GR                  GSGS j_[         R                  GR                  GSGS j_[         GR                  GSRGS j_[         GR                  GSGS j_[         GRl                  GSGS j_[         GR                  GS _[         GR                  GSGS j_[         GR                  GS _E0 [         GR                  GS _[         GR                  GSGS j_[         GR                  GSGS j_[         GR                  GSSGS j_[         R                  GR                  GSBGS j_[         GR                  GSGS j_[         GRn                  GS:GS j_[         GR                  GSGS j_[         GR                  GS _[         GR                  GSGS j_[         GR                  GSGS j_[         GR                  GS _[         GR                  GSTGS j_[         GR                  GSGS j_[         GR                  GS _[         GR                   GSGS j_[         GR                  GSGS j_E0 [         GR                  GSGS j_[         GR                  GSGS j_[         R                  GR                  GSGS j_[         GR
                  GSGS j_[         GR                  GSGS j_[         GR                  GS _[         GR                  GSGS j_[         GR                  GSGS j_[         GR                  GS _[         GR                  GS _[         GR                  GSGS j_[         GR                  GS _[         GR                  GS _[         GR                  GS _[         GR                   GS _[         GR"                  GS _[         GR$                  GS _E0 [         GR&                  GSGS j_[         GR(                  GS _[         GR*                  GSGS j_[         GR,                  SGS.GS j_[         GR.                  GS _[         GR0                  GS _[         GR2                  GS _[         GR4                  GS _[         GR6                  GS _[         GR8                  GSMGS j_[         GR:                  GSGS j_[         GR<                  GSGS j_[         GR>                  GS _[         GR@                  GS _[         GRB                  GS _[         GRD                  GS _[         GRF                  GS _E0 [         GRH                  GS _[         GRJ                  GS _[         GRL                  GS _[         GRN                  GS _[         GRP                  GS _[         GRR                  GS _[         GRT                  GS _[         GRV                  GSGS j_[         GRX                  GS _[         GRZ                  GS _[         GR\                  GS _U GR^                  GS _U GR`                  GS _U GRb                  GS _U GRd                  GS _U GRf                  GS _U GRh                  GS _E0 U GRj                  GS _U GRl                  GS _U GRn                  GS _U GRp                  GS _U GRr                  GS _U GRt                  GS _U GRv                  GS  _U GRx                  GS _U GRz                  GS _U GR|                  GS _U GR~                  GS _U GR                  GS _U GR                  GS _U GR                  GS _U GR                  GS _U GR                  GS	 _U GR                  GS
 _E0 U GR                  GS _U GR                  GS _U GR                  GS _U GR                  GS _U GR                  GS _U GR                  GS _U GR                  GS _U GR                  GS _U GR                  GS _U GR                  GS _U GR                  GS _U GR                  GS _U GR                  SGS.GS j_U GR                  GS _U GR                  GS _U GR                  GR                  GS _U GR                  GR                  GS _E0 U GR                  GR                  GS _U GR                  GR                  GS _U GR                  GR                  GS _U GR                  GR                  GS  _U GR                  GR                  GS! _U GR                  GR                  GS" _U GR                  GR                  GS# _U GR                  GR                  GS$ _U GR                  GR                  GS% _U GR                  GR                  GS& _U GR                  GR                  GS' _U GR                  GR                  GS( _U GR                  GS) _U GR                  GS* _U GR                  GS+ _U GR                  GR                  GS, _U GR                  GR                  GS- _E0 U GR                  GR                  GS. _U GR                  GR                  GS/ _U GR                  GR                  GS0 _U GR                  GR                  GS1 _U GR                  GR                  GS2 _U GR                  GR                  GS3 _U GR                  GR                  GS4 _U GR                  GR                  GS5 _U GR                  GR                  GS6 _U GR                  GR                  GS7 _U GR                  GR                  GS8 _U GR                  GR                  GS9 _U GR                  GR                  GS: _U GR                  GR                  GS; _U GR                  GR                  GS< _U GR                  GR                  GS= _U GR                  GR                  GS> _E0 U GR                  GR                  GS? _U GR                  GR                  GS@ _U GR                  GR                  GSA _U GR                  GR                  GSB _U GR                  GR                  GSC _U GR                  GR                  GSD _U GR                   GR                  GSE _U GR                  GR                  GSF _U GR                  GR                  GSG _U GR                  GR                  GSH _U GR                  GR                  GSI _U GR                  GR                  GSJ _U GR                  GR                  GSK _U GR
                  GR                  GSL _U GR                  GSGSM j_U GR                  GSN _U GR                  GSO _E0 U GR                  GSP _U GR                  GSQ _U GR                  GSR _U GR                  GSS _U GR                  GST _U GR                  GSU _U GR                  GSV _U GR                   GSW _U GR"                  GSX _U R                  GSY _U GR$                  GSZ _U GR&                  GS[ _U GR(                  GS\ _U GR*                  GS] _U GR,                  GS^ _U GR.                  GSGS_ j_U GR0                  [         GR2                  4GS` j_E0 U GR4                  [         GR2                  4GSa j_U GR6                  [         GR2                  4GSb j_U GR8                  [         GR2                  4GSc j_U GR:                  GS(SGSd.GSe jj_U GR<                  GSf _U GR>                  GSg _U GR@                  [         GRB                  4GSh j_U GRD                  GSGSi j_U GRF                  [         GR2                  4GSj j_U GRH                  [         GR2                  4GSk j_U GRJ                  [         GR2                  4GSl j_U GRL                  [         GR2                  4GSm j_U GRN                  [         GR2                  4GSn j_U GRP                  GSo _U GRR                  GSp _U GR                  GSGSq j_U GRT                  GSr _E0 U GRV                  GSGSs j_U GRX                  [         GR2                  4GSt j_U GRZ                  [         GR2                  4GSu j_U GR\                  GSv _U GR^                  GSw _U GR`                  GSx _U GRb                  GSSGSd.GSy jj_U GRd                  GSz _U GRf                  GS{ _U GRh                  [         GR2                  4GS| j_U GRj                  [         GR2                  4GS} j_U GRl                  SGSd.GS~ j_U GR                  GS _U GRn                  [         GR2                  4GS j_U GRp                  [         GR2                  4GS j_U GRr                  GS _U GRt                  GS _E0 U GRv                  [         GR2                  4GS j_U GRx                  GS _U GRz                  GS _U GR                  GS _U GR|                  GS _U GR~                  GS _U GR                  GS _U GR                  GS _U GR                  GSUSGSd.GS jj_U GR@                  GS _U GR                  [         GR2                  4GS j_U GR                  GS _U GR                  GS _U GR                  GSGS j_U GR                  GSGS j_U GR.                  GS _U GR                  GS _E0 U GR                  GS _U GR                  GS _U GR                  GS _U GR                  GS _U GRx                  GS _U GR                  GS _U GR                  GS _U GR                  GS _U GR                  GSGS j_U GR                  GS _U GR                  GSSGSd.GS jj_U GR                  GS _U GR                  GS _U GR                  GS _U GR                  GS _U GR                  GS _U GR                  GS _E0 U GR                  GSGS j_U GR                  GS _U GR                  GS _U GR                  GS _U GR                  GS _U GR                  GS _U GR                  GS _U GR                  GSVGS j_U GR                  GS _U GR                  GS _U GR                  [         GR2                  4GS j_U GR                  GS _U GR                  GSMGS j_U GR                  GS _U GR                  GS _U GR                  GSGS j_U GR                  GS _E0 U GR                  GS _U GR<                  GSGS j_U GR                  GS _U GR                  GS _U GR                  GS _U GR                  GS _U GR                  GS _U GR                  GS _U GR                  SS[         GR2                  4GS j_U GR                  GSSGS.GS jj_U GR                  GSGS j_U GR                  GS _U GR                  GS _U GR                  GS _U GR                  GS _U GRr                  GS _U GRv                  GS(GS j_EU GR                  GS U GR                  GS U GR                  GS U GR                  GS U GR                  GSWGS jU GR                  GS U GR                  GS [         R                  GR                  GSGS j0En[         GR                  GR                  GR                  nG[        X5      (       a5  GSGS jUG[        X5      '   GS UG[        U GSU 35      GR                  '   0 nG[        5       nUGR                  5        GH  u  pVUGR                  UGR                  GS-   GSUGR                  -   GS-   GSUGR                  -   GS-   GSUGR                  -   GS-   /nUGR                  GR                  GS5      (       aH  UGR                  G[	        GS5      S nUGR                  GSU-   GS-   GSU-   GS-   GSU-   GS-   /5        U H5  n	G[        X	S5      n
G[        U
5      (       d  M#  X;  d  M*  X;  d  M1  XcU
'   M7     GM	     UGR                  U5        U$ (X  a:  Return a dict containing dummy overrides for all overridable functions

Returns
-------
Dict[Callable, Callable]
    A dictionary that maps overridable functions in the PyTorch API to
    lambda functions that have the same signature as the real function
    and unconditionally return -1. These lambda functions are useful
    for testing API coverage for a type that defines ``__torch_function__``.

Examples
--------
>>> import inspect
>>> my_add = torch.overrides.get_testing_overrides()[torch.add]
>>> inspect.signature(my_add)
<Signature (input, other, out=None)>
Nc                     gN inputouts     r-   <lambda>'get_testing_overrides.<locals>.<lambda>      2r1   c                     grE  rG  rH  s     r-   rK  rL        r1   c                     grE  rG  rI  output_sizes     r-   rK  rL        br1   c                     grE  rG  )inputsrR  s     r-   rK  rL        rr1   c                     grE  rG  rH  s     r-   rK  rL        Br1   c                     grE  rG  rI  s    r-   rK  rL        Rr1   c                     grE  rG  rH  s     r-   rK  rL        br1   c                     grE  rG  rH  s     r-   rK  rL        Rr1   c                     grE  rG  rH  s     r-   rK  rL        rr1   c                     grE  rG  rI  otherrJ  s      r-   rK  rL        "r1   c                     grE  rG  rI  batch1batch2alphabetarJ  s         r-   rK  rL        rr1   c                     grE  rG  rI  tensor1tensor2valuerJ  s        r-   rK  rL        "r1   c                     grE  rG  rn  s        r-   rK  rL    rr  r1   c                     grE  rG  rI  mat1mat2rk  rj  rJ  s         r-   rK  rL    rr  r1   c                     grE  rG  )rI  matvecrk  rj  rJ  s         r-   rK  rL        r1   c                     grE  rG  )rI  vec1vec2rk  rj  rJ  s         r-   rK  rL        r1   c                     grE  rG  thetasizealign_cornerss      r-   rK  rL    r{  r1   c                     grE  rG  rI  dims     r-   rK  rL    rM  r1   Fc                     grE  rG  )rI  rd  trolatol	equal_nans        r-   rK  rL        VXr1   c                     grE  rG  rI  ptraininplaces       r-   rK  rL        Br1   c                     grE  rG  r  s     r-   rK  rL    rX  r1   c                     grE  rG  r  s     r-   rK  rL    rX  r1   c                     grE  rG  rI  r  keepdimrJ  s       r-   rK  rL    r{  r1   c                     grE  rG  rH  s     r-   rK  rL    r_  r1   c                     grE  rG  r  s       r-   rK  rL    r  r1   c                     grE  rG  rZ  s    r-   rK  rL        Br1   c                     grE  rG  rZ  s    r-   rK  rL    r  r1   c                     grE  rG  r  s     r-   rK  rL    ra  r1   c                     grE  rG  rH  s     r-   rK  rL    rX  r1   c                     grE  rG  )rI  msgs     r-   rK  rL    rO  r1   c                     grE  rG  rH  s     r-   rK  rL    r]  r1   c                     grE  rG  rH  s     r-   rK  rL    r_  r1   c                     grE  rG  rH  s     r-   rK  rL    ra  r1   c                     grE  rG  rH  s     r-   rK  rL    rX  r1   c                     grE  rG  rH  s     r-   rK  rL    r]  r1   c                     grE  rG  rc  s      r-   rK  rL        Br1   c                     grE  rG  rc  s      r-   rK  rL        br1   c                     grE  rG  rH  s     r-   rK  rL    r_  r1   c                     grE  rG  rH  s     r-   rK  rL    ra  r1   c                      grE  rG  tensorss    r-   rK  rL    rM  r1   c                      grE  rG  r  s    r-   rK  rL    rM  r1   c                      grE  rG  r  s    r-   rK  rL    rM  r1   c                     grE  rG  )rI  kernel_sizer  padding	ceil_modecount_include_pads         r-   rK  rL        vxr1   c                     grE  rG  rg  s         r-   rK  rL        PRr1   c	                     grE  rG  )	rI  weightbiasrunning_meanrunning_vartrainingmomentumepscudnn_enableds	            r-   rK  rL        y{r1   c                     grE  rG  )grad_outrI  meaninvstdr  sum_dy
sum_dy_xmucount_tensors           r-   rK  rL    r  r1   c                     grE  rG  )r  rI  r  r  r  input_gweight_gbias_gs           r-   rK  rL        sur1   c                     grE  rG  )rI  r  r  r  r  r  s         r-   rK  rL    rl  r1   c                     grE  rG  rI  r  r  r  r  r  r  counts           r-   rK  rL        tvr1   c                     grE  rG  r  s           r-   rK  rL    	      ACr1   c                     grE  rG  rI  r  s     r-   rK  rL        2r1   c                     grE  rG  )rI  r  r  r  s       r-   rK  rL        Z\r1   c                     grE  rG  )rI  	generatorrJ  s      r-   rK  rL        r1   c                     grE  rG  input1input2r  r  s       r-   rK  rL        Rr1   r  c                     grE  rG  rI  targetr  size_averagereduce	reduction
pos_weights          r-   rK  rL        rtr1   c                     grE  rG  )rI  weights	minlengths      r-   rK  rL    r  r1   c                     grE  rG  )r  probr  s      r-   rK  rL        Br1   c                     grE  rG  rc  s      r-   rK  rL        "r1   c                     grE  rG  rH  s     r-   rK  rL    r  r1   c                     grE  rG  rc  s      r-   rK  rL        r1   c                     grE  rG  rc  s      r-   rK  rL    r  r1   c                     grE  rG  rc  s      r-   rK  rL     r  r1   c                     grE  rG  rc  s      r-   rK  rL        "r1   c                      grE  rG  r  s    r-   rK  rL    rM  r1   c                     grE  rG  rI  rw  	out_dtyperJ  s       r-   rK  rL    r  r1   c                      grE  rG  r  s    r-   rK  rL    re  r1   c                     grE  rG  selfr  s     r-   rK  rL    ra  r1   c                     grE  rG  )rI  
boundaries	out_int32rightrJ  s        r-   rK  rL        []r1   c                      grE  rG  r  s    r-   rK  rL    ra  r1   c                     grE  rG  r  r  rJ  s      r-   rK  rL    r  r1   c                     grE  rG  r	  s      r-   rK  rL  	      rr1   c                     grE  rG  r	  s      r-   rK  rL  
  r  r1   c                     grE  rG  )x1x2r  compute_modes       r-   rK  rL        _ar1   c                     grE  rG  rH  s     r-   rK  rL    rX  r1         ?c                     grE  rG  rI  rj  r  s      r-   rK  rL    r  r1   )rJ  c                     grE  rG  )rJ  matricess     r-   rK  rL        r1   c                     grE  rG  rI  groupss     r-   rK  rL        Rr1   c                     grE  rG  rI  upperrJ  s      r-   rK  rL    r  r1   c                     grE  rG  rH  s     r-   rK  rL    r  r1   c                     grE  rG  rI  check_errorsrJ  s      r-   rK  rL        br1   c                     grE  rG  r  s      r-   rK  rL        Rr1   c                     grE  rG  )r  r  r  rJ  s       r-   rK  rL        Br1   c                     grE  rG  )rI  numeln_binsratio	bit_widths        r-   rK  rL        WYr1   c                     grE  rG  rI  chunksr  s      r-   rK  rL    re  r1   c                     grE  rG  rI  minmaxrJ  s       r-   rK  rL    r  r1   c                     grE  rG  r3  s       r-   rK  rL        r1   c                     grE  rG  )rI  r4  rJ  s      r-   rK  rL    r  r1   c                     grE  rG  )rI  r5  rJ  s      r-   rK  rL    r  r1   c                     grE  rG  r  rJ  s     r-   rK  rL    r  r1   c                     grE  rG  )rI  
correctionfweightsaweightss       r-   rK  rL        Rr1   c                     grE  rG  rZ  s    r-   rK  rL        2r1   c                     grE  rG  )rI  rwith_replacements      r-   rK  rL        rr1   c                     grE  rG  )realimags     r-   rK  rL        "r1   c                     grE  rG  rc  s      r-   rK  rL     r  r1   c                     grE  rG  )absangs     r-   rK  rL  !      br1   c                     grE  rG  )rI  ords     r-   rK  rL  "  r  r1   c                     grE  rG  rH  s     r-   rK  rL  #  rX  r1   c                     grE  rG  rH  s     r-   rK  rL  $  r  r1   c                     grE  rG  rH  s     r-   rK  rL  %  r  r1   c                     grE  rG  rH  s     r-   rK  rL  &  r  r1   c                     grE  rG  )rI  padrq  s      r-   rK  rL  '      2r1   c                     grE  rG  rI  r  r  r  r  dilationr  s          r-   rK  rL  (      bdr1   c                     grE  rG  rZ  s          r-   rK  rL  )  r\  r1   c                     grE  rG  rZ  s          r-   rK  rL  *  r\  r1   c	                     grE  rG  )	rI  r  r  r  r  r[  
transposedoutput_addingr  s	            r-   rK  rL  +      uwr1   c                     grE  rG  )rI  r  r  rW  s       r-   rK  rL  ,  rX  r1   c                     grE  rG  rI  r  r  r  r  output_paddingr  r[  s           r-   rK  rL  -  	      Ar1   c                     grE  rG  re  s           r-   rK  rL  .  rg  r1   c                     grE  rG  re  s           r-   rK  rL  /  rg  r1   c                     grE  rG  rZ  s    r-   rK  rL  0  rO  r1   c                     grE  rG  rH  s     r-   rK  rL  1  rM  r1   c                     grE  rG  r  r  r  marginr  r  r  s          r-   rK  rL  2  r  r1   c                     grE  rG  rH  s     r-   rK  rL  3  rX  r1   c                     grE  rG  )r  r  r  r  s       r-   rK  rL  4  r  r1   c                     grE  rG  rZ  s    r-   rK  rL  5  rM  r1   c                     grE  rG  rI  rd  r  rJ  s       r-   rK  rL  6  rS  r1   rF  c                     grE  rG  rs  s       r-   rK  rL  7      2r1   c                     grE  rG  	log_probstargetsinput_lengthstarget_lengthsblankr  zero_infinitys          r-   rK  rL  9  r  r1   c                     grE  rG  rI  r  rJ  s      r-   rK  rL  ;  r  r1   c                     grE  rG  r  s      r-   rK  rL  <  r  r1   c                     grE  rG  rI  r  rJ  r`   s       r-   rK  rL  =  r7  r1   c                     grE  rG  r  s       r-   rK  rL  >  rV  r1   c                     grE  rG  yxr  s      r-   rK  rL  ?  rS  r1   c                     grE  rG  r  s      r-   rK  rL  @  r  r1   c                     grE  rG  rH  s     r-   rK  rL  A  ra  r1   c                     grE  rG  rZ  s    r-   rK  rL  B      r1   c                     grE  rG  rZ  s    r-   rK  rL  C      r1   c                     grE  rG  rZ  s    r-   rK  rL  D  r  r1   c                     grE  rG  rZ  s    r-   rK  rL  E  r  r1   c                     grE  rG  rI  diagonalrJ  s      r-   rK  rL  F  r  r1   c                     grE  rG  r  s      r-   rK  rL  G  rS  r1   c                     grE  rG  )rI  offsets     r-   rK  rL  H  rO  r1   c                     grE  rG  )rI  nr  prependappendrJ  s         r-   rK  rL  I      TVr1   c                     grE  rG  rI  r  dim1dim2s       r-   rK  rL  J  r7  r1   c                     grE  rG  r  s       r-   rK  rL  K  r  r1   c                     grE  rG  )rI  srcr  r  r  s        r-   rK  rL  L  r@  r1   c                     grE  rG  )r  r  r  r  storage_offsets        r-   rK  rL  M  r.  r1   c                     grE  rG  rH  s     r-   rK  rL  N  ra  r1   c                     grE  rG  )rI  rd  r  s      r-   rK  rL  O  r]  r1   c                     grE  rG  rI  rd  rounding_moderJ  s       r-   rK  rL  P      br1   c                     grE  rG  r  s       r-   rK  rL  Q  r  r1   c                     grE  rG  rc  s      r-   rK  rL  R  re  r1   c                     grE  rG  r  s       r-   rK  rL  S  rS  r1   c                     grE  rG  rI  rw  r  s      r-   rK  rL  T  r  r1   c                     grE  rG  )rv  rw  s     r-   rK  rL  U      rr1   c                     grE  rG  rI  indices_or_sectionss     r-   rK  rL  V  r  r1   c                     grE  rG  r;  s     r-   rK  rL  W  rO  r1   c                     grE  rG  rH  s     r-   rK  rL  X  re  r1   c                     grE  rG  rH  s     r-   rK  rL  Y  r  r1   c                     grE  rG  rI  UPLOrJ  s      r-   rK  rL  Z  r  r1   c                     grE  rG  r  s      r-   rK  rL  [  r  r1   c                     grE  rG  )equationoperandss     r-   rK  rL  \  re  r1   c                     grE  rG  rI  r  padding_idxmax_norm	norm_typescale_grad_by_freqr   s          r-   rK  rL  ^      z|r1   c
                     grE  rG  )
rI  r  offsetsr  r  r  moder   per_sample_weightsr  s
             r-   rK  rL  a  s	      hjr1   c                     grE  rG  rI  r`   rn   r_   requires_grads        r-   rK  rL  c      cer1   c                     grE  rG  rc  s      r-   rK  rL  d      r1   c                     grE  rG  rI  rd  s     r-   rK  rL  e  rJ  r1   c                     grE  rG  rH  s     r-   rK  rL  f  rM  r1   c                     grE  rG  rH  s     r-   rK  rL  g  rX  r1   c                     grE  rG  rH  s     r-   rK  rL  h  r]  r1   c                     grE  rG  rH  s     r-   rK  rL  i  rM  r1   c                     grE  rG  rH  s     r-   rK  rL  j  rX  r1   c                     grE  rG  rH  s     r-   rK  rL  k  r_  r1   c                     grE  rG  )rI  scale
zero_pointaxis	quant_min	quant_maxs         r-   rK  rL  l      mor1   c                     grE  rG  )rI  r  r  r  r  s        r-   rK  rL  m      fhr1   c                     grE  rG  )r  observer_onfake_quant_onaveraging_construnning_minrunning_maxr  r  r  r  ch_axisper_row_fake_quantsymmetric_quants                r-   rK  rL  o  s	      ACr1   c                     grE  rG  rI  packed_weightr  outputs       r-   rK  rL  q  r  r1   c                     grE  rG  r  s       r-   rK  rL  r      dfr1   c                     grE  rG  rI  r  packedcol_offsetsweight_scaleweight_zero_pointr  s          r-   rK  rL  s      {}r1   c                     grE  rG  r  s          r-   rK  rL  u      ^`r1   c                     grE  rG  rZ  s    r-   rK  rL  w  rX  r1   c                     grE  rG  rZ  s    r-   rK  rL  x  r  r1   c                     grE  rG  )rI  abs      r-   rK  rL  y  r7  r1   c                     grE  rG  rI  r  r  s      r-   rK  rL  z  r  r1   c                     grE  rG  r  s      r-   rK  rL  {  r  r1   c                     grE  rG  rI  r  r  norms       r-   rK  rL  |  r  r1   c                     grE  rG  r  s       r-   rK  rL  }  r  r1   c                     grE  rG  r  s       r-   rK  rL  ~  r  r1   c                     grE  rG  r  s       r-   rK  rL    r  r1   c                     grE  rG  r  s       r-   rK  rL    r  r1   c                     grE  rG  rI  sr  r  s       r-   rK  rL    r{  r1   c                     grE  rG  r  s       r-   rK  rL    r  r1   c                     grE  rG  r  s       r-   rK  rL    r  r1   c                     grE  rG  r  s       r-   rK  rL    ru  r1   c                     grE  rG  r  s       r-   rK  rL    ru  r1   c                     grE  rG  r  s       r-   rK  rL    r  r1   c                     grE  rG  r  s       r-   rK  rL    r  r1   c                     grE  rG  r  s       r-   rK  rL    r&  r1   c                     grE  rG  r  s       r-   rK  rL    rF  r1   c                     grE  rG  r  s       r-   rK  rL    r{  r1   c                     grE  rG  r  s       r-   rK  rL    r{  r1   c                     grE  rG  r  s       r-   rK  rL    r  r1   c                     grE  rG  r  s     r-   rK  rL    r  r1   c                     grE  rG  r  s     r-   rK  rL    r  r1   c                     grE  rG  r  s       r-   rK  rL    r7  r1   c                     grE  rG  rH  s     r-   rK  rL    rM  r1   c                     grE  rG  )rI  	start_dimend_dims      r-   rK  rL    rS  r1   c                     grE  rG  rI  dimss     r-   rK  rL    r  r1   c                     grE  rG  rZ  s    r-   rK  rL    r  r1   c                     grE  rG  rZ  s    r-   rK  rL    r  r1   c                     grE  rG  r  s       r-   rK  rL    rl  r1   c                     grE  rG  rH  s     r-   rK  rL    r_  r1   c                     grE  rG  r  s     r-   rK  rL    r  r1   c                     grE  rG  rI  exponentrJ  s      r-   rK  rL    r  r1   c                     grE  rG  rc  s      r-   rK  rL    r  r1   c                     grE  rG  rH  s     r-   rK  rL    rX  r1   c                     grE  rG  rH  s     r-   rK  rL    r_  r1   c                     grE  rG  )rI  
fill_valuerJ  r`   rn   r_   r  s          r-   rK  rL    s	      BDr1   c                     grE  rG  )rI  r  	dep_tokens      r-   rK  rL    r  r1   c                     grE  rG  )LU_data	LU_pivotsunpack_dataunpack_pivotss       r-   rK  rL    r  r1   c                     grE  rG  )rI  r  indexrJ  sparse_grads        r-   rK  rL    r@  r1   c                     grE  rG  rc  s      r-   rK  rL    re  r1   c                     grE  rG  rc  s      r-   rK  rL    r  r1   c                     grE  rG  rZ  s    r-   rK  rL    r  r1   c                     grE  rG  rc  s      r-   rK  rL    r  r1   c                     grE  rG  rH  s     r-   rK  rL    r_  r1   c                     grE  rG  rH  s     r-   rK  rL    rJ  r1   c                     grE  rG  rc  s      r-   rK  rL    r  r1   c                     grE  rG  rI  r~  rJ  s      r-   rK  rL    r  r1   c                     grE  rG  r>  s      r-   rK  rL    r  r1   c                     grE  rG  )rI  spacingr  
edge_orders       r-   rK  rL    r(  r1   c                     grE  rG  rI  gridinterpolation_modepadding_moder  s        r-   rK  rL        acr1   c                     grE  rG  rD  s        r-   rK  rL    r  r1   c                     grE  rG  rD  s        r-   rK  rL    r  r1   c                     grE  rG  )rI  
num_groupsr  r  r  r  s         r-   rK  rL        kmr1   c	                     grE  rG  	rI  hxparams
has_biases
num_layersdropoutr  bidirectionalbatch_firsts	            r-   rK  rL        qsr1   c                     grE  rG  rI  rP  w_ihw_hhb_ihb_hhs         r-   rK  rL    r(  r1   c                     grE  rG  rc  s      r-   rK  rL    r  r1   c                     grE  rG  rc  s      r-   rK  rL    r  r1   c                     grE  rG  rI  lambds     r-   rK  rL    r  r1   c                     grE  rG  )rI  r  r  r  rJ  s        r-   rK  rL    r  r1   c                     grE  rG  )rI  valuesrJ  s      r-   rK  rL    r  r1   c                     grE  rG  rI  r  rn  r  r  r  s         r-   rK  rL        xzr1   c                     grE  rG  )rI  binsr4  r5  rJ  s        r-   rK  rL    r&  r1   c                     grE  rG  )rI  rj  r4  r5  r  densityrJ  s          r-   rK  rL    rM  r1   c                     grE  rG  )rI  rj  r   r  rl  s        r-   rK  rL    r.  r1   c                     grE  rG  rI  taus     r-   rK  rL    r  r1   c                     grE  rG  )rv  rw  rJ  s      r-   rK  rL    re  r1   c                     grE  rG  r  s     r-   rK  rL    r  r1   c                     grE  rG  r;  s     r-   rK  rL    rO  r1   c                     grE  rG  rc  s      r-   rK  rL    r  r1   c                     grE  rG  rc  s      r-   rK  rL    r  r1   c                     grE  rG  rc  s      r-   rK  rL    r  r1   c                     grE  rG  rH  s     r-   rK  rL    rX  r1   c                     grE  rG  rI  r  r4  sources       r-   rK  rL    rX  r1   c                     grE  rG  ry  s       r-   rK  rL    r  r1   c                     grE  rG  )rI  indicesre  
accumulates       r-   rK  rL    rr  r1   c                     grE  rG  )rI  r  r4  rJ  s       r-   rK  rL    r7  r1   c                     grE  rG  )rI  r  r4  rq  s       r-   rK  rL    rX  r1   c                     grE  rG  )rI  r  r4  rz  r  include_inputs         r-   rK  rL    r  r1   c                     grE  rG  rZ   s    r-   rK  rL    r  r1   c                     grE  rG  )eteassume_uniqueinverts       r-   rK  rL    r&  r1   c                     grE  rG  r  s    r-   rK  rL    r  r1   c                     grE  rG  r  s    r-   rK  rL    r[  r1   c                     grE  rG  rH  s     r-   rK  rL    rO  r1   c                     grE  rG  rH  s     r-   rK  rL    rO  r1   c	                     grE  rG  )	rI  r  r  r  r  use_input_statsr  r  r  s	            r-   rK  rL    r  r1   c                     grE  rG  rZ  s    r-   rK  rL    rO  r1   c                     grE  rG  rH  s     r-   rK  rL    ra  r1   c                     grE  rG  rH  s     r-   rK  rL    re  r1   c                     grE  rG  r"  s      r-   rK  rL    r  r1   c                     grE  rG  rZ  s    r-   rK  rL    r  r1   c                     grE  rG  rZ  s    r-   rK  rL    r[  r1   c                     grE  rG  rZ  s    r-   rK  rL    r  r1   c                     grE  rG  rZ  s    r-   rK  rL    rX  r1   c                     grE  rG  rZ  s    r-   rK  rL    rJ  r1   c                     grE  rG  rZ  s    r-   rK  rL    ra  r1   c                     grE  rG  rZ  s    r-   rK  rL    r  r1   c                     grE  rG  r  s     r-   rK  rL    r  r1   c                     grE  rG  rZ  s    r-   rK  rL    r  r1   c                     grE  rG  )rI  rd  rtolr  r  s        r-   rK  rL        UWr1   c                     grE  rG  rZ  s    r-   rK  rL    rB  r1   c
                     grE  rG  )
rI  n_fft
hop_length
win_lengthwindowcenter
normalizedonesidedlengthreturn_complexs
             r-   rK  rL    	      bdr1   c                     grE  rG  rI  r  r  r  r  
log_targets         r-   rK  rL    s    prr1   c                     grE  rG  r  s     r-   rK  rL        r1   c                     grE  rG  )rI  kr  r  rJ  s        r-   rK  rL    r(  r1   c                     grE  rG  )rI  	hermitianr#  rJ  s       r-   rK  rL    rH  r1   c                     grE  rG  )rI  r  rJ  s      r-   rK  rL    rr  r1   c                     grE  rG  )LDpivotsBr  rJ  s        r-   rK  rL        QSr1   c                     grE  rG  )rI  normalized_shaper  r  espr  s         r-   rK  rL    rW  r1   c                     grE  rG  rc  s      r-   rK  rL    re  r1   c                     grE  rG  rc  s      r-   rK  rL    r  r1   c                     grE  rG  rc  s      r-   rK  rL    r  r1   c                     grE  rG  rc  s      r-   rK  rL    r  r1   c                     grE  rG  )rI  endr  rJ  s       r-   rK  rL    r  r1   c                     grE  rG  rH  s     r-   rK  rL    r]  r1   c                     grE  rG  )rI  r  r  Xr  iKnitertollargestmethodtrackerortho_iparamsortho_fparamsortho_bparamss                 r-   rK  rL    s	      IKr1   c                     grE  rG  rH  s     r-   rK  rL    rM  r1   c                     grE  rG  rI  r  r`   s      r-   rK  rL    r  r1   c                     grE  rG  rH  s     r-   rK  rL    r_  r1   c                     grE  rG  rH  s     r-   rK  rL    r_  r1   c                     grE  rG  rH  s     r-   rK  rL    rX  r1   c                     grE  rG  rc  s      r-   rK  rL    r  r1   c                     grE  rG  rc  s      r-   rK  rL    r  r1   c                     grE  rG  rZ  s    r-   rK  rL    r  r1   c                     grE  rG  )r  r  rJ  s      r-   rK  rL    rX  r1   c                     grE  rG  rc  s      r-   rK  rL    r  r1   c                     grE  rG  rH  s     r-   rK  rL    r  r1   c                     grE  rG  rc  s      r-   rK  rL    r  r1   c                     grE  rG  rc  s      r-   rK  rL    r  r1   c                     grE  rG  r  s     r-   rK  rL    r_  r1   c                     grE  rG  )rI  namesr  rJ  s       r-   rK  rL    rF  r1   c	                     grE  rG  )	databatch_sizesrP  rQ  rR  rS  rT  r  rU  s	            r-   rK  rL    rW  r1   c                     grE  rG  rY  s         r-   rK  rL     r@  r1   c                     grE  rG  rc  s      r-   rK  rL    r  r1   c                     grE  rG  rc  s      r-   rK  rL    r  r1   c                     grE  rG  )Apivot	get_infosrJ  s       r-   rK  rL    ru  r1   c                     grE  rG  )r  r/  r0  rJ  s       r-   rK  rL    r7  r1   c                     grE  rG  rm  s          r-   rK  rL    rg  r1   c                     grE  rG  )rI  maskrq  s      r-   rK  rL    r  r1   c                     grE  rG  )rI  r  rz  s      r-   rK  rL    r  r1   c                     grE  rG  )rI  r  rJ  s      r-   rK  rL    rX  r1   c                     grE  rG  rc  s      r-   rK  rL  	  r  r1   c                     grE  rG  rI  r  rJ  s      r-   rK  rL  
  r  r1   c                     grE  rG  r  s      r-   rK  rL    r  r1   c                     grE  rG  )rI  r  r#  rJ  s       r-   rK  rL    r  r1   c                     grE  rG  )LUr  r  leftadjointrJ  s         r-   rK  rL        Y[r1   c                     grE  rG  rc  s      r-   rK  rL    r  r1   c                     grE  rG  )rI  r  s     r-   rK  rL    r_  r1   c                     grE  rG  rI  r  rJ  s      r-   rK  rL    rS  r1   c                     grE  rG  )rI  r  r  s      r-   rK  rL        2r1   c                     grE  rG  r;  s     r-   rK  rL    r  r1   c                     grE  rG  rZ  s    r-   rK  rL    r  r1   c                     grE  rG  rZ  s    r-   rK  rL    ra  r1   c                     grE  rG  rH  s     r-   rK  rL    rM  r1   c                     grE  rG  rc  s      r-   rK  rL    r  r1   c                     grE  rG  rc  s      r-   rK  rL    r  r1   c                     grE  rG  rI  r  r  r  r[  r  s         r-   rK  rL        jlr1   c                     grE  rG  r  s         r-   rK  rL    r	  r1   c                     grE  rG  r  s         r-   rK  rL    r	  r1   c                     grE  rG  rI  r  r  r  r[  return_indicesr  s          r-   rK  rL    r  r1   c                     grE  rG  r  s     r-   rK  rL    rX  r1   c                     grE  rG  )rI  r  r  r`   rJ  s        r-   rK  rL    r  r1   c                     grE  rG  r  s     r-   rK  rL     r]  r1   c                     grE  rG  r  s     r-   rK  rL  !  r  r1   c                      grE  rG  )r  r$   s     r-   rK  rL  "  r  r1   c                     grE  rG  rH  s     r-   rK  rL  #  rM  r1   c                     grE  rG  rc  s      r-   rK  rL  $  r  r1   c                     grE  rG  rc  s      r-   rK  rL  %  r  r1   c                     grE  rG  )rI  r  r  r  r  r  exponential_average_factorepsilons           r-   rK  rL  '  r  r1   c	                     grE  rG  	rI  r  r  r  r  r[  r  	benchmarkdeterministics	            r-   rK  rL  )  r  r1   c	                     grE  rG  )	rI  r  zrj  r  r  r  r[  r  s	            r-   rK  rL  *  r  r1   c                     grE  rG  rZ  s          r-   rK  rL  +  r  r1   c
                     grE  rG  )
rI  r  r  r  rf  r  r[  r  r  r  s
             r-   rK  rL  -  rb  r1   c	                     grE  rG  r  s	            r-   rK  rL  0      egr1   c                     grE  rG  )rI  r  weight_stride0rP  cxr  hidden_sizerS  rV  rT  r  rU  r  dropout_states                 r-   rK  rL  3  r  r1   c                     grE  rG  r  s       r-   rK  rL  5  r7  r1   c                     grE  rG  r  s       r-   rK  rL  6  ru  r1   c                     grE  rG  rI  rz  destinations      r-   rK  rL  7  r  r1   c                     grE  rG  r,  s      r-   rK  rL  8  rX  r1   c                     grE  rG  )rI  
descendingrJ  s      r-   rK  rL  9  rV  r1   c                     grE  rG  rc  s      r-   rK  rL  :  re  r1   c                     grE  rG  rc  s      r-   rK  rL  ;  r  r1   c                     grE  rG  )rI  num_samplesreplacementrJ  s       r-   rK  rL  <      SUr1   c                     grE  rG  )rI  rz  rJ  s      r-   rK  rL  =  ra  r1   c                     grE  rG  rI  r  s     r-   rK  rL  >  r  r1   c                     grE  rG  )rI  r  startr  s       r-   rK  rL  ?  r  r1   c                     grE  rG  )rI  nanposinfneginfrJ  s        r-   rK  rL  @  r  r1   c                     grE  rG  )rI  r  r  r  r  r  r  r  s           r-   rK  rL  A  rW  r1   c                     grE  rG  )rI  r  r  r  r  r  s         r-   rK  rL  B      ]_r1   c                     grE  rG  r  s      r-   rK  rL  C  r  r1   c                     grE  rG  rI  r  r  r  r  s        r-   rK  rL  D  r  r1   c                     grE  rG  rI  r  r  r  s       r-   rK  rL  E  r.  r1   c                     grE  rG  )rI  r  r  NCHxWgroupr  s           r-   rK  rL  F  r  r1   c                     grE  rG  )rI  r  r  r  r`   s        r-   rK  rL  G  r6  r1   c                     grE  rG  r  s     r-   rK  rL  H  r  r1   c                     grE  rG  rc  s      r-   rK  rL  I  r  r1   c                     grE  rG  rc  s      r-   rK  rL  J  r  r1   c                     grE  rG  rH  s     r-   rK  rL  K  rM  r1   c                     grE  rG  rH  s     r-   rK  rL  L  rO  r1   c                     grE  rG  rc  s      r-   rK  rL  M  r  r1   c                     grE  rG  rQ  s     r-   rK  rL  N  r(  r1   c                     grE  rG  rQ  s     r-   rK  rL  O  r(  r1   c                     grE  rG  rI  rR  r  s      r-   rK  rL  P  r\  r1   c                     grE  rG  rW  s      r-   rK  rL  Q      oqr1   c                     grE  rG  rW  s      r-   rK  rL  R  r\  r1   c                     grE  rG  rW  s      r-   rK  rL  S  rY  r1   c                     grE  rG  rW  s      r-   rK  rL  T  r\  r1   c                     grE  rG  rW  s      r-   rK  rL  U  rY  r1   c                     grE  rG  r  s      r-   rK  rL  V  r  r1   c                     grE  rG  rI  r  r  r  s       r-   rK  rL  W  r  r1   c                     grE  rG  rI  r  r  r  r  r  divisor_overrides          r-   rK  rL  Y  	      @Br1   c                     grE  rG  rb  s          r-   rK  rL  \  rd  r1   c                     grE  rG  )rI  r  r  r  r  r  r  r  s           r-   rK  rL  _  r  r1   c                     grE  rG  r  s       r-   rK  rL  a  r  r1   c                     grE  rG  rI  r  r  r  r  r  s         r-   rK  rL  c  rH  r1   c                     grE  rG  r  s          r-   rK  rL  f  r  r1   c                     grE  rG  r  s      r-   rK  rL  h  rr  r1   c                     grE  rG  rm  s          r-   rK  rL  j      gir1   c                     grE  rG  )rI  r  r  r  ignore_indexr  r  label_smoothings           r-   rK  rL  m  	      JLr1   c                     grE  rG  rw  s          r-   rK  rL  p  r  r1   c                     grE  rG  r`  s       r-   rK  rL  r      XZr1   c                     grE  rG  r`  s       r-   rK  rL  s  r  r1   c                     grE  rG  r`  s       r-   rK  rL  t  r  r1   c                     grE  rG  r`  s       r-   rK  rL  u  r  r1   c                     grE  rG  r  s      r-   rK  rL  v  r  r1   c                     grE  rG  r  s          r-   rK  rL  x  r  r1   c                     grE  rG  )rI  r  r  r  r  r  r  r   r  include_last_offsetr  s              r-   rK  rL  {  s	      HJr1   c                     grE  rG  r`  s       r-   rK  rL  }  rm  r1   c                     grE  rG  )rI  rR  r  r[  r  r  s         r-   rK  rL  ~  rM  r1   c                     grE  rG  rI  r  rR  output_ratior  _random_sampless         r-   rK  rL    rh  r1   c                     grE  rG  r  s         r-   rK  rL    rh  r1   c                     grE  rG  r  s         r-   rK  rL    rh  r1   c                     grE  rG  r  s         r-   rK  rL    rh  r1   c                     grE  rG  )rI  r  varr   r  r  s         r-   rK  rL    r  r1   c                     grE  rG  )rI  approximates     r-   rK  rL    r  r1   c                     grE  rG  r  s     r-   rK  rL    r  r1   c                     grE  rG  )rI  rE  r  rG  r  s        r-   rK  rL    rh  r1   c                     grE  rG  )rI  rL  r  r  r  s        r-   rK  rL    r#  r1   c                     grE  rG  )logitsrp  hardr  r  s        r-   rK  rL    rH  r1   c                     grE  rG  ra  s     r-   rK  rL    r  r1   c                     grE  rG  )rI  min_valmax_valr  s       r-   rK  rL    r  r1   c                     grE  rG  rg  s         r-   rK  rL        `br1   c                     grE  rG  )rI  r  r  r  r  r  r  r  s           r-   rK  rL    s	      GIr1   c                     grE  rG  )rI  r  scale_factorr  r  recompute_scale_factor	antialiass          r-   rK  rL    s	      KMr1   c                     grE  rG  r  s         r-   rK  rL    rg  r1   c                     grE  rG  rI  r  r  r  r  r  s         r-   rK  rL    r  r1   c                     grE  rG  rE  s        r-   rK  rL    rM  r1   c                     grE  rG  )rI  negative_sloper  s      r-   rK  rL    r  r1   c                     grE  rG  )rI  r  r  s      r-   rK  rL    r&  r1   c                     grE  rG  )rI  r  rj  rk  r  s        r-   rK  rL    r#  r1   c                     grE  rG  rI  r  _stacklevelr`   s       r-   rK  rL    s    \^r1   c                     grE  rG  rZ  s    r-   rK  rL    r  r1   c                     grE  rG  rI  r  r  r  r  s        r-   rK  rL    rM  r1   c                     grE  rG  r  s        r-   rK  rL    rM  r1   c                     grE  rG  r  s        r-   rK  rL    rM  r1   c                     grE  rG  rm  s          r-   rK  rL    rm  r1   c                     grE  rG  rI  r  r  r  r[  r  r  s          r-   rK  rL    r  r1   c                     grE  rG  r  s          r-   rK  rL    r  r1   c                     grE  rG  r  s          r-   rK  rL    r  r1   c                     grE  rG  r  s          r-   rK  rL    r  r1   c                     grE  rG  r  s          r-   rK  rL    r  r1   c                     grE  rG  r  s          r-   rK  rL    r  r1   c                     grE  rG  rI  r}  r  r  r  rR  s         r-   rK  rL    rh  r1   c                     grE  rG  r  s         r-   rK  rL    rh  r1   c                     grE  rG  r  s         r-   rK  rL    rh  r1   c                     grE  rG  r  s         r-   rK  rL    r  r1   c                     grE  rG  )querykeyrq  embed_dim_to_check	num_headsin_proj_weightin_proj_biasbias_kbias_vadd_zero_attn	dropout_pout_proj_weightout_proj_biasr  key_padding_maskneed_weights	attn_maskuse_separate_proj_weightq_proj_weightk_proj_weightv_proj_weightstatic_kstatic_vaverage_attn_weights	is_causals                            r-   rK  rL    s	      ]_r1   c                     grE  rG  )rI  r  r  rn  r  r  r  r  s           r-   rK  rL    r  r1   c                     grE  rG  rI  r  r  r  r  s        r-   rK  rL    r  r1   c                     grE  rG  ri  s         r-   rK  rL    rH  r1   c                     grE  rG  )rI  r  r  r  ro  r  r  s          r-   rK  rL    r  r1   c                     grE  rG  )rI  r  r  r  rJ  s        r-   rK  rL    r  r1   c                     grE  rG  )rZ   num_classess     r-   rK  rL    r  r1   c                     grE  rG  )rI  rW  r  rq  s       r-   rK  rL    r$  r1   c                     grE  rG  r  r  r  r  r  s        r-   rK  rL    r  r1   c                     grE  rG  )rI  r  	log_inputr   r  r  r  r  s           r-   rK  rL    r  r1   c                     grE  rG  rI  r  s     r-   rK  rL    r  r1   c                     grE  rG  rI  r  s     r-   rK  rL    rV  r1   c                     grE  rG  r  s     r-   rK  rL    r7  r1   c                     grE  rG  rG  s       r-   rK  rL    rB  r1   c                     grE  rG  rI  lowerr  r  r  s        r-   rK  rL    s    wyr1   c                     grE  rG  r  s     r-   rK  rL    rV  r1   c                     grE  rG  r  s     r-   rK  rL    rV  r1   c                     grE  rG  r  s     r-   rK  rL    rV  r1   c                     grE  rG  )r  r  rq  r  r  s        r-   rK  rL    r  r1   c                     grE  rG  )rI  r  r  r  r  rk  s         r-   rK  rL    rg  r1   c                     grE  rG  )rI  r  r  deltar  s        r-   rK  rL    s    hjr1   c                     grE  rG  r  s        r-   rK  rL    r  r1   c                     grE  rG  r  s       r-   rK  rL    rt  r1   c                     grE  rG  r  s       r-   rK  rL    rt  r1   c                     grE  rG  )rI  rk  	thresholds      r-   rK  rL    rr  r1   c                     grE  rG  ra  s     r-   rK  rL    r  r1   c                     grE  rG  rZ  s    r-   rK  rL    r  r1   c                     grE  rG  rZ  s    r-   rK  rL    r  r1   c                     grE  rG  rI  r  rq  r  s       r-   rK  rL    r  r1   c
                     grE  rG  
anchorpositivenegativern  r  r  swapr  r  r  s
             r-   rK  rL    rq  r1   )distance_functionrn  r  r  c                    grE  rG  )r  r  r  r  rn  r  r  s          r-   rK  rL    r  r1   c                     grE  rG  )rI  r  r[  r  r  s        r-   rK  rL    r  r1   c                     grE  rG  )rZ   r  r  r  s       r-   rK  rL    r@  r1   c                     grE  rG  )rZ   r  stdr  s       r-   rK  rL    r  r1   c                     grE  rG  )rZ   vals     r-   rK  rL    r  r1   c                     grE  rG  )rZ   r  r  nonlinearityr  s        r-   rK  rL    r  r1   c                     grE  rG  )rI  as_tuples     r-   rK  rL    r  r1   )r+  c                    grE  rG  )rI  r  r+  s      r-   rK  rL    r  r1   c                     grE  rG  rZ  s    r-   rK  rL    rO  r1   c                     grE  rG  rI  r  r  r  rJ  r`   s         r-   rK  rL    r  r1   c                     grE  rG  rI  rQ  r  r  rJ  r`   s         r-   rK  rL    r\  r1   c                     grE  rG  r  s         r-   rK  rL    r  r1   c                     grE  rG  r  s         r-   rK  rL    s     13r1   c                     grE  rG  )vpowr  s      r-   rK  rL    r  r1   c                     grE  rG  r  s         r-   rK  rL    r\  r1   c                     grE  rG  rZ  s    r-   rK  rL     rB  r1   c                     grE  rG  ro  s     r-   rK  rL    r  r1   c                     grE  rG  )rI  r  input3r  	transposes        r-   rK  rL    rl  r1   c                     grE  rG  r  s        r-   rK  rL    r  r1   c                     grE  rG  r  r  s     r-   rK  rL    r  r1   c                     grE  rG  )rI  qr  r  s       r-   rK  rL    rF  r1   c                     grE  rG  r9  s     r-   rK  rL    r  r1   c                     grE  rG  )rI  rconds     r-   rK  rL    r  r1   c                     grE  rG  )rI  r   r  s      r-   rK  rL    rF  r1   c                     grE  rG  )rI  upscale_factors     r-   rK  rL  	  rX  r1   c                     grE  rG  )rI  downscale_factors     r-   rK  rL  
  rV  r1   c                     grE  rG  )rI  r  s     r-   rK  rL    r  r1   c                     grE  rG  )rI  r  r  r   r  r  s         r-   rK  rL    r.  r1   c                     grE  rG  r  s      r-   rK  rL    r  r1   c                     grE  rG  rH  s     r-   rK  rL    rO  r1   c                     grE  rG  r  s     r-   rK  rL    rM  r1   c                     grE  rG  r  s        r-   rK  rL    r\  r1   c                     grE  rG  r%  s      r-   rK  rL    r  r1   c                     grE  rG  )rI  r`   s     r-   rK  rL    r]  r1   c                     grE  rG  )rI  r4  rz  r~  s       r-   rK  rL    r  r1   c                     grE  rG  rZ  s    r-   rK  rL    rO  r1   c                     grE  rG  rZ  s    r-   rK  rL    re  r1   c                     grE  rG  rZ  s    r-   rK  rL    r  r1   c                     grE  rG  rZ  s    r-   rK  rL    r[  r1   c                     grE  rG  rZ  s    r-   rK  rL    rJ  r1   c                     grE  rG  )rI  somerJ  s      r-   rK  rL    r  r1   c                     grE  rG  )rI  r  rJ  s      r-   rK  rL    r  r1   c                     grE  rG  rI  r  r  r  interpolationrJ  s         r-   rK  rL    r  r1   c                     grE  rG  r8  s         r-   rK  rL    rm  r1   c                     grE  rG  )rI  scaleszero_pointsr  r`   s        r-   rK  rL    r  r1   c                     grE  rG  )rI  r  r  r`   s       r-   rK  rL    r   r1   c                     grE  rG  )rI  r`   reduce_ranges      r-   rK  rL    r$  r1   c                     grE  rG  )rI  r  r  r  r  r  output_scaleoutput_zero_points           r-   rK  rL     rW  r1   c                     grE  rG  rI  rP  rZ  r[  r\  r]  	packed_ih	packed_hhcol_offsets_ihcol_offsets_hhscale_ihscale_hhzero_point_ihzero_point_hhs                 r-   rK  rL  "  	      _ar1   c                     grE  rG  rE  s                 r-   rK  rL  %  rN  r1   r      c                     grE  rG  r  s         r-   rK  rL  (  s     "r1   c                     grE  rG  r  s         r-   rK  rL  -  s     !#r1   c                     grE  rG  r  s         r-   rK  rL  3  s     !#r1   c                     grE  rG  rE  s                 r-   rK  rL  :  rN  r1   c                     grE  rG  rE  s                 r-   rK  rL  =  rN  r1   c                     grE  rG  rH  s     r-   rK  rL  ?  ra  r1   c                     grE  rG  rZ  s    r-   rK  rL  @  rB  r1   c                     grE  rG  rH  s     r-   rK  rL  A  rX  r1   c                     grE  rG  rc  s      r-   rK  rL  B  r  r1   c                     grE  rG  rs  s       r-   rK  rL  C  r  r1   c                     grE  rG  rZ  s    r-   rK  rL  D  rJ  r1   c                     grE  rG  rZ  s    r-   rK  rL  E  r_  r1   c                     grE  rG  rH  s     r-   rK  rL  F  re  r1   c                     grE  rG  r  s     r-   rK  rL  G  r  r1   c                     grE  rG  rc  s      r-   rK  rL  H  r  r1   c                     grE  rG  )rI  r  r  maxnormrJ  s        r-   rK  rL  I  rV  r1   c                     grE  rG  r  s     r-   rK  rL  J  r  r1   c                     grE  rG  )rI  shapes     r-   rK  rL  K  rX  r1   c                     grE  rG  rG  s       r-   rK  rL  L  rl  r1   c	                     grE  rG  rO  s	            r-   rK  rL  M  r  r1   c                     grE  rG  rY  s         r-   rK  rL  N  r  r1   c	                     grE  rG  rO  s	            r-   rK  rL  O  r  r1   c                     grE  rG  rY  s         r-   rK  rL  P  r  r1   c                     grE  rG  )rI  shiftsr  s      r-   rK  rL  Q  r  r1   r   rR  c                     grE  rG  )rI  r  r  s      r-   rK  rL  R  r  r1   c                     grE  rG  rH  s     r-   rK  rL  S  r_  r1   c                     grE  rG  r;  s     r-   rK  rL  T  r  r1   c                     grE  rG  )r  r  compressed_indices_dtypes      r-   rK  rL  U  r$  r1   c                     grE  rG  r  s        r-   rK  rL  V  r  r1   c                     grE  rG  rH  s     r-   rK  rL  W  r_  r1   c                     grE  rG  )rI  rd  rj  s      r-   rK  rL  X  re  r1   c                     grE  rG  ru  s         r-   rK  rL  Y  r   r1   c                     grE  rG  rI  r  r4  r  s       r-   rK  rL  Z  r  r1   c                     grE  rG  ry  s       r-   rK  rL  [  r  r1   c                     grE  rG  )rI  r  r4  r  r  include_selfs         r-   rK  rL  \  rt  r1   c                     grE  rG  )sorted_sequencerI  r  r  rJ  s        r-   rK  rL  ]  r  r1   c                     grE  rG  )r  r  lengthsr}  r  r  unsafes          r-   rK  rL  ^  r  r1   c                     grE  rG  )rI  r  r4  s      r-   rK  rL  _  rO  r1   c                     grE  rG  )rI  r  r  r4  s       r-   rK  rL  `  r  r1   c                     grE  rG  rI  r  r  r;  r  steps         r-   rK  rL  a  r  r1   c                     grE  rG  r  s         r-   rK  rL  b  r  r1   c                     grE  rG  r  s     r-   rK  rL  c  r  r1   c                     grE  rG  rH  s     r-   rK  rL  d  ra  r1   c                     grE  rG  rH  s     r-   rK  rL  e  rX  r1   c                     grE  rG  rH  s     r-   rK  rL  f  ra  r1   c                     grE  rG  rH  s     r-   rK  rL  g  rM  r1   c                     grE  rG  rH  s     r-   rK  rL  h  rM  r1   c                     grE  rG  rH  s     r-   rK  rL  i  rX  r1   c                     grE  rG  rH  s     r-   rK  rL  j  rX  r1   c                     grE  rG  rZ  s    r-   rK  rL  k  r[  r1   c                     grE  rG  rZ  s    r-   rK  rL  l  rX  r1   c                     grE  rG  r  s      r-   rK  rL  m  r  r1   c                     grE  rG  r  s      r-   rK  rL  n  r  r1   c                     grE  rG  r  s      r-   rK  rL  o  r  r1   c                     grE  rG  )r  r  r  rJ  s       r-   rK  rL  p  rS  r1   c                     grE  rG  )r  r  r  r#  rJ  s        r-   rK  rL  q  r  r1   )stablerJ  c                    grE  rG  )rI  r  r0  r  rJ  s        r-   rK  rL  r  r.  r1   c                     grE  rG  rZ   split_size_or_sectionsr  s      r-   rK  rL  s  ru  r1   c                     grE  rG  r  s      r-   rK  rL  t  r$  r1   c                     grE  rG  rH  s     r-   rK  rL  u  rX  r1   c                     grE  rG  rH  s     r-   rK  rL  v  r]  r1   c                     grE  rG  r  s      r-   rK  rL  w  r  r1   c                     grE  rG  ru  s         r-   rK  rL  x  r@  r1   c                     grE  rG  r	  s      r-   rK  rL  y  r  r1   c                     grE  rG  r  s     r-   rK  rL  z  rM  r1   c                     grE  rG  r  s     r-   rK  rL  {  rO  r1   c                     grE  rG  )rI  r  r  r  r  r  pad_moder  r  r  align_to_windows              r-   rK  rL  }  s	      ~@r1   c                     grE  rG  rc  s      r-   rK  rL    re  r1   c                     grE  rG  rc  s      r-   rK  rL    r  r1   c                     grE  rG  r  s     r-   rK  rL    rM  r1   c                     grE  rG  rZ  s    r-   rK  rL    r  r1   c                     grE  rG  rZ  s    r-   rK  rL    r[  r1   c                     grE  rG  r  r  s     r-   rK  rL    r  r1   c                     grE  rG  r  s     r-   rK  rL    r  r1   c                     grE  rG  rZ  s    r-   rK  rL    r[  r1   c                     grE  rG  )r  r  cs      r-   rK  rL    r  r1   c                     grE  rG  )r#   s    r-   rK  rL    r  r1   c                     grE  rG  rZ  s    r-   rK  rL    r  r1   c                     grE  rG  rZ  s    r-   rK  rL    rO  r1   c                     grE  rG  rZ  s    r-   rK  rL    r  r1   c                     grE  rG  rZ  s    r-   rK  rL    rO  r1   c                     grE  rG  rZ  s    r-   rK  rL    r  r1   c                     grE  rG  rZ  s    r-   rK  rL    rO  r1   c                     grE  rG  rZ  s    r-   rK  rL    r  r1   c                     grE  rG  rZ  s    r-   rK  rL    r  r1   c                     grE  rG  rZ  s    r-   rK  rL    r  r1   c                     grE  rG  rZ  s    r-   rK  rL    r  r1   c                     grE  rG  r  s     r-   rK  rL    r]  r1   c                     grE  rG  )rI  r5  
compute_uvrJ  s       r-   rK  rL    rF  r1   c                     grE  rG  )rI  r  r  Ms       r-   rK  rL    rV  r1   c                     grE  rG  )rI  full_matricesrJ  s      r-   rK  rL    r  r1   c                     grE  rG  rH  s     r-   rK  rL    r  r1   c                     grE  rG  rI  dim0r  s      r-   rK  rL    re  r1   c                     grE  rG  )rI  axis0axis1s      r-   rK  rL    r  r1   c                     grE  rG  rZ  s    r-   rK  rL    r_  r1   c                     grE  rG  rZ  s    r-   rK  rL    ra  r1   c                     grE  rG  rZ  s    r-   rK  rL    ra  r1   c                     grE  rG  rZ  s    r-   rK  rL    ra  r1   c                     grE  rG  rZ  s    r-   rK  rL    ra  r1   c                     grE  rG  r  s      r-   rK  rL    r  r1   c                     grE  rG  r  s      r-   rK  rL    r  r1   c                     grE  rG  r  s      r-   rK  rL    r  r1   c                     grE  rG  r  s      r-   rK  rL    r  r1   c                     grE  rG  rZ  s    r-   rK  rL    r_  r1   c                     grE  rG  rZ  s    r-   rK  rL    rJ  r1   c                     grE  rG  rZ  s    r-   rK  rL    r  r1   c                     grE  rG  rZ  s    r-   rK  rL    rJ  r1   c                     grE  rG  rZ  s    r-   rK  rL    rM  r1   c                     grE  rG  rZ  s    r-   rK  rL    rX  r1   c                     grE  rG  rZ  s    r-   rK  rL    rJ  r1   c                     grE  rG  rZ  s    r-   rK  rL    rM  r1   c                     grE  rG  rZ  s    r-   rK  rL    rM  r1   c                     grE  rG  rc  s      r-   rK  rL    rV  r1   c                     grE  rG  rc  s      r-   rK  rL    r7  r1   c                     grE  rG  rZ  s    r-   rK  rL    r_  r1   c                     grE  rG  r  s      r-   rK  rL    rF  r1   c                     grE  rG  r  s      r-   rK  rL    r{  r1   c                     grE  rG  rZ  s    r-   rK  rL    r  r1   c                     grE  rG  rZ  s    r-   rK  rL    r  r1   c                     grE  rG  rZ  s    r-   rK  rL    r  r1   c                     grE  rG  rZ  s    r-   rK  rL    r  r1   c                     grE  rG  r  s      r-   rK  rL    r{  r1   c                     grE  rG  r  s      r-   rK  rL    r{  r1   c                     grE  rG  rZ  s    r-   rK  rL    rM  r1   c                     grE  rG  rZ  s    r-   rK  rL    r]  r1   c                     grE  rG  r  s      r-   rK  rL    r  r1   c                     grE  rG  rZ  s    r-   rK  rL    rM  r1   c                     grE  rG  r  s       r-   rK  rL    r@  r1   c                     grE  rG  rZ  s    r-   rK  rL    r  r1   c                     grE  rG  rZ  s    r-   rK  rL    r  r1   c                     grE  rG  rZ  s    r-   rK  rL    r  r1   c                     grE  rG  rZ  s    r-   rK  rL    r  r1   c                     grE  rG  r9  s     r-   rK  rL    r  r1   c                     grE  rG  rZ  s    r-   rK  rL    rJ  r1   c                     grE  rG  rZ  s    r-   rK  rL    rM  r1   c                     grE  rG  r  s      r-   rK  rL    r  r1   c                     grE  rG  rZ  s    r-   rK  rL    r  r1   c                     grE  rG  rZ  s    r-   rK  rL    rM  r1   c                     grE  rG  rZ  s    r-   rK  rL    rV  r1   c                     grE  rG  rZ  s    r-   rK  rL    rV  r1   c                     grE  rG  r  s      r-   rK  rL    r  r1   c                     grE  rG  r  s      r-   rK  rL    r  r1   c                     grE  rG  r  s      r-   rK  rL    r  r1   c                     grE  rG  r  s      r-   rK  rL    r  r1   c                     grE  rG  rZ  s    r-   rK  rL    rJ  r1   c                     grE  rG  r  s      r-   rK  rL    rS  r1   c                     grE  rG  rZ  s    r-   rK  rL    r  r1   c                     grE  rG  rc  s      r-   rK  rL    rS  r1   c                     grE  rG  rc  s      r-   rK  rL    r  r1   c                     grE  rG  )r  rd  rJ  s      r-   rK  rL    r  r1   c                     grE  rG  rZ  s    r-   rK  rL    s    rr1   c                     grE  rG  )rI  r4  s     r-   rK  rL    r  r1   c                     grE  rG  )rI  r}  r  rJ  s       r-   rK  rL    r  r1   c                     grE  rG  rH  s     r-   rK  rL    rM  r1   c                     grE  rG  rH  s     r-   rK  rL    rX  r1   c                     grE  rG  )r  inds     r-   rK  rL    r  r1   c                     grE  rG  )r  r  r  s      r-   rK  rL    r  r1   c                     grE  rG  )r  r  r  rJ  s       r-   rK  rL    r  r1   c                     grE  rG  )rI  r  r  s      r-   rK  rL    r  r1   c                     grE  rG  r  s       r-   rK  rL    r{  r1   c                     grE  rG  r  s     r-   rK  rL    r  r1   c                     grE  rG  )rI  r  r  r0  rJ  s        r-   rK  rL    r  r1   c                     grE  rG  rZ  s    r-   rK  rL    rB  r1   c                     grE  rG  r  s      r-   rK  rL    r  r1   c                     grE  rG  r  s      r-   rK  rL    ra  r1   c                     grE  rG  r  s      r-   rK  rL    r  r1   c                     grE  rG  )rI  r  r  r  unitriangulars        r-   rK  rL    r  r1   c                     grE  rG  )rI  r  r  r  r  s        r-   rK  rL    r  r1   c                     grE  rG  r  s      r-   rK  rL    r  r1   c
                     grE  rG  r  s
             r-   rK  rL    rq  r1   c                     grE  rG  r  s      r-   rK  rL    r  r1   c                     grE  rG  r  s     r-   rK  rL    rO  r1   c                     grE  rG  rH  s     r-   rK  rL    r_  r1   c                     grE  rG  r  s     r-   rK  rL    rM  r1   c                     grE  rG  )rI  r  sizesr  s       r-   rK  rL    r  r1   c                     grE  rG  )rI  sortedreturn_inversereturn_countsr  s        r-   rK  rL    r  r1   c                     grE  rG  )rI  r!  r"  r  s       r-   rK  rL    r#  r1   c                     grE  rG  )r}  rf  s     r-   rK  rL    r  r1   c                     grE  rG  r0  s      r-   rK  rL    r  r1   c                     grE  rG  r  s      r-   rK  rL    rr  r1   c                     grE  rG  r  s      r-   rK  rL    r  r1   c                     grE  rG  r  s      r-   rK  rL    r  r1   c                     grE  rG  )r  rI  s     r-   rK  rL    ra  r1   c                     grE  rG  r  s     r-   rK  rL    rM  r1   c                     grE  rG  r  s     r-   rK  rL    rO  r1   c                     grE  rG  r  s     r-   rK  rL    r  r1   c                     grE  rG  r;  s     r-   rK  rL    rO  r1   c                     grE  rG  )	conditionr  r  s      r-   rK  rL    r  r1   c                     grE  rG  )r  r  r  r  s       r-   rK  rL    r  r1   c                     grE  rG  )rI  input_scaleinput_zero_point	prepacked	out_scaleout_zero_pointout_channels          r-   rK  rL    r  r1   c                     grE  rG  r  s        r-   rK  rL    r  r1   c                     grE  rG  )r  levels     r-   rK  rL    r  r1   c                     grE  rG  )primaltangentr:  s      r-   rK  rL     rS  r1   c                     grE  rG  r  s    r-   rK  rL    r]  r1   c                     grE  rG  r?  s    r-   rK  rL    r  r1   c                     grE  rG  r?  s    r-   rK  rL    r  r1   c                     grE  rG  r?  s    r-   rK  rL    rM  r1   c                     grE  rG  )r  r  r  r  s       r-   rK  rL    rl  r1   c                     grE  rG  r   s     r-   rK  rL    r  r1   c                     grE  rG  )r  r  r  r  s       r-   rK  rL    r  r1   )implicitc                    grE  rG  )r  r  rF  s      r-   rK  rL    r  r1   c                     grE  rG  )r  r  r;  r  s       r-   rK  rL  	  r  r1   c                     grE  rG  )r  r  s     r-   rK  rL  
  ra  r1   c                     grE  rG  r  r  r  s      r-   rK  rL    rS  r1   c                     grE  rG  )r  r  r4  s      r-   rK  rL    r  r1   c                     grE  rG  r?  s    r-   rK  rL    r  r1   c                     grE  rG  )r  r  r;  r  r  s        r-   rK  rL    r(  r1   c                     grE  rG  )r  
split_sizer  s      r-   rK  rL    r  r1   c                     grE  rG  )r  split_sizesr  s      r-   rK  rL    r  r1   c                     grE  rG  r  s     r-   rK  rL    r]  r1   c                     grE  rG  r?  s    r-   rK  rL    rB  r1   c                     grE  rG  )r  r  r  s      r-   rK  rL    r  r1   c                     grE  rG  r  s     r-   rK  rL    rO  r1   c                     grE  rG  r?  s    r-   rK  rL    rJ  r1   c                     grE  rG  r?  s    r-   rK  rL    r  r1   c                     grE  rG  r?  s    r-   rK  rL    r  r1   c                     grE  rG  r?  s    r-   rK  rL    r  r1   c                     grE  rG  r?  s    r-   rK  rL    r]  r1   c                     grE  rG  r?  s    r-   rK  rL    r_  r1   c                     grE  rG  r?  s    r-   rK  rL    r]  r1   c                     grE  rG  r?  s    r-   rK  rL    r_  r1   c                     grE  rG  r  s     r-   rK  rL    ra  r1   c                     grE  rG  r  r`   s     r-   rK  rL    r_  r1   c                     grE  rG  r  	dimensionr  r  s       r-   rK  rL    rV  r1   c                     grE  rG  r?  s    r-   rK  rL     r  r1   c                     grE  rG  r  rd  s     r-   rK  rL  !  r  r1   c                     grE  rG  rg  s     r-   rK  rL  "  re  r1   c                     grE  rG  rg  s     r-   rK  rL  #  re  r1   c                     grE  rG  rg  s     r-   rK  rL  $  rO  r1   c                     grE  rG  rg  s     r-   rK  rL  %  r  r1   c                     grE  rG  rg  s     r-   rK  rL  &  r  r1   c                     grE  rG  rg  s     r-   rK  rL  '  ra  r1   c                     grE  rG  rg  s     r-   rK  rL  (  rO  r1   c                     grE  rG  rg  s     r-   rK  rL  )  rO  r1   c                     grE  rG  rg  s     r-   rK  rL  *  ra  r1   c                     grE  rG  rg  s     r-   rK  rL  +  rO  r1   c                     grE  rG  rg  s     r-   rK  rL  ,  rO  r1   c                     grE  rG  rg  s     r-   rK  rL  -  rX  r1   c                     grE  rG  rg  s     r-   rK  rL  .  rM  r1   c                     grE  rG  rg  s     r-   rK  rL  /  rX  r1   c                     grE  rG  r?  s    r-   rK  rL  0  r  r1   c                     grE  rG  r?  s    r-   rK  rL  1  r  r1   c                     grE  rG  ra  s     r-   rK  rL  2  r]  r1   c                     grE  rG  r?  s    r-   rK  rL  3  rO  r1   c                     grE  rG  rg  s     r-   rK  rL  4  r  r1   c                     grE  rG  r?  s    r-   rK  rL  5  r[  r1   c                     grE  rG  r?  s    r-   rK  rL  6  r  r1   c                     grE  rG  rg  s     r-   rK  rL  7  rX  r1   c                     grE  rG  rg  s     r-   rK  rL  8  r_  r1   c                     grE  rG  rg  s     r-   rK  rL  9  r_  r1   c                     grE  rG  )r  arrays     r-   rK  rL  :  r  r1   c                     grE  rG  )r  idxs     r-   rK  rL  ;  r]  r1   c                     grE  rG  )r  memos     r-   rK  rL  <  rO  r1   c                     grE  rG  r?  s    r-   rK  rL  =  r[  r1   c                     grE  rG  r?  s    r-   rK  rL  >  rO  r1   c                     grE  rG  r?  s    r-   rK  rL  ?  r  r1   c                     grE  rG  r?  s    r-   rK  rL  @  r[  r1   c                     grE  rG  )r  format_specs     r-   rK  rL  A  r  r1   c                     grE  rG  )r  protos     r-   rK  rL  B  re  r1   c                     grE  rG  r?  s    r-   rK  rL  C  rJ  r1   )tensor_contentsc                    grE  rG  )r  r  s     r-   rK  rL  D  rV  r1   c                     grE  rG  )r  r  r  s      r-   rK  rL  E  ra  r1   c                     grE  rG  )r  ds     r-   rK  rL  F  r_  r1   c                     grE  rG  r?  s    r-   rK  rL  G  r  r1   c                     grE  rG  r?  s    r-   rK  rL  H  r  r1   c                     grE  rG  r?  s    r-   rK  rL  I  r  r1   c                     grE  rG  r?  s    r-   rK  rL  J  r  r1   c                     grE  rG  r?  s    r-   rK  rL  K  r  r1   c                     grE  rG  r?  s    r-   rK  rL  L  r  r1   c                     grE  rG  r?  s    r-   rK  rL  M  rM  r1   c                     grE  rG  r?  s    r-   rK  rL  N  rX  r1   c                     grE  rG  r?  s    r-   rK  rL  O  rJ  r1   c                     grE  rG  r?  s    r-   rK  rL  P  rM  r1   c                     grE  rG  r?  s    r-   rK  rL  Q  r]  r1   c                     grE  rG  r?  s    r-   rK  rL  R  r_  r1   c                     grE  rG  r?  s    r-   rK  rL  S  rO  r1   c                     grE  rG  r?  s    r-   rK  rL  T  r]  r1   c                     grE  rG  )r  cuda_enabledcpu_enabled
cuda_dtype	cpu_dtypes        r-   rK  rL  U  s    npr1   c                     grE  rG  )r  r  r  s      r-   rK  rL  V  r  r1   c                     grE  rG  r?  s    r-   rK  rL  W  r  r1   c                     grE  rG  r?  s    r-   rK  rL  X  rJ  r1   c                     grE  rG  r?  s    r-   rK  rL  Y  rX  r1   c                     grE  rG  r?  s    r-   rK  rL  Z  rM  r1   c                     grE  rG  r?  s    r-   rK  rL  [  r_  r1   c                     grE  rG  r?  s    r-   rK  rL  \  rX  r1   c                     grE  rG  r?  s    r-   rK  rL  ]  rX  r1   c                     grE  rG  r?  s    r-   rK  rL  ^  rX  r1   c                     grE  rG  r?  s    r-   rK  rL  _  rX  r1   c                     grE  rG  r?  s    r-   rK  rL  `  r_  r1   c                     grE  rG  r?  s    r-   rK  rL  a  re  r1   c                     grE  rG  r?  s    r-   rK  rL  b  r_  r1   c                     grE  rG  r?  s    r-   rK  rL  c  rX  r1   c                     grE  rG  r?  s    r-   rK  rL  d  r_  r1   c                     grE  rG  r?  s    r-   rK  rL  e  ra  r1   c                     grE  rG  r?  s    r-   rK  rL  f  r_  r1   c                     grE  rG  r?  s    r-   rK  rL  g  ra  r1   c                     grE  rG  r?  s    r-   rK  rL  h  re  r1   c                     grE  rG  r?  s    r-   rK  rL  i  ra  r1   c                     grE  rG  r?  s    r-   rK  rL  j  r  r1   c                     grE  rG  r?  s    r-   rK  rL  k  ra  r1   c                     grE  rG  r?  s    r-   rK  rL  l  r]  r1   c                     grE  rG  r?  s    r-   rK  rL  m  rX  r1   c                     grE  rG  r?  s    r-   rK  rL  n  rJ  r1   c                     grE  rG  r?  s    r-   rK  rL  o  rM  r1   c                     grE  rG  r?  s    r-   rK  rL  p  rX  r1   c                     grE  rG  r?  s    r-   rK  rL  q  rJ  r1   c                     grE  rG  r?  s    r-   rK  rL  r  ra  r1   c                     grE  rG  r?  s    r-   rK  rL  s  r  r1   c                     grE  rG  r?  s    r-   rK  rL  t  rM  r1   c                     grE  rG  r?  s    r-   rK  rL  u  r]  r1   c                     grE  rG  r?  s    r-   rK  rL  v  rJ  r1   c                     grE  rG  r?  s    r-   rK  rL  w  rJ  r1   c                     grE  rG  r?  s    r-   rK  rL  x  rS  r1   c                     grE  rG  )r  r`   non_blockingr$   s       r-   rK  rL  y  r(  r1   c                     grE  rG  r?  s    r-   rK  rL  z  rB  r1   c                     grE  rG  r?  s    r-   rK  rL  {  rB  r1   c                     grE  rG  r?  s    r-   rK  rL  |  rO  r1   c                     grE  rG  r?  s    r-   rK  rL  }  rO  r1   c                     grE  rG  r?  s    r-   rK  rL  ~      "r1   c                     grE  rG  r?  s    r-   rK  rL    rJ  r1   c                     grE  rG  r?  s    r-   rK  rL    r  r1   c                     grE  rG  r?  s    r-   rK  rL    rJ  r1   c                     grE  rG  r?  s    r-   rK  rL    r  r1   c                     grE  rG  )r  r  r  s      r-   rK  rL    rX  r1   c                     grE  rG  r?  s    r-   rK  rL    r[  r1   c                     grE  rG  r?  s    r-   rK  rL    r[  r1   c                     grE  rG  rg  s     r-   rK  rL    r_  r1   c                     grE  rG  )r  orderellipsis_idxs      r-   rK  rL    rX  r1   c                     grE  rG  )r  callables     r-   rK  rL    r]  r1   c                     grE  rG  rK  s      r-   rK  rL    r  r1   c                     grE  rG  rK  s      r-   rK  rL    r  r1   c                     grE  rG  )r  gradientretain_graphcreate_graphrU  s        r-   rK  rL    s    ikr1   c                     grE  rG  r  rg   s     r-   rK  rL    r   r1   c                     grE  rG  r  s     r-   rK  rL    rF  r1   c                     grE  rG  r  s     r-   rK  rL    rF  r1   c                     grE  rG  r  s     r-   rK  rL    rF  r1   )r  c                    grE  rG  )r  mediansigmar  s       r-   rK  rL    r   r1   c                     grE  rG  r?  s    r-   rK  rL    rO  r1   c                     grE  rG  )r  	coalesceds     r-   rK  rL    r  r1   c                     grE  rG  r  s     r-   rK  rL    rl  r1   c                     grE  rG  )r  r  r  s      r-   rK  rL    r  r1   c                     grE  rG  r  s     r-   rK  rL    r  r1   c                     grE  rG  r  s     r-   rK  rL    rF  r1   c                     grE  rG  r  s     r-   rK  rL    rF  r1   c                     grE  rG  r  s     r-   rK  rL    r  r1   c                     grE  rG  r  s     r-   rK  rL    r  r1   c                     grE  rG  r?  s    r-   rK  rL    rO  r1   c                     grE  rG  r?  s    r-   rK  rL    r  r1   c                     grE  rG  )r  r  r  r  r  s        r-   rK  rL    r@  r1   c                     grE  rG  r?  s    r-   rK  rL    r  r1   c                     grE  rG  )r  ambiguity_checks     r-   rK  rL    rS  r1   c                     grE  rG  r  s     r-   rK  rL    r  r1   c                     grE  rG  r  s     r-   rK  rL    rr  r1   c                     grE  rG  r?  s    r-   rK  rL    rJ  r1   c                     grE  rG  r   s     r-   rK  rL    rJ  r1   c                     grE  rG  rg  s     r-   rK  rL    r]  r1   c                    grE  rG  )r  rb  r  s      r-   rK  rL    r  r1   c                     grE  rG  r  rq  s     r-   rK  rL    rJ  r1   c                     grE  rG  r  s     r-   rK  rL    r  r1   c                     grE  rG  r  s     r-   rK  rL    r{  r1   c                     grE  rG  r  s     r-   rK  rL    r  r1   c                    grE  rG  )r  r  r  s      r-   rK  rL    rS  r1   c                     grE  rG  r?  s    r-   rK  rL    r  r1   c                     grE  rG  r  s     r-   rK  rL    rF  r1   c                     grE  rG  r  s     r-   rK  rL    r{  r1   c                     grE  rG  r?  s    r-   rK  rL    r  r1   c                     grE  rG  r?  s    r-   rK  rL    r[  r1   c                     grE  rG  r  s     r-   rK  rL    r  r1   c                     grE  rG  r?  s    r-   rK  rL    rJ  r1   c                     grE  rG  r?  s    r-   rK  rL    rM  r1   c                     grE  rG  r?  s    r-   rK  rL    rJ  r1   c                     grE  rG  r?  s    r-   rK  rL    r  r1   c                     grE  rG  )r  rZ   s     r-   rK  rL    ra  r1   c                     grE  rG  r?  s    r-   rK  rL    r  r1   c                     grE  rG  r?  s    r-   rK  rL    r  r1   c                    grE  rG  )r  r  r  r  s       r-   rK  rL    r   r1   c                     grE  rG  r  s     r-   rK  rL    r]  r1   c                     grE  rG  r  s     r-   rK  rL    rF  r1   c                     grE  rG  )r  rZ   r  s      r-   rK  rL    r  r1   c                     grE  rG  )r  r  r  r  s       r-   rK  rL    r  r1   c                     grE  rG  )r  rw  r  s      r-   rK  rL    r  r1   c                     grE  rG  )r  rd  assigns      r-   rK  rL    rS  r1   c                     grE  rG  )r  rd  r;  r  s       r-   rK  rL    ru  r1   c                     grE  rG  r?  s    r-   rK  rL    r  r1   c                     grE  rG  r?  s    r-   rK  rL    rO  r1   c                     grE  rG  r?  s    r-   rK  rL    r  r1   c                     grE  rG  r?  s    r-   rK  rL    r  r1   c                     grE  rG  r?  s    r-   rK  rL    r  r1   c                     grE  rG  r?  s    r-   rK  rL    r[  r1   c                     grE  rG  r?  s    r-   rK  rL    rB  r1   c                     grE  rG  r  s     r-   rK  rL    rJ  r1   c                     grE  rG  r?  s    r-   rK  rL    r  r1   c                     grE  rG  )r  r}  rZ   r~  s       r-   rK  rL    r&  r1   c                     grE  rG  r?  s    r-   rK  rL    r[  r1   c                    grE  rG  )r  from_tor  s       r-   rK  rL    rr  r1   c                     grE  rG  )r  streams     r-   rK  rL    r  r1   c                     grE  rG  )r  r  s     r-   rK  rL    r  r1   c                     grE  rG  r  hooks     r-   rK  rL    r  r1   c                     grE  rG  r1  s     r-   rK  rL    r  r1   c                     grE  rG  )r  names     r-   rK  rL    rJ  r1   c                     grE  rG  r   s     r-   rK  rL    rM  r1   c                     grE  rG  )r  r  s     r-   rK  rL    r7  r1   c                     grE  rG  rg  s     r-   rK  rL    ra  r1   c                     grE  rG  r   s     r-   rK  rL    rM  r1   c                     grE  rG  r   s     r-   rK  rL    rM  r1   c                     grE  rG  rg  s     r-   rK  rL    r]  r1   c                     grE  rG  rg  s     r-   rK  rL    r  r1   c                     grE  rG  r?  s    r-   rK  rL    r  r1   c                     grE  rG  )r  rz  r  r  r  s        r-   rK  rL    r  r1   c                     grE  rG  )r  r  r  r4  s       r-   rK  rL    r  r1   c                     grE  rG  r?  s    r-   rK  rL    rM  r1   c                     grE  rG  r  s     r-   rK  rL    r{  r1   c                     grE  rG  r?  s    r-   rK  rL    r  r1   c                     grE  rG  )r  r  r  r;  r  r  s         r-   rK  rL    r  r1   c                     grE  rG  r?  s    r-   rK  rL    r  r1   c                     grE  rG  )r  r  s     r-   rK  rL    ra  r1   c                     grE  rG  )r  r  accumulate_matchess      r-   rK  rL    r  r1   c                     grE  rG  r  size1size2	dense_dims       r-   rK  rL    r&  r1   c                     grE  rG  rI  s       r-   rK  rL    rl  r1   c                     grE  rG  )r  rv  rw  rk  rj  rJ  s         r-   rK  rL    r@  r1   c                     grE  rG  r?  s    r-   rK  rL    r[  r1   c                     grE  rG  r?  s    r-   rK  rL    r_  r1   c                     grE  rG  r?  s    r-   rK  rL    rX  r1   c                     grE  rG  r?  s    r-   rK  rL    rJ  r1   c                     grE  rG  r   s     r-   rK  rL    ra  r1   c                     grE  rG  )r  repss     r-   rK  rL    r  r1   c                     grE  rG  )r  r`   r  copyrg   s        r-   rK  rL    s    lnr1   )masked_gradc                    grE  rG  r  r`   rX  s      r-   rK  rL    rF  r1   c                     grE  rG  rZ  s      r-   rK  rL    r&  r1   c                     grE  rG  r?  s    r-   rK  rL    r  r1   c                     grE  rG  r?  s    r-   rK  rL    r  r1   c                     grE  rG  r?  s    r-   rK  rL    r  r1   c                     grE  rG  rg  s     r-   rK  rL    rX  r1   c                     grE  rG  rc  s       r-   rK  rL    rX  r1   c                     grE  rG  )r  r+  r,  s      r-   rK  rL    r  r1   c                     grE  rG  r?  s    r-   rK  rL    r  r1   c                     grE  rG  )r  rf  s     r-   rK  rL    r  r1   c                     grE  rG  rg  s     r-   rK  rL    rX  r1   c                     grE  rG  r?  s    r-   rK  rL    rB  r1   c                     grE  rG  )r  r.  max_version	dl_devicerW  s        r-   rK  rL    r\  r1   c                     grE  rG  r?  s    r-   rK  rL    ra  r1   c                     grE  rG  )r  r  r  s      r-   rK  rL    r  r1   c                     grE  rG  )r  r  r   drivers       r-   rK  rL    r  r1   c                     grE  rG  )r  r_   r  r$   s       r-   rK  rL    r  r1   c                     grE  rG  r?  s    r-   rK  rL    r  r1   is______i__rbitwise_N)rR  rR  N)rR  N)h㈵>:0yE>F)F)NFN)Nr   FT)NN)NNNr  N)Nr   )FFN)r   N)       @#use_mm_for_euclid_dist_if_necessary)r  F)FN)NNN)rR  NN)   F)NrR  r   rR  rR  )NrR  r   r   rR  rR  )r   NNr  )rR  rw  )rF  N)r   r  FrE  )rR  rF  NNN)r   r   rR  )r   rF  )rz  )LN)NNrx  FF)Nrz  Fr  FNN)NNNF)FF)NrF  N)Nr{  rF  N)r   rF  )TT)NF)NNrR  )NNrv  T)      ?)NFr   N)r  NNr  )d   r   r   N)r  NNNFN)NNF)T)NNNTFNNF)NNr  F)NNNNNNNNNNNNN)TFN)TN)Nr   rR  F)Nr   rR  FF)NFNN)rF  FN)        NNN)NNrv  )Nrv  )rz  NFN)r~  FF)Nr   FTN)NNF皙?rv  )NNNr  )NNNr  r  )r~  TF)	NNrz  Fr  FNFN)rR  r   rR  )NNFN)Fư>r  )none)rF  )bilinearr   N)rR  Fg|=rF  )g      r  F)NNNNTr  rv  )NNnearestNNF)NNr  N)g{Gz?F)g-C6?g      ?r  )Nr3   N)Nr   N)TNTNFNNNNNNF)rR  r  NNNr  )NNr  )NNr  Nr  )rz  rR  g-q=N)r   r   )rx  r  F)TFNrw  Nr  )Nr  )g      ?gUUUUUU?FF)Nr  )NNr  r  )r  r  N)rR     )r  rz  r  FNNr  )r  r  N)r   fan_in
leaky_reluN)froNFNN)NNFNN)rz  NFNN)r  r}  FNN)rz  r   )TF)NTrz  )V瞯<)r  F)reducedN)NFlinearN)rG  rP  rQ  F)rG  )r   r   )rR  rR  F)rG  )r   r   r   )rR  rR  rR  F)rR  rn  )r5  NNNr   F)r   NNrR  )rF  F)	NNNTreflectFTNN)TTN)   rz  N)rz  N)TFF)TFFN)rR  rz  )Nr   NN)NNNN(  r5   r6   rM  absoluteadaptive_avg_pool1dadaptive_max_pool1dacosr  arccosacosharccoshr;  addbmmaddcdivaddcmuladdmmaddmvaddraffine_grid_generatorallallclosealpha_dropoutamaxaminaminmaxangleanyargmaxargminargsortasin_assert_asyncarcsinasinharcsinhatanarctanatan2arctan2atanharctanh
atleast_1d
atleast_2d
atleast_3d
avg_pool1dbaddbmm
batch_normbatch_norm_backward_elemtbatch_norm_backward_reducebatch_norm_elemtbatch_norm_gather_stats#batch_norm_gather_stats_with_countsbatch_norm_statsbatch_norm_update_stats	bernoullir   binary_cross_entropy_with_logitsbincountbinomialbitwise_andbitwise_not
bitwise_orbitwise_xorbitwise_left_shiftbitwise_right_shift
block_diagbmmbroadcast_tensorsbroadcast_to	bucketizecartesian_prodcatconcatconcatenatecdistceilceluchain_matmulchannel_shufflecholeskylinalgcholesky_excholesky_inversecholesky_solvechoose_qparams_optimizedchunkclampclip	clamp_min	clamp_maxcolumn_stackcovclonecombinationscomplexcopysignpolarr   conjconj_physicalresolve_conjresolve_negconstant_pad_ndconv1dconv2dconv3dconvolutionconv_tbcconv_transpose1dconv_transpose2dconv_transpose3dcorrcoefcoscosine_embedding_losscoshcosine_similaritycount_nonzerocrossctc_losscummaxcummincumprodcumsumcumulative_trapezoidlogcumsumexpdeg2rad
dequantizedetdetachdiag
diag_embeddiagflatdiffr  diagonal_scatteras_strided_scatterdigammadistdivdividedotrT  dsmmhsmmdsplitdstackr  eigvalseigheigvalsheinsum	embeddingembedding_bag
empty_likeeqequalerferfcerfinvexpexp2expm1 fake_quantize_per_channel_affinefake_quantize_per_tensor_affinefused_moving_avg_obs_fake_quantfbgemm_linear_fp16_weight)fbgemm_linear_fp16_weight_fp32_activationfbgemm_linear_int8_weight)fbgemm_linear_int8_weight_fp32_activationfbgemm_linear_quantize_weightfbgemm_pack_gemm_matrix_fp16fbgemm_pack_quantized_matrixfeature_alpha_dropoutfeature_dropoutr   ifftrfftirffthfftihffthfft2ihfft2hfftnihfftnfftnifftnrfftnirfftnfft2ifft2rfft2irfft2fftshift	ifftshiftfixflattenflipfliplrflipudfrobenius_normfloorfloor_dividefloat_powerfmodfracfrexp	full_likestrided_functional_assert_async	lu_unpackgathergcdge
get_devicegreater_equalgeqrfi0inneroutergerr  grid_samplergrid_sampler_2dgrid_sampler_3d
group_normgrugru_cellgtgreater
hardshrinkhash_tensor	heavisidehinge_embedding_losshistc	histogramhistogramddhouseholder_producthspmmhsplithstackhypotigammaigammacrI  	index_add
index_copy	index_putindex_select
index_fillindex_reduceisfiniteisinisinfisrealisposinfisneginfinstance_normint_reprinverseinvinv_ex
is_complexis_conjis_negis_distributedis_inferenceis_floating_point
is_nonzerois_same_size	is_signediscloseisnanistftkl_divkronkthvalueldl_factor_ex
ldl_factor	ldl_solve
layer_normlcmldexple
less_equallerplgammalobpcgloglog_softmaxlog10log1plog2	logaddexp
logaddexp2logdetxlogylogical_andlogical_not
logical_orlogical_xorlogit	logsumexplstm	lstm_cellltlesslulu_solvemargin_ranking_lossmasked_fillmasked_scattermasked_selectmatmul	lu_factorlu_factor_exmatrix_powermatrix_rank	multi_dot
matrix_expr5  maximumfmax
max_pool1d
max_pool2d
max_pool3dmax_pool1d_with_indicesr  nanmeanr  	nanmedianmeshgridr4  minimumfminmiopen_batch_normmiopen_convolutionmiopen_convolution_add_relumiopen_convolution_relumiopen_convolution_transposemiopen_depthwise_convolution
miopen_rnnmmr  movedimmoveaxismsortmulmultiplymultinomialmvmvlgammanarrow
nan_to_numnative_batch_norm_native_batch_norm_legitnative_dropoutnative_layer_norm_fused_rms_normnative_group_normnative_normnative_channel_shufflene	not_equalnegr  	nextafterr   r   adaptive_avg_pool2dadaptive_avg_pool3d adaptive_max_pool1d_with_indicesadaptive_max_pool2d adaptive_max_pool2d_with_indicesadaptive_max_pool3d adaptive_max_pool3d_with_indicesaffine_grid
avg_pool2d
avg_pool3dbinary_cross_entropycross_entropy	dropout1d	dropout2d	dropout3delufoldfractional_max_pool2d"fractional_max_pool2d_with_indicesfractional_max_pool3d"fractional_max_pool3d_with_indicesgaussian_nll_lossgeluglugrid_samplegumbel_softmaxhardtanhinterpolatel1_lossr  r  local_response_norm
logsigmoid	lp_pool1d	lp_pool2d	lp_pool3dmax_pool2d_with_indicesmax_pool3d_with_indicesmax_unpool1dmax_unpool2dmax_unpool3dmse_lossmulti_head_attention_forwardmulti_margin_lossmultilabel_margin_lossmultilabel_soft_margin_lossnll_loss	normalizeone_hotrW  pairwise_distancepoisson_nll_lossprelurelurelu6rms_normrreluselusilumishscaled_dot_product_attentionsmooth_l1_loss
huber_losssoft_margin_losssoftmaxsoftminsoftplus
softshrinksoftsign
tanhshrinkr  triplet_margin_loss!triplet_margin_with_distance_lossunfoldr   uniform_normal_	constant_kaiming_uniform_nonzerononzero_staticargwherer  vector_normmatrix_normnorm_except_dimnuclear_normr*  orgqrormqrpermutepca_lowrankpdistpinversepinvpixel_shufflepixel_unshufflepoisson	polygammar  	ones_liker  prodputq_per_channel_axisq_per_channel_scalesq_per_channel_zero_pointsq_scaleq_zero_pointqrquantilenanquantilequantize_per_channelquantize_per_tensorquantize_per_tensor_dynamicquantized_batch_normquantized_gru_cellquantized_lstm_cellquantized_max_pool1dquantized_max_pool2dquantized_max_pool3dquantized_rnn_relu_cellquantized_rnn_tanh_cellrad2degravelrH  vdotvecdotview_as_realview_as_complex
reciprocal	remainderrenormrepeat_interleavereshapernn_relurnn_relu_cellrnn_tanhrnn_tanh_cellrollrot90round	row_stack_rowwise_prunersqrtrsubsaddmmscatterscatter_addscatter_reducesearchsorted_segment_reduceselectselect_scatterslice_inverseslice_scatterr   signsignbitsgnsinsincsinhslogdetsmmspmmr  solve_exsortsplitsplit_with_sizessqrtsquaresqueezesspaddmmstackr  std_meanstftsubsubtractsum	sym_floatsym_intsym_maxsym_minsym_notsym_itesym_sum	_sym_sqrt_sym_cos	_sym_cosh_sym_sin	_sym_sinh_sym_tan	_sym_tanh	_sym_asin	_sym_acos	_sym_atannansumsvdsvd_lowranksvdvalsswapaxesswapdimsspecialairy_ai	bessel_j0	bessel_j1	bessel_y0	bessel_y1chebyshev_polynomial_tchebyshev_polynomial_uchebyshev_polynomial_vchebyshev_polynomial_wentrerfcxexpitgammainc	gammainccgammalnhermite_polynomial_hhermite_polynomial_hei0ei1i1elaguerre_polynomial_llegendre_polynomial_plog_ndtrmodified_bessel_i0modified_bessel_i1modified_bessel_k0modified_bessel_k1multigammalnndtrndtripsiscaled_modified_bessel_k0scaled_modified_bessel_k1shifted_chebyshev_polynomial_tshifted_chebyshev_polynomial_ushifted_chebyshev_polynomial_vshifted_chebyshev_polynomial_wspherical_bessel_j0xlog1pyzetattaketake_along_dimtanr   	tensorinvtensorsolve	tensordottensor_splittiletopktracer  trapz	trapezoidtriangular_solvesolve_triangulartriltriutrue_dividetruncunbindr  uniqueunique_consecutiveunravel_indexunsafe_chunkunsafe_splitunsafe_split_with_sizes	unsqueezer   r  var_meanvsplitvstackwhere_wrapped_linear_prepack#_wrapped_quantized_linear_prepacked
zeros_like_fw_primal_copy_make_dual_copyview_as_real_copyview_as_complex_copy
_conj_copy_neg_view_copyas_strided_copy_sparse_broadcast_to_copydiagonal_copyexpand_copynarrow_copypermute_copy_reshape_alias_copyselect_copydetach_copy
slice_copy
split_copysplit_with_sizes_copysqueeze_copyt_copytranspose_copyunsqueeze_copy_indices_copy_values_copyindices_copyvalues_copycrow_indices_copycol_indices_copyccol_indices_copyrow_indices_copyunbind_copy	view_copyunfold_copy
alias_copy__floordiv____rfloordiv____ifloordiv____truediv____rtruediv____itruediv__
__lshift____rlshift____ilshift__
__rshift____rrshift____irshift____and____or____xor__	__float____complex__	__array____bool____contains____neg__
__invert____mod____rmod____imod____array_wrap____getitem____deepcopy____int____long__	__index____len__
__format____reduce_ex____reversed____repr____setitem____setstate__Tr.  HmTmH_backward_hooks_post_accumulate_grad_hooksr?  _cdatar@  rA  _grad_fngrad_fn
grad_dtype_version_autocast_to_reduced_precision_autocast_to_full_precision#_clear_non_serializable_cached_datar  r_   r`   is_cudais_cpuis_xlais_xpuis_ipuis_leafretains_gradis_metais_mpsis_mtia	is_nestedis_maia	is_mkldnnis_quantized	is_sparseis_sparse_csr	is_vulkanitemsizern   r5  r  nbytesndim	output_nrr  rf  volatile__cuda_array_interface__type_dimI_dimV_indices_is_view_nnzcrow_indicescol_indicesccol_indicesrow_indices_update_names_valuesalign_asalign_toapply_rq   as_strided_backwardbfloat16preserve_formatboolbytecharcauchy_coalesce_coalesced_
contiguouscontiguous_formatcopy_cpucudamtiaxpuipudata_ptrrL  r  	dim_orderdoublecdoubleelement_sizeexpand	expand_asexponential_fill_fill_diagonal_floatcfloat
geometric_halfchalf	has_namesr}  intis_coalescedis_contiguous	is_pinned	is_set_to	is_shareditemlog_normal_longmap_map2_module_load
ndimensionnelement_nested_tensor_size_nested_tensor_storage_offsets_nested_tensor_stridesnumpy
pin_memoryput_rh   random_record_streamrefine_namesregister_hook"register_post_accumulate_grad_hookrenamerepeatrequires_grad_
reshape_asresizeresize_	resize_asresize_as_sparse_retain_gradset_share_memory_shortr  
sparse_dimsparse_mask_sparse_mask_projectionsparse_resize_sparse_resize_and_clear_storageuntyped_storager  storage_typesum_to_sizer,  to_dense	_to_dense	to_sparsetolist	to_mkldnntype_asre  viewview_aszero_
__dlpack____dlpack_device__r4  r  utilsbackend_registration_privateuse1_backend_namehasattrgetattrr   items__name__
startswithlenextendr  update)r6   retprivateuse1_backend_nameret2ignoredr  r  r  subnamer5  r   s              r-   r   r     sW   6 \\F{%		-{%2{% 	!!#@{% 	!!#A	{%
 	

.{% 	'{% 	0{% 	/{% 	1{% 			4{% 	Q{% 	L{% 	L{% 	L{% 	J{%  	

K!{%" 	##%J#{%$ 			-%{%& 	X'{%( 	F){%* 	

.+{%, 	

.-{%. 	J/{%0 	/1{%2 			F3{%4 	&5{%6 	&7{%8 	19{%: 	

.;{%< 	2={%> 	0?{%@ 	/A{%B 	1C{%D 	

.E{%F 	0G{%H 	6I{%J 	8K{%L 	/M{%N 	1O{%P 	-Q{%R 	-S{%T 	-U{%V 	xW{%X 	RY{%Z 	{[{%\ 	''){]{%^ 	((*u_{%` 	 Qa{%b 	%%'vc{%d 	11  4Ce{%f 	 5g{%h 	%%'\i{%j 	Ck{%l 	?m{%n 	..tq{%t 	Cu{%v 	>w{%x 	<y{%z 	5{{%| 	;}{%~ 	<{%@ 	  "CA{%B 	!!#DC{%D 	-E{%F 			CG{%H 	!4I{%J 	1K{%L 	]M{%N 	1O{%P 			6Q{%R 	9S{%T 	>U{%V 	aW{%X 	

.Y{%Z 	

>[{%\ 	$:]{%^ 	7_{%` 	?a{%b 	9c{%d 	  "Pe{%f 	 Gg{%h 	Ni{%j 	&&(Yk{%l 	4m{%n 	Co{%p 	

Bq{%r 	8s{%t 	8u{%v 	8w{%x 			Oy{%z 	%{{%| 	I}{%~ 	,{%@ 	9A{%B 	(C{%D 	5E{%F 	

.G{%H 	7I{%J 	6K{%L 	5M{%N 	=O{%P 	dQ{%R 	dS{%T 	dU{%V 	wW{%X 	=Y{%Z 	  !A[{%\ 	  !A]{%^ 	  !A_{%` 	(a{%b 			-c{%d 	##  &Ce{%f 	

.g{%h 	!Ci{%j 	-k{%l 	@m{%n 	Eo{%p 	xs{%v 	5w{%x 	5y{%z 	B{{%| 	A}{%~ 	""$@{%@ 	;A{%B 	1C{%D 	*E{%F 			#G{%H 	*I{%J 	&K{%L 	

:M{%N 	@O{%P 	2Q{%R 	

VS{%T 	BU{%V 	KW{%X 	 OY{%Z 	  "Y[{%\ 	1]{%^ 	

0_{%` 			Ha{%b 	Kc{%d 			4e{%f 	@g{%h 	

:i{%j 	

)k{%l 	;m{%n 	2o{%p 	4q{%r 	8s{%t 	?u{%v 	Cw{%x 	4y{%z 	|}{%@ 	 jC{%F 	eG{%H 	3I{%J 	,K{%L 			-M{%N 	

.O{%P 	0Q{%R 			-S{%T 	

.U{%V 	/W{%X 	..0oY{%Z 	--/h[{%\ 	-- C_{%b 	'')Vc{%d 	779fe{%f 	'')}g{%h 	77`k{%n 	++-=o{%p 	**,<q{%r 	**,Bs{%t 	##%?u{%v 	9w{%x 			Cy{%z 			C{{%| 			D}{%~ 			C{%@ 			DA{%B 			JC{%D 			KE{%F 			DG{%H 			EI{%J 			EK{%L 			FM{%N 			FO{%P 			GQ{%R 			IS{%T 			JU{%V 			JW{%X 			KY{%Z 			6[{%\ 			7]{%^ 			B_{%` 			-a{%b 	@c{%d 	

*e{%f 	&g{%h 	&i{%j 	Qk{%l 	/m{%n 	3o{%p 	?q{%r 	

5s{%t 	

.u{%v 	/w{%x 	t4PUP]P]fjz  Dy{%z 	&&(H{{%| 	\}{%~ 	O{%@ 			4A{%B 	3C{%D 	*E{%F 	>G{%H 	/I{%J 	,K{%L 	6M{%N 	5O{%P 			3Q{%R 	NS{%T 	cU{%V 	fW{%X 	fY{%Z 	m[{%\ 			s]{%^ 	N_{%` 	3a{%b 	8c{%d 	5e{%f 	Vg{%h 	;i{%j 	""$zk{%l 	Gm{%n 	mo{%p 	Yq{%r 	((*?s{%t 	4u{%v 	;w{%x 	2y{%z 	6{{%| 	7}{%~ 	8{%@ 	

.A{%B 	=C{%D 	>E{%F 	LG{%H 	BI{%J 	=K{%L 	\M{%N 	)O{%P 	

GQ{%R 	&S{%T 	'U{%V 	2W{%X 	2Y{%Z 	t]{%` 	(a{%b 	1c{%d 	4e{%f 	Kg{%h 	*i{%j 	'k{%l 	&m{%n 	.o{%p 	,q{%r 	!1s{%t 	*u{%v 	3w{%x 	)y{%z 	W{{%| 	%}{%~ 	 dA	{%D	 	rE	{%F	 	

+G	{%H	 	NI	{%J	 	""$cK	{%L	 	!LM	{%N	 	 SO	{%P	 	sQ	{%R	 			4S	{%T	 	6U	{%V	 	3W	{%X	 	;Y	{%Z	 	

;[	{%\	 	0]	{%^	 	  K_	{%`	 			-a	{%b	 	<c	{%d	 	/e	{%f	 	/g	{%h	 	

.i	{%j	 	:k	{%l	 	;m	{%n	 	&o	{%p	 	.q	{%r	 	<s	{%t	 	5u	{%v	 	;w	{%x	 	<y	{%z	 	/{	{%|	 	I}	{%~	 	

s	{%@
 	OA
{%B
 	3C
{%D
 	

5E
{%F
 	EG
{%H
 	BI
{%J
 	!!  $AK
{%L
 	8M
{%N
 	<O
{%P
 	=Q
{%R
 	7S
{%T
 	?U
{%V
 	 FW
{%X
 	!!#]Y
{%Z
 	[[
{%\
 	>]
{%^
 	/_
{%`
 	!!#@a
{%b
 	  "Mc
{%d
 	 <e
{%f
 	*g
{%h
 	!1i
{%j
 			-k
{%l
 	8m
{%n
 	

5o
{%p
 	lq
{%r
 	ls
{%t
 	lu
{%v
 	%%ty
{%|
 	

.}
{%~
 	V
{%@ 	0A{%B 	3C{%D 	5E{%F 			-G{%H 	8I{%J 	

5K{%L 	tO{%R 	  "}S{%T 	))+vU{%V 	%%'hW{%X 	**w[{%^ 	**ga{%d 	 dg{%j 	Bk{%l 	

Em{%n 	<o{%p 	=q{%r 	As{%t 			4u{%v 	9w{%x 	Uy{%z 	1{{%| 	+}{%~ 	:{%@ 	WA{%B 	!sC{%D 	&&(_E{%F 	8G{%H 	!fI{%J 	YK{%L 	!VM{%N 	UO{%P 	$$&>Q{%R 	3S{%T 	:U{%V 			-W{%X 	2Y{%Z 	:[{%\ 	//1N]{%^ 	//1N_{%` 	//1da{%b 	<<>qc{%d 	//1de{%f 	<<>qg{%h 	//1di{%j 	<<>qk{%l 	'')Sm{%n 	))+ao{%p 	&& Bs{%v 	&& By{%| 	&&x{%B 	$$&RC{%D 	00cG{%J 	<<tM{%P 	  "LQ{%R 	11iU{%X 	)) L[{%^ 	$$xa{%d 	##%Ze{%f 	%%'\g{%h 	%%'\i{%j 	%%'\k{%l 	!Km{%n 	%%|q{%t 	)) Jw{%z 	113i{{%| 	  "m}{%~ 	11zA{%D 	>>zG{%J 	11zM{%P 	>>zS{%V 	--/uW{%X 	  "FY{%Z 	!9[{%\ 	'')z]{%^ 	&&(g_{%` 	**,ca{%b 	&&(Cc{%d 	$$&`e{%f 	00bi{%l 	)) Io{%r 	'' Mu{%x 	""  %Ay{%z 	##%|{{%| 	&&(m}{%~ 	&&(\{%@ 	""$GA{%B 	//1gC{%D 	'')^E{%F 	&&(8G{%H 	%%'mI{%J 	%%'mK{%L 	%%'mM{%N 	//iQ{%T 	&&tW{%Z 	33t]{%` 	&&tc{%f 	33ti{%l 	&&to{%r 	33tu{%x 	((*zy{%z 	((*z{{%| 	((*z}{%~ 	$$&}{%@ 	88 _C{%F 	--tI{%L 	22VO{%R 	77cU{%X 	$$v[{%^ 	%%'X_{%` 	##%Fa{%b 	!Pc{%d 	--/ae{%f 	,,}i{%l 	!!#;m{%n 	  "Ao{%p 	!!#Bq{%r 	$$&_s{%t 	!!#yu{%v 	  "Aw{%x 	  "Ay{%z 	  "A{{%| 	88:u}{%~ 	**  -A{%@ 	&&(jA{%B 	,,.xC{%D 	##%ZE{%F 	##%ZG{%H 	$$&LI{%J 	&&(CK{%L 	$$&6M{%N 	&&(8O{%P 	%%'XQ{%R 	// LU{%X 	==DHQT[`lrv[{%^ 	""$b_{%` 	 Oa{%b 	Sc{%d 	!7e{%f 	&&(xg{%h 	7i{%j 	Fk{%l 	(m{%n 	

\o{%p 	dq{%r 	  "hs{%t 	   +/#3u{%| 	9}{%~ 	d{%@ 	%A{%B 	*C{%D 	QE{%F 	!SG{%H 	+I{%J 	IK{%L 	*M{%N 	5O{%P 	IQ{%R 	=S{%T 	AU{%V 	7W{%X 	 YY{%Z 	6[{%\ 	2]{%^ 	-_{%` 	da{%b 			7c{%d 	

0e{%f 			Dg{%h 	  "2i{%j 	""$4k{%l 	'')9m{%n 	'o{%p 	,q{%r 	7s{%t 	Cu{%v 	fw{%x 	iy{%z 	""$V{{%| 	!!#M}{%~ 	))+P{%@ 	""$sA{%B 	   aE{%H 	!! aK{%N 	""J#Q{%X 	""L #[{%d 	""O 	#g{%r 	%% au{%x 	%% a{{%~ 	1{%@ 	%A{%B 	

.C{%D 	

5E{%F 	FG{%H 	,I{%J 	/K{%L 	4M{%N 	

3O{%P 	:Q{%R 	AS{%T 	!;U{%V 	.W{%X 	QY{%Z 	x[{%\ 	S]{%^ 	x_{%` 	Sa{%b 	

7c{%d 	7e{%f 	/g{%h 	5i{%j 	Pk{%l 	bm{%n 	/o{%p 	

4q{%r 	Ms{%t 	8u{%v 	<w{%x 	Zy{%z 	e{{%| 	|}{%~ 	2{%@ 	?A{%B 	WC{%D 	WE{%F 	

3G{%H 	1I{%J 	

.K{%L 	1M{%N 			-O{%P 			-Q{%R 	

.S{%T 	

.U{%V 	'W{%X 	.Y{%Z 			9[{%\ 	

:]{%^ 	8_{%` 	@a{%b 	Wc{%d 	

YeQUYe{%f 	Eg{%h 	 Pi{%j 	

.k{%l 	0m{%n 	;o{%p 	Oq{%r 	8s{%t 			-u{%v 	2w{%x 	

 @{{%~ 			4{%@ 	9A{%B 			-C{%D 	)E{%F 	'G{%H 	I{%J 	K{%L 	'M{%N 	)O{%P 	Q{%R 	)S{%T 	(U{%V 	)W{%X 	(Y{%Z 	)[{%\ 	(]{%^ 	)_{%` 	)a{%b 	)c{%d 	)e{%f 	0g{%h 			Ii{%j 	Ak{%l 	Hm{%n 	8o{%p 	4q{%r 	6s{%t 	/u{%v 	!1w{%x 	!1y{%z 	!1{{%| 	!1}{%~ 	,,.K{%@ 	,,.KA{%B 	,,.KC{%D 	,,.KE{%F 	/G{%H 	,I{%J 	+K{%L 	,M{%N 	-O{%P 	.Q{%R 	,S{%T 	-U{%V 	-W{%X 	 AY{%Z 	!B[{%\ 	/]{%^ 	**,I_{%` 	++-Ja{%b 	*c{%d 	+e{%f 	*g{%h 	+i{%j 	++-Jk{%l 	++-Jm{%n 	-o{%p 	 0q{%r 	!!#Ds{%t 	-u{%v 	!Ow{%x 	((*:y{%z 	((*:{{%| 	((*:}{%~ 	((*:{%@ 	""$7A{%B 	,C{%D 	-E{%F 	!>G{%H 	+I{%J 	-K{%L 	//1AM{%N 	//1AO{%P 	446SQ{%R 	446SS{%T 	446SU{%V 	446SW{%X 	,Y{%Z 	@[{%\ 	))+;]{%^ 	@_{%` 	>a{%b 	<c{%d 	!e{%f 	

+g{%h 	Ki{%j 			-k{%l 	

.m{%n 	 3o{%p 	  "<q{%r 	:s{%t 	Hu{%v 	Jw{%x 	

*y{%z 	

K{{%| 	%}{%~ 	5{%@ 	1A{%B 	5C{%D 	 eE{%F 	%%'aG{%H 	

:I{%J 	!! LM{%P 	

:Q{%R 	2S{%T 	/U{%V 	-W{%X 	<Y{%Z 	h[{%\ 	  "g]{%^ 	6_{%` 	;a{%b 	Lc{%d 	%%'We{%f 	8g{%h 	1i{%j 			-k{%l 	2m{%n 	;o{%p 	2q{%r 	9s{%t 	%%'`u{%v 	11oy{%| 	e}{%~ 	5{%@ 	@A{%B 	C{%D 	""OE{%F 	/G{%H 	oI{%J 	QK{%L 	'')>M{%N 	FO{%P 	%CQ{%R 	>S{%T 	1U{%V 	!!#@W{%X 	6Y{%Z 	?[{%\ 	N]{%^ 	<_{%` 	##%Ha{%b 	0c{%d 	oe{%f 	9g{%h 	2i{%j 	_k{%l 	Om{%n 	Oo{%p 	?q{%r 	s{%t 	u{%v 	w{%x 	y{%z 	1{{%| 	/}{%~ 	A{%@ 	/A{%B 	3C{%D 	4E{%F 	4G{%H 	2I{%J 	3K{%L 	3M{%N 	1O{%P 	2Q{%R 	2S{%T 	1U{%V 	2W{%X 	2Y{%Z 	.[{%\ 	-]{%^ 	._{%` 	/a{%b 	Oc{%d 	0e{%f 	g{%h 	3i{%j 	k{%l 	?m{%n 	.o{%p 	/q{%r 	/s{%t 	5u{%v 	0w{%x 	2y{%z 	{{%| 	}{%~ 	/{%@ 	A{%B 	7C{%D 	4E{%F 	_G{%H 	AI{%J 	1K{%L 	/M{%N 	/O{%P 	/Q{%R 			?S{%T 			?U{%V 	&&W{%X 	**22OY{%Z 	o[{%\ 	]{%^ 	__{%` 	oa{%b 	c{%d 	e{%f 	!!?g{%h 	i{%j 	--/pk{%l 	**,Vm{%n 	22Oo{%p 	_q{%r 	s{%t 	ou{%v 	w{%x 	y{%z 	{{%| 	}{%~ 	{%@ 	A{%B 	##_C{%D 	E{%F 	G{%H 	I{%J 	  /K{%L 	M{%N 	  /O{%P 	##_Q{%R 	  /S{%T 	$$oU{%V 	  /W{%X 	Y{%Z 	[{%\ 	_]{%^ 	o_{%` 	a{%b 	_c{%d 	  /e{%f 	$$og{%h 	oi{%j 	k{%l 	_m{%n 	_o{%p 	''//q{%r 	Ns{%t 	ou{%v 	ow{%x 	y{%z 	{{%| 	_}{%~ 	_{%@ 	OA{%B 	_C{%D 	OE{%F 	=G{%H 	I{%J 	K{%L 	/M{%N 	=O{%P 	0Q{%R 	8S{%T 	9U{%V 	kW{%X 	E4I4IMY{%Z 	0E0EI[{%\ 	0E0EI]{%^ 	0E0EI_{%` 	MTMa{%b 	c{%d 	6e{%f 	e6M6MQg{%h 	>i{%j 	

u/D/DHk{%l 	0E0EIm{%n 	0E0EIo{%p 	

u/D/DHq{%r 	

u/D/DHs{%t 	u{%v 	/w{%x 	!Oy{%z 	

O{{%| 	@}{%~ 	%2G2GK{%@ 	53H3HLA{%B 	_C{%D 	,E{%F 	0G{%H 	HHI{%J 	,K{%L 	5M{%N 	1F1FJO{%P 	%2G2GKQ{%R 	@S{%T 	?U{%V 	0E0EIW{%X 	1F1FJY{%Z 	/[{%\ 	]{%^ 	

u/D/DH_{%` 	_a{%b 	oc{%d 	_e{%f 	/g{%h 	1i{%j 	/k{%l 	_m{%n 	MTMo{%p 	0q{%r 	0E0EIs{%t 	6u{%v 	5w{%x 			8y{%z 	@{{%| 	E}{%~ 	?{%@  	A {%B  	""OC {%D  	--E {%F  	%%G {%H  	I {%J  	oK {%L  	,M {%N  	?O {%P  	GQ {%R  	S {%T  	LDLU {%V  	5W {%X  	3Y {%Z  	3[ {%\  	113H] {%^  	,_ {%`  	-a {%b  	Bc {%d  	1e {%f  	-g {%h  	-i {%j  	0k {%l  	  "8m {%n  	Oo {%p  	[q {%r  	?s {%t  	ou {%v  	1F1FJw {%x  	_y {%z  	W{ {%|  	?} {%~  	1 {%@! 	&&(WA!{%B! 	GC!{%D! 	'')QE!{%F! 	OG!{%H! 	I!{%J! 	K!{%L! 	M!{%N! 	_O!{%P! 	1Q!{%R! 	+S!{%T! 			EUZUjUjnU!{%V! 	IIW!{%X! 	GY!{%Z! 	/[!{%\! 	]!{%^! 	/_!{%`! 	.a!{%b! 	=c!{%d! 	7e!{%f! 	+.od  /+Fu!{%C|! 	((BB  v00F 	GF56 JYGFc":!;<=EEFD#%G		 JJJJ1::$AJJ%AJJ%
 ::  ,, jjZ!23GLL$&$(>RV@VW D6.D~~$/d6IT
 % . JJtJr1   
dispatcherc                    ^  U 4S jnU$ )a=  Wraps a given function with ``__torch_function__`` -related functionality.

Parameters
----------
dispatcher: Callable
    A callable that returns an iterable of Tensor-likes passed into the function.

Note
----
This decorator may reduce the performance of your code. Generally, it's enough to express
your code as a series of functions that, themselves, support __torch_function__. If you
find yourself in the rare situation where this is not the case, e.g. if you're wrapping a
low-level library and you also need it to work for Tensor-likes, then this function is available.

Examples
--------
>>> def dispatcher(a):  # Must have the same signature as func
...     return (a,)
>>> @torch.overrides.wrap_torch_function(dispatcher)
>>> def func(a):  # This will make func dispatchable by __torch_function__
...     return a + 0
c                 N   >^ ^ [         R                  " T 5      UU U4S j5       mT$ )Nc                  d   > T" U 0 UD6n[        U5      (       a  [        TU/U Q70 UD6$ T" U 0 UD6$ ru  )r   r   )r#   r$   relevant_argsr
  r   wrappeds      r-   r
  3wrap_torch_function.<locals>.inner.<locals>.wrapped=  sD    &77M!-00,WmUdUfUU(((r1   )	functoolsr   )r   r
  r
  s   `@r-   r^  "wrap_torch_function.<locals>.inner<  s%    			) 
	) r1   rG  )r
  r^  s   ` r-   r   r   $  s    0	 Lr1   r
  get_type_fnc                    Uc  [         n[        R                  R                  5       (       d  / $ [	        5       n/ nU  H  nU" U5      nXR;  d  M  [        US5      (       d  M%  UR                  [        R                  R                  Ld  MN  U(       a]  UR                  U5        [        U5      n[        U5       H  u  px[        XQ" U5      5      (       d  M  Un  O   UR                  Xd5        M  U1nU/nM     U$ )a  Returns a list of arguments on which to call __torch_function__.

Checks arguments in relevant_args for __torch_function__ implementations,
storing references to the arguments and their types in overloaded_args and
overloaded_types in order of calling precedence. Only distinct types are
considered. If a type is a subclass of another type it will have higher
precedence, otherwise the precedence order is the same as the order of
arguments in relevant_args, that is, from left-to-right in the argument list.

The precedence-determining algorithm implemented in this function is
described in `NEP-0018`_.

See torch::append_overloaded_arg for the equivalent function in the C++
implementation.

Parameters
----------
relevant_args : iterable of array-like
    Iterable of array-like arguments to check for __torch_function__
    methods.

get_type_fn : callable, optional
    Function to call on each argument in relevant_args to get its type.

Returns
-------
overloaded_args : list
    Arguments from relevant_args on which to call __torch_function__
    methods, in the order in which they should be called.

.. _NEP-0018:
   https://numpy.org/neps/nep-0018-array-function-protocol.html
r  )rc
  r5   _C_is_torch_function_enabledsetr
  r  _disabled_torch_function_implr;  r
  	enumerate
issubclassinsert)	r
  r
  overloaded_typesoverloaded_argsargarg_typer4  iold_args	            r-   _get_overloaded_argsr
  J  s    J  88..00	"%%!#Os# ,"677++8899:
   $$X. O,"+O"<JA!(K,@AA ! #=  &&u2$,: #&%; < r1   
public_apic           	         [        U5      n[        [        [        U5      5      n[	        5       (       a0  [        5        nUR                  XX#5      nSSS5        W[        La  U$ U H|  nUR                  n	[        U	S5      (       aF  U	R                  UL a7  U	[        R                  R                  La  [        R                  " S[        SS9  U	" XX#5      nU[        Ld  Mz  Us  $    U R                    SU R"                   3n
SU
 SU Vs/ s H  n[        U5      PM     sn 3n[	        5       (       a  US	[%        5        3-  n['        U5      e! , (       d  f       GN= fs  snf )
a  Implement a function with checks for ``__torch_function__`` overrides.

See torch::autograd::handle_torch_function for the equivalent of this
function in the C++ implementation.

Arguments
---------
public_api : function
    Function exposed by the public torch API originally called like
    ``public_api(*args, **kwargs)`` on which arguments are now being
    checked.
relevant_args : iterable
    Iterable of arguments to check for __torch_function__ methods.
args : tuple
    Arbitrary positional arguments originally passed into ``public_api``.
kwargs : tuple
    Arbitrary keyword arguments originally passed into ``public_api``.

Returns
-------
object
    Result from calling ``implementation`` or an ``__torch_function__``
    method, as appropriate.

Raises
------
TypeError : if no implementation is found.

Example
-------
>>> def func(a):
...     if has_torch_function_unary(a):
...         return handle_torch_function(func, (a,), a)
...     return a + 0
N__self__zDefining your `__torch_function__ as a plain method is deprecated and will be an error in future, please define it as a classmethod.rz  
stacklevel.zno implementation found for 'z.' on types that implement __torch_function__: z nor in mode )r
  tuplemaprc
  r   _pop_mode_temporarilyr  NotImplementedr
  r
  r5   r
  r
  r)   warnDeprecationWarning
__module__r
  _get_current_function_mode	TypeError)r
  r
  r#   r$   r
  typesr  resultoverloaded_argtorch_func_method	func_namer
  r  s                r-   r   r     s_   T +=9O#dO,-E '(( #$,,ZMF %'M * +==%z22!**n<!)O)OOMMQ"	 #:dC'M+ *. (():+>+>*?@I
'	{ 35DE_cS	_EF	H  '((9;<==
C.I %$@  Fs   E	E

Ea  Check for __torch_function__ implementations in the elements of an iterable
    or if a __torch_function__ mode is enabled.  Considers exact ``Tensor`` s
    and ``Parameter`` s non-dispatchable.  Use this to guard a call to
    :func:`handle_torch_function`; don't use it to test if something
    is Tensor-like, use :func:`is_tensor_like` instead.
    Arguments
    ---------
    relevant_args : iterable
        Iterable or arguments to check for __torch_function__ methods.
    Returns
    -------
    bool
        True if any of the elements of relevant_args have __torch_function__
        implementations, False otherwise.
    See Also
    ________
    torch.is_tensor_like
        Checks if something is a Tensor-like, including an exact ``Tensor``.
    zSpecial case of `has_torch_function` for single inputs.
    Instead of:
      `has_torch_function((t,))`
    call:
      `has_torch_function_unary(t)`
    which skips unnecessary packing and unpacking work.
    a'  Special case of `has_torch_function` that skips tuple creation.

    This uses the METH_FASTCALL protocol introduced in Python 3.7

    Instead of:
      `has_torch_function((a, b))`
    call:
      `has_torch_function_variadic(a, b)`
    which skips unnecessary packing and unpacking work.
    c                     [         R                  " [        5      n 0 nS[        [        R                  4S[        R
                  [        R
                  R                  4S[        R                  R
                  [        [        R                  R
                  5      4S[        R                  R                  [        [        R                  R                  5      4S[        R                  [        [        R                  5      4S[        R                  [        [        R                  5      4S[        R                  [        [        R                  5      4S[        R                  [        [        R                  5      4/nU GHz  u  p4nU GHl  nS	nU[        R                  Lan  UR                  S
5      (       a  M1  UR                  S5      (       a  SnOgUR                  S5      (       a  SnONUS   R                  5       (       d  SnO3US:X  a  M  O*[!        XF5      n[!        ["        US 5      U:X  a  M  US:X  a  M  [!        XF5      nU[        R                  L a  [!        ["        US 5      U:X  a  M  [%        U[&        R(                  5      (       a  GM  [%        U[*        R,                  5      (       a  GM*  [/        U5      (       d  [1        US5      (       a  U SU S3XR2                  '   U SU S3XR4                  '   U(       a  GM}  UR2                  [7        5       ;   a=  Sn	UR2                  [9        5       ;  d    U	R;                  XHR<                  5      5       eGM  X   R?                  UR2                  5        GM  [/        U5      (       d  GM  U SU 3X'   U(       a  GM  U[7        5       ;   a3  Sn	U[9        5       ;  d    U	R;                  XHR<                  5      5       eGMY  X   R?                  U5        GMo     GM}     X4$ )Nr5   ztorch.functionalztorch.nn.functionalztorch.nn.initztorch.Tensorztorch.linalgz	torch.fftztorch.specialFrq  rp  Tr   
unique_dim__weakref__r.  r
  z.__get__z.__set__zk{}.{} is in the tuple returned by torch._overrides.get_ignored_functions but still has an explicit override) collectionsdefaultdictlistr5   __all__r   r   dirr   r6   r  r   r	  r
  endswithislowerr
  object
isinstancer  
ModuleType
__future___Featurer  r
  r.  __set__r   r   formatr
  r  )
overridable_funcsr4  tested_namespacesnamespace_str	namespacens_funcsr	  r&   r   r  s
             r-   _get_overridable_functionsr   #  sB    $//5E	%'	U--u/?/?/G/GH	 3 3S9L9L5MN	%((--UXX]]);<	s5<<'89	s5<<'89	eiiUYY0	%--U]]);<	 /@*(!IF,''--))#..!F'',,!F"1--//!F,. / y469d3t;-90DELL(WVY-MQU-U$ 0 011$
 3 344D>>gdI&>&>)6q8&Lll#)6q8&Lll#<<#8#::=   <</D/FF 

!==I F %+224<<@D>>*O1YK8EK ,..9  #8#:: CJJ}}= : (//5E " /@H ##r1   c                      [        5       S   $ )zList functions that are overridable via __torch_function__

Returns
-------
Dict[Any, List[Callable]]
    A dictionary that maps namespaces that contain overridable functions
    to functions in that namespace that can be overridden.
r   )r   rG  r1   r-   r   r   z  s     &'**r1   c                     [        U [        R                  R                  [        R                  R                  45      (       a  [        U 5      $ [        5       S   R                  U 5      $ )zGet a human readable string name for a function passed to
__torch_function__

Arguments
---------
f : Callable
    Function to resolve the name of.

Returns
-------
str
    Name of the function; if eval'ed it should give back the input
    function.
rR  )r  r5   _ops
OpOverloadOpOverloadPacketstrr   get)fs    r-   r   r     sL      !ejj++UZZ-H-HIJJ1v%'*..q11r1   c                  R    [        5       n [        U [        R                     5      nU$ )z<Returns a set of the overridable methods on ``torch.Tensor``)r   r
  r5   r6   )r  methodss     r-   _get_tensor_methodsr+    s&     23#ELL12GNr1   c                 H    U [        5       ;   =(       d    U R                  S:H  $ )a7  
Returns True if the function passed in is a handler for a
method or property belonging to ``torch.Tensor``, as passed
into ``__torch_function__``.

.. note::
   For properties, their ``__get__`` method must be passed in.

This may be needed, in particular, for the following reasons:

1. Methods/properties sometimes don't contain a `__module__` slot.
2. They require that the first passed-in argument is an instance
   of ``torch.Tensor``.

Examples
--------
>>> is_tensor_method_or_property(torch.Tensor.add)
True
>>> is_tensor_method_or_property(torch.add)
False
r.  )r+  r
  )r   s    r-   r   r     s!    . &((FDMMY,FFr1   c                 ^    [        U 5      [        R                  L =(       d    [        U S5      $ )a  
Returns ``True`` if the passed-in input is a Tensor-like.

Currently, this occurs whenever there's a ``__torch_function__``
attribute on the type of the input.

Examples
--------
A subclass of tensor is generally a Tensor-like.

>>> class SubTensor(torch.Tensor): ...
>>> is_tensor_like(SubTensor([0]))
True

Built-in or user types aren't usually Tensor-like.

>>> is_tensor_like(6)
False
>>> is_tensor_like(None)
False
>>> class NotATensor: ...
>>> is_tensor_like(NotATensor())
False

But, they can be made Tensor-like by implementing __torch_function__.

>>> class TensorLike:
...     @classmethod
...     def __torch_function__(cls, func, types, args, kwargs):
...         return -1
>>> is_tensor_like(TensorLike())
True
r  )rc
  r5   r6   r
  )inps    r-   r   r     s%    D 9$J5I(JJr1   c                   T    \ rS rSr% SrS \S'   SS jrSS jrS rS	 r	\
S
 5       rSrg)TorchFunctionModei  a  
A ``TorchFunctionMode`` allows you to override the meaning of all
``__torch_function__`` overridable functions within a dynamic scope,
without having to actually create a tensor subclass or manually
monkey-patch functions in the PyTorch API.  Some common situations
where you should use a mode:

    * You want to override the meaning of factory functions, or other
      functions that do not otherwise take a tensor as an argument
      (these cannot be overridden with tensor subclasses).

    * You want to override the behavior of all functions without needing
      to wrap your inputs in tensor subclasses; e.g., if you are just
      interested in logging intermediate computations.

    * You want to control the order of execution of various tensor
      subclasses explicitly, rather than implicitly via the return of
      ``NotImplemented``.

Independent subclasses of :class:`TorchFunctionMode` are compositional:
modes can be pushed onto a stack using ``with MyMode():``.
When you call functions in the PyTorch API inside your
``__torch_function__`` implementation, by default, they will forward on to
the next mode on the mode stack.  If you want recursively call back into
your current ``__torch_function__`` implementation, either explicitly
invoke ``self.__torch_function__(...)``, or use the context manager
``enable_torch_function_mode(self, replace=self.inner)`` to make PyTorch
API self-referential (beware of infinite loops, in this case!)
r^  Nc                     g ru  rG  r?  s    r-   r   TorchFunctionMode.__init__  s    r1   rG  c                     [         eru  )NotImplementedErrorr  r   r  r#   r$   s        r-   r  $TorchFunctionMode.__torch_function__  s    !!r1   c                     [        U 5        U $ ru  )
_push_moder?  s    r-   	__enter__TorchFunctionMode.__enter__  s    4r1   c                     [        5         g ru  )	_pop_mode)r  exc_typeexc_valexc_tbs       r-   __exit__TorchFunctionMode.__exit__  s    r1   c                 @    [         R                  " SSS9  U " U0 UD6nU$ )NzP`Mode.push()` is no longer necessary and can be replaced with just `with Mode()`rz  r
  )r)   r   )clsr#   r$   instances       r-   pushTorchFunctionMode.push  s*    ^	
 ''r1   )r!   NrG  N)r
  r  __qualname____firstlineno____doc____annotations__r   r  r9  r@  classmethodrE  __static_attributes__rG  r1   r-   r0  r0    s7    < "  r1   r0  c                  B    [        5       n U S:  a  [        U S-
  5      $ S $ )Nr   rR  )r   r
   )	stack_lens    r-   r  r    s%    )+I4=M!)a-0KtKr1   c                  j    [        5       n [        U 5       Vs/ s H  n[        U5      PM     sn$ s  snf ru  )r   r   r
   )rO  r
  s     r-    _get_current_function_mode_stackrQ  !  s/    )+I/4Y/?@/?!"1%/?@@@s   0c                     [        U 5        g ru  )r   )r  s    r-   r8  r8  &  s
    !$'r1   c                      [        5       n U $ ru  )r   olds    r-   r<  r<  *  s    
#
%CJr1   c               #   `   #    [        5       n  U v   [        U 5        g ! [        U 5        f = f7fru  )r<  r8  rT  s    r-   r
  r
  /  s$     
+C	3
3s   . .+.c                       \ rS rSrSS jrSrg)BaseTorchFunctionModei8  rG  Nc                     Uc  0 nU" U0 UD6$ ru  rG  r5  s        r-   r  (BaseTorchFunctionMode.__torch_function__9  s    >FT$V$$r1   rG  )r
  r  rH  rI  r  rM  rG  r1   r-   rX  rX  8  s    %r1   rX  c               #   Z  #    [         R                  R                  5       n  [         R                  R                  [         R                  R                  R
                  5        S v   [         R                  R                  U 5        g ! [         R                  R                  U 5        f = f7fru  )r5   r
  _get_torch_function_state_set_torch_function_state_TorchFunctionStateENABLED)	old_states    r-   _enable_torch_functionra  ?  se     224I6**588+G+G+O+OP**95**95s   B+AB ' B+!B((B+c               #      #    [         R                  R                  5           S v    S S S 5        g ! f = f! , (       d  f       g = f7fru  )r5   r
  _RestorePythonTLSSnapshotrG  r1   r-   r   r   I  s9      
	+	+	-		 
.	- 	 
.	-s%   A61	A36
A A)z.*is deprecated, please use.*r5   ru  )ArJ  r  r  
contextlibr
  r9  r  r)   collections.abcr   r   r   typingr   r   typing_extensionsr   r5   torch._Cr	   r
   r   r   r   r   r   r   r   r  r   r   r&  r0   cacher
  r   rB  dictr   r   rc
  r  r
  r   r   r   r   r
  r   r   r   r+  rv
  r   r   r0  r  rQ  r8  r<  contextmanagerr
  rX  ra  r   rG  r1   r-   <module>rl     s*  ,     
   .   ' 
 
 
 t_T]
 1 
2r6
     b"f	 F _s8} _  _D	 c(m  2 {tHh$67 {  {|##H #P 15LC=L3%+&-L 
#YL^VVC=V
 	Vr ! . '	  * 	  S$Ed8n	tHcM22% S$ S$l 	+4T(^(;#< 	+ 	+ 2 2( S]   Gx GD G G2"KJ6 6rL
A
(
  %- % 6 6  r1   