Zj'YSrSSKJr SSKJr SSKrSSKJr SSKJr SSK J r J r SS K J r SS KJr SS KJr SS KJrJrJr SS KJrJr SSKJrJr SSKJrJr SSKJ r SSK!J"r"J#r#J$r$J%r% SSK&J'r'J(r( SSK)J*r* SSK+J,r, \%RZ"\.5r/"SS\R`5r1Sr2S3Sjr3"SS\R`5r4S4S\R`S\RjS\RjS\RjS \RjS-S!\6S"\64S#jjr7"S$S%\R`5r8"S&S'\5r9\#"S(S)\55r:\#"S*S+\:55r;"S,S-\:\ 5r<"S.S/\\:5r="S0S1\\:5r>/S2Qr?g)5zPyTorch Persimmon model.)Callable)OptionalN)nn)ACT2FN)Cache DynamicCache)GenerationMixin)create_causal_mask)FlashAttentionKwargs) GenericForSequenceClassificationGenericForTokenClassificationGradientCheckpointingLayer)BaseModelOutputWithPastCausalLMOutputWithPast)ROPE_INIT_FUNCTIONSdynamic_rope_update)ALL_ATTENTION_FUNCTIONSPreTrainedModel)Unpack)TransformersKwargsauto_docstringcan_return_tuplelogging)maybe_autocastmerge_with_config_defaults)capture_outputs)PersimmonConfigc ^\rSrSr%\R \S'SS\4U4Sjjjr\ SS\S-S\ SS\ S-S \ S \ 44S jj5r\R"5\S 55rS rU=r$)PersimmonRotaryEmbedding9inv_freqNconfigc>[TU]5 URUlURUlXlUR R SUlURnURS:wa[URnU"UR U5uo@l URSUSS9 URSUR5SS9 g)N rope_typedefaultr#F) persistentoriginal_inv_freq) super__init__max_position_embeddingsmax_seq_len_cachedoriginal_max_seq_lenr$rope_parametersr&compute_default_rope_parametersrattention_scalingregister_bufferclone)selfr$device rope_init_fnr# __class__s ځ/root/GenerationalWealth/GenerationalWealth/venv/lib/python3.13/site-packages/transformers/models/persimmon/modeling_persimmon.pyr+!PersimmonRotaryEmbedding.__init__<s "("@"@$*$B$B! 44[A!%!E!E >>Y &.t~~>L+7 V+L(( ZeD 0(..2BuUr5z torch.deviceseq_lenreturnz torch.Tensorc jURSnURRSS5n[USS5=(d URUR-n[ XT-5nSnSU[ R"SUS[ RS9RU[ RS 9U- -- nX4$) aH Computes the inverse frequencies according to the original RoPE implementation Args: config ([`~transformers.PreTrainedConfig`]): The model configuration. device (`torch.device`): The device to use for initialization of the inverse frequencies. seq_len (`int`, *optional*): The current sequence length. Unused for this type of RoPE. Returns: Tuple of (`torch.Tensor`, `float`), containing the inverse frequencies for the RoPE embeddings and the post-processing scaling factor applied to the computed cos/sin (unused in this type of RoPE). rope_thetapartial_rotary_factorg?head_dimNrdtype)r5rC) r/getgetattr hidden_sizenum_attention_headsinttorcharangeint64tofloat) r$r5r;baser?r@dimattention_factorr#s r8r08PersimmonRotaryEmbedding.compute_default_rope_parametersLs(%%l3 & 6 6 : :;RTW X6:t4h8J8JfNhNh8h(23 U\\!S!5;;?BB&X]XcXcBdgjj k ))r:cLURSSS2S4R5RURSSS5R UR 5nUSS2SSS24R5n[ UR R[5(a0UR RS:waUR ROSn[USS9 UR5UR5-RSS5n[R"Xf4SS 9nUR5UR-nUR5UR-n SSS5 WR UR S 9W R UR S 94$!,(df  N@=f) NrrmpscpuF) device_typeenabledrArOrB)r#rMexpandshaperLr5 isinstancetypestrr transposerIcatcosr1sinrC) r4x position_idsinv_freq_expandedposition_ids_expandedrVfreqsembr`ras r8forward PersimmonRotaryEmbedding.forwardmsN!MM$4-8>>@GG HZHZ[\H]_acdehhijiqiqr ,QaZ 8 > > @'1!((--'E'E!((--[`J`ahhmmfk  U C&,,.1F1L1L1NNYYZ[]^_E))UN3C'')d444C'')d444C D vvAGGv$cff177f&;;; D Cs BF F#)r1r$r-r.r&N)NNN)__name__ __module__ __qualname____firstlineno__rITensor__annotations__rr+ staticmethodrrHtuplerMr0no_gradrrh__static_attributes__ __classcell__r7s@r8r!r!9sllVVV *.+/"*$&*(*t* ~u$ % **> ]]_ <