ZjX>SSKJr SSKJr SSKJr SSKJr SSKJ r SSK J r SSK J r SS KJrJr SS KJrJr SS KJrJr SS KJr SS KJrJrJr SSKJrJrJ r SSK!J"r" SSK#J$r$J%r% SSK&J'r'J(r( \"5(a SSK)r)SSK)J*r* "SS\*RV5r,Sr-S\)R\S\/S\)R\4Sjr0S8S\*RVS\)R\S\)R\S \)R\S!\)R\S-S"\1S#\1S$\\4S%jjr2S9S&jr3\ "\35"S'S(\*RV55r4"S)S*\*RV5r5"S+S,\ 5r6\"S-S.\55r7"S/S0\75r8"S1S2\*RV5r9\"S3S49"S5S6\7\ 55r:/S7Qr;g):)Callable)Optional)ACT2FN)Cache)GenerationMixin)use_kernelized_func)GradientCheckpointingLayer)BaseModelOutputWithPoolingCausalLMOutputWithPast)ROPE_INIT_FUNCTIONSdynamic_rope_update)ALL_ATTENTION_FUNCTIONSPreTrainedModel)Unpack)TransformersKwargsauto_docstringis_torch_available)can_return_tuplemaybe_autocastmerge_with_config_defaults)capture_outputs) AutoModelAutoModelForCausalLM) GlmAsrConfigGlmAsrEncoderConfigN)nnc ^\rSrSr%\R \S'SS\4U4Sjjjr\ SS\S-S\ SS\ S-S \ S \ 44S jj5r\R"5\S 55rS rU=r$)GlmAsrRotaryEmbedding-inv_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$rope_parametersr&compute_default_rope_parametersr attention_scalingregister_bufferclone)selfr$device rope_init_fnr# __class__s {/root/GenerationalWealth/GenerationalWealth/venv/lib/python3.13/site-packages/transformers/models/glmasr/modeling_glmasr.pyr+GlmAsrRotaryEmbedding.__init__0s "("@"@$*$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_dimNrrdtype)r5rB) r/getgetattr hidden_sizenum_attention_headsinttorcharangeint64tofloat) r$r5r;baser?r@dimattention_factorr#s r8r05GlmAsrRotaryEmbedding.compute_default_rope_parameters@s&%%l3 & 6 6 : :;RTW X6:t4h8J8JfNhNh8h(23 U\\!S!5;;?BB&X]XcXcBdgjj k ))r:cLURSSS2S4R5RURSSS5R UR 5nUSS2SSS24R5n[ UR R[5(a0UR RS:waUR ROSn[USS9 UR5UR5-RSS5n[R"Xf4SS 9nUR5UR-nUR5UR-n SSS5 WR UR S 9W R UR S 94$!,(df  N@=f) NrrmpscpuF) device_typeenabledrrNrA)r#rLexpandshaperKr5 isinstancetypestrr transposerHcatcosr1sinrB) r4x position_idsinv_freq_expandedposition_ids_expandedrUfreqsembr_r`s r8forwardGlmAsrRotaryEmbedding.forward`sN!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$r-r.r&N)NNN)__name__ __module__ __qualname____firstlineno__rHTensor__annotations__rr+ staticmethodrrGtuplerLr0no_gradrrg__static_attributes__ __classcell__r7s@r8r!r!-sllV|VV &*+/"*t#*(*t* ~u$ % **> ]]_ <