tjxfddlmZddlmZddlZddlmcmZddlmZddl m Z ddl m Z ddlmZmZdd lmZdd lmZmZmZmZdd lmZdd lmZdd lmZmZddlm Z m!Z!ddl"m#Z#m$Z$ddl%m&Z&ddl'm(Z(m)Z)m*Z*ddl+m,Z,m-Z-ddl.m/Z/m0Z0ddl1m2Z2edGddej3Z4Gddej3Z5Gddej3Z6dZ7eddCdZ8d ej9d!e:d"ej9fd#Z; dDd%ej3d&ej9d'ej9d(ej9d)ej9dzd*eeGd0d1ej3Z?Gd2d3ej3Z@Gd4d5ej3ZAGd6d7eZBe)Gd8d9e$ZCe)Gd:d;eCZD dEd=ej9eEej9zdzd>e:dzd)ej9dzd"ej9e:zfd?ZFe)Gd@dAeCeZGgdBZHdS)F)Callable)OptionalN)nn)initialization)ACT2FN)Cache DynamicCache)GenerationMixin)use_experts_implementationuse_kernel_forward_from_hubuse_kernel_func_from_hubuse_kernelized_func)create_causal_mask)GradientCheckpointingLayer)MoeCausalLMOutputWithPastMoeModelOutputWithPast)ROPE_INIT_FUNCTIONSdynamic_rope_update)ALL_ATTENTION_FUNCTIONSPreTrainedModel)Unpack)TransformersKwargsauto_docstringcan_return_tuple)maybe_autocastmerge_with_config_defaults)OutputRecordercapture_outputs) OlmoeConfigRMSNormcLeZdZdd fd ZdejdejfdZdZxZS) OlmoeRMSNormh㈵>returnNcttjt j||_||_dS)z; OlmoeRMSNorm is equivalent to T5LayerNorm N)super__init__r Parametertorchonesweightvariance_epsilon)self hidden_sizeeps __class__s f/var/www/html/CA-Chatbot/venv/lib/python3.11/site-packages/transformers/models/olmoe/modeling_olmoe.pyr)zOlmoeRMSNorm.__init__2sD l5:k#:#:;; # hidden_statesc|j}|tj}|ddd}|tj||jzz}|j||zS)NT)keepdim) dtypetor+float32powmeanrsqrtr.r-)r/r5 input_dtypevariances r3forwardzOlmoeRMSNorm.forward:s|#) %((77  $$Q'',,R,>>% Ht?T4T(U(UU {]--k::::r4cHt|jjd|jS)Nz, eps=)tupler-shaper.)r/s r3 extra_reprzOlmoeRMSNorm.extra_reprAs& )**II$2GIIIr4)r%)r&N) __name__ __module__ __qualname__r)r+TensorrBrF __classcell__r2s@r3r$r$0s~$$$$$$$;U\;el;;;;JJJJJJJr4r$c eZdZUejed<d deffd Ze d dedzde dde dzde d e ffd Z ejed ZxZS)OlmoeRotaryEmbeddinginv_freqNconfigct|j|_|j|_||_|jjd|_|j}|jdkrt|j}||j|\}|_ | d|d| d| ddS)N rope_typedefaultrOF) persistentoriginal_inv_freq) r(r)max_position_embeddingsmax_seq_len_cachedoriginal_max_seq_lenrPrope_parametersrRcompute_default_rope_parametersrattention_scalingregister_bufferclone)r/rPdevice rope_init_fnrOr2s r3r)zOlmoeRotaryEmbedding.__init__Hs "("@$*$B! 4[A!%!E >Y & &.t~>L+7< V+L+L($( ZeDDD 0(..2B2BuUUUUUr4r^z torch.deviceseq_lenr&z torch.Tensorc|jd}t|ddp|j|jz}d}d|t jd|dtj|tj|z zz }||fS) a Computes the inverse frequencies according to the original RoPE implementation Args: config ([`~transformers.PreTrainedConfig`]): The model configuration. device (`torch.device`): The device to use for initialization of the inverse frequencies. seq_len (`int`, *optional*): The current sequence length. Unused for this type of RoPE. Returns: Tuple of (`torch.Tensor`, `float`), containing the inverse frequencies for the RoPE embeddings and the post-processing scaling factor applied to the computed cos/sin (unused in this type of RoPE). rope_thetahead_dimNg?rr7r:)r^r:) rYgetattrr0num_attention_headsr+arangeint64r;float)rPr^r`basedimattention_factorrOs r3rZz4OlmoeRotaryEmbedding.compute_default_rope_parametersXs&%l3fj$//c63EIc3c U\!S!5;???BB&X]XcBddgjj k )))r4cN|jddddf|jddd|j}|dddddf}t |jjtr|jjdkr |jjnd}t|d5||z dd}tj ||fd }| |jz}||jz} dddn #1swxYwY||j | |j fS) Nrr8r mpscpuF) device_typeenabledr7rkrd)rOriexpandrEr;r^ isinstancetypestrr transposer+catcosr[sinr:) r/x position_idsinv_freq_expandedposition_ids_expandedrpfreqsembryrzs r3rBzOlmoeRotaryEmbedding.forwardvs!M$4-8>>@@GG HZ[\H]_acdeehhijiqrr ,QQQaaaZ 8 > > @ @'1!(-'E'Ek!(-[`J`J`ahmmfk  U C C C 5 5&,,..1F1L1L1N1NNYYZ[]^__E)UEN333C''))d44C''))d44C  5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 vvAGv$$cff17f&;&;;;s BE&&E*-E*N)NNN)rGrHrIr+rJ__annotations__r!r) staticmethodrintrDrirZno_gradrrBrKrLs@r3rNrNEslVV{VVVVVV %)+/"**d"*(*t* ~u$ % ***\*:U]__ < <_ < < < <