qikdZddlmZddlmZddlZddlmZddlmZddl m Z m Z dd l m Z dd lmZdd lmZdd lmZmZmZdd lmZmZddlmZmZddlmZmZddlm Z ddl!m"Z"m#Z#m$Z$ddl%m&Z&ddl'm(Z(e$jRe*Z+GddejXZ-dZ.d2dZ/GddejXZ0 d3dejXdejbdejbdejbdejbdzd e2d!e2fd"Z3Gd#d$ejXZ4Gd%d&eZ5e"Gd'd(eZ6e"Gd)d*e6Z7Gd+d,e6e Z8Gd-d.ee6Z9Gd/d0ee6Z:gd1Z;y)4zPyTorch Persimmon model.)Callable)OptionalN)nn)ACT2FN)Cache DynamicCache)GenerationMixin)create_causal_mask)FlashAttentionKwargs) GenericForSequenceClassificationGenericForTokenClassificationGradientCheckpointingLayer)BaseModelOutputWithPastCausalLMOutputWithPast)ROPE_INIT_FUNCTIONSdynamic_rope_update)ALL_ATTENTION_FUNCTIONSPreTrainedModel)Unpack)auto_docstringcan_return_tuplelogging)maybe_autocast)PersimmonConfigc eZdZUejed<d deffd Ze d dedzde dde dzde d e ffd Z ejed ZxZS)PersimmonRotaryEmbeddinginv_freqNconfigct||j|_|j|_||_|j j d|_|j}|jdk7rt|j}||j |\}|_ |jd|d|jd|jdy)N rope_typedefaultrF) 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 b/opt/pipecat/venv/lib/python3.12/site-packages/transformers/models/persimmon/modeling_persimmon.pyr'z!PersimmonRotaryEmbedding.__init__;s "("@"@$*$B$B! 44[A!%!E!E >>Y &.t~~>L+7 V+L($( ZeD 0(..2BuUr1z torch.deviceseq_lenreturnz torch.Tensorcn|jd}|jjdd}t|ddxs|j|jz}t ||z}d}d|t jd|dt jj|t j |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_thetapartial_rotary_factorg?head_dimNrdtype)r1r>) r+getgetattr hidden_sizenum_attention_headsinttorcharangeint64tofloat) r r1r6baser:r;dimattention_factorrs r4r,z8PersimmonRotaryEmbedding.compute_default_rope_parametersKs(%%l3 & 6 6 : :;RTW X6:t4h8J8JfNhNh8h(223 U\\!S!5;;?BB&X]XcXcBdgjj k )))r5cN|jddddfjj|jdddj |j }|dddddfj}t |j jtr/|j jdk7r|j jnd}t|d5|j|jzjdd}tj||fd }|j|jz}|j|jz} dddj |j  j |j fS#1swYAxYw) NrrmpscpuF) device_typeenabledr<rJr=)rrHexpandshaperGr1 isinstancetypestrr transposerDcatcosr-sinr>) r0x position_idsinv_freq_expandedposition_ids_expandedrPfreqsembrZr[s r4forwardz PersimmonRotaryEmbedding.forwardlsR!MM$4-8>>@GG HZHZ[\H]_acdehhijiqiqr ,QaZ 8 > > @'1!((--'E!((--[`J`ahhmmfk  U C 5&,,.1F1L1L1NNYYZ[]^_E))UEN3C'')d444C'')d444C  5 vvAGGv$cff177f&;;;  5 5s BFF$N)NNN)__name__ __module__ __qualname__rDTensor__annotations__rr' staticmethodrrCtuplerHr,no_gradrrb __classcell__r3s@r4rr8sllVV *.+/"*$&*(*t* ~u$ % **>U]]_ <