
     `iV                     
   d dl mZmZmZ d dlZd dlmZ d dlmZ ddl	m
Z
 ddlmZmZ ddlmZ ddlmZ dd	lmZmZ dd
lmZ ddlmZmZ ddlmZmZ ddlmZmZ ddl m!Z! ddl"m#Z#m$Z$ ddl%m&Z& ddl'm(Z( ddl)m*Z*  ed           G d dej+                              Z,dej-        de.dej-        fdZ/	 d6dej+        dej-        dej-        dej-        d eej-                 d!e0d"e0d#e!e         fd$Z1d7d%Z2d& Z3 G d' d(ej+                  Z4 G d) d*ej+                  Z5 G d+ d,e          Z6 G d- d.ej+                  Z7e# G d/ d0e                      Z8e# G d1 d2e8                      Z9e# G d3 d4e8e                      Z:g d5Z;dS )8    )CallableOptionalUnionN)TransformersKwargs   )ACT2FN)CacheDynamicCache)GenerationMixin)use_kernel_forward_from_hub)create_causal_mask!create_sliding_window_causal_mask)GradientCheckpointingLayer)BaseModelOutputWithPastCausalLMOutputWithPast)ROPE_INIT_FUNCTIONSdynamic_rope_update)ALL_ATTENTION_FUNCTIONSPreTrainedModel)Unpack)auto_docstringcan_return_tuple)deprecate_kwarg)check_model_inputs   )Olmo3ConfigRMSNormc                   ,     e Zd Zd fd	Zd Zd Z xZS )Olmo3RMSNormư>c                     t                                                       t          j        t	          j        |                    | _        || _        dS )z;
        Olmo3RMSNorm is equivalent to T5LayerNorm
        N)super__init__nn	Parametertorchonesweightvariance_epsilon)selfhidden_sizeeps	__class__s      |/home/jaya/work/projects/VOICE-AGENT/VIET/agent-env/lib/python3.11/site-packages/transformers/models/olmo3/modeling_olmo3.pyr#   zOlmo3RMSNorm.__init__/   sD     	l5:k#:#:;; #    c                    |j         }|                    t          j                  }|                    d                              dd          }|t          j        || j        z             z  }| j        |z                      |          S )N   T)keepdim)	dtypetor&   float32powmeanrsqrtr)   r(   )r*   hidden_statesinput_dtypevariances       r.   forwardzOlmo3RMSNorm.forward7   s|    #)%((77 $$Q'',,R,>>%Ht?T4T(U(UUm+//<<<r/   c                 H    t          | j        j                   d| j         S )Nz, eps=)tupler(   shaper)   )r*   s    r.   
extra_reprzOlmo3RMSNorm.extra_repr>   s&    )**II$2GIIIr/   )r    )__name__
__module____qualname__r#   r=   rA   __classcell__r-   s   @r.   r   r   -   sb        $ $ $ $ $ $= = =J J J J J J Jr/   r   r:   n_repreturnc                     | j         \  }}}}|dk    r| S | dddddddddf                             |||||          } |                     |||z  ||          S )z
    This is the equivalent of torch.repeat_interleave(x, dim=1, repeats=n_rep). The hidden states go from (batch,
    num_key_value_heads, seqlen, head_dim) to (batch, num_attention_heads, seqlen, head_dim)
    r   N)r@   expandreshape)r:   rG   batchnum_key_value_headsslenhead_dims         r.   	repeat_kvrP   B   s    
 2?1D.Ehzz!!!!QQQaaa"23::5BUW\^bdlmmM  (;e(CT8TTTr/           modulequerykeyvalueattention_maskscalingdropoutkwargsc                 R   t          || j                  }t          || j                  }	t          j        ||                    dd                    |z  }
|$|d d d d d d d |j        d         f         }|
|z   }
t          j                            |
dt          j	                  
                    |j                  }
t          j                            |
|| j                  }
t          j        |
|	          }|                    dd                                          }||
fS )Nr1   r   r2   )dimr4   )ptrainingr   )rP   num_key_value_groupsr&   matmul	transposer@   r$   
functionalsoftmaxr6   r5   r4   rX   r^   
contiguous)rR   rS   rT   rU   rV   rW   rX   rY   
key_statesvalue_statesattn_weightscausal_maskattn_outputs                r.   eager_attention_forwardrj   N   s    3 ;<<JUF$?@@L<z';';Aq'A'ABBWLL!$QQQ111.D
0@0D.D%DE#k1=((2U](SSVVW\WbccL=((6?([[L,|\::K''1--88::K$$r/   c                 &   | j         |j         }}|                    |          }|                    |          }| |z  t          |           |z  z   }||z  t          |          |z  z   }	|                    |          |	                    |          fS )a  Applies Rotary Position Embedding to the query and key tensors.

    Args:
        q (`torch.Tensor`): The query tensor.
        k (`torch.Tensor`): The key tensor.
        cos (`torch.Tensor`): The cosine part of the rotary embedding.
        sin (`torch.Tensor`): The sine part of the rotary embedding.
        position_ids (`torch.Tensor`, *optional*):
            Deprecated and unused.
        unsqueeze_dim (`int`, *optional*, defaults to 1):
            The 'unsqueeze_dim' argument specifies the dimension along which to unsqueeze cos[position_ids] and
            sin[position_ids] so that they can be properly broadcasted to the dimensions of q and k. For example, note
            that cos[position_ids] and sin[position_ids] have the shape [batch_size, seq_len, head_dim]. Then, if q and
            k have the shape [batch_size, heads, seq_len, head_dim], then setting unsqueeze_dim=1 makes
            cos[position_ids] and sin[position_ids] broadcastable to the shapes of q and k. Similarly, if q and k have
            the shape [batch_size, seq_len, heads, head_dim], then set unsqueeze_dim=2.
    Returns:
        `tuple(torch.Tensor)` comprising of the query and key tensors rotated using the Rotary Position Embedding.
    )r4   	unsqueezerotate_halfr5   )
qkcossinposition_idsunsqueeze_dimq_typek_typeq_embedk_embeds
             r.   apply_rotary_pos_embrx   h   s    ( WagFF
--
&
&C
--
&
&C3w;q>>C/0G3w;q>>C/0G::fwzz&1111r/   c                     | dd| j         d         dz  f         }| d| j         d         dz  df         }t          j        | |fd          S )z*Rotates half the hidden dims of the input..Nr2   r1   r\   )r@   r&   cat)xx1x2s      r.   rm   rm      s]    	
3"!'"+"""	#B	
3q """	#B9rc2YB''''r/   c                        e Zd ZdZdedef fdZ eddd          	 	 dd
ej	        de
ej	        ej	        f         deej	                 dee         deej                 dee         de
ej	        eej	                 f         fd            Z xZS )Olmo3Attentionz=Multi-headed attention from 'Attention Is All You Need' paperconfig	layer_idxc                    t                                                       || _        || _        t	          |d|j        |j        z            | _        |j        |j        z  | _	        | j        dz  | _
        |j        | _        d| _        t          j        |j        |j        | j        z  |j                  | _        t          j        |j        |j        | j        z  |j                  | _        t          j        |j        |j        | j        z  |j                  | _        t          j        |j        | j        z  |j        |j                  | _        t)          |j        | j        z  |j                  | _        t)          |j        | j        z  |j                  | _        |j        J |j        |         | _        | j        dk    r|j        nd | _        d S )NrO   g      Tbiassliding_attention)r"   r#   r   r   getattrr+   num_attention_headsrO   rM   r_   rW   attention_dropout	is_causalr$   Linearattention_biasq_projk_projv_projo_projr   rms_norm_epsq_normk_normlayer_typesattention_typesliding_windowr*   r   r   r-   s      r.   r#   zOlmo3Attention.__init__   s   "
F4F&Jd4dee$*$>&B\$\!}d*!'!9i :T] JQWQf
 
 
 i :T] JQWQf
 
 
 i :T] JQWQf
 
 
 i&68JQWQf
 
 
 #6#=#MvObcc"6#=#MvObcc!---$0;7;7JNa7a7af33gkr/   past_key_valuepast_key_values4.58new_nameversionNr:   position_embeddingsrV   cache_positionrY   rH   c                    |j         d d         }g |d| j        R }|                     |                     |                    }	|                     |                     |                    }
|                     |          }|	                    |                              dd          }	|
                    |                              dd          }
|                    |                              dd          }|\  }}t          |	|
||          \  }	}
|&|||d}|
                    |
|| j        |          \  }
}t          }| j        j        dk    rt          | j        j                 } || |	|
||f| j        sdn| j        | j        | j        d|\  }} |j        g |dR                                  }|                     |          }||fS )Nr2   r   r1   )rq   rp   r   eagerrQ   )rX   rW   r   )r@   rO   r   r   r   r   r   viewra   rx   updater   rj   r   _attn_implementationr   r^   r   rW   r   rK   rd   r   )r*   r:   r   rV   r   r   rY   input_shapehidden_shapequery_statesre   rf   rp   rq   cache_kwargsattention_interfaceri   rg   s                     r.   r=   zOlmo3Attention.forward   s     $)#2#.88b8$-88{{4;;}#=#=>>[[]!;!;<<
{{=11#((66@@AFF__\22<<QBB
#((66@@AFF&S#7jRUWZ#[#[ j&#&snUUL'6'='=j,X\Xfht'u'u$J(?;+w66"9$+:Z"[$7$7
%
  $}HCC$2HL.
%
 
%
 
%
 
%
!\ *k);;;;;;FFHHkk+..L((r/   NN)rB   rC   rD   __doc__r   intr#   r   r&   Tensorr?   r   r	   
LongTensorr   r   r=   rE   rF   s   @r.   r   r      s       GGl{ ls l l l l l l8 _%0A6RRR ,059.) .)|.) #5<#=>.) !.	.)
 "%.) !!12.) +,.) 
u|Xel33	4.) .) .) SR.) .) .) .) .)r/   r   c                   $     e Zd Z fdZd Z xZS )Olmo3MLPc                    t                                                       || _        |j        | _        |j        | _        t          j        | j        | j        d          | _        t          j        | j        | j        d          | _        t          j        | j        | j        d          | _	        t          |j                 | _        d S NFr   )r"   r#   r   r+   intermediate_sizer$   r   	gate_projup_proj	down_projr   
hidden_actact_fnr*   r   r-   s     r.   r#   zOlmo3MLP.__init__   s    !-!'!94#3T5KRWXXXy!143IPUVVV4#94;KRWXXXV./r/   c                     |                      |                     |                     |                    |                     |          z            }|S )N)r   r   r   r   )r*   r|   r   s      r.   r=   zOlmo3MLP.forward   sA    NN4;;t~~a/@/@#A#ADLLQROO#STT	r/   )rB   rC   rD   r#   r=   rE   rF   s   @r.   r   r      sG        0 0 0 0 0      r/   r   c                   4    e Zd Zdedef fdZ eddd          	 	 	 	 	 	 dd
ej        de	ej                 de	ej
                 de	e         de	e         de	ej
                 de	eej        ej        f                  dee         dej        fd            Z xZS )Olmo3DecoderLayerr   r   c                 4   t                                                       |j        | _        t          ||          | _        t          |          | _        t          |j        |j                  | _	        t          |j        |j                  | _
        d S )N)r   r   r,   )r"   r#   r+   r   	self_attnr   mlpr   r   post_attention_layernormpost_feedforward_layernormr   s      r.   r#   zOlmo3DecoderLayer.__init__   s    !-'vKKKF##(4V5GVM`(a(a(a%*6v7IvOb*c*c*c'''r/   r   r   r   r   NFr:   rV   rr   	use_cacher   r   rY   rH   c                     |}	 | j         d|||||||d|\  }}
|                     |          }|	|z   }|}	|                     |          }|                     |          }|	|z   }|S )N)r:   rV   rr   r   r   r   r    )r   r   r   r   )r*   r:   rV   rr   r   r   r   r   rY   residual_s              r.   r=   zOlmo3DecoderLayer.forward   s     !)4> 	
')%+) 3	
 	
 	
 	
q 55mDD =0 !//77FF =0r/   )NNNFNN)rB   rC   rD   r   r   r#   r   r&   r   r   r   r	   boolr?   r   r   r=   rE   rF   s   @r.   r   r      s5       d{ ds d d d d d d _%0A6RRR 2637+/$)59KO | !. u/0	
 "% D> !!12 &eEL%,,F&GH +, 
   SR    r/   r   c                        e Zd ZU ej        ed<   ddedee         f fdZ	 ej
                    ed                         Z xZS )Olmo3RotaryEmbeddinginv_freqNr   	rope_typec                 <   t                                                       ||| _        njt          |d          rSt	          |j        t                    r9|j                            d|j                            d                    | _        nd| _        | j        J |j        | _	        |j        | _
        || _        t          | j                 | _        |                     | j        |          \  }| _        |                     d|d           | j        | _        d S )Nrope_scalingr   typedefaultr   F)
persistent)r"   r#   r   hasattr
isinstancer   dictgetmax_position_embeddingsmax_seq_len_cachedoriginal_max_seq_lenr   r   rope_init_fnattention_scalingregister_bufferr   original_inv_freq)r*   r   devicer   r   r-   s        r.   r#   zOlmo3RotaryEmbedding.__init__  s    &DNNV^,, 	'F<OQU1V1V 	'#044[&BUBYBYZ`BaBabbDNN&DN~)))"("@$*$B!/?+/+<+<T[&+Q+Q($(ZeDDD!%r/   c                    | j         d d d d f                                                             |j        d         dd                              |j                  }|d d d d d f                                         }t          |j        j        t                    r|j        j        dk    r|j        j        nd}t          j
        |d          5  |                                |                                z                      dd          }t          j        ||fd	          }|                                | j        z  }|                                | j        z  }	||	fcd d d            S # 1 swxY w Y   d S )
Nr   r2   r   mpscpuF)device_typeenabledr1   rz   )r   floatrJ   r@   r5   r   r   r   strr&   autocastra   r{   rp   r   rq   )
r*   r|   rr   inv_freq_expandedposition_ids_expandedr   freqsembrp   rq   s
             r.   r=   zOlmo3RotaryEmbedding.forward0  s    !M$4-8>>@@GGHZ[\H]_acdeehhijiqrr ,QQQaaaZ 8 > > @ @'1!(-'E'Ek!(-[`J`J`ahmmfk^UCCC 	 	&,,..1F1L1L1N1NNYYZ[]^__E)UEN333C''))d44C''))d44C8	 	 	 	 	 	 	 	 	 	 	 	 	 	 	 	 	 	s   BE//E36E3r   )rB   rC   rD   r&   r   __annotations__r   r   r   r#   no_gradr   r=   rE   rF   s   @r.   r   r     s         l/ /{ /HSM / / / / / /* U]__
 
  _
 
 
 
 
r/   r   c                   L    e Zd ZU eed<   dZdZdgZdgZdZ	dZ
dZdZdZeedZdS )Olmo3PreTrainedModelr   modelTr   r   )r:   
attentionsN)rB   rC   rD   r   r   base_model_prefixsupports_gradient_checkpointing_no_split_modules_skip_keys_device_placement_supports_flash_attn_supports_sdpa_supports_flex_attn_can_compile_fullgraph_supports_attention_backendr   r   _can_record_outputsr   r/   r.   r   r   ?  sl         &*#,-#4"5N!"&*$ r/   r   c                       e Zd Zdef fdZee	 	 	 	 	 	 	 ddeej	                 deej
                 deej	                 dee         deej                 d	eej	                 d
ee         dee         defd                        Z xZS )
Olmo3Modelr   c                 &   t                                                     j        | _        j        | _        t          j        j        j        | j                  | _        t          j	        fdt          j                  D                       | _        t          j        j                  | _        d| _        t          j        t%          d          t%                    d          | _        |                                  d S )Nc                 0    g | ]}t          |          S r   )r   ).0r   r   s     r.   
<listcomp>z'Olmo3Model.__init__.<locals>.<listcomp>[  s$    cccivy11cccr/   r   Fr   )r   r   r   r   full_attention)r"   r#   pad_token_idpadding_idx
vocab_sizer$   	Embeddingr+   embed_tokens
ModuleListrangenum_hidden_layerslayersr   r   normgradient_checkpointing
ModuleDictr   rotary_embs	post_initr   s    `r.   r#   zOlmo3Model.__init__T  s       !. +L):F<NPTP`aamcccc5IaCbCbccc
 
 !!39LMMM	&+#=%9S\%]%]%]"6f"E"E"E 
 
 	r/   N	input_idsrV   rr   r   inputs_embedsr   r   rY   rH   c           
         |d u |d uz  rt          d          ||                     |          }|r|t          | j                  }|B||                                nd}	t          j        |	|	|j        d         z   |j                  }||	                    d          }t          |x}
t                    s'| j        |||||d}t          di |t          di |d}
|} | j        d         ||           | j        d	         ||          d
}| j        d | j        j                 D ]1} ||f|
|j        j                 |||||j        j                 d|}2|                     |          }t)          ||          S )Nz:You must specify exactly one of input_ids or inputs_embedsr   r   r   )r   )r   input_embedsrV   r   r   rr   )r  r   r   r  r  )rV   rr   r   r   r   )last_hidden_stater   r   )
ValueErrorr  r
   r   get_seq_lengthr&   aranger@   r   rl   r   r   r   r   r  r  r
  r   r   r  r   )r*   r  rV   rr   r   r  r   r   rY   past_seen_tokenscausal_mask_mappingmask_kwargsr:   position_embeddings_mappingdecoder_layers                  r.   r=   zOlmo3Model.forwardi  s%    -t";< 	[YZZZ *.*;*;I*F*FM 	?0*$+>>>O!CRC^==???de+0< "2]5H5K"KTaTh, , ,N )33A66L ?-FF 	 + -"0"0#2 , K #5"C"C{"C"C%F%U%U%U%U# #
 &!F!12E!F}Vb!c!c@d./?@P\]]'
 '
#
 "[)H4;+H)HI 		 		M)M2=3J3YZ) /-$?@W@f$g   MM 		-00&++
 
 
 	
r/   )NNNNNNN)rB   rC   rD   r   r#   r   r   r   r&   r   r   r	   FloatTensorr   r   r   r   r=   rE   rF   s   @r.   r   r   R  s*       {      *  151537+/5959$(C
 C
E,-C
 !.C
 u/0	C

 "%C
   12C
 !!12C
 D>C
 +,C
 
!C
 C
 C
 ^ C
 C
 C
 C
 C
r/   r   c                   f    e Zd ZdgZddiZddgdgfiZ fdZee	 	 	 	 	 	 	 	 	 dd	e	e
j                 d
e	e
j                 de	e
j                 de	e         de	e
j                 de	e
j                 de	e         de	e
j                 deee
j        f         dee         defd                        Z xZS )Olmo3ForCausalLMzlm_head.weightlm_headcolwise_repr:   logitsc                     t                                          |           t          |          | _        |j        | _        t          j        |j        |j        d          | _        | 	                                 d S r   )
r"   r#   r   r   r  r$   r   r+   r!  r  r   s     r.   r#   zOlmo3ForCausalLM.__init__  sj       ''
 +y!3V5FUSSS 	r/   Nr   r  rV   rr   r   r  labelsr   r   logits_to_keeprY   rH   c
                 R    | j         d|||||||d|
}|j        }t          |	t                    rt	          |	 d          n|	}|                     |dd|ddf                   }d}| | j        d||| j        j        d|
}t          |||j
        |j        |j                  S )a  
        Example:

        ```python
        >>> from transformers import AutoTokenizer, Olmo3ForCausalLM

        >>> model = Olmo3ForCausalLM.from_pretrained("meta-olmo3/Olmo3-2-7b-hf")
        >>> tokenizer = AutoTokenizer.from_pretrained("meta-olmo3/Olmo3-2-7b-hf")

        >>> prompt = "Hey, are you conscious? Can you talk to me?"
        >>> inputs = tokenizer(prompt, return_tensors="pt")

        >>> # Generate
        >>> generate_ids = model.generate(inputs.input_ids, max_length=30)
        >>> tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
        "Hey, are you conscious? Can you talk to me?\nI'm not conscious, but I can talk to you."
        ```)r  rV   rr   r   r  r   r   N)r#  r%  r  )lossr#  r   r:   r   r   )r   r  r   r   slicer!  loss_functionr   r  r   r   r:   r   )r*   r  rV   rr   r   r  r%  r   r   r&  rY   outputsr:   slice_indicesr#  r(  s                   r.   r=   zOlmo3ForCausalLM.forward  s    @ ,64: 	,
)%+')	,
 	,
 	,
 	,
  18B>SV8W8Wk~ot444]kmAAA}aaa,?@AA%4%pVFt{OeppioppD%#3!/)
 
 
 	
r/   )	NNNNNNNNr   )rB   rC   rD   _tied_weights_keys_tp_plan_pp_planr#   r   r   r   r&   r   r   r	   r  r   r   r   r   r   r   r=   rE   rF   s   @r.   r   r     sa       *+=)H_-z:;H      151537+/59-1$(59348
 8
E,-8
 !.8
 u/0	8

 "%8
   128
 )*8
 D>8
 !!128
 c5</08
 +,8
 
 8
 8
 8
 ^ 8
 8
 8
 8
 8
r/   r   )r   r   r   )rQ   )Nr   )<typingr   r   r   r&   torch.nnr$   transformers.utils.genericr   activationsr   cache_utilsr	   r
   
generationr   integrationsr   masking_utilsr   r   modeling_layersr   modeling_outputsr   r   modeling_rope_utilsr   r   modeling_utilsr   r   processing_utilsr   utilsr   r   utils.deprecationr   utils.genericr   configuration_olmo3r   Moduler   r   r   rP   r   rj   rx   rm   r   r   r   r   r   r   r   __all__r   r/   r.   <module>rC     s  , - , , , , , , , , ,        9 9 9 9 9 9 ! ! ! ! ! ! . . . . . . . . ) ) ) ) ) ) 7 7 7 7 7 7 R R R R R R R R 9 9 9 9 9 9 O O O O O O O O K K K K K K K K F F F F F F F F & & & & & & 5 5 5 5 5 5 5 5 0 0 0 0 0 0 / / / / / / , , , , , , Y''J J J J J29 J J ('J(	UU\ 	U# 	U%, 	U 	U 	U 	U& % %I%<% 
% <	%
 U\*% % % '(% % % %42 2 2 28( ( (N) N) N) N) N)RY N) N) N)b    ry    ) ) ) ) )2 ) ) )X$ $ $ $ $29 $ $ $N     ?   $ [
 [
 [
 [
 [
% [
 [
 [
| H
 H
 H
 H
 H
+_ H
 H
 H
V E
D
Dr/   