+ j~1^Rt^RIHt^RIHt^RIHt^RIHtH t ]!RR7]!RR]444t ]!RR7]!R R ]444t ]!RR7]!R R ]444t ]!RR7]!R R]444t ]!RR7]!RR]444t.ROtR#)zSAM2 model configuration)strict)PreTrainedConfig)auto_docstring)CONFIG_MAPPING AutoConfigzfacebook/sam2.1-hiera-tiny) checkpointcaa]tRt^toRtRtRt^`t^t^t Rt Rt Rt Rt RtRt^tRtRtRtRtRtRtRtRtRtV3R ltV3R ltR tVtV;t#) Sam2HieraDetConfiga patch_kernel_size (`list[int]`, *optional*, defaults to `[7, 7]`): The kernel size of the patch. patch_stride (`list[int]`, *optional*, defaults to `[4, 4]`): The stride of the patch. patch_padding (`list[int]`, *optional*, defaults to `[3, 3]`): The padding of the patch. query_stride (`list[int]`, *optional*, defaults to `[2, 2]`): The downsample stride between stages. window_positional_embedding_background_size (`list[int]`, *optional*, defaults to `[7, 7]`): The window size per stage when not using global attention. num_query_pool_stages (`int`, *optional*, defaults to 3): The number of query pool stages. blocks_per_stage (`list[int]`, *optional*, defaults to `[1, 2, 7, 2]`): The number of blocks per stage. embed_dim_per_stage (`list[int]`, *optional*, defaults to `[96, 192, 384, 768]`): The embedding dimension per stage. num_attention_heads_per_stage (`list[int]`, *optional*, defaults to `[1, 2, 4, 8]`): The number of attention heads per stage. window_size_per_stage (`list[int]`, *optional*, defaults to `[8, 4, 14, 7]`): The window size per stage. global_attention_blocks (`list[int]`, *optional*, defaults to `[5, 7, 9]`): The blocks where global attention is used. backbone_configsam2_hiera_det_modelNg@geluư>{Gz?c *<VPe VPMRR.VnVPe VPM^^.VnVPe VPM^^.VnVPe VPM^^.VnVPe VPM^^.VnVP e VP M^^.VnVP e VP M.ROVnVPe VPM.ROVnVPe VPM.ROVnVPe VPM.ROVn VPe VPM.ROVn \SV`0!R/VBR#)N)r)`)rr)rrr)r ) image_sizepatch_kernel_size patch_stride patch_padding query_stride+window_positional_embedding_background_sizeblocks_per_stageembed_dim_per_stagenum_attention_heads_per_stagewindow_size_per_stageglobal_attention_blockssuper __post_init__selfkwargs __class__s&,l/home/luca/screen-checking/.venv/lib/python3.14/site-packages/transformers/models/sam2/configuration_sam2.pyr* Sam2HieraDetConfig.__post_init__Js-1__-H$//tUYl;?;Q;Q;]!7!7deghci151B1B1ND--UVXYTZ373E3E3QT//XY[\W]151B1B1ND--UVXYTZ??K  < <Q 8 :>9N9N9Z 5 5`l(,(@(@(LD $ $Re  372T2T2`D . .fr *+/*D*D*PD & &Vc "-1,H,H,TD ( (Zc $ ''c<V^8dQh/S[;R&S[;R&S[;R&S[S[S[,,R,;R&S[S[S[,,R,;R&S[S[S[,,R,;R&S[S[S[,,R,;R&S[S[S[,,R,;R &S[S[,R,;R &S[;R &S[S[,R,;R &S[S[,R,;R &S[S[,R,;R&S[S[,R,;R&S[S[,R,;R&S[;R&S[;R&S[;R&S[;R&#)r hidden_sizenum_attention_heads num_channelsNrrr r!r"r#num_query_pool_stagesr$r%r&r'r( mlp_ratio hidden_actlayer_norm_epsinitializer_range)intlistfloatstr)format __classdict__s"r/ __annotate__Sam2HieraDetConfig.__annotate__s>?@ ABCDd3i$&-EFT#Y-4GHS /D(/IJc?T)0KLS /D(/MN26cT1AHOP"QR3i$&-STcT)0UV$(9t#3:WX 9t+2YZ"#Y-4[\]^_` ab#cr1) r$r%r(rr&rr!r r"r#r')__name__ __module__ __qualname____firstlineno____doc__base_config_key model_typer3r4r5rrr r!r"r#r6r$r%r&r'r(r7r8r9r:r*__annotate_func____static_attributes____classdictcell__ __classcell__r.r@s@@r/r r s2(O'JK L)-J04+/L,0M+/LDH/!")-,06:!.204IJ N#(gr1r caa]tRt^etoRtRtRtR]/tRt Rt Rt Rt ^t ^t^tRt^tRtRtR tV3R ltV3R ltR tVtV;t#) Sam2VisionConfiga backbone_channel_list (`List[int]`, *optional*, defaults to `[768, 384, 192, 96]`): The list of channel dimensions for the backbone. backbone_feature_sizes (`List[List[int]]`, *optional*, defaults to `[[256, 256], [128, 128], [64, 64]]`): The spatial sizes of the feature maps from the backbone. fpn_hidden_size (`int`, *optional*, defaults to 256): The hidden dimension of the FPN. fpn_kernel_size (`int`, *optional*, defaults to 1): The kernel size for the convolutions in the neck. fpn_stride (`int`, *optional*, defaults to 1): The stride for the convolutions in the neck. fpn_padding (`int`, *optional*, defaults to 0): The padding for the convolutions in the neck. fpn_top_down_levels (`List[int]`, *optional*, defaults to `[2, 3]`): The levels for the top-down FPN connections. num_feature_levels (`int`, *optional*, defaults to 3): The number of feature levels from the FPN to use. vision_configsam2_vision_modelr Nr r rc <<VPf.ROM VPVnVPf RR.^^.^@^@..M VPVnVPf^^.M VPVn\VP\ 4'd^VPP RR4VPR&\VPR,,!R/VPBVnMVPf\4Vn\SV`(!R/VBR#)NrSrIr )rrrrr) backbone_channel_listbackbone_feature_sizesfpn_top_down_levels isinstancer dictgetrr r)r*r+s&,r/r*Sam2VisionConfig.__post_init__s#'#=#=#E 4KeKe "372M2M2Uc3Z#sb"X .[_[v[v #.2-E-E-MAq6SWSkSk d**D 1 1151E1E1I1I,Xn1oD  .#1$2F2F|2T#U#mX\XlXl#mD  ! ! )#5#7D  ''r1c<V^8dQh/S[S[,R,;R&S[S[,R,;R&S[R,;R&S[;R&S[;R&S[;R&S[;R&S[S[,R,;R &S[;R &S[;R &S[;R &S[;R &#)rNr rUrVfpn_hidden_sizefpn_kernel_size fpn_stride fpn_paddingrWnum_feature_levelsr8r9r:)rYrr<r;r>r=)r?r@s"r/rASam2VisionConfig.__annotate__es8,,t3:9: 9t+2;<!4K.=>?@ABCDEFcT)0GHIJKL MN#Or1)rUr rVrW)rCrDrErFrGrHrIr sub_configsr rUrVr]r^r_r`rWrar8r9r:r*rJrKrLrMrNs@@r/rPrPesr&&O$J:K7;O.2*.OOJK,0J N#(Sr1rPcTa]tRt^toRtRtRtRt^t^t ^t Rt Rt ^t V3RltRtVtR #) Sam2PromptEncoderConfiga= mask_input_channels (`int`, *optional*, defaults to 16): The number of channels to be fed to the `MaskDecoder` module. num_point_embeddings (`int`, *optional*, defaults to 4): The number of point embeddings to be used. scale (`float`, *optional*, defaults to 1): The scale factor for the prompt encoder. prompt_encoder_configrSrr r c<V^8dQh/S[;R&S[S[S[,,S[S[S[3,,;R&S[S[S[,,S[S[S[3,,;R&S[;R&S[;R&S[;R&S[;R&S[;R&#) rr3r patch_sizemask_input_channelsnum_point_embeddingsr8r9scale)r;r<tupler>r=)r?r@s"r/rA$Sam2PromptEncoderConfig.__annotate__sd3i%S/18 d3i%S/16!"!#$!%&'( )* N+r1rN)rCrDrErFrGrHr3rrhrirjr8r9rkrJrKrLr@s@r/reresB.OK48J46J! !J NE+r1recda]tRt^toRtRtRtRtRt^t ^t ^t ^t ^t RtRtRtRtV3R ltR tVtR #) Sam2MaskDecoderConfigam mlp_dim (`int`, *optional*, defaults to 2048): The dimension of the MLP in the two-way transformer. attention_downsample_rate (`int`, *optional*, defaults to 2): The downsample rate for the attention layers. num_multimask_outputs (`int`, *optional*, defaults to 3): The number of multimask outputs. iou_head_depth (`int`, *optional*, defaults to 3): The depth of the IoU head. iou_head_hidden_dim (`int`, *optional*, defaults to 256): The hidden dimension of the IoU head. dynamic_multimask_via_stability (`bool`, *optional*, defaults to `True`): Whether to use dynamic multimask via stability. dynamic_multimask_stability_delta (`float`, *optional*, defaults to 0.05): The stability delta for the dynamic multimask. dynamic_multimask_stability_thresh (`float`, *optional*, defaults to 0.98): The stability threshold for the dynamic multimask. mask_decoder_configrSr iTg?g\(\?c<V^8dQh/S[;R&S[;R&S[;R&S[;R&S[;R&S[;R&S[;R&S[;R&S[;R &S[;R &S[;R &S[;R &#) rr3r8mlp_dimnum_hidden_layersr4attention_downsample_ratenum_multimask_outputsiou_head_depthiou_head_hidden_dimdynamic_multimask_via_stability!dynamic_multimask_stability_delta"dynamic_multimask_stability_thresh)r;r>boolr=)r?r@s"r/rA"Sam2MaskDecoderConfig.__annotate__s012345678 9: #&;<"=>?@"AB&*0CD(-3EF).4Gr1rN)rCrDrErFrGrHr3r8rsrtr4rurvrwrxryrzr{rJrKrLrns@r/rprps]&,OKJG %&!"N",0#/3%04&Gr1rpcfaa]tRt^toRtRtR]R]R]/t Rt Rt Rt Rt V3RltV3R ltR tVtV;t#) Sam2Configa prompt_encoder_config (Union[`dict`, `Sam2PromptEncoderConfig`], *optional*): Dictionary of configuration options used to initialize [`Sam2PromptEncoderConfig`]. mask_decoder_config (Union[`dict`, `Sam2MaskDecoderConfig`], *optional*): Dictionary of configuration options used to initialize [`Sam2MaskDecoderConfig`]. Example: ```python >>> from transformers import ( ... Sam2VisionConfig, ... Sam2PromptEncoderConfig, ... Sam2MaskDecoderConfig, ... Sam2Model, ... ) >>> # Initializing a Sam2Config with `"facebook/sam2.1_hiera_tiny"` style configuration >>> configuration = Sam2Config() >>> # Initializing a Sam2Model (with random weights) from the `"facebook/sam2.1_hiera_tiny"` style configuration >>> model = Sam2Model(configuration) >>> # Accessing the model configuration >>> configuration = model.config >>> # We can also initialize a Sam2Config from a Sam2VisionConfig, Sam2PromptEncoderConfig, and Sam2MaskDecoderConfig >>> # Initializing SAM2 vision encoder, memory attention, and memory encoder configurations >>> vision_config = Sam2VisionConfig() >>> prompt_encoder_config = Sam2PromptEncoderConfig() >>> mask_decoder_config = Sam2MaskDecoderConfig() >>> config = Sam2Config(vision_config, prompt_encoder_config, mask_decoder_config) ```sam2rQrfrqNrc <\VP\4'd^VPPRR4VPR&\VPR,,!R/VPBVnM%VPf\R,!4Vn\VP \4'd\ R/VP BVnMVP f\ 4Vn\VP\4'd\R/VPBVnMVPf\4Vn\SV`(!R/VBR#)rIrRNr) rXrQrYrZrrfrerqrpr)r*r+s&,r/r*Sam2Config.__post_init__s d(($ / //3/A/A/E/ElTg/hD  | ,!/0B0B<0P!Q!gTXTfTf!gD     '!/0C!D!FD  d00$ 7 7)@)^4C]C])^D &  ' ' /)@)BD & d.. 5 5'<'Xt?W?W'XD $  % % -'<'>D $ ''r1c<V^8dQh/S[S[,R,;R&S[S[,R,;R&S[S[,R,;R&S[;R&#)rNrQrfrqr:)rYrr=)r?r@s"r/rASam2Config.__annotate__sbZ**T18[\ "22T9@]^ 0047>_`#ar1)rqrfrQ)rCrDrErFrGrIrrerprcrQrfrqr:r*rJrKrLrMrNs@@r/rrsP! FJ!84K 59M<@:>#(er1rN)rr rPrerp)rGhuggingface_hub.dataclassesrconfiguration_utilsrutilsrautorrr rPrerpr__all__rr1r/rs.3#-78I()I(9I(X786('6(96(r78.9,78!5,!59!5H78A(!A(9A(H r1