optimum-neuron/v0.4.4/en/_app/immutable/nodes/42.13cb5247.js

import{s as ga,n as _a,o as fa}from"../chunks/scheduler.56725da7.js";import{S as va,i as ba,e as a,s as r,c as u,h as ha,a as o,d as l,b as n,f,g as p,j as m,k as v,l as e,m as T,n as d,t as c,o as g,p as _}from"../chunks/index.18a26576.js";import{C as $a}from"../chunks/CopyLLMTxtMenu.4513c8ed.js";import{D as b}from"../chunks/Docstring.6448db33.js";import{H as kn}from"../chunks/MermaidChart.svelte_svelte_type_style_lang.049405bf.js";function xa(wn){let D,Dt,Lt,Pt,re,It,ne,Mt,ae,Ln="Training classes for AWS Trainium accelerators.",Et,oe,Ht,$,se,ur,x,ie,pr,Fe,zn=`Returns the log level to be used depending on whether this process is the main process of node 0, main process
of node non-0, or a non-main process.`,dr,Re,Dn=`For the main process the log level defaults to the logging level set (<code>logging.WARNING</code> if you didn’t do
anything) unless overridden by <code>log_level</code> argument.`,cr,je,Pn=`For the replica processes the log level defaults to <code>logging.WARNING</code> unless overridden by <code>log_level_replica</code>
argument.`,gr,qe,In="The choice between the main and replica process settings is made according to the return value of <code>should_log</code>.",_r,P,le,fr,Oe,Mn="Get number of steps used for a linear warmup.",vr,I,me,br,We,En=`Serializes this instance while replace <code>Enum</code> by their values (for JSON serialization support). It obfuscates
the token values by removing their value.`,hr,M,ue,$r,Be,Hn="Serializes this instance to a JSON string.",xr,E,pe,Tr,Ge,An="Sanitized serialization to use with TensorBoard’s hparams",At,de,Vt,s,ce,yr,H,ge,Nr,Ue,Vn="Add a callback to the current list of <code>TrainerCallback</code>.",Cr,A,_e,kr,Je,Sn=`A helper wrapper that creates an appropriate context manager for <code>autocast</code> while feeding it the desired
arguments, depending on the situation.`,wr,V,fe,Lr,Ye,Fn="Creates NeuronAccelerator instance and prepares model for distributed training.",zr,C,ve,Dr,Ke,Rn="Setup the optimizer.",Pr,Qe,jn=`We provide a reasonable default that works well. If you want to use something else, you can pass a tuple in the
NeuronTrainer’s init through <code>optimizers</code>, or subclass and override this method in a subclass.`,Ir,k,be,Mr,Xe,qn="Setup the optimizer and the learning rate scheduler.",Er,Ze,On=`We provide a reasonable default that works well. If you want to use something else, you can pass a tuple in the
NeuronTrainer’s init through <code>optimizers</code>, or subclass and override this method (or <code>create_optimizer</code> and/or
<code>create_scheduler</code>) in a subclass.`,Hr,S,he,Ar,et,Wn=`Setup the scheduler. The optimizer of the trainer must have been set up either before this method is called or
passed as an argument.`,Vr,y,$e,Sr,tt,Bn="Get all parameter names that weight decay will be applied to.",Fr,rt,Gn="This function filters out parameters in two ways:",Rr,nt,Un="<li>By layer type (instances of layers specified in ALL_LAYERNORM_LAYERS)</li> <li>By parameter name patterns (containing ‘bias’, ‘layernorm’, or ‘rmsnorm’)</li>",jr,F,xe,qr,at,Jn="Returns the learning rate of each parameter from self.optimizer.",Or,R,Te,Wr,ot,Yn="Get the number of trainable parameters.",Br,j,ye,Gr,st,Kn="Returns the optimizer class and optimizer parameters based on the training arguments.",Ur,q,Ne,Jr,it,Qn="Returns optimizer group for a parameter if given, else returns all optimizer groups for params.",Yr,O,Ce,Kr,lt,Xn="Returns the training DataLoader with appropriate sampler and batch size.",Qr,W,ke,Xr,mt,Zn=`Whether or not this process is the local (e.g., on one machine if training in a distributed fashion on several
machines) main process.`,Zr,B,we,en,ut,ea=`Whether or not this process is the global main process (when training in a distributed fashion on several
machines, this is only going to be <code>True</code> for one process).`,tn,G,Le,rn,pt,ta="Log training metrics to the state history and callbacks.",nn,U,ze,an,dt,ra="Log training step metrics if logging is due.",on,J,De,sn,ct,na="Save checkpoint if saving is due.",ln,Y,Pe,mn,gt,aa=`Helper to get number of samples in a <code>~torch.utils.data.DataLoader</code> by accessing its dataset. When
dataloader.dataset does not exist or has no length, estimates as best it can`,un,K,Ie,pn,_t,oa="Helper to get number of tokens in a <code>~torch.utils.data.DataLoader</code> by enumerating dataloader.",dn,w,Me,cn,ft,sa="Remove a callback from the current list of <code>TrainerCallback</code> and returns it.",gn,vt,ia="If the callback is not found, returns <code>None</code> (and no error is raised).",_n,Q,Ee,fn,bt,la="Remove a callback from the current list of <code>TrainerCallback</code>.",vn,X,He,bn,ht,ma="Report and save comprehensive training summary metrics at the end of training.",hn,L,Ae,$n,$t,ua="Calculates and returns the following values:",xn,xt,pa="<li><code>num_train_epochs</code></li> <li><code>num_update_steps_per_epoch</code></li> <li><code>num_examples</code></li> <li><code>num_train_samples</code></li> <li><code>epoch_based</code></li> <li><code>len_dataloader</code></li> <li><code>max_steps</code></li>",Tn,Z,Ve,yn,Tt,da=`Setup everything to prepare for the training loop.
This methods does not return anything but initializes many attributes of the class for training.`,Nn,ee,Se,Cn,yt,ca=`Main training entry point.
Wraps around <code>self._train()</code> to handle cache synchronization.`,St,zt,Ft;return re=new $a({props:{containerStyle:"float: right; margin-left: 10px; display: inline-flex; position: relative; z-index: 10;"}}),ne=new kn({props:{title:"NeuronTrainer",local:"neurontrainer",headingTag:"h1"}}),oe=new kn({props:{title:"NeuronTrainingArguments",local:"optimum.neuron.NeuronTrainingArguments",headingTag:"h2"}}),se=new b({props:{name:"class optimum.neuron.NeuronTrainingArguments",anchor:"optimum.neuron.NeuronTrainingArguments",parameters:[{name:"output_dir",val:": str | None = None"},{name:"overwrite_output_dir",val:": bool = False"},{name:"do_train",val:": bool = False"},{name:"do_eval",val:": bool = False"},{name:"eval_strategy",val:": transformers.trainer_utils.IntervalStrategy | str = 'no'"},{name:"per_device_train_batch_size",val:": int = 1"},{name:"per_device_eval_batch_size",val:": int = 1"},{name:"gradient_accumulation_steps",val:": int = 1"},{name:"learning_rate",val:": float = 5e-05"},{name:"weight_decay",val:": float = 0.0"},{name:"adam_beta1",val:": float = 0.9"},{name:"adam_beta2",val:": float = 0.999"},{name:"adam_epsilon",val:": float = 1e-08"},{name:"max_grad_norm",val:": float = 1.0"},{name:"num_train_epochs",val:": float = 3.0"},{name:"max_steps",val:": int = -1"},{name:"lr_scheduler_type",val:": transformers.trainer_utils.SchedulerType | str = 'linear'"},{name:"lr_scheduler_kwargs",val:": dict[str, typing.Any] | str | None = <factory>"},{name:"warmup_ratio",val:": float = 0.0"},{name:"warmup_steps",val:": int = 0"},{name:"log_level",val:": str = 'info'"},{name:"log_level_replica",val:": str = 'silent'"},{name:"logging_dir",val:": str | None = None"},{name:"logging_strategy",val:": transformers.trainer_utils.IntervalStrategy | str = 'steps'"},{name:"logging_first_step",val:": bool = False"},{name:"logging_steps",val:": float = 500"},{name:"save_strategy",val:": transformers.trainer_utils.SaveStrategy | str = 'steps'"},{name:"save_steps",val:": float = 500"},{name:"save_total_limit",val:": int | None = None"},{name:"save_only_model",val:": bool = False"},{name:"restore_callback_states_from_checkpoint",val:": bool = False"},{name:"seed",val:": int = 42"},{name:"bf16",val:": bool = False"},{name:"dataloader_drop_last",val:": bool = False"},{name:"eval_steps",val:": float | None = None"},{name:"dataloader_num_workers",val:": int = 0"},{name:"dataloader_prefetch_factor",val:": int | None = None"},{name:"run_name",val:": str | None = None"},{name:"disable_tqdm",val:": bool | None = None"},{name:"remove_unused_columns",val:": bool | None = True"},{name:"label_names",val:": list[str] | None = None"},{name:"accelerator_config",val:": dict | str | None = None"},{name:"label_smoothing_factor",val:": float = 0.0"},{name:"optim",val:": transformers.training_args.OptimizerNames | str = 'adamw_torch'"},{name:"optim_args",val:": str | None = None"},{name:"report_to",val:": None | str | list[str] = None"},{name:"resume_from_checkpoint",val:": str | None = None"},{name:"gradient_checkpointing",val:": bool = False"},{name:"gradient_checkpointing_kwargs",val:": dict[str, typing.Any] | str | None = None"},{name:"use_liger_kernel",val:": bool | None = False"},{name:"average_tokens_across_devices",val:": bool | None = False"},{name:"dataloader_prefetch_size",val:": int = None"},{name:"skip_cache_push",val:": bool = False"},{name:"use_autocast",val:": bool = False"},{name:"zero_1",val:": bool = True"},{name:"stochastic_rounding_enabled",val:": bool = True"},{name:"optimizer_use_master_weights",val:": bool = True"},{name:"optimizer_use_fp32_grad_acc",val:": bool = True"},{name:"optimizer_save_master_weights_in_ckpt",val:": bool = False"},{name:"tensor_parallel_size",val:": int = 1"},{name:"disable_sequence_parallel",val:": bool = False"},{name:"pipeline_parallel_size",val:": int = 1"},{name:"pipeline_parallel_num_microbatches",val:": int = -1"},{name:"kv_size_multiplier",val:": int | None = None"},{name:"num_local_ranks_per_step",val:": int = 8"},{name:"use_xser",val:": bool = True"},{name:"async_save",val:": bool = False"},{name:"fuse_qkv",val:": bool = False"},{name:"recompute_causal_mask",val:": bool = True"},{name:"enable_throughput_metrics",val:": bool = True"},{name:"enable_mfu_metrics",val:": bool = True"},{name:"enable_efficiency_metrics",val:": bool = True"},{name:"metrics_window_size",val:": int = 50"}],source:"https://github.com/huggingface/optimum-neuron/blob/v0.4.4/optimum/neuron/trainers/training_args.py#L49"}}),ie=new b({props:{name:"get_process_log_level",anchor:"optimum.neuron.NeuronTrainingArguments.get_process_log_level",parameters:[],source:"https://github.com/huggingface/optimum-neuron/blob/v0.4.4/optimum/neuron/trainers/training_args.py#L761"}}),le=new b({props:{name:"get_warmup_steps",anchor:"optimum.neuron.NeuronTrainingArguments.get_warmup_steps",parameters:[{name:"num_training_steps",val:": int"}],source:"https://github.com/huggingface/optimum-neuron/blob/v0.4.4/optimum/neuron/trainers/training_args.py#L783"}}),me=new b({props:{name:"to_dict",anchor:"optimum.neuron.NeuronTrainingArguments.to_dict",parameters:[],source:"https://github.com/huggingface/optimum-neuron/blob/v0.4.4/optimum/neuron/trainers/training_args.py#L803"}}),ue=new b({props:{name:"to_json_string",anchor:"optimum.neuron.NeuronTrainingArguments.to_json_string",parameters:[],source:"https://github.com/huggingface/optimum-neuron/blob/v0.4.4/optimum/neuron/trainers/training_args.py#L830"}}),pe=new b({props:{name:"to_sanitized_dict",anchor:"optimum.neuron.NeuronTrainingArguments.to_sanitized_dict",parameters:[],source:"https://github.com/huggingface/optimum-neuron/blob/v0.4.4/optimum/neuron/trainers/training_args.py#L836"}}),de=new kn({props:{title:"NeuronTrainer",local:"optimum.neuron.NeuronTrainer",headingTag:"h2"}}),ce=new b({props:{name:"class optimum.neuron.NeuronTrainer",anchor:"optimum.neuron.NeuronTrainer",parameters:[{name:"model",val:": transformers.modeling_utils.PreTrainedModel | torch.nn.modules.module.Module"},{name:"args",val:": NeuronTrainingArguments"},{name:"data_collator",val:": typing.Optional[typing.Callable[[list[typing.Any]], dict[str, typing.Any]]] = None"},{name:"train_dataset",val:": Dataset | IterableDataset | datasets.Dataset | None = None"},{name:"eval_dataset",val:": Dataset | dict[str, Dataset] | datasets.Dataset | None = None"},{name:"processing_class",val:": transformers.tokenization_utils_base.PreTrainedTokenizerBase | transformers.image_processing_utils.BaseImageProcessor | transformers.feature_extraction_utils.FeatureExtractionMixin | transformers.processing_utils.ProcessorMixin | None = None"},{name:"callbacks",val:": list[transformers.trainer_callback.TrainerCallback] | None = None"},{name:"optimizers",val:": tuple[torch.optim.optimizer.Optimizer | None, torch.optim.lr_scheduler.LambdaLR | None] = (None, None)"},{name:"optimizer_cls_and_kwargs",val:": tuple[type[torch.optim.optimizer.Optimizer], dict[str, typing.Any]] | None = None"},{name:"tokenizer",val:": transformers.tokenization_utils_base.PreTrainedTokenizerBase | None = None"}],source:"https://github.com/huggingface/optimum-neuron/blob/v0.4.4/optimum/neuron/trainers/transformers.py#L119"}}),ge=new b({props:{name:"add_callback",anchor:"optimum.neuron.NeuronTrainer.add_callback",parameters:[{name:"callback",val:": typing.Union[typing.Type[transformers.trainer_callback.TrainerCallback], transformers.trainer_callback.TrainerCallback]"}],parametersDescription:[{anchor:"optimum.neuron.NeuronTrainer.add_callback.callback",description:`<strong>callback</strong> (<code>Type[TrainerCallback] | TrainerCallback</code>) &#x2014;
A <code>TrainerCallback</code> class or an instance of a <code>TrainerCallback</code>. In the
first case, will instantiate a member of that class.`,name:"callback"}],source:"https://github.com/huggingface/optimum-neuron/blob/v0.4.4/optimum/neuron/trainers/transformers.py#L375"}}),_e=new b({props:{name:"autocast_smart_context_manager",anchor:"optimum.neuron.NeuronTrainer.autocast_smart_context_manager",parameters:[{name:"cache_enabled",val:": bool | None = True"}],source:"https://github.com/huggingface/optimum-neuron/blob/v0.4.4/optimum/neuron/trainers/transformers.py#L743"}}),fe=new b({props:{name:"create_accelerator_and_postprocess",anchor:"optimum.neuron.NeuronTrainer.create_accelerator_and_postprocess",parameters:[],source:"https://github.com/huggingface/optimum-neuron/blob/v0.4.4/optimum/neuron/trainers/transformers.py#L291"}}),ve=new b({props:{name:"create_optimizer",anchor:"optimum.neuron.NeuronTrainer.create_optimizer",parameters:[],source:"https://github.com/huggingface/optimum-neuron/blob/v0.4.4/optimum/neuron/trainers/transformers.py#L569"}}),be=new b({props:{name:"create_optimizer_and_scheduler",anchor:"optimum.neuron.NeuronTrainer.create_optimizer_and_scheduler",parameters:[{name:"num_training_steps",val:": int"}],source:"https://github.com/huggingface/optimum-neuron/blob/v0.4.4/optimum/neuron/trainers/transformers.py#L547"}}),he=new b({props:{name:"create_scheduler",anchor:"optimum.neuron.NeuronTrainer.create_scheduler",parameters:[{name:"num_training_steps",val:": int"},{name:"optimizer",val:": torch.optim.optimizer.Optimizer | None = None"}],parametersDescription:[{anchor:"optimum.neuron.NeuronTrainer.create_scheduler.num_training_steps",description:"<strong>num_training_steps</strong> (int) &#x2014; The number of training steps to do.",name:"num_training_steps"}],source:"https://github.com/huggingface/optimum-neuron/blob/v0.4.4/optimum/neuron/trainers/transformers.py#L683"}}),$e=new b({props:{name:"get_decay_parameter_names",anchor:"optimum.neuron.NeuronTrainer.get_decay_parameter_names",parameters:[{name:"model",val:""}],source:"https://github.com/huggingface/optimum-neuron/blob/v0.4.4/optimum/neuron/trainers/transformers.py#L558"}}),xe=new b({props:{name:"get_learning_rates",anchor:"optimum.neuron.NeuronTrainer.get_learning_rates",parameters:[],source:"https://github.com/huggingface/optimum-neuron/blob/v0.4.4/optimum/neuron/trainers/transformers.py#L626"}}),Te=new b({props:{name:"get_num_trainable_parameters",anchor:"optimum.neuron.NeuronTrainer.get_num_trainable_parameters",parameters:[],source:"https://github.com/huggingface/optimum-neuron/blob/v0.4.4/optimum/neuron/trainers/transformers.py#L620"}}),ye=new b({props:{name:"get_optimizer_cls_and_kwargs",anchor:"optimum.neuron.NeuronTrainer.get_optimizer_cls_and_kwargs",parameters:[{name:"args",val:": TrainingArguments"},{name:"model",val:": transformers.modeling_utils.PreTrainedModel | None = None"}],parametersDescription:[{anchor:"optimum.neuron.NeuronTrainer.get_optimizer_cls_and_kwargs.args",description:`<strong>args</strong> (<code>transformers.training_args.TrainingArguments</code>) &#x2014;
The training arguments for the training session.`,name:"args"}],source:"https://github.com/huggingface/optimum-neuron/blob/v0.4.4/optimum/neuron/trainers/transformers.py#L650"}}),Ne=new b({props:{name:"get_optimizer_group",anchor:"optimum.neuron.NeuronTrainer.get_optimizer_group",parameters:[{name:"param",val:": str | torch.nn.parameter.Parameter | None = None"}],parametersDescription:[{anchor:"optimum.neuron.NeuronTrainer.get_optimizer_group.param",description:`<strong>param</strong> (<code>str | torch.nn.parameter.Parameter | None</code>, defaults to <code>None</code>) &#x2014;
The parameter for which optimizer group needs to be returned.`,name:"param"}],source:"https://github.com/huggingface/optimum-neuron/blob/v0.4.4/optimum/neuron/trainers/transformers.py#L634"}}),Ce=new b({props:{name:"get_train_dataloader",anchor:"optimum.neuron.NeuronTrainer.get_train_dataloader",parameters:[],source:"https://github.com/huggingface/optimum-neuron/blob/v0.4.4/optimum/neuron/trainers/transformers.py#L528"}}),ke=new b({props:{name:"is_local_process_zero",anchor:"optimum.neuron.NeuronTrainer.is_local_process_zero",parameters:[],source:"https://github.com/huggingface/optimum-neuron/blob/v0.4.4/optimum/neuron/trainers/transformers.py#L1251"}}),we=new b({props:{name:"is_world_process_zero",anchor:"optimum.neuron.NeuronTrainer.is_world_process_zero",parameters:[],source:"https://github.com/huggingface/optimum-neuron/blob/v0.4.4/optimum/neuron/trainers/transformers.py#L1258"}}),Le=new b({props:{name:"log",anchor:"optimum.neuron.NeuronTrainer.log",parameters:[{name:"logs",val:": dict[str, float]"}],source:"https://github.com/huggingface/optimum-neuron/blob/v0.4.4/optimum/neuron/trainers/transformers.py#L1318"}}),ze=new b({props:{name:"maybe_log_train_step_metrics",anchor:"optimum.neuron.NeuronTrainer.maybe_log_train_step_metrics",parameters:[],source:"https://github.com/huggingface/optimum-neuron/blob/v0.4.4/optimum/neuron/trainers/transformers.py#L1028"}}),De=new b({props:{name:"maybe_save_checkpoint",anchor:"optimum.neuron.NeuronTrainer.maybe_save_checkpoint",parameters:[],source:"https://github.com/huggingface/optimum-neuron/blob/v0.4.4/optimum/neuron/trainers/transformers.py#L1080"}}),Pe=new b({props:{name:"num_examples",anchor:"optimum.neuron.NeuronTrainer.num_examples",parameters:[{name:"dataloader",val:": DataLoader"}],source:"https://github.com/huggingface/optimum-neuron/blob/v0.4.4/optimum/neuron/trainers/transformers.py#L703"}}),Ie=new b({props:{name:"num_tokens",anchor:"optimum.neuron.NeuronTrainer.num_tokens",parameters:[{name:"train_dl",val:": DataLoader"},{name:"max_steps",val:": int | None = None"}],source:"https://github.com/huggingface/optimum-neuron/blob/v0.4.4/optimum/neuron/trainers/transformers.py#L717"}}),Me=new b({props:{name:"pop_callback",anchor:"optimum.neuron.NeuronTrainer.pop_callback",parameters:[{name:"callback",val:": typing.Union[typing.Type[transformers.trainer_callback.TrainerCallback], transformers.trainer_callback.TrainerCallback]"}],parametersDescription:[{anchor:"optimum.neuron.NeuronTrainer.pop_callback.callback",description:`<strong>callback</strong> (<code>Type[TrainerCallback] | TrainerCallback</code>) &#x2014;
A <code>TrainerCallback</code> class or an instance of a <code>TrainerCallback</code>. In the
first case, will pop the first member of that class found in the list of callbacks.`,name:"callback"}],source:"https://github.com/huggingface/optimum-neuron/blob/v0.4.4/optimum/neuron/trainers/transformers.py#L386",returnDescription:`<script context="module">export const metadata = 'undefined';<\/script>


<p>The callback removed, if found.</p>
`,returnType:`<script context="module">export const metadata = 'undefined';<\/script>


<p><code>TrainerCallback | None</code></p>
`}}),Ee=new b({props:{name:"remove_callback",anchor:"optimum.neuron.NeuronTrainer.remove_callback",parameters:[{name:"callback",val:": typing.Union[typing.Type[transformers.trainer_callback.TrainerCallback], transformers.trainer_callback.TrainerCallback]"}],parametersDescription:[{anchor:"optimum.neuron.NeuronTrainer.remove_callback.callback",description:`<strong>callback</strong> (<code>Type[TrainerCallback] | TrainerCallback</code>) &#x2014;
A <code>TrainerCallback</code> class or an instance of a <code>TrainerCallback</code>. In the
first case, will remove the first member of that class found in the list of callbacks.`,name:"callback"}],source:"https://github.com/huggingface/optimum-neuron/blob/v0.4.4/optimum/neuron/trainers/transformers.py#L402"}}),He=new b({props:{name:"report_and_save_summary_metrics",anchor:"optimum.neuron.NeuronTrainer.report_and_save_summary_metrics",parameters:[],source:"https://github.com/huggingface/optimum-neuron/blob/v0.4.4/optimum/neuron/trainers/transformers.py#L1326"}}),Ae=new b({props:{name:"set_initial_training_values",anchor:"optimum.neuron.NeuronTrainer.set_initial_training_values",parameters:[{name:"args",val:": NeuronTrainingArguments"},{name:"dataloader",val:": DataLoader"},{name:"total_train_batch_size",val:": int"}],source:"https://github.com/huggingface/optimum-neuron/blob/v0.4.4/optimum/neuron/trainers/transformers.py#L754"}}),Ve=new b({props:{name:"setup_training",anchor:"optimum.neuron.NeuronTrainer.setup_training",parameters:[{name:"train_dataloader",val:": DataLoader"},{name:"max_steps",val:": int"},{name:"num_train_epochs",val:": int"},{name:"num_examples",val:": int"},{name:"total_train_batch_size",val:": int"}],source:"https://github.com/huggingface/optimum-neuron/blob/v0.4.4/optimum/neuron/trainers/transformers.py#L818"}}),Se=new b({props:{name:"train",anchor:"optimum.neuron.NeuronTrainer.train",parameters:[{name:"resume_from_checkpoint",val:": str | bool | None = None"}],source:"https://github.com/huggingface/optimum-neuron/blob/v0.4.4/optimum/neuron/trainers/transformers.py#L1240"}}),{c(){D=a("meta"),Dt=r(),Lt=a("p"),Pt=r(),u(re.$$.fragment),It=r(),u(ne.$$.fragment),Mt=r(),ae=a("p"),ae.textContent=Ln,Et=r(),u(oe.$$.fragment),Ht=r(),$=a("div"),u(se.$$.fragment),ur=r(),x=a("div"),u(ie.$$.fragment),pr=r(),Fe=a("p"),Fe.textContent=zn,dr=r(),Re=a("p"),Re.innerHTML=Dn,cr=r(),je=a("p"),je.innerHTML=Pn,gr=r(),qe=a("p"),qe.innerHTML=In,_r=r(),P=a("div"),u(le.$$.fragment),fr=r(),Oe=a("p"),Oe.textContent=Mn,vr=r(),I=a("div"),u(me.$$.fragment),br=r(),We=a("p"),We.innerHTML=En,hr=r(),M=a("div"),u(ue.$$.fragment),$r=r(),Be=a("p"),Be.textContent=Hn,xr=r(),E=a("div"),u(pe.$$.fragment),Tr=r(),Ge=a("p"),Ge.textContent=An,At=r(),u(de.$$.fragment),Vt=r(),s=a("div"),u(ce.$$.fragment),yr=r(),H=a("div"),u(ge.$$.fragment),Nr=r(),Ue=a("p"),Ue.innerHTML=Vn,Cr=r(),A=a("div"),u(_e.$$.fragment),kr=r(),Je=a("p"),Je.innerHTML=Sn,wr=r(),V=a("div"),u(fe.$$.fragment),Lr=r(),Ye=a("p"),Ye.textContent=Fn,zr=r(),C=a("div"),u(ve.$$.fragment),Dr=r(),Ke=a("p"),Ke.textContent=Rn,Pr=r(),Qe=a("p"),Qe.innerHTML=jn,Ir=r(),k=a("div"),u(be.$$.fragment),Mr=r(),Xe=a("p"),Xe.textContent=qn,Er=r(),Ze=a("p"),Ze.innerHTML=On,Hr=r(),S=a("div"),u(he.$$.fragment),Ar=r(),et=a("p"),et.textContent=Wn,Vr=r(),y=a("div"),u($e.$$.fragment),Sr=r(),tt=a("p"),tt.textContent=Bn,Fr=r(),rt=a("p"),rt.textContent=Gn,Rr=r(),nt=a("ol"),nt.innerHTML=Un,jr=r(),F=a("div"),u(xe.$$.fragment),qr=r(),at=a("p"),at.textContent=Jn,Or=r(),R=a("div"),u(Te.$$.fragment),Wr=r(),ot=a("p"),ot.textContent=Yn,Br=r(),j=a("div"),u(ye.$$.fragment),Gr=r(),st=a("p"),st.textContent=Kn,Ur=r(),q=a("div"),u(Ne.$$.fragment),Jr=r(),it=a("p"),it.textContent=Qn,Yr=r(),O=a("div"),u(Ce.$$.fragment),Kr=r(),lt=a("p"),lt.textContent=Xn,Qr=r(),W=a("div"),u(ke.$$.fragment),Xr=r(),mt=a("p"),mt.textContent=Zn,Zr=r(),B=a("div"),u(we.$$.fragment),en=r(),ut=a("p"),ut.innerHTML=ea,tn=r(),G=a("div"),u(Le.$$.fragment),rn=r(),pt=a("p"),pt.textContent=ta,nn=r(),U=a("div"),u(ze.$$.fragment),an=r(),dt=a("p"),dt.textContent=ra,on=r(),J=a("div"),u(De.$$.fragment),sn=r(),ct=a("p"),ct.textContent=na,ln=r(),Y=a("div"),u(Pe.$$.fragment),mn=r(),gt=a("p"),gt.innerHTML=aa,un=r(),K=a("div"),u(Ie.$$.fragment),pn=r(),_t=a("p"),_t.innerHTML=oa,dn=r(),w=a("div"),u(Me.$$.fragment),cn=r(),ft=a("p"),ft.innerHTML=sa,gn=r(),vt=a("p"),vt.innerHTML=ia,_n=r(),Q=a("div"),u(Ee.$$.fragment),fn=r(),bt=a("p"),bt.innerHTML=la,vn=r(),X=a("div"),u(He.$$.fragment),bn=r(),ht=a("p"),ht.textContent=ma,hn=r(),L=a("div"),u(Ae.$$.fragment),$n=r(),$t=a("p"),$t.textContent=ua,xn=r(),xt=a("ul"),xt.innerHTML=pa,Tn=r(),Z=a("div"),u(Ve.$$.fragment),yn=r(),Tt=a("p"),Tt.textContent=da,Nn=r(),ee=a("div"),u(Se.$$.fragment),Cn=r(),yt=a("p"),yt.innerHTML=ca,St=r(),zt=a("p"),this.h()},l(t){const h=ha("svelte-u9bgzb",document.head);D=o(h,"META",{name:!0,content:!0}),h.forEach(l),Dt=n(t),Lt=o(t,"P",{}),f(Lt).forEach(l),Pt=n(t),p(re.$$.fragment,t),It=n(t),p(ne.$$.fragment,t),Mt=n(t),ae=o(t,"P",{"data-svelte-h":!0}),m(ae)!=="svelte-8btytl"&&(ae.textContent=Ln),Et=n(t),p(oe.$$.fragment,t),Ht=n(t),$=o(t,"DIV",{class:!0});var N=f($);p(se.$$.fragment,N),ur=n(N),x=o(N,"DIV",{class:!0});var z=f(x);p(ie.$$.fragment,z),pr=n(z),Fe=o(z,"P",{"data-svelte-h":!0}),m(Fe)!=="svelte-hj8f41"&&(Fe.textContent=zn),dr=n(z),Re=o(z,"P",{"data-svelte-h":!0}),m(Re)!=="svelte-1iq1lj0"&&(Re.innerHTML=Dn),cr=n(z),je=o(z,"P",{"data-svelte-h":!0}),m(je)!=="svelte-18bal86"&&(je.innerHTML=Pn),gr=n(z),qe=o(z,"P",{"data-svelte-h":!0}),m(qe)!=="svelte-oacj0p"&&(qe.innerHTML=In),z.forEach(l),_r=n(N),P=o(N,"DIV",{class:!0});var Rt=f(P);p(le.$$.fragment,Rt),fr=n(Rt),Oe=o(Rt,"P",{"data-svelte-h":!0}),m(Oe)!=="svelte-9pbc1"&&(Oe.textContent=Mn),Rt.forEach(l),vr=n(N),I=o(N,"DIV",{class:!0});var jt=f(I);p(me.$$.fragment,jt),br=n(jt),We=o(jt,"P",{"data-svelte-h":!0}),m(We)!=="svelte-1ciob6u"&&(We.innerHTML=En),jt.forEach(l),hr=n(N),M=o(N,"DIV",{class:!0});var qt=f(M);p(ue.$$.fragment,qt),$r=n(qt),Be=o(qt,"P",{"data-svelte-h":!0}),m(Be)!=="svelte-5ayq1f"&&(Be.textContent=Hn),qt.forEach(l),xr=n(N),E=o(N,"DIV",{class:!0});var Ot=f(E);p(pe.$$.fragment,Ot),Tr=n(Ot),Ge=o(Ot,"P",{"data-svelte-h":!0}),m(Ge)!=="svelte-lg45ly"&&(Ge.textContent=An),Ot.forEach(l),N.forEach(l),At=n(t),p(de.$$.fragment,t),Vt=n(t),s=o(t,"DIV",{class:!0});var i=f(s);p(ce.$$.fragment,i),yr=n(i),H=o(i,"DIV",{class:!0});var Wt=f(H);p(ge.$$.fragment,Wt),Nr=n(Wt),Ue=o(Wt,"P",{"data-svelte-h":!0}),m(Ue)!=="svelte-erlepi"&&(Ue.innerHTML=Vn),Wt.forEach(l),Cr=n(i),A=o(i,"DIV",{class:!0});var Bt=f(A);p(_e.$$.fragment,Bt),kr=n(Bt),Je=o(Bt,"P",{"data-svelte-h":!0}),m(Je)!=="svelte-9kwitf"&&(Je.innerHTML=Sn),Bt.forEach(l),wr=n(i),V=o(i,"DIV",{class:!0});var Gt=f(V);p(fe.$$.fragment,Gt),Lr=n(Gt),Ye=o(Gt,"P",{"data-svelte-h":!0}),m(Ye)!=="svelte-1wko3le"&&(Ye.textContent=Fn),Gt.forEach(l),zr=n(i),C=o(i,"DIV",{class:!0});var Nt=f(C);p(ve.$$.fragment,Nt),Dr=n(Nt),Ke=o(Nt,"P",{"data-svelte-h":!0}),m(Ke)!=="svelte-1w438iv"&&(Ke.textContent=Rn),Pr=n(Nt),Qe=o(Nt,"P",{"data-svelte-h":!0}),m(Qe)!=="svelte-17qjzpp"&&(Qe.innerHTML=jn),Nt.forEach(l),Ir=n(i),k=o(i,"DIV",{class:!0});var Ct=f(k);p(be.$$.fragment,Ct),Mr=n(Ct),Xe=o(Ct,"P",{"data-svelte-h":!0}),m(Xe)!=="svelte-wdco14"&&(Xe.textContent=qn),Er=n(Ct),Ze=o(Ct,"P",{"data-svelte-h":!0}),m(Ze)!=="svelte-x1lyka"&&(Ze.innerHTML=On),Ct.forEach(l),Hr=n(i),S=o(i,"DIV",{class:!0});var Ut=f(S);p(he.$$.fragment,Ut),Ar=n(Ut),et=o(Ut,"P",{"data-svelte-h":!0}),m(et)!=="svelte-qi4mtl"&&(et.textContent=Wn),Ut.forEach(l),Vr=n(i),y=o(i,"DIV",{class:!0});var te=f(y);p($e.$$.fragment,te),Sr=n(te),tt=o(te,"P",{"data-svelte-h":!0}),m(tt)!=="svelte-c1jesw"&&(tt.textContent=Bn),Fr=n(te),rt=o(te,"P",{"data-svelte-h":!0}),m(rt)!=="svelte-25ysg0"&&(rt.textContent=Gn),Rr=n(te),nt=o(te,"OL",{"data-svelte-h":!0}),m(nt)!=="svelte-1jln558"&&(nt.innerHTML=Un),te.forEach(l),jr=n(i),F=o(i,"DIV",{class:!0});var Jt=f(F);p(xe.$$.fragment,Jt),qr=n(Jt),at=o(Jt,"P",{"data-svelte-h":!0}),m(at)!=="svelte-fo0w3k"&&(at.textContent=Jn),Jt.forEach(l),Or=n(i),R=o(i,"DIV",{class:!0});var Yt=f(R);p(Te.$$.fragment,Yt),Wr=n(Yt),ot=o(Yt,"P",{"data-svelte-h":!0}),m(ot)!=="svelte-n48d75"&&(ot.textContent=Yn),Yt.forEach(l),Br=n(i),j=o(i,"DIV",{class:!0});var Kt=f(j);p(ye.$$.fragment,Kt),Gr=n(Kt),st=o(Kt,"P",{"data-svelte-h":!0}),m(st)!=="svelte-1enq7q"&&(st.textContent=Kn),Kt.forEach(l),Ur=n(i),q=o(i,"DIV",{class:!0});var Qt=f(q);p(Ne.$$.fragment,Qt),Jr=n(Qt),it=o(Qt,"P",{"data-svelte-h":!0}),m(it)!=="svelte-4yzrvz"&&(it.textContent=Qn),Qt.forEach(l),Yr=n(i),O=o(i,"DIV",{class:!0});var Xt=f(O);p(Ce.$$.fragment,Xt),Kr=n(Xt),lt=o(Xt,"P",{"data-svelte-h":!0}),m(lt)!=="svelte-3lk00k"&&(lt.textContent=Xn),Xt.forEach(l),Qr=n(i),W=o(i,"DIV",{class:!0});var Zt=f(W);p(ke.$$.fragment,Zt),Xr=n(Zt),mt=o(Zt,"P",{"data-svelte-h":!0}),m(mt)!=="svelte-16imdke"&&(mt.textContent=Zn),Zt.forEach(l),Zr=n(i),B=o(i,"DIV",{class:!0});var er=f(B);p(we.$$.fragment,er),en=n(er),ut=o(er,"P",{"data-svelte-h":!0}),m(ut)!=="svelte-1s7jdq8"&&(ut.innerHTML=ea),er.forEach(l),tn=n(i),G=o(i,"DIV",{class:!0});var tr=f(G);p(Le.$$.fragment,tr),rn=n(tr),pt=o(tr,"P",{"data-svelte-h":!0}),m(pt)!=="svelte-1ivw6sf"&&(pt.textContent=ta),tr.forEach(l),nn=n(i),U=o(i,"DIV",{class:!0});var rr=f(U);p(ze.$$.fragment,rr),an=n(rr),dt=o(rr,"P",{"data-svelte-h":!0}),m(dt)!=="svelte-1mzc3sd"&&(dt.textContent=ra),rr.forEach(l),on=n(i),J=o(i,"DIV",{class:!0});var nr=f(J);p(De.$$.fragment,nr),sn=n(nr),ct=o(nr,"P",{"data-svelte-h":!0}),m(ct)!=="svelte-5fsriy"&&(ct.textContent=na),nr.forEach(l),ln=n(i),Y=o(i,"DIV",{class:!0});var ar=f(Y);p(Pe.$$.fragment,ar),mn=n(ar),gt=o(ar,"P",{"data-svelte-h":!0}),m(gt)!=="svelte-19inmpu"&&(gt.innerHTML=aa),ar.forEach(l),un=n(i),K=o(i,"DIV",{class:!0});var or=f(K);p(Ie.$$.fragment,or),pn=n(or),_t=o(or,"P",{"data-svelte-h":!0}),m(_t)!=="svelte-tkw811"&&(_t.innerHTML=oa),or.forEach(l),dn=n(i),w=o(i,"DIV",{class:!0});var kt=f(w);p(Me.$$.fragment,kt),cn=n(kt),ft=o(kt,"P",{"data-svelte-h":!0}),m(ft)!=="svelte-11dvmkl"&&(ft.innerHTML=sa),gn=n(kt),vt=o(kt,"P",{"data-svelte-h":!0}),m(vt)!=="svelte-1ojzwr1"&&(vt.innerHTML=ia),kt.forEach(l),_n=n(i),Q=o(i,"DIV",{class:!0});var sr=f(Q);p(Ee.$$.fragment,sr),fn=n(sr),bt=o(sr,"P",{"data-svelte-h":!0}),m(bt)!=="svelte-1hz0n8s"&&(bt.innerHTML=la),sr.forEach(l),vn=n(i),X=o(i,"DIV",{class:!0});var ir=f(X);p(He.$$.fragment,ir),bn=n(ir),ht=o(ir,"P",{"data-svelte-h":!0}),m(ht)!=="svelte-1drd5rt"&&(ht.textContent=ma),ir.forEach(l),hn=n(i),L=o(i,"DIV",{class:!0});var wt=f(L);p(Ae.$$.fragment,wt),$n=n(wt),$t=o(wt,"P",{"data-svelte-h":!0}),m($t)!=="svelte-130oxb1"&&($t.textContent=ua),xn=n(wt),xt=o(wt,"UL",{"data-svelte-h":!0}),m(xt)!=="svelte-39b8ej"&&(xt.innerHTML=pa),wt.forEach(l),Tn=n(i),Z=o(i,"DIV",{class:!0});var lr=f(Z);p(Ve.$$.fragment,lr),yn=n(lr),Tt=o(lr,"P",{"data-svelte-h":!0}),m(Tt)!=="svelte-9r3hwj"&&(Tt.textContent=da),lr.forEach(l),Nn=n(i),ee=o(i,"DIV",{class:!0});var mr=f(ee);p(Se.$$.fragment,mr),Cn=n(mr),yt=o(mr,"P",{"data-svelte-h":!0}),m(yt)!=="svelte-2h3wjd"&&(yt.innerHTML=ca),mr.forEach(l),i.forEach(l),St=n(t),zt=o(t,"P",{}),f(zt).forEach(l),this.h()},h(){v(D,"name","hf:doc:metadata"),v(D,"content",Ta),v(x,"class","docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"),v(P,"class","docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"),v(I,"class","docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"),v(M,"class","docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"),v(E,"class","docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"),v($,"class","docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"),v(H,"class","docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"),v(A,"class","docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"),v(V,"class","docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"),v(C,"class","docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"),v(k,"class","docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"),v(S,"class","docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"),v(y,"class","docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"),v(F,"class","docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"),v(R,"class","docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"),v(j,"class","docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"),v(q,"class","docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"),v(O,"class","docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"),v(W,"class","docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"),v(B,"class","docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"),v(G,"class","docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"),v(U,"class","docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"),v(J,"class","docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"),v(Y,"class","docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"),v(K,"class","docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"),v(w,"class","docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"),v(Q,"class","docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"),v(X,"class","docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"),v(L,"class","docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"),v(Z,"class","docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"),v(ee,"class","docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8"),v(s,"class","docstring border-l-2 border-t-2 pl-4 pt-3.5 border-gray-100 rounded-tl-xl mb-6 mt-8")},m(t,h){e(document.head,D),T(t,Dt,h),T(t,Lt,h),T(t,Pt,h),d(re,t,h),T(t,It,h),d(ne,t,h),T(t,Mt,h),T(t,ae,h),T(t,Et,h),d(oe,t,h),T(t,Ht,h),T(t,$,h),d(se,$,null),e($,ur),e($,x),d(ie,x,null),e(x,pr),e(x,Fe),e(x,dr),e(x,Re),e(x,cr),e(x,je),e(x,gr),e(x,qe),e($,_r),e($,P),d(le,P,null),e(P,fr),e(P,Oe),e($,vr),e($,I),d(me,I,null),e(I,br),e(I,We),e($,hr),e($,M),d(ue,M,null),e(M,$r),e(M,Be),e($,xr),e($,E),d(pe,E,null),e(E,Tr),e(E,Ge),T(t,At,h),d(de,t,h),T(t,Vt,h),T(t,s,h),d(ce,s,null),e(s,yr),e(s,H),d(ge,H,null),e(H,Nr),e(H,Ue),e(s,Cr),e(s,A),d(_e,A,null),e(A,kr),e(A,Je),e(s,wr),e(s,V),d(fe,V,null),e(V,Lr),e(V,Ye),e(s,zr),e(s,C),d(ve,C,null),e(C,Dr),e(C,Ke),e(C,Pr),e(C,Qe),e(s,Ir),e(s,k),d(be,k,null),e(k,Mr),e(k,Xe),e(k,Er),e(k,Ze),e(s,Hr),e(s,S),d(he,S,null),e(S,Ar),e(S,et),e(s,Vr),e(s,y),d($e,y,null),e(y,Sr),e(y,tt),e(y,Fr),e(y,rt),e(y,Rr),e(y,nt),e(s,jr),e(s,F),d(xe,F,null),e(F,qr),e(F,at),e(s,Or),e(s,R),d(Te,R,null),e(R,Wr),e(R,ot),e(s,Br),e(s,j),d(ye,j,null),e(j,Gr),e(j,st),e(s,Ur),e(s,q),d(Ne,q,null),e(q,Jr),e(q,it),e(s,Yr),e(s,O),d(Ce,O,null),e(O,Kr),e(O,lt),e(s,Qr),e(s,W),d(ke,W,null),e(W,Xr),e(W,mt),e(s,Zr),e(s,B),d(we,B,null),e(B,en),e(B,ut),e(s,tn),e(s,G),d(Le,G,null),e(G,rn),e(G,pt),e(s,nn),e(s,U),d(ze,U,null),e(U,an),e(U,dt),e(s,on),e(s,J),d(De,J,null),e(J,sn),e(J,ct),e(s,ln),e(s,Y),d(Pe,Y,null),e(Y,mn),e(Y,gt),e(s,un),e(s,K),d(Ie,K,null),e(K,pn),e(K,_t),e(s,dn),e(s,w),d(Me,w,null),e(w,cn),e(w,ft),e(w,gn),e(w,vt),e(s,_n),e(s,Q),d(Ee,Q,null),e(Q,fn),e(Q,bt),e(s,vn),e(s,X),d(He,X,null),e(X,bn),e(X,ht),e(s,hn),e(s,L),d(Ae,L,null),e(L,$n),e(L,$t),e(L,xn),e(L,xt),e(s,Tn),e(s,Z),d(Ve,Z,null),e(Z,yn),e(Z,Tt),e(s,Nn),e(s,ee),d(Se,ee,null),e(ee,Cn),e(ee,yt),T(t,St,h),T(t,zt,h),Ft=!0},p:_a,i(t){Ft||(c(re.$$.fragment,t),c(ne.$$.fragment,t),c(oe.$$.fragment,t),c(se.$$.fragment,t),c(ie.$$.fragment,t),c(le.$$.fragment,t),c(me.$$.fragment,t),c(ue.$$.fragment,t),c(pe.$$.fragment,t),c(de.$$.fragment,t),c(ce.$$.fragment,t),c(ge.$$.fragment,t),c(_e.$$.fragment,t),c(fe.$$.fragment,t),c(ve.$$.fragment,t),c(be.$$.fragment,t),c(he.$$.fragment,t),c($e.$$.fragment,t),c(xe.$$.fragment,t),c(Te.$$.fragment,t),c(ye.$$.fragment,t),c(Ne.$$.fragment,t),c(Ce.$$.fragment,t),c(ke.$$.fragment,t),c(we.$$.fragment,t),c(Le.$$.fragment,t),c(ze.$$.fragment,t),c(De.$$.fragment,t),c(Pe.$$.fragment,t),c(Ie.$$.fragment,t),c(Me.$$.fragment,t),c(Ee.$$.fragment,t),c(He.$$.fragment,t),c(Ae.$$.fragment,t),c(Ve.$$.fragment,t),c(Se.$$.fragment,t),Ft=!0)},o(t){g(re.$$.fragment,t),g(ne.$$.fragment,t),g(oe.$$.fragment,t),g(se.$$.fragment,t),g(ie.$$.fragment,t),g(le.$$.fragment,t),g(me.$$.fragment,t),g(ue.$$.fragment,t),g(pe.$$.fragment,t),g(de.$$.fragment,t),g(ce.$$.fragment,t),g(ge.$$.fragment,t),g(_e.$$.fragment,t),g(fe.$$.fragment,t),g(ve.$$.fragment,t),g(be.$$.fragment,t),g(he.$$.fragment,t),g($e.$$.fragment,t),g(xe.$$.fragment,t),g(Te.$$.fragment,t),g(ye.$$.fragment,t),g(Ne.$$.fragment,t),g(Ce.$$.fragment,t),g(ke.$$.fragment,t),g(we.$$.fragment,t),g(Le.$$.fragment,t),g(ze.$$.fragment,t),g(De.$$.fragment,t),g(Pe.$$.fragment,t),g(Ie.$$.fragment,t),g(Me.$$.fragment,t),g(Ee.$$.fragment,t),g(He.$$.fragment,t),g(Ae.$$.fragment,t),g(Ve.$$.fragment,t),g(Se.$$.fragment,t),Ft=!1},d(t){t&&(l(Dt),l(Lt),l(Pt),l(It),l(Mt),l(ae),l(Et),l(Ht),l($),l(At),l(Vt),l(s),l(St),l(zt)),l(D),_(re,t),_(ne,t),_(oe,t),_(se),_(ie),_(le),_(me),_(ue),_(pe),_(de,t),_(ce),_(ge),_(_e),_(fe),_(ve),_(be),_(he),_($e),_(xe),_(Te),_(ye),_(Ne),_(Ce),_(ke),_(we),_(Le),_(ze),_(De),_(Pe),_(Ie),_(Me),_(Ee),_(He),_(Ae),_(Ve),_(Se)}}}const Ta='{"title":"NeuronTrainer","local":"neurontrainer","sections":[{"title":"NeuronTrainingArguments","local":"optimum.neuron.NeuronTrainingArguments","sections":[],"depth":2},{"title":"NeuronTrainer","local":"optimum.neuron.NeuronTrainer","sections":[],"depth":2}],"depth":1}';function ya(wn){return fa(()=>{new URLSearchParams(window.location.search).get("fw")}),[]}class za extends va{constructor(D){super(),ba(this,D,ya,xa,ga,{})}}export{za as component};