import{s as pt,n as ct,o as dt}from"../chunks/scheduler.b9285784.js";import{S as mt,i as gt,e as i,s as r,c as p,h as ut,a as s,d as t,b as n,f as _,g as c,j as v,k as h,l,m as o,n as d,t as m,o as g,p as u}from"../chunks/index.26bc89a1.js";import{C as ft,H as N,E as _t}from"../chunks/MermaidChart.svelte_svelte_type_style_lang.e364eac2.js";import{D as b}from"../chunks/Docstring.43e9d871.js";function ht(Xe){let D,de,pe,me,W,ge,T,ue,k,fe,L,_e,x,I,Re,X,Ye="Returns the currently active DeepSpeedPlugin.",he,f,M,Ae,Y,et="This plugin is used to integrate DeepSpeed.",qe,P,V,Fe,ee,tt="Process the DeepSpeed config with the values from the kwargs.",Ze,O,R,je,te,at="Sets the HfDeepSpeedWeakref to use the current deepspeed plugin configuration",$e,S,A,He,ae,rt=`Dummy scheduler presents model parameters or param groups, this is primarily used to follow conventional training
loop when scheduler config is specified in the deepspeed config file.`,ve,q,be,$,F,Be,re,nt="Internal wrapper for deepspeed.runtime.engine.DeepSpeedEngine. This is used to follow conventional training loop.",Ge,C,Z,Je,ne,ot="Get the global gradient norm from DeepSpeed engine.",De,j,xe,y,H,Qe,oe,lt="Internal wrapper around a deepspeed optimizer.",Se,B,ye,w,G,Ue,le,it="Internal wrapper around a deepspeed scheduler.",we,J,ze,z,Q,Ke,ie,st=`Dummy optimizer presents model parameters or param groups, this is primarily used to follow conventional training
loop when optimizer config is specified in the deepspeed config file.`,Pe,U,Oe,K,Ce,ce,Ee;return W=new ft({props:{containerStyle:"float: right; margin-left: 10px; display: inline-flex; position: relative; z-index: 10;"}}),T=new N({props:{title:"DeepSpeed utilities",local:"deepspeed-utilities",headingTag:"h1"}}),k=new N({props:{title:"DeepSpeedPlugin",local:"deepspeedplugin",headingTag:"h2"}}),L=new N({props:{title:"get_active_deepspeed_plugin",local:"accelerate.utils.get_active_deepspeed_plugin",headingTag:"h2"}}),I=new b({props:{name:"accelerate.utils.get_active_deepspeed_plugin",anchor:"accelerate.utils.get_active_deepspeed_plugin",parameters:[{name:"state",val:""}],source:"https://github.com/huggingface/accelerate/blob/main/src/accelerate/utils/deepspeed.py#L100",raiseDescription:`<script context="module">export const metadata = 'undefined';<\/script>


<ul>
<li><code>ValueError</code> — If DeepSpeed was not enabled and this function is called.</li>
</ul>
`,raiseType:`<script context="module">export const metadata = 'undefined';<\/script>


<p><code>ValueError</code></p>
`}}),M=new b({props:{name:"class accelerate.DeepSpeedPlugin",anchor:"accelerate.DeepSpeedPlugin",parameters:[{name:"hf_ds_config",val:": typing.Any = None"},{name:"gradient_accumulation_steps",val:": int = None"},{name:"gradient_clipping",val:": float = None"},{name:"zero_stage",val:": int = None"},{name:"is_train_batch_min",val:": bool = True"},{name:"offload_optimizer_device",val:": str = None"},{name:"offload_param_device",val:": str = None"},{name:"offload_optimizer_nvme_path",val:": str = None"},{name:"offload_param_nvme_path",val:": str = None"},{name:"zero3_init_flag",val:": bool = None"},{name:"zero3_save_16bit_model",val:": bool = None"},{name:"transformer_moe_cls_names",val:": str = None"},{name:"enable_msamp",val:": bool = None"},{name:"msamp_opt_level",val:": typing.Optional[typing.Literal['O1', 'O2']] = None"}],parametersDescription:[{anchor:"accelerate.DeepSpeedPlugin.hf_ds_config",description:`<strong>hf_ds_config</strong> (<code>Any</code>, defaults to <code>None</code>) &#x2014;
Path to DeepSpeed config file or dict or an object of class <code>accelerate.utils.deepspeed.HfDeepSpeedConfig</code>.`,name:"hf_ds_config"},{anchor:"accelerate.DeepSpeedPlugin.gradient_accumulation_steps",description:`<strong>gradient_accumulation_steps</strong> (<code>int</code>, defaults to <code>None</code>) &#x2014;
Number of steps to accumulate gradients before updating optimizer states. If not set, will use the value
from the <code>Accelerator</code> directly.`,name:"gradient_accumulation_steps"},{anchor:"accelerate.DeepSpeedPlugin.gradient_clipping",description:`<strong>gradient_clipping</strong> (<code>float</code>, defaults to <code>None</code>) &#x2014;
Enable gradient clipping with value.`,name:"gradient_clipping"},{anchor:"accelerate.DeepSpeedPlugin.zero_stage",description:`<strong>zero_stage</strong> (<code>int</code>, defaults to <code>None</code>) &#x2014;
Possible options are 0, 1, 2, 3. Default will be taken from environment variable.`,name:"zero_stage"},{anchor:"accelerate.DeepSpeedPlugin.is_train_batch_min",description:`<strong>is_train_batch_min</strong> (<code>bool</code>, defaults to <code>True</code>) &#x2014;
If both train &amp; eval dataloaders are specified, this will decide the <code>train_batch_size</code>.`,name:"is_train_batch_min"},{anchor:"accelerate.DeepSpeedPlugin.offload_optimizer_device",description:`<strong>offload_optimizer_device</strong> (<code>str</code>, defaults to <code>None</code>) &#x2014;
Possible options are none|cpu|nvme. Only applicable with ZeRO Stages 2 and 3.`,name:"offload_optimizer_device"},{anchor:"accelerate.DeepSpeedPlugin.offload_param_device",description:`<strong>offload_param_device</strong> (<code>str</code>, defaults to <code>None</code>) &#x2014;
Possible options are none|cpu|nvme. Only applicable with ZeRO Stage 3.`,name:"offload_param_device"},{anchor:"accelerate.DeepSpeedPlugin.offload_optimizer_nvme_path",description:`<strong>offload_optimizer_nvme_path</strong> (<code>str</code>, defaults to <code>None</code>) &#x2014;
Possible options are /nvme|/local_nvme. Only applicable with ZeRO Stage 3.`,name:"offload_optimizer_nvme_path"},{anchor:"accelerate.DeepSpeedPlugin.offload_param_nvme_path",description:`<strong>offload_param_nvme_path</strong> (<code>str</code>, defaults to <code>None</code>) &#x2014;
Possible options are /nvme|/local_nvme. Only applicable with ZeRO Stage 3.`,name:"offload_param_nvme_path"},{anchor:"accelerate.DeepSpeedPlugin.zero3_init_flag",description:`<strong>zero3_init_flag</strong> (<code>bool</code>, defaults to <code>None</code>) &#x2014;
Flag to indicate whether to save 16-bit model. Only applicable with ZeRO Stage-3.`,name:"zero3_init_flag"},{anchor:"accelerate.DeepSpeedPlugin.zero3_save_16bit_model",description:`<strong>zero3_save_16bit_model</strong> (<code>bool</code>, defaults to <code>None</code>) &#x2014;
Flag to indicate whether to save 16-bit model. Only applicable with ZeRO Stage-3.`,name:"zero3_save_16bit_model"},{anchor:"accelerate.DeepSpeedPlugin.transformer_moe_cls_names",description:`<strong>transformer_moe_cls_names</strong> (<code>str</code>, defaults to <code>None</code>) &#x2014;
Comma-separated list of Transformers MoE layer class names (case-sensitive). For example,
<code>MixtralSparseMoeBlock</code>, <code>Qwen2MoeSparseMoeBlock</code>, <code>JetMoEAttention</code>, <code>JetMoEBlock</code>, etc.`,name:"transformer_moe_cls_names"},{anchor:"accelerate.DeepSpeedPlugin.enable_msamp",description:`<strong>enable_msamp</strong> (<code>bool</code>, defaults to <code>None</code>) &#x2014;
Flag to indicate whether to enable MS-AMP backend for FP8 training.`,name:"enable_msamp"},{anchor:"accelerate.DeepSpeedPlugin.msasmp_opt_level",description:`<strong>msasmp_opt_level</strong> (<code>Optional[Literal[&quot;O1&quot;, &quot;O2&quot;]]</code>, defaults to <code>None</code>) &#x2014;
Optimization level for MS-AMP (defaults to &#x2018;O1&#x2019;). Only applicable if <code>enable_msamp</code> is True. Should be one
of [&#x2018;O1&#x2019; or &#x2018;O2&#x2019;].`,name:"msasmp_opt_level"}],source:"https://github.com/huggingface/accelerate/blob/main/src/accelerate/utils/dataclasses.py#L1086"}}),V=new b({props:{name:"deepspeed_config_process",anchor:"accelerate.DeepSpeedPlugin.deepspeed_config_process",parameters:[{name:"prefix",val:" = ''"},{name:"mismatches",val:" = None"},{name:"config",val:" = None"},{name:"must_match",val:" = True"},{name:"**kwargs",val:""}],source:"https://github.com/huggingface/accelerate/blob/main/src/accelerate/utils/dataclasses.py#L1355"}}),R=new b({props:{name:"select",anchor:"accelerate.DeepSpeedPlugin.select",parameters:[{name:"_from_accelerator_state",val:": bool = False"}],source:"https://github.com/huggingface/accelerate/blob/main/src/accelerate/utils/dataclasses.py#L1506"}}),A=new b({props:{name:"class accelerate.utils.DummyScheduler",anchor:"accelerate.utils.DummyScheduler",parameters:[{name:"optimizer",val:""},{name:"total_num_steps",val:" = None"},{name:"warmup_num_steps",val:" = 0"},{name:"lr_scheduler_callable",val:" = None"},{name:"**kwargs",val:""}],parametersDescription:[{anchor:"accelerate.utils.DummyScheduler.optimizer",description:`<strong>optimizer</strong> (<code>torch.optim.optimizer.Optimizer</code>) &#x2014;
The optimizer to wrap.`,name:"optimizer"},{anchor:"accelerate.utils.DummyScheduler.total_num_steps",description:`<strong>total_num_steps</strong> (int, <em>optional</em>) &#x2014;
Total number of steps.`,name:"total_num_steps"},{anchor:"accelerate.utils.DummyScheduler.warmup_num_steps",description:`<strong>warmup_num_steps</strong> (int, <em>optional</em>) &#x2014;
Number of steps for warmup.`,name:"warmup_num_steps"},{anchor:"accelerate.utils.DummyScheduler.lr_scheduler_callable",description:`<strong>lr_scheduler_callable</strong> (callable, <em>optional</em>) &#x2014;
A callable function that creates an LR Scheduler. It accepts only one argument <code>optimizer</code>.`,name:"lr_scheduler_callable"},{anchor:"accelerate.utils.DummyScheduler.*kwargs",description:`*<strong>*kwargs</strong> (additional keyword arguments, <em>optional</em>) &#x2014;
Other arguments.`,name:"*kwargs"}],source:"https://github.com/huggingface/accelerate/blob/main/src/accelerate/utils/deepspeed.py#L362"}}),q=new N({props:{title:"DeepSpeedEnginerWrapper",local:"accelerate.utils.DeepSpeedEngineWrapper",headingTag:"h2"}}),F=new b({props:{name:"class accelerate.utils.DeepSpeedEngineWrapper",anchor:"accelerate.utils.DeepSpeedEngineWrapper",parameters:[{name:"engine",val:""}],parametersDescription:[{anchor:"accelerate.utils.DeepSpeedEngineWrapper.engine",description:"<strong>engine</strong> (deepspeed.runtime.engine.DeepSpeedEngine) &#x2014; deepspeed engine to wrap",name:"engine"}],source:"https://github.com/huggingface/accelerate/blob/main/src/accelerate/utils/deepspeed.py#L253"}}),Z=new b({props:{name:"get_global_grad_norm",anchor:"accelerate.utils.DeepSpeedEngineWrapper.get_global_grad_norm",parameters:[],source:"https://github.com/huggingface/accelerate/blob/main/src/accelerate/utils/deepspeed.py#L286"}}),j=new N({props:{title:"DeepSpeedOptimizerWrapper",local:"accelerate.utils.DeepSpeedOptimizerWrapper",headingTag:"h2"}}),H=new b({props:{name:"class accelerate.utils.DeepSpeedOptimizerWrapper",anchor:"accelerate.utils.DeepSpeedOptimizerWrapper",parameters:[{name:"optimizer",val:""}],parametersDescription:[{anchor:"accelerate.utils.DeepSpeedOptimizerWrapper.optimizer",description:`<strong>optimizer</strong> (<code>torch.optim.optimizer.Optimizer</code>) &#x2014;
The optimizer to wrap.`,name:"optimizer"}],source:"https://github.com/huggingface/accelerate/blob/main/src/accelerate/utils/deepspeed.py#L295"}}),B=new N({props:{title:"DeepSpeedSchedulerWrapper",local:"accelerate.utils.DeepSpeedSchedulerWrapper",headingTag:"h2"}}),G=new b({props:{name:"class accelerate.utils.DeepSpeedSchedulerWrapper",anchor:"accelerate.utils.DeepSpeedSchedulerWrapper",parameters:[{name:"scheduler",val:""},{name:"optimizers",val:""}],parametersDescription:[{anchor:"accelerate.utils.DeepSpeedSchedulerWrapper.scheduler",description:`<strong>scheduler</strong> (<code>torch.optim.lr_scheduler.LambdaLR</code>) &#x2014;
The scheduler to wrap.`,name:"scheduler"},{anchor:"accelerate.utils.DeepSpeedSchedulerWrapper.optimizers",description:"<strong>optimizers</strong> (one or a list of <code>torch.optim.Optimizer</code>) &#x2014;",name:"optimizers"}],source:"https://github.com/huggingface/accelerate/blob/main/src/accelerate/utils/deepspeed.py#L322"}}),J=new N({props:{title:"DummyOptim",local:"accelerate.utils.DummyOptim",headingTag:"h2"}}),Q=new b({props:{name:"class accelerate.utils.DummyOptim",anchor:"accelerate.utils.DummyOptim",parameters:[{name:"params",val:""},{name:"lr",val:" = 0.001"},{name:"weight_decay",val:" = 0"},{name:"**kwargs",val:""}],parametersDescription:[{anchor:"accelerate.utils.DummyOptim.lr",description:`<strong>lr</strong> (float) &#x2014;
Learning rate.`,name:"lr"},{anchor:"accelerate.utils.DummyOptim.params",description:`<strong>params</strong> (iterable) &#x2014; iterable of parameters to optimize or dicts defining
parameter groups`,name:"params"},{anchor:"accelerate.utils.DummyOptim.weight_decay",description:`<strong>weight_decay</strong> (float) &#x2014;
Weight decay.`,name:"weight_decay"},{anchor:"accelerate.utils.DummyOptim.*kwargs",description:`*<strong>*kwargs</strong> (additional keyword arguments, <em>optional</em>) &#x2014;
Other arguments.`,name:"*kwargs"}],source:"https://github.com/huggingface/accelerate/blob/main/src/accelerate/utils/deepspeed.py#L339"}}),U=new N({props:{title:"DummyScheduler",local:"dummyscheduler",headingTag:"h2"}}),K=new 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