o ?߱iA@s@ddlZddlZddlZddlmZmZGdddejj Z dS)N) distributedlogcsJeZdZdZ         dfdd Zdd d Zfd dZZS) FusedAdama Implements Adam algorithm. Currently GPU-only. Requires Apex to be installed via ``pip install -v --no-cache-dir --global-option="--cpp_ext" --global-option="--cuda_ext" ./``. This version of fused Adam implements 2 fusions. * Fusion of the Adam update's elementwise operations * A multi-tensor apply launch that batches the elementwise updates applied to all the model's parameters into one or a few kernel launches. :class:`FusedAdam` may be used as a drop-in replacement for ``torch.optim.AdamW``, or ``torch.optim.Adam`` with ``adam_w_mode=False``:: opt = FusedAdam(model.parameters(), lr = ....) ... opt.step() .. warning:: A previous version of :class:`FusedAdam` allowed a number of additional arguments to ``step``. These additional arguments are now deprecated and unnecessary. Adam was been proposed in `Adam: A Method for Stochastic Optimization`_. Arguments: params (iterable): iterable of parameters to optimize or dicts defining parameter groups. lr (float, optional): learning rate. (default: 1e-3) betas (Tuple[float, float], optional): coefficients used for computing running averages of gradient and its square. (default: (0.9, 0.999)) eps (float, optional): term added to the denominator to improve numerical stability. (default: 1e-8) weight_decay (float, optional): weight decay (L2 penalty) (default: 0) amsgrad (boolean, optional): whether to use the AMSGrad variant of this algorithm from the paper `On the Convergence of Adam and Beyond`_ (default: False) NOT SUPPORTED in FusedAdam! adam_w_mode (boolean, optional): Apply L2 regularization or weight decay True for decoupled weight decay(also known as AdamW) (default: True) capturable (bool, optional): whether to use the version of the optimizer that can be used with CUDA Graphs. (default: False) master_weights (bool, optional): whether to maintain FP32 master weights in the optimizer with FP16 mixed precision training, currently can only be used with capturable set to True. (default: False) .. _Adam - A Method for Stochastic Optimization: https://arxiv.org/abs/1412.6980 .. _On the Convergence of Adam and Beyond: https://openreview.net/forum?id=ryQu7f-RZ MbP?Tg?g+?:0yE>Fc sH|rtd| r| stdtd| d| | r#tj|tjdn|}t|||||d} tt| || |r;dnd|_ | |_ | |_ d|_ | rt|jD]9\} } t| d dkr[qN| d dj}d D]"}t| |trytj| |tjd| |<| |j|d |j| |<qdqNd |_tjdgtjd d|_tj|_tj|_tj|_dS)Nz/FusedAdam does not support the AMSGrad variant.zGMaster weights is currently only supported with the capturable version.zFusedAdam master_weights: z capturable: dtype)lrbias_correctionbetaseps weight_decayrparams)r deviceTcudar r) RuntimeErrorrwarningtorchtensorfloat32dictsuperr__init__ adam_w_mode capturablemaster_weightsparam_groups_master enumerate param_groupslenr isinstancefloatto_step_supports_amp_scalingint_dummy_overflow_buftexmulti_tensor_adammulti_tensor_adam_capturable#multi_tensor_adam_capturable_master)selfrr r r rrramsgradrr defaultsidxgroupritem __class__Z/data/cameron/vidgen/cosmos-predict2.5/cosmos_predict2/_src/imaginaire/utils/fused_adam.pyrJs6  zFusedAdam.__init__Nc%shtdd||||fDrtdd}|dur|}jdur?g_tjD]\}} | d} jdfdd| Diq'tjjD]\} } t| ddkrTqF| ddj} d | vre| d red nd}| d \}}d | vrj rt | d t j r| d j | d n t j| d t j| d| d <| d jd k t j7<n| d d 7<nj sd n t jd gt j| d| d <j rt | dt j r| dj | d n t j| dt j| d| d<ggggf\}}}}ggggf\}}}}ggggf\}}}}g}g}g}t| d| dD]\} }!| jdurq| jjjrtdj| }"t|"dkr>t | j|"d<t | j|"d<| jt jkrljrO||!j|| jj|| j||"d||"dq| jt jkrjr}||!j|| j|| ||"d||"dq| jt jkrƈjr||!j|| jj|| j||"d||"dqtdj r|dur|| nt jd| d }#j|#d\}}$|r| }|!"}$nt j#d| t jd}t j#d| t jd}$t|dkrGt$j%j&'jrj(nj)jjr.|||||gn||||g| d||| d| d j*|| d|$ t|dkrt$j%j&'jrYj(nj)jjrh|||||gn||||g| d||| d| d j*|| d|$ t|dkrt$j%j&'jrj(nj)jjr|||||gn||||g| d||| d| d j*|| d|$ qFt|dkrt$j%j&'j+j||||g| d||| d| d j*|| d t|dkr t$j%j&'j+j||||g| d||| d| d j*|| d t|dkr1t$j%j&'j+j||||g| d||| d| d j*|| d qF|S)a+Performs a single optimization step. Arguments: closure (callable, optional): A closure that reevaluates the model and returns the loss. The remaining arguments are deprecated, and are only retained (for the moment) for error-checking purposes. css|]}|duVqdSNr7.0pr7r7r8 sz!FusedAdam.step..ztFusedAdam has been updated. Simply initialize it identically to torch.optim.Adam, and call step() with no arguments.Nrcs&g|]}jr|ndqSr9)r clonedetachr&r:r/r7r8 s&z"FusedAdam.step..rr rr steprrr zOFusedAdam does not support sparse gradients, please consider SparseAdam insteadexp_avg exp_avg_sqz%FusedAdam only support fp16 and fp32.)r)NN)rr rr),anyrr!r"r#appendzipr$rrr%rTensorr'rint32r*r)rgraddata is_sparsestate zeros_liker&r float16r bfloat16_check_inf_per_devicezeroscopy__get_scale_asyncdouble reciprocalonestepytorch optimizersmulti_tensor_applierr.r-rr,)%r/closuregrads output_paramsscaleZ grad_norms grad_scalerlossipg param_listr3 group_masterrr beta1beta2Zg_16Zp_16Zm_16Zv_16Zg_bfZp_bfZm_bfZv_bfZg_32Zp_32Zm_32Zv_32Z p_16_masterZ p_32_masterZ bf16_masterr<p_masterrM found_inf inv_scaler7r@r8rBysl    "                      zFusedAdam.stepcs6t||jD]}|jr*t|dtjr|dn tj|dtj d|d<d|vrx|jrht dkrSt|dtjrE|dn tj|dgtj d}n tj dtj d}t |d||d<nt|dtjrx|d|d<|dD]}|j|}d|vr|d|d<|d|d<q|q dS) Nr r rBrrrrCrD)rload_state_dictr#rr%rrHrrrrget_rankrIrR broadcastr4rMr&)r/ state_dictr3rBr<rMr5r7r8rkbs6       zFusedAdam.load_state_dict) rTrrTrFFF)NNNNNN)__name__ __module__ __qualname____doc__rrBrk __classcell__r7r7r5r8rs5 /jr) rtransformer_enginerXtransformer_engine_torchr+%cosmos_predict2._src.imaginaire.utilsrroptim Optimizerrr7r7r7r8s