Pi ddlZddlmZddlZddlmZddlmZmZmZddl m Z m Z m Z m Z ddlmZddlmZedZ dd eeefd ed dfd Zddejd ed ejfdZdS)N)Union)nn)TransformerCrossAttentionLayerTransformerDecoderTransformerSelfAttentionLayer)CEWithChunkedOutputLossForwardKLWithChunkedOutputLossReverseKLWithChunkedOutputLoss SymmetricKLWithChunkedOutputLoss)DeepFusionModel) get_loggerINFOTmodelverbosereturnctjdd}t|tr|j}|rt dtt| D]B}t|tst|tr| |CdS)a Utility to compile a transformer model inplace. On PyTorch nightlies we use per-layer compile to reduce compile times. Otherwise we compile the full model, which takes longer. Args: model (Union[TransformerDecoder, DeepFusionModel]): A model to compile. Can be a TransformerDecoder or DeepFusionModel; in the latter case only the model's decoder will be compiled. verbose (bool): Whether to log compile info. Default: True Returns: None TORCH_COMPILE_BACKENDinductorz,Compiling model layers with torch.compile...backendN)osenvironget isinstancer decoderloginforeversedlistmodulesrrcompile)rrrms o/home/jaya/work/projects/VOICE-AGENT/VIET/agent-env/lib/python3.11/site-packages/torchtune/training/_compile.py compile_modelr$s"jnn4jAAG%)) A ?@@@ d5==??++ , ,'' a6 7 7 ': -< <  ' IIgI & & & ''losscZtjdd}|rtdt |t r!tj|j ||_ nt |tr!tj|j ||_ nt |tr!tj|j ||_ nLt |tr!tj|j||_ntj||}|S)a0 Utility to compile and return loss function. If the loss function is chunked cross-entropy, we only compile the upcast + cross-entropy calculation, not the chunking. For other losses we compile the entire loss function. Args: loss (nn.Module): A loss function to compile. verbose (bool): Whether to log compile info. Default: True Returns: loss (nn.Module): loss with either entire module compiled or (in the case of CEWithChunkedOutputLoss) only the upcast and cross-entropy calculation compiled. rrz$Compiling loss with torch.compile...r)rrrrrrrtorchr!compute_cross_entropyr fkl_lossr rkl_lossr sym_kl_loss)r&rrs r# compile_lossr-<sjnn4jAAG9 7888$/00 4%*]  && & & "" D8 9 94 dmWEEE D8 9 94 dmWEEE D: ; ;4 =)97KKK}T7333 Kr%)T)rtypingrr(rtorchtune.modulesrrrtorchtune.modules.lossrr r r torchtune.modules.model_fusionr torchtune.utilsr rboolr$Moduler-r%r#r6s_    ;:::::&&&&&&j '' #_4 5' ' ''''<ry429r%