32fa5cfaf3
* fix gpu init after removing debug print in mpu Signed-off-by: ericharper <complex451@gmail.com> * add fused_adam Signed-off-by: ericharper <complex451@gmail.com> * check ds is not none before logging len Signed-off-by: ericharper <complex451@gmail.com> * set fp16 arg to true and fix enum conflict Signed-off-by: ericharper <complex451@gmail.com> * make fp16 arg configurable Signed-off-by: ericharper <complex451@gmail.com> * add grad clip from megatron Signed-off-by: ericharper <complex451@gmail.com> * Linear warmup with cosine annealing and constant holding (#2846) * Testing cosine schedule Signed-off-by: MaximumEntropy <sandeep.subramanian.1@umontreal.ca> * Style fixes Signed-off-by: MaximumEntropy <sandeep.subramanian.1@umontreal.ca> * Fixes Signed-off-by: MaximumEntropy <sandeep.subramanian.1@umontreal.ca> * More fixes Signed-off-by: MaximumEntropy <sandeep.subramanian.1@umontreal.ca> * update config for constant steps in schedule Signed-off-by: ericharper <complex451@gmail.com> * temporarily import enum from megatron Signed-off-by: ericharper <complex451@gmail.com> * add grad clip for fp32 Signed-off-by: ericharper <complex451@gmail.com> * update check for _del_model_without_trainer Signed-off-by: ericharper <complex451@gmail.com> * updating restore for model parallel Signed-off-by: ericharper <complex451@gmail.com> * add predict script Signed-off-by: ericharper <complex451@gmail.com> * update test iters Signed-off-by: ericharper <complex451@gmail.com> * add barrier Signed-off-by: ericharper <complex451@gmail.com> * return if clip_val is 0 or None Signed-off-by: ericharper <complex451@gmail.com> * when using amp clip grads after they are unscaled Signed-off-by: ericharper <complex451@gmail.com> * make native amp scaler hyperparams configurable Signed-off-by: ericharper <complex451@gmail.com> * (1) nvfuser, (2) amp-casting decoration (#2894) * (1) nvfuser, (2) amp-casting decoration Signed-off-by: Sangkug Lym <slym@nvidia.com> * support bf16 Signed-off-by: Sangkug Lym <slym@nvidia.com> * update package info Signed-off-by: ericharper <complex451@gmail.com> * add set device to constructor Signed-off-by: ericharper <complex451@gmail.com> * set_device in constructor Signed-off-by: ericharper <complex451@gmail.com> * [BigNLP] Remove megatron-lm dependency. (#2910) * remove args Signed-off-by: ericharper <complex451@gmail.com> * remove args Signed-off-by: ericharper <complex451@gmail.com> * remove args Signed-off-by: ericharper <complex451@gmail.com> * remove args Signed-off-by: ericharper <complex451@gmail.com> * remove args in progress Signed-off-by: ericharper <complex451@gmail.com> * remove args in progress Signed-off-by: ericharper <complex451@gmail.com> * remove args in progress Signed-off-by: ericharper <complex451@gmail.com> * remove args in progress Signed-off-by: ericharper <complex451@gmail.com> * add load_fused_kernels Signed-off-by: ericharper <complex451@gmail.com> * add load_fused_kernels Signed-off-by: ericharper <complex451@gmail.com> * update megatron_init Signed-off-by: ericharper <complex451@gmail.com> * add fused kernels Signed-off-by: ericharper <complex451@gmail.com> * add fused kernels Signed-off-by: ericharper <complex451@gmail.com> * update process batch Signed-off-by: ericharper <complex451@gmail.com> * remove erroneous import Signed-off-by: ericharper <complex451@gmail.com> * remove erroneous import Signed-off-by: ericharper <complex451@gmail.com> * remove erroneous import Signed-off-by: ericharper <complex451@gmail.com> * add megatron clip_grad Signed-off-by: ericharper <complex451@gmail.com> * trying to resolve circular import error Signed-off-by: ericharper <complex451@gmail.com> * rename file Signed-off-by: ericharper <complex451@gmail.com> * remove non-gpt models and datasets from __init__ files Signed-off-by: ericharper <complex451@gmail.com> * set device in constructorfor gpu init Signed-off-by: ericharper <complex451@gmail.com> * set device in constructorfor gpu init Signed-off-by: ericharper <complex451@gmail.com> * set_device in constructor Signed-off-by: ericharper <complex451@gmail.com> * clean config Signed-off-by: ericharper <complex451@gmail.com> * update MegatronDataset Signed-off-by: ericharper <complex451@gmail.com> * clean up MegatronModule Signed-off-by: ericharper <complex451@gmail.com> * clean up MegatronModule Signed-off-by: ericharper <complex451@gmail.com> * rename fp16 and bf16 flags to fused_softmax_input_in_fp16/bf16 Signed-off-by: ericharper <complex451@gmail.com> * rename to fused_fp16 Signed-off-by: ericharper <complex451@gmail.com> * add fused_fp16 arg to LayerNorm calls Signed-off-by: ericharper <complex451@gmail.com> * fix arg name Signed-off-by: ericharper <complex451@gmail.com> * fix arg name Signed-off-by: ericharper <complex451@gmail.com> * fix import Signed-off-by: ericharper <complex451@gmail.com> * update arg Signed-off-by: ericharper <complex451@gmail.com> * skip warmup default to True Signed-off-by: ericharper <complex451@gmail.com> * skip warmup default to True Signed-off-by: ericharper <complex451@gmail.com> * Adding complete method to MegatronGPTModel (#2935) Signed-off-by: Oleksii Kuchaiev <okuchaiev@nvidia.com> * make ffn_hidden_size mandatory Signed-off-by: ericharper <complex451@gmail.com> * Manually migrating timing of step into branch (#2937) * 1. Manually migrating timing of step into branch. Signed-off-by: Micha Livne <mlivne@nvidia.com> * 1. Updated file name and content. Signed-off-by: Micha Livne <mlivne@nvidia.com> * 1. Updated to latest code. Signed-off-by: Micha Livne <mlivne@nvidia.com> Co-authored-by: Micha Livne <mlivne@nvidia.com> * remove unused imports Signed-off-by: ericharper <complex451@gmail.com> * remove unused import Signed-off-by: ericharper <complex451@gmail.com> * remove unused import Signed-off-by: ericharper <complex451@gmail.com> * remove unused import Signed-off-by: ericharper <complex451@gmail.com> * check fused_fp16 and fused_bf16 are not both True Signed-off-by: ericharper <complex451@gmail.com> * update predict script for model parallel .nemo Signed-off-by: ericharper <complex451@gmail.com> * typo Signed-off-by: ericharper <complex451@gmail.com> * typo Signed-off-by: ericharper <complex451@gmail.com> Co-authored-by: Oleksii Kuchaiev <okuchaiev@users.noreply.github.com> Co-authored-by: Micha Livne <michalivne@users.noreply.github.com> Co-authored-by: Micha Livne <mlivne@nvidia.com> * NVfuser (#2943) * activation checkpoint recompute Signed-off-by: Sangkug Lym <slym@nvidia.com> * selective nvfuser setup * Megatron gpt bfloat support (#2926) * Save/restore fix Signed-off-by: MaximumEntropy <sandeep.subramanian.1@umontreal.ca> * Another merge Signed-off-by: MaximumEntropy <sandeep.subramanian.1@umontreal.ca> * Bf16 args in init Signed-off-by: MaximumEntropy <sandeep.subramanian.1@umontreal.ca> * Set precision Signed-off-by: MaximumEntropy <sandeep.subramanian.1@umontreal.ca> * Remove debug stuff Signed-off-by: MaximumEntropy <sandeep.subramanian.1@umontreal.ca> * add bf16 casting decorator Signed-off-by: Sangkug Lym <slym@nvidia.com> * Bfloat layernorm propagation Signed-off-by: MaximumEntropy <sandeep.subramanian.1@umontreal.ca> * activation checkpoint recompute Signed-off-by: Sangkug Lym <slym@nvidia.com> * selective nvfuser setup * More arg removal Signed-off-by: MaximumEntropy <sandeep.subramanian.1@umontreal.ca> * Remove BERTDataset Signed-off-by: MaximumEntropy <sandeep.subramanian.1@umontreal.ca> * update to latest apex and patch transformer autocast Signed-off-by: ericharper <complex451@gmail.com> Co-authored-by: Sangkug Lym <slym@nvidia.com> Co-authored-by: ericharper <complex451@gmail.com> * don't set jit for bf16 Signed-off-by: ericharper <complex451@gmail.com> * replace apex.mpu Signed-off-by: ericharper <complex451@gmail.com> * fix grad clip Signed-off-by: ericharper <complex451@gmail.com> * NVFuser fixes (#2951) * Fuser fixes Signed-off-by: MaximumEntropy <sandeep.subramanian.1@umontreal.ca> * Remove dummy handler Signed-off-by: MaximumEntropy <sandeep.subramanian.1@umontreal.ca> * Remove PTL plugin based logic for fusion Signed-off-by: MaximumEntropy <sandeep.subramanian.1@umontreal.ca> * remove duplicated file Signed-off-by: ericharper <complex451@gmail.com> * typo (#2960) Signed-off-by: ericharper <complex451@gmail.com> * [BigNLP] Script to convert GPT checkpoint to .nemo (#2958) * remove args Signed-off-by: ericharper <complex451@gmail.com> * remove args Signed-off-by: ericharper <complex451@gmail.com> * remove args Signed-off-by: ericharper <complex451@gmail.com> * remove args Signed-off-by: ericharper <complex451@gmail.com> * remove args in progress Signed-off-by: ericharper <complex451@gmail.com> * remove args in progress Signed-off-by: ericharper <complex451@gmail.com> * remove args in progress Signed-off-by: ericharper <complex451@gmail.com> * remove args in progress Signed-off-by: ericharper <complex451@gmail.com> * add load_fused_kernels Signed-off-by: ericharper <complex451@gmail.com> * add load_fused_kernels Signed-off-by: ericharper <complex451@gmail.com> * update megatron_init Signed-off-by: ericharper <complex451@gmail.com> * add fused kernels Signed-off-by: ericharper <complex451@gmail.com> * add fused kernels Signed-off-by: ericharper <complex451@gmail.com> * update process batch Signed-off-by: ericharper <complex451@gmail.com> * remove erroneous import Signed-off-by: ericharper <complex451@gmail.com> * remove erroneous import Signed-off-by: ericharper <complex451@gmail.com> * remove erroneous import Signed-off-by: ericharper <complex451@gmail.com> * add megatron clip_grad Signed-off-by: ericharper <complex451@gmail.com> * trying to resolve circular import error Signed-off-by: ericharper <complex451@gmail.com> * rename file Signed-off-by: ericharper <complex451@gmail.com> * remove non-gpt models and datasets from __init__ files Signed-off-by: ericharper <complex451@gmail.com> * set device in constructorfor gpu init Signed-off-by: ericharper <complex451@gmail.com> * set device in constructorfor gpu init Signed-off-by: ericharper <complex451@gmail.com> * set_device in constructor Signed-off-by: ericharper <complex451@gmail.com> * clean config Signed-off-by: ericharper <complex451@gmail.com> * update MegatronDataset Signed-off-by: ericharper <complex451@gmail.com> * clean up MegatronModule Signed-off-by: ericharper <complex451@gmail.com> * clean up MegatronModule Signed-off-by: ericharper <complex451@gmail.com> * rename fp16 and bf16 flags to fused_softmax_input_in_fp16/bf16 Signed-off-by: ericharper <complex451@gmail.com> * rename to fused_fp16 Signed-off-by: ericharper <complex451@gmail.com> * add fused_fp16 arg to LayerNorm calls Signed-off-by: ericharper <complex451@gmail.com> * fix arg name Signed-off-by: ericharper <complex451@gmail.com> * fix arg name Signed-off-by: ericharper <complex451@gmail.com> * fix import Signed-off-by: ericharper <complex451@gmail.com> * update arg Signed-off-by: ericharper <complex451@gmail.com> * skip warmup default to True Signed-off-by: ericharper <complex451@gmail.com> * skip warmup default to True Signed-off-by: ericharper <complex451@gmail.com> * Adding complete method to MegatronGPTModel (#2935) Signed-off-by: Oleksii Kuchaiev <okuchaiev@nvidia.com> * make ffn_hidden_size mandatory Signed-off-by: ericharper <complex451@gmail.com> * Manually migrating timing of step into branch (#2937) * 1. Manually migrating timing of step into branch. Signed-off-by: Micha Livne <mlivne@nvidia.com> * 1. Updated file name and content. Signed-off-by: Micha Livne <mlivne@nvidia.com> * 1. Updated to latest code. Signed-off-by: Micha Livne <mlivne@nvidia.com> Co-authored-by: Micha Livne <mlivne@nvidia.com> * remove unused imports Signed-off-by: ericharper <complex451@gmail.com> * remove unused import Signed-off-by: ericharper <complex451@gmail.com> * remove unused import Signed-off-by: ericharper <complex451@gmail.com> * remove unused import Signed-off-by: ericharper <complex451@gmail.com> * check fused_fp16 and fused_bf16 are not both True Signed-off-by: ericharper <complex451@gmail.com> * update predict script for model parallel .nemo Signed-off-by: ericharper <complex451@gmail.com> * typo Signed-off-by: ericharper <complex451@gmail.com> * add script to convert .ckpt to .nemo Signed-off-by: ericharper <complex451@gmail.com> * in progress Signed-off-by: ericharper <complex451@gmail.com> * update Signed-off-by: ericharper <complex451@gmail.com> * convert mp checkpoints to nemo Signed-off-by: ericharper <complex451@gmail.com> * update help Signed-off-by: ericharper <complex451@gmail.com> * add safeguard for model parallel save_to Signed-off-by: ericharper <complex451@gmail.com> * adjust NLPModel save_to to be safer for model parallel Signed-off-by: Oleksii Kuchaiev <okuchaiev@nvidia.com> Co-authored-by: Oleksii Kuchaiev <okuchaiev@users.noreply.github.com> Co-authored-by: Micha Livne <michalivne@users.noreply.github.com> Co-authored-by: Micha Livne <mlivne@nvidia.com> Co-authored-by: Oleksii Kuchaiev <okuchaiev@nvidia.com> * [BigNLP] Update GPT evaluation to work with tensor model parallel (#2959) * in progress Signed-off-by: ericharper <complex451@gmail.com> * update args Signed-off-by: ericharper <complex451@gmail.com> * add request dataset Signed-off-by: ericharper <complex451@gmail.com> * tokenize request Signed-off-by: ericharper <complex451@gmail.com> * in progress Signed-off-by: ericharper <complex451@gmail.com> * able to run Signed-off-by: ericharper <complex451@gmail.com> * reduce logits Signed-off-by: ericharper <complex451@gmail.com> * capture response Signed-off-by: ericharper <complex451@gmail.com> * squeeze and unsqueeze Signed-off-by: ericharper <complex451@gmail.com> * handle non model parallel case Signed-off-by: ericharper <complex451@gmail.com> * clean imports Signed-off-by: ericharper <complex451@gmail.com> * add file Signed-off-by: ericharper <complex451@gmail.com> * convert logits to log_probs Signed-off-by: Oleksii Kuchaiev <okuchaiev@nvidia.com> * rename logits to log_probs Signed-off-by: Oleksii Kuchaiev <okuchaiev@nvidia.com> Co-authored-by: Oleksii Kuchaiev <okuchaiev@nvidia.com> * add megatron gpt pretraining Signed-off-by: ericharper <complex451@gmail.com> * add megatron gpt pretraining Signed-off-by: ericharper <complex451@gmail.com> * add megatron gpt pretraining Signed-off-by: ericharper <complex451@gmail.com> * updating to work with latest megatron Signed-off-by: ericharper <complex451@gmail.com> * updating to work with latest megatron Signed-off-by: ericharper <complex451@gmail.com> * update _del_model Signed-off-by: ericharper <complex451@gmail.com> * adding gpt model Signed-off-by: ericharper <complex451@gmail.com> * adding gpt model Signed-off-by: ericharper <complex451@gmail.com> * adding gpt model Signed-off-by: ericharper <complex451@gmail.com> * instantiate GPTmodel Signed-off-by: ericharper <complex451@gmail.com> * adding build dataset Signed-off-by: ericharper <complex451@gmail.com> * build megatron dataset in .setup Signed-off-by: ericharper <complex451@gmail.com> * setup dataloader Signed-off-by: ericharper <complex451@gmail.com> * add vocab_file and merge_file to megatron init Signed-off-by: ericharper <complex451@gmail.com> * add forward Signed-off-by: ericharper <complex451@gmail.com> * add train loss Signed-off-by: ericharper <complex451@gmail.com> * add optimizer Signed-off-by: ericharper <complex451@gmail.com> * add exp_manager Signed-off-by: ericharper <complex451@gmail.com> * multi-gpu is working Signed-off-by: ericharper <complex451@gmail.com> * adding val loop Signed-off-by: ericharper <complex451@gmail.com> * style Signed-off-by: ericharper <complex451@gmail.com> * adding val loop Signed-off-by: ericharper <complex451@gmail.com> * fix ranks Signed-off-by: ericharper <complex451@gmail.com> * fix model parallel checkpoint saving Signed-off-by: ericharper <complex451@gmail.com> * fix _del_model Signed-off-by: ericharper <complex451@gmail.com> * added megatron batch sampler Signed-off-by: ericharper <complex451@gmail.com> * try to fix num steps Signed-off-by: ericharper <complex451@gmail.com> * add wandb to config Signed-off-by: ericharper <complex451@gmail.com> * log lr Signed-off-by: ericharper <complex451@gmail.com> * add warmup ratio to config Signed-off-by: ericharper <complex451@gmail.com> * update configs Signed-off-by: ericharper <complex451@gmail.com> * update configs Signed-off-by: ericharper <complex451@gmail.com> * add cpu init to args Signed-off-by: ericharper <complex451@gmail.com> * update config Signed-off-by: ericharper <complex451@gmail.com> * update config Signed-off-by: ericharper <complex451@gmail.com> * Initial megatron dataset port Signed-off-by: MaximumEntropy <sandeep.subramanian.1@umontreal.ca> * Fix merge conflicts Signed-off-by: MaximumEntropy <sandeep.subramanian.1@umontreal.ca> * License fixes and megatron model porting Signed-off-by: MaximumEntropy <sandeep.subramanian.1@umontreal.ca> * Style fixes Signed-off-by: MaximumEntropy <sandeep.subramanian.1@umontreal.ca> * More fixes to import from nemo rather than megatron Signed-off-by: MaximumEntropy <sandeep.subramanian.1@umontreal.ca> * Fix circular imports Signed-off-by: MaximumEntropy <sandeep.subramanian.1@umontreal.ca> * Style fixes Signed-off-by: MaximumEntropy <sandeep.subramanian.1@umontreal.ca> * Revert config file Signed-off-by: MaximumEntropy <sandeep.subramanian.1@umontreal.ca> * Restructure further to avoid circular imports Signed-off-by: MaximumEntropy <sandeep.subramanian.1@umontreal.ca> * add Makefile Signed-off-by: ericharper <complex451@gmail.com> * Add megatron modules Signed-off-by: MaximumEntropy <sandeep.subramanian.1@umontreal.ca> * add license Signed-off-by: ericharper <complex451@gmail.com> * Port from latest megatron Signed-off-by: MaximumEntropy <sandeep.subramanian.1@umontreal.ca> * update cfg Signed-off-by: ericharper <complex451@gmail.com> * update config Signed-off-by: ericharper <complex451@gmail.com> * add _del_model_without_trainer Signed-off-by: ericharper <complex451@gmail.com> * add data preprocessing script Signed-off-by: ericharper <complex451@gmail.com> * update config Signed-off-by: ericharper <complex451@gmail.com> * use apex mpu Signed-off-by: ericharper <complex451@gmail.com> * replace print_rank_0 with nemo utils logging Signed-off-by: ericharper <complex451@gmail.com> * use apex mpu Signed-off-by: ericharper <complex451@gmail.com> * use apex mpu Signed-off-by: ericharper <complex451@gmail.com> * add use_cpu_initialization Signed-off-by: ericharper <complex451@gmail.com> * fixing autoresume in progress Signed-off-by: ericharper <complex451@gmail.com> * properly removing last checkpoint Signed-off-by: ericharper <complex451@gmail.com> * log consumed samples Signed-off-by: ericharper <complex451@gmail.com> * fix mp autoresume Signed-off-by: ericharper <complex451@gmail.com> * add NLPSaveRestoreConnector Signed-off-by: ericharper <complex451@gmail.com> * Megatron GPT training with NeMo tokenizers (#2818) * Update files from megatron repo Signed-off-by: MaximumEntropy <sandeep.subramanian.1@umontreal.ca> * Remove non NLP data related files from megatron Signed-off-by: MaximumEntropy <sandeep.subramanian.1@umontreal.ca> * Merge megatron and nemo tokenizers Signed-off-by: MaximumEntropy <sandeep.subramanian.1@umontreal.ca> * Remove get_tokenizer() calls from gpt model Signed-off-by: MaximumEntropy <sandeep.subramanian.1@umontreal.ca> * Update tokenizer yaml config Signed-off-by: MaximumEntropy <sandeep.subramanian.1@umontreal.ca> * add todo Signed-off-by: ericharper <complex451@gmail.com> * update config Signed-off-by: ericharper <complex451@gmail.com> * make init_method_std configurable Signed-off-by: ericharper <complex451@gmail.com> * make gpu init work by setting random seed earlier Signed-off-by: ericharper <complex451@gmail.com> * fix gpu init after removing debug print in mpu Signed-off-by: ericharper <complex451@gmail.com> * add fused_adam Signed-off-by: ericharper <complex451@gmail.com> * check ds is not none before logging len Signed-off-by: ericharper <complex451@gmail.com> * set fp16 arg to true and fix enum conflict Signed-off-by: ericharper <complex451@gmail.com> * make fp16 arg configurable Signed-off-by: ericharper <complex451@gmail.com> * add grad clip from megatron Signed-off-by: ericharper <complex451@gmail.com> * Linear warmup with cosine annealing and constant holding (#2846) * Testing cosine schedule Signed-off-by: MaximumEntropy <sandeep.subramanian.1@umontreal.ca> * Style fixes Signed-off-by: MaximumEntropy <sandeep.subramanian.1@umontreal.ca> * Fixes Signed-off-by: MaximumEntropy <sandeep.subramanian.1@umontreal.ca> * More fixes Signed-off-by: MaximumEntropy <sandeep.subramanian.1@umontreal.ca> * update config for constant steps in schedule Signed-off-by: ericharper <complex451@gmail.com> * temporarily import enum from megatron Signed-off-by: ericharper <complex451@gmail.com> * add grad clip for fp32 Signed-off-by: ericharper <complex451@gmail.com> * update check for _del_model_without_trainer Signed-off-by: ericharper <complex451@gmail.com> * updating restore for model parallel Signed-off-by: ericharper <complex451@gmail.com> * add predict script Signed-off-by: ericharper <complex451@gmail.com> * update test iters Signed-off-by: ericharper <complex451@gmail.com> * add barrier Signed-off-by: ericharper <complex451@gmail.com> * return if clip_val is 0 or None Signed-off-by: ericharper <complex451@gmail.com> * when using amp clip grads after they are unscaled Signed-off-by: ericharper <complex451@gmail.com> * make native amp scaler hyperparams configurable Signed-off-by: ericharper <complex451@gmail.com> * (1) nvfuser, (2) amp-casting decoration (#2894) * (1) nvfuser, (2) amp-casting decoration Signed-off-by: Sangkug Lym <slym@nvidia.com> * support bf16 Signed-off-by: Sangkug Lym <slym@nvidia.com> * update package info Signed-off-by: ericharper <complex451@gmail.com> * add set device to constructor Signed-off-by: ericharper <complex451@gmail.com> * set_device in constructor Signed-off-by: ericharper <complex451@gmail.com> * [BigNLP] Remove megatron-lm dependency. (#2910) * remove args Signed-off-by: ericharper <complex451@gmail.com> * remove args Signed-off-by: ericharper <complex451@gmail.com> * remove args Signed-off-by: ericharper <complex451@gmail.com> * remove args Signed-off-by: ericharper <complex451@gmail.com> * remove args in progress Signed-off-by: ericharper <complex451@gmail.com> * remove args in progress Signed-off-by: ericharper <complex451@gmail.com> * remove args in progress Signed-off-by: ericharper <complex451@gmail.com> * remove args in progress Signed-off-by: ericharper <complex451@gmail.com> * add load_fused_kernels Signed-off-by: ericharper <complex451@gmail.com> * add load_fused_kernels Signed-off-by: ericharper <complex451@gmail.com> * update megatron_init Signed-off-by: ericharper <complex451@gmail.com> * add fused kernels Signed-off-by: ericharper <complex451@gmail.com> * add fused kernels Signed-off-by: ericharper <complex451@gmail.com> * update process batch Signed-off-by: ericharper <complex451@gmail.com> * remove erroneous import Signed-off-by: ericharper <complex451@gmail.com> * remove erroneous import Signed-off-by: ericharper <complex451@gmail.com> * remove erroneous import Signed-off-by: ericharper <complex451@gmail.com> * add megatron clip_grad Signed-off-by: ericharper <complex451@gmail.com> * trying to resolve circular import error Signed-off-by: ericharper <complex451@gmail.com> * rename file Signed-off-by: ericharper <complex451@gmail.com> * remove non-gpt models and datasets from __init__ files Signed-off-by: ericharper <complex451@gmail.com> * set device in constructorfor gpu init Signed-off-by: ericharper <complex451@gmail.com> * set device in constructorfor gpu init Signed-off-by: ericharper <complex451@gmail.com> * set_device in constructor Signed-off-by: ericharper <complex451@gmail.com> * clean config Signed-off-by: ericharper <complex451@gmail.com> * update MegatronDataset Signed-off-by: ericharper <complex451@gmail.com> * clean up MegatronModule Signed-off-by: ericharper <complex451@gmail.com> * clean up MegatronModule Signed-off-by: ericharper <complex451@gmail.com> * rename fp16 and bf16 flags to fused_softmax_input_in_fp16/bf16 Signed-off-by: ericharper <complex451@gmail.com> * rename to fused_fp16 Signed-off-by: ericharper <complex451@gmail.com> * add fused_fp16 arg to LayerNorm calls Signed-off-by: ericharper <complex451@gmail.com> * fix arg name Signed-off-by: ericharper <complex451@gmail.com> * fix arg name Signed-off-by: ericharper <complex451@gmail.com> * fix import Signed-off-by: ericharper <complex451@gmail.com> * update arg Signed-off-by: ericharper <complex451@gmail.com> * skip warmup default to True Signed-off-by: ericharper <complex451@gmail.com> * skip warmup default to True Signed-off-by: ericharper <complex451@gmail.com> * Adding complete method to MegatronGPTModel (#2935) Signed-off-by: Oleksii Kuchaiev <okuchaiev@nvidia.com> * make ffn_hidden_size mandatory Signed-off-by: ericharper <complex451@gmail.com> * Manually migrating timing of step into branch (#2937) * 1. Manually migrating timing of step into branch. Signed-off-by: Micha Livne <mlivne@nvidia.com> * 1. Updated file name and content. Signed-off-by: Micha Livne <mlivne@nvidia.com> * 1. Updated to latest code. Signed-off-by: Micha Livne <mlivne@nvidia.com> Co-authored-by: Micha Livne <mlivne@nvidia.com> * remove unused imports Signed-off-by: ericharper <complex451@gmail.com> * remove unused import Signed-off-by: ericharper <complex451@gmail.com> * remove unused import Signed-off-by: ericharper <complex451@gmail.com> * remove unused import Signed-off-by: ericharper <complex451@gmail.com> * check fused_fp16 and fused_bf16 are not both True Signed-off-by: ericharper <complex451@gmail.com> * update predict script for model parallel .nemo Signed-off-by: ericharper <complex451@gmail.com> * typo Signed-off-by: ericharper <complex451@gmail.com> * typo Signed-off-by: ericharper <complex451@gmail.com> Co-authored-by: Oleksii Kuchaiev <okuchaiev@users.noreply.github.com> Co-authored-by: Micha Livne <michalivne@users.noreply.github.com> Co-authored-by: Micha Livne <mlivne@nvidia.com> * NVfuser (#2943) * activation checkpoint recompute Signed-off-by: Sangkug Lym <slym@nvidia.com> * selective nvfuser setup * Megatron gpt bfloat support (#2926) * Save/restore fix Signed-off-by: MaximumEntropy <sandeep.subramanian.1@umontreal.ca> * Another merge Signed-off-by: MaximumEntropy <sandeep.subramanian.1@umontreal.ca> * Bf16 args in init Signed-off-by: MaximumEntropy <sandeep.subramanian.1@umontreal.ca> * Set precision Signed-off-by: MaximumEntropy <sandeep.subramanian.1@umontreal.ca> * Remove debug stuff Signed-off-by: MaximumEntropy <sandeep.subramanian.1@umontreal.ca> * add bf16 casting decorator Signed-off-by: Sangkug Lym <slym@nvidia.com> * Bfloat layernorm propagation Signed-off-by: MaximumEntropy <sandeep.subramanian.1@umontreal.ca> * activation checkpoint recompute Signed-off-by: Sangkug Lym <slym@nvidia.com> * selective nvfuser setup * More arg removal Signed-off-by: MaximumEntropy <sandeep.subramanian.1@umontreal.ca> * Remove BERTDataset Signed-off-by: MaximumEntropy <sandeep.subramanian.1@umontreal.ca> * update to latest apex and patch transformer autocast Signed-off-by: ericharper <complex451@gmail.com> Co-authored-by: Sangkug Lym <slym@nvidia.com> Co-authored-by: ericharper <complex451@gmail.com> * don't set jit for bf16 Signed-off-by: ericharper <complex451@gmail.com> * replace apex.mpu Signed-off-by: ericharper <complex451@gmail.com> * fix grad clip Signed-off-by: ericharper <complex451@gmail.com> * NVFuser fixes (#2951) * Fuser fixes Signed-off-by: MaximumEntropy <sandeep.subramanian.1@umontreal.ca> * Remove dummy handler Signed-off-by: MaximumEntropy <sandeep.subramanian.1@umontreal.ca> * Remove PTL plugin based logic for fusion Signed-off-by: MaximumEntropy <sandeep.subramanian.1@umontreal.ca> * remove duplicated file Signed-off-by: ericharper <complex451@gmail.com> * typo (#2960) Signed-off-by: ericharper <complex451@gmail.com> * [BigNLP] Script to convert GPT checkpoint to .nemo (#2958) * remove args Signed-off-by: ericharper <complex451@gmail.com> * remove args Signed-off-by: ericharper <complex451@gmail.com> * remove args Signed-off-by: ericharper <complex451@gmail.com> * remove args Signed-off-by: ericharper <complex451@gmail.com> * remove args in progress Signed-off-by: ericharper <complex451@gmail.com> * remove args in progress Signed-off-by: ericharper <complex451@gmail.com> * remove args in progress Signed-off-by: ericharper <complex451@gmail.com> * remove args in progress Signed-off-by: ericharper <complex451@gmail.com> * add load_fused_kernels Signed-off-by: ericharper <complex451@gmail.com> * add load_fused_kernels Signed-off-by: ericharper <complex451@gmail.com> * update megatron_init Signed-off-by: ericharper <complex451@gmail.com> * add fused kernels Signed-off-by: ericharper <complex451@gmail.com> * add fused kernels Signed-off-by: ericharper <complex451@gmail.com> * update process batch Signed-off-by: ericharper <complex451@gmail.com> * remove erroneous import Signed-off-by: ericharper <complex451@gmail.com> * remove erroneous import Signed-off-by: ericharper <complex451@gmail.com> * remove erroneous import Signed-off-by: ericharper <complex451@gmail.com> * add megatron clip_grad Signed-off-by: ericharper <complex451@gmail.com> * trying to resolve circular import error Signed-off-by: ericharper <complex451@gmail.com> * rename file Signed-off-by: ericharper <complex451@gmail.com> * remove non-gpt models and datasets from __init__ files Signed-off-by: ericharper <complex451@gmail.com> * set device in constructorfor gpu init Signed-off-by: ericharper <complex451@gmail.com> * set device in constructorfor gpu init Signed-off-by: ericharper <complex451@gmail.com> * set_device in constructor Signed-off-by: ericharper <complex451@gmail.com> * clean config Signed-off-by: ericharper <complex451@gmail.com> * update MegatronDataset Signed-off-by: ericharper <complex451@gmail.com> * clean up MegatronModule Signed-off-by: ericharper <complex451@gmail.com> * clean up MegatronModule Signed-off-by: ericharper <complex451@gmail.com> * rename fp16 and bf16 flags to fused_softmax_input_in_fp16/bf16 Signed-off-by: ericharper <complex451@gmail.com> * rename to fused_fp16 Signed-off-by: ericharper <complex451@gmail.com> * add fused_fp16 arg to LayerNorm calls Signed-off-by: ericharper <complex451@gmail.com> * fix arg name Signed-off-by: ericharper <complex451@gmail.com> * fix arg name Signed-off-by: ericharper <complex451@gmail.com> * fix import Signed-off-by: ericharper <complex451@gmail.com> * update arg Signed-off-by: ericharper <complex451@gmail.com> * skip warmup default to True Signed-off-by: ericharper <complex451@gmail.com> * skip warmup default to True Signed-off-by: ericharper <complex451@gmail.com> * Adding complete method to MegatronGPTModel (#2935) Signed-off-by: Oleksii Kuchaiev <okuchaiev@nvidia.com> * make ffn_hidden_size mandatory Signed-off-by: ericharper <complex451@gmail.com> * Manually migrating timing of step into branch (#2937) * 1. Manually migrating timing of step into branch. Signed-off-by: Micha Livne <mlivne@nvidia.com> * 1. Updated file name and content. Signed-off-by: Micha Livne <mlivne@nvidia.com> * 1. Updated to latest code. Signed-off-by: Micha Livne <mlivne@nvidia.com> Co-authored-by: Micha Livne <mlivne@nvidia.com> * remove unused imports Signed-off-by: ericharper <complex451@gmail.com> * remove unused import Signed-off-by: ericharper <complex451@gmail.com> * remove unused import Signed-off-by: ericharper <complex451@gmail.com> * remove unused import Signed-off-by: ericharper <complex451@gmail.com> * check fused_fp16 and fused_bf16 are not both True Signed-off-by: ericharper <complex451@gmail.com> * update predict script for model parallel .nemo Signed-off-by: ericharper <complex451@gmail.com> * typo Signed-off-by: ericharper <complex451@gmail.com> * add script to convert .ckpt to .nemo Signed-off-by: ericharper <complex451@gmail.com> * in progress Signed-off-by: ericharper <complex451@gmail.com> * update Signed-off-by: ericharper <complex451@gmail.com> * convert mp checkpoints to nemo Signed-off-by: ericharper <complex451@gmail.com> * update help Signed-off-by: ericharper <complex451@gmail.com> * add safeguard for model parallel save_to Signed-off-by: ericharper <complex451@gmail.com> * adjust NLPModel save_to to be safer for model parallel Signed-off-by: Oleksii Kuchaiev <okuchaiev@nvidia.com> Co-authored-by: Oleksii Kuchaiev <okuchaiev@users.noreply.github.com> Co-authored-by: Micha Livne <michalivne@users.noreply.github.com> Co-authored-by: Micha Livne <mlivne@nvidia.com> Co-authored-by: Oleksii Kuchaiev <okuchaiev@nvidia.com> * [BigNLP] Update GPT evaluation to work with tensor model parallel (#2959) * in progress Signed-off-by: ericharper <complex451@gmail.com> * update args Signed-off-by: ericharper <complex451@gmail.com> * add request dataset Signed-off-by: ericharper <complex451@gmail.com> * tokenize request Signed-off-by: ericharper <complex451@gmail.com> * in progress Signed-off-by: ericharper <complex451@gmail.com> * able to run Signed-off-by: ericharper <complex451@gmail.com> * reduce logits Signed-off-by: ericharper <complex451@gmail.com> * capture response Signed-off-by: ericharper <complex451@gmail.com> * squeeze and unsqueeze Signed-off-by: ericharper <complex451@gmail.com> * handle non model parallel case Signed-off-by: ericharper <complex451@gmail.com> * clean imports Signed-off-by: ericharper <complex451@gmail.com> * add file Signed-off-by: ericharper <complex451@gmail.com> * convert logits to log_probs Signed-off-by: Oleksii Kuchaiev <okuchaiev@nvidia.com> * rename logits to log_probs Signed-off-by: Oleksii Kuchaiev <okuchaiev@nvidia.com> Co-authored-by: Oleksii Kuchaiev <okuchaiev@nvidia.com> * style Signed-off-by: ericharper <complex451@gmail.com> * fix copyright headers Signed-off-by: ericharper <complex451@gmail.com> * fix copyright headers Signed-off-by: ericharper <complex451@gmail.com> * remove old TimingCallback Signed-off-by: ericharper <complex451@gmail.com> * style Signed-off-by: ericharper <complex451@gmail.com> * update jenkins to use latest apex and sandeep's fork Signed-off-by: ericharper <complex451@gmail.com> * update jenkins Signed-off-by: ericharper <complex451@gmail.com> * update jenkins Signed-off-by: ericharper <complex451@gmail.com> * update jenkins Signed-off-by: ericharper <complex451@gmail.com> * update jenkins Signed-off-by: ericharper <complex451@gmail.com> * try 2109 container Signed-off-by: ericharper <complex451@gmail.com> * try cuda container Signed-off-by: ericharper <complex451@gmail.com> * use internal container Signed-off-by: ericharper <complex451@gmail.com> * update checkpoint tests Signed-off-by: ericharper <complex451@gmail.com> * fix scheduler args Signed-off-by: ericharper <complex451@gmail.com> * update eval Signed-off-by: ericharper <complex451@gmail.com> * style Signed-off-by: ericharper <complex451@gmail.com> * update jenkins to use ptl 1.5 rc Signed-off-by: ericharper <complex451@gmail.com> * add import guard to jenkins Signed-off-by: ericharper <complex451@gmail.com> * add import guard to jenkins Signed-off-by: ericharper <complex451@gmail.com> * remove deterministic Signed-off-by: ericharper <complex451@gmail.com> * install numba .53 Signed-off-by: ericharper <complex451@gmail.com> * allow for more variance Signed-off-by: ericharper <complex451@gmail.com> * update trainer config dataclass Signed-off-by: ericharper <complex451@gmail.com> * test_get_optimizer on gpu Signed-off-by: ericharper <complex451@gmail.com> * revert comment Signed-off-by: ericharper <complex451@gmail.com> * change trainer config default to 32 Signed-off-by: ericharper <complex451@gmail.com> * [BigNLP] Remove fused kernel code instead use Apex (#2984) * remove fused_kernels Signed-off-by: ericharper <complex451@gmail.com> * remove fused_kernels Signed-off-by: ericharper <complex451@gmail.com> * remove fused layer norm and fused softmax and use apex instead Signed-off-by: ericharper <complex451@gmail.com> * update imports Signed-off-by: ericharper <complex451@gmail.com> * remove comment Signed-off-by: ericharper <complex451@gmail.com> * use apex enums Signed-off-by: ericharper <complex451@gmail.com> * use apex enums Signed-off-by: ericharper <complex451@gmail.com> * add tab Signed-off-by: ericharper <complex451@gmail.com> * Timer with sliding window (#3002) Co-authored-by: Micha Livne <michalivne@users.noreply.github.com> * revert tab Signed-off-by: ericharper <complex451@gmail.com> * check for rank zero Signed-off-by: ericharper <complex451@gmail.com> * check for rank zero Signed-off-by: ericharper <complex451@gmail.com> * try explicit log dir Signed-off-by: ericharper <complex451@gmail.com> * add + Signed-off-by: ericharper <complex451@gmail.com> * don't rm Signed-off-by: ericharper <complex451@gmail.com> * make dir if it doesn't exist Signed-off-by: ericharper <complex451@gmail.com> * create mp nemo file in temp directory Signed-off-by: ericharper <complex451@gmail.com> * simplify mp save_to Signed-off-by: ericharper <complex451@gmail.com> * handle mp 1 case Signed-off-by: ericharper <complex451@gmail.com> * style fix Signed-off-by: ericharper <complex451@gmail.com> * remove files Signed-off-by: ericharper <complex451@gmail.com> * fix consumed_samples when resuming Signed-off-by: ericharper <complex451@gmail.com> * fix reinstall.sh Signed-off-by: ericharper <complex451@gmail.com> * update req Signed-off-by: ericharper <complex451@gmail.com> * add more detailed log for dataloaders Signed-off-by: ericharper <complex451@gmail.com> * check if cuda is available before using fused_adam Signed-off-by: ericharper <complex451@gmail.com> * revert comment Signed-off-by: ericharper <complex451@gmail.com> * update eval script to use model.freeze Signed-off-by: ericharper <complex451@gmail.com> * log train loss averaged over gradient accumulation steps Signed-off-by: ericharper <complex451@gmail.com> * check copyright earlier Signed-off-by: ericharper <complex451@gmail.com> * todo Signed-off-by: ericharper <complex451@gmail.com> * override SaveRestoreConnector in NLPModel init Signed-off-by: ericharper <complex451@gmail.com> * move to scripts Signed-off-by: ericharper <complex451@gmail.com> * remove star import Signed-off-by: ericharper <complex451@gmail.com> * remove comments Signed-off-by: ericharper <complex451@gmail.com> * remove unused dataset Signed-off-by: ericharper <complex451@gmail.com> * removed barrier Signed-off-by: ericharper <complex451@gmail.com> * check cfg Signed-off-by: ericharper <complex451@gmail.com> * remove logging Signed-off-by: ericharper <complex451@gmail.com> * freeze, unfreeze Signed-off-by: ericharper <complex451@gmail.com> * return None Signed-off-by: ericharper <complex451@gmail.com> * remove unused imports Signed-off-by: ericharper <complex451@gmail.com> * add TODO Signed-off-by: ericharper <complex451@gmail.com> * typecheck Signed-off-by: ericharper <complex451@gmail.com> * typo Signed-off-by: ericharper <complex451@gmail.com> * todo Signed-off-by: ericharper <complex451@gmail.com> * add common native plugin Signed-off-by: ericharper <complex451@gmail.com> * restore with trainer Signed-off-by: ericharper <complex451@gmail.com> * style Signed-off-by: ericharper <complex451@gmail.com> * deprecate megatron-lm bert Signed-off-by: ericharper <complex451@gmail.com> * deprecate megatron-lm bert Signed-off-by: ericharper <complex451@gmail.com> * compile helpers ont he fly Signed-off-by: ericharper <complex451@gmail.com> * remove amp_level Signed-off-by: ericharper <complex451@gmail.com> * remove amp_level from configs Signed-off-by: ericharper <complex451@gmail.com> * add missing import Signed-off-by: ericharper <complex451@gmail.com> * typo Signed-off-by: ericharper <complex451@gmail.com> * remove amp_level Signed-off-by: ericharper <complex451@gmail.com> * use fast huggingface tokenizers by default Signed-off-by: ericharper <complex451@gmail.com> * deal with huggingface tokenizer positional args Signed-off-by: ericharper <complex451@gmail.com> * deal with huggingface tokenizer positional args Signed-off-by: ericharper <complex451@gmail.com> * deal with huggingface tokenizer positional args Signed-off-by: ericharper <complex451@gmail.com> * revert use_fast default to False Signed-off-by: ericharper <complex451@gmail.com> * return super training_epoch_end Signed-off-by: ericharper <complex451@gmail.com> * remove optimizer_idx arg from training_step Signed-off-by: ericharper <complex451@gmail.com> * remove unused arg from on_train_epoch_end Signed-off-by: ericharper <complex451@gmail.com> * add restore_from_path to nemo config Signed-off-by: ericharper <complex451@gmail.com> * add comment Signed-off-by: ericharper <complex451@gmail.com> * revert Signed-off-by: ericharper <complex451@gmail.com> * override connector if not subclassing NLPSaveRestoreConnector for model parallel save Signed-off-by: ericharper <complex451@gmail.com> * update test optimizer Signed-off-by: ericharper <complex451@gmail.com> * clean up Signed-off-by: ericharper <complex451@gmail.com> * clean up Signed-off-by: ericharper <complex451@gmail.com> * clean up Signed-off-by: ericharper <complex451@gmail.com> * clean up Signed-off-by: ericharper <complex451@gmail.com> * make data_prefix mandatory in config Signed-off-by: ericharper <complex451@gmail.com> * update installation instructions on readme Signed-off-by: ericharper <complex451@gmail.com> * update dockerfile Signed-off-by: ericharper <complex451@gmail.com> * add todo Signed-off-by: ericharper <complex451@gmail.com> * raise error if trying to use always_save_nemo with model parallel model Signed-off-by: ericharper <complex451@gmail.com> * remove comment Signed-off-by: ericharper <complex451@gmail.com> Co-authored-by: Sandeep Subramanian <sandeep.subramanian.1@umontreal.ca> Co-authored-by: Sangkug Lym <slym@nvidia.com> Co-authored-by: Oleksii Kuchaiev <okuchaiev@users.noreply.github.com> Co-authored-by: Micha Livne <michalivne@users.noreply.github.com> Co-authored-by: Micha Livne <mlivne@nvidia.com> Co-authored-by: Oleksii Kuchaiev <okuchaiev@nvidia.com>
506 lines
22 KiB
C++
506 lines
22 KiB
C++
/* coding=utf-8
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* Copyright (c) 2020, NVIDIA CORPORATION. All rights reserved.
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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#pragma once
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#include <assert.h>
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#include <cuda_fp16.h>
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#include <cfloat>
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#include <limits>
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#include <stdint.h>
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#include <cuda_fp16.h>
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#include <c10/macros/Macros.h>
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namespace {
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template <typename Datatype, int ELEMENTS_PER_LDG>
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__device__ __inline__ void copy_vector(Datatype *dst, const Datatype *src);
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template <>
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__device__ __inline__ void copy_vector<c10::BFloat16, 1>(c10::BFloat16 *dst, const c10::BFloat16 *src) { *dst = *src; }
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template <>
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__device__ __inline__ void copy_vector<c10::BFloat16, 4>(c10::BFloat16 *dst, const c10::BFloat16 *src) { *((float2*) dst) = *((float2*) src); }
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template <>
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__device__ __inline__ void copy_vector<c10::Half, 1>(c10::Half *dst, const c10::Half *src) { *dst = *src; }
|
|
|
|
template <>
|
|
__device__ __inline__ void copy_vector<c10::Half, 4>(c10::Half *dst, const c10::Half *src) { *((float2*) dst) = *((float2*) src); }
|
|
|
|
template <>
|
|
__device__ __inline__ void copy_vector<uint8_t, 1>(uint8_t *dst, const uint8_t *src) { *dst = *src; }
|
|
|
|
template <>
|
|
__device__ __inline__ void copy_vector<uint8_t, 4>(uint8_t *dst, const uint8_t *src) {*((half2*) dst) = *((half2*) src); }
|
|
|
|
int log2_ceil(int value) {
|
|
int log2_value = 0;
|
|
while ((1 << log2_value) < value) ++log2_value;
|
|
return log2_value;
|
|
}
|
|
|
|
template<typename T>
|
|
struct Add {
|
|
__device__ __forceinline__ T operator()(T a, T b) const {
|
|
return a + b;
|
|
}
|
|
};
|
|
|
|
template<typename T>
|
|
struct Max {
|
|
__device__ __forceinline__ T operator()(T a, T b) const {
|
|
return a < b ? b : a;
|
|
}
|
|
};
|
|
|
|
template <typename T>
|
|
__device__ __forceinline__ T WARP_SHFL_XOR_NATIVE(T value, int laneMask, int width = warpSize, unsigned int mask = 0xffffffff)
|
|
{
|
|
#if CUDA_VERSION >= 9000
|
|
return __shfl_xor_sync(mask, value, laneMask, width);
|
|
#else
|
|
return __shfl_xor(value, laneMask, width);
|
|
#endif
|
|
}
|
|
|
|
template <typename acc_t, int WARP_BATCH, int WARP_SIZE, template<typename> class ReduceOp>
|
|
__device__ __forceinline__ void warp_reduce(acc_t* sum) {
|
|
ReduceOp<acc_t> r;
|
|
#pragma unroll
|
|
for (int offset = WARP_SIZE / 2; offset > 0; offset /= 2) {
|
|
#pragma unroll
|
|
for (int i = 0; i < WARP_BATCH; ++i) {
|
|
acc_t b = WARP_SHFL_XOR_NATIVE(sum[i], offset, WARP_SIZE);
|
|
sum[i] = r(sum[i], b);
|
|
}
|
|
}
|
|
}
|
|
|
|
/*
|
|
* Extended softmax (from native aten pytorch) with following additional features
|
|
* 1) input scaling
|
|
* 2) Explicit masking
|
|
*/
|
|
template <typename input_t, typename output_t, typename acc_t, int log2_elements>
|
|
__global__ void scaled_masked_softmax_warp_forward(
|
|
output_t *dst,
|
|
const input_t *src,
|
|
const uint8_t *mask,
|
|
const acc_t scale,
|
|
int micro_batch_size,
|
|
int element_count,
|
|
int pad_batches)
|
|
{
|
|
// WARP_SIZE and WARP_BATCH must match the return values batches_per_warp and
|
|
// warp_size of method warp_softmax_forward_kernel.
|
|
constexpr int next_power_of_two = 1 << log2_elements;
|
|
constexpr int WARP_SIZE = (next_power_of_two < C10_WARP_SIZE) ? next_power_of_two : C10_WARP_SIZE;
|
|
constexpr int WARP_ITERATIONS = next_power_of_two / WARP_SIZE;
|
|
constexpr int WARP_BATCH = (next_power_of_two <= 128) ? 2 : 1;
|
|
constexpr int ELEMENTS_PER_LDG_STG = (WARP_ITERATIONS < 4) ? 1 : 4;
|
|
|
|
// blockDim/threadIdx = (WARP_SIZE, WARPS_PER_BLOCK, )
|
|
// gridDim/blockIdx = (seq_len, attn_heads, batches)
|
|
int first_batch = (blockDim.y * (blockIdx.x + gridDim.x * (blockIdx.y + gridDim.y * blockIdx.z))+ threadIdx.y) * WARP_BATCH;
|
|
int pad_first_batch = 0;
|
|
if (pad_batches != 1) { // bert style
|
|
pad_first_batch = (blockDim.y * (blockIdx.x + gridDim.x * blockIdx.z) + threadIdx.y) * WARP_BATCH;
|
|
} else { // gpt2 style
|
|
pad_first_batch = (blockDim.y * blockIdx.x + threadIdx.y) * WARP_BATCH;
|
|
}
|
|
|
|
// micro_batch_size might not be a multiple of WARP_BATCH. Check how
|
|
// many batches have to computed within this WARP.
|
|
int local_batches = micro_batch_size - first_batch;
|
|
if (local_batches > WARP_BATCH)
|
|
local_batches = WARP_BATCH;
|
|
|
|
// there might be multiple batches per warp. compute the index within the batch
|
|
int local_idx = threadIdx.x;
|
|
|
|
src += first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
|
|
dst += first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
|
|
mask += pad_first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
|
|
|
|
// load data from global memory
|
|
acc_t elements[WARP_BATCH][WARP_ITERATIONS];
|
|
input_t temp_data[ELEMENTS_PER_LDG_STG];
|
|
uint8_t temp_mask[ELEMENTS_PER_LDG_STG];
|
|
#pragma unroll
|
|
for (int i = 0; i < WARP_BATCH; ++i) {
|
|
int batch_element_count = (i >= local_batches) ? 0 : element_count;
|
|
|
|
#pragma unroll
|
|
for (int it = 0; it < WARP_ITERATIONS; it+=ELEMENTS_PER_LDG_STG) {
|
|
int element_index = ELEMENTS_PER_LDG_STG * local_idx + it * WARP_SIZE;
|
|
|
|
if (element_index < batch_element_count) {
|
|
int itr_idx = i*element_count+it*WARP_SIZE;
|
|
copy_vector<input_t, ELEMENTS_PER_LDG_STG>(temp_data, src + itr_idx);
|
|
copy_vector<uint8_t, ELEMENTS_PER_LDG_STG>(temp_mask, mask + itr_idx);
|
|
|
|
#pragma unroll
|
|
for (int element = 0; element < ELEMENTS_PER_LDG_STG; ++element) {
|
|
if (temp_mask[element] != 1) {
|
|
elements[i][it + element] = (acc_t)temp_data[element] * scale;
|
|
} else {
|
|
elements[i][it + element] = -10000.0;
|
|
}
|
|
}
|
|
} else {
|
|
#pragma unroll
|
|
for (int element = 0; element < ELEMENTS_PER_LDG_STG; ++element) {
|
|
elements[i][it + element] = -std::numeric_limits<acc_t>::infinity();
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
// compute max_value
|
|
acc_t max_value[WARP_BATCH];
|
|
#pragma unroll
|
|
for (int i = 0; i < WARP_BATCH; ++i) {
|
|
max_value[i] = elements[i][0];
|
|
#pragma unroll
|
|
for (int it = 1; it < WARP_ITERATIONS; ++it) {
|
|
max_value[i] = (max_value[i] > elements[i][it]) ? max_value[i] : elements[i][it];
|
|
}
|
|
}
|
|
warp_reduce<acc_t, WARP_BATCH, WARP_SIZE, Max>(max_value);
|
|
|
|
acc_t sum[WARP_BATCH] { 0.0f };
|
|
#pragma unroll
|
|
for (int i = 0; i < WARP_BATCH; ++i) {
|
|
#pragma unroll
|
|
for (int it = 0; it < WARP_ITERATIONS; ++it) {
|
|
elements[i][it] = std::exp((elements[i][it] - max_value[i]));
|
|
sum[i] += elements[i][it];
|
|
}
|
|
}
|
|
warp_reduce<acc_t, WARP_BATCH, WARP_SIZE, Add>(sum);
|
|
|
|
// store result
|
|
output_t out[ELEMENTS_PER_LDG_STG];
|
|
#pragma unroll
|
|
for (int i = 0; i < WARP_BATCH; ++i) {
|
|
if (i >= local_batches)
|
|
break;
|
|
#pragma unroll
|
|
for (int it = 0; it < WARP_ITERATIONS; it+=ELEMENTS_PER_LDG_STG) {
|
|
int element_index = ELEMENTS_PER_LDG_STG * local_idx + it * WARP_SIZE;
|
|
if (element_index < element_count) {
|
|
#pragma unroll
|
|
for (int element = 0; element < ELEMENTS_PER_LDG_STG; ++element) {
|
|
out[element] = elements[i][it + element] / sum[i];
|
|
}
|
|
copy_vector<output_t, ELEMENTS_PER_LDG_STG>(dst + i * element_count + it * WARP_SIZE, out);
|
|
} else {
|
|
break;
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
template <typename input_t, typename output_t, typename acc_t, int log2_elements>
|
|
__global__ void scaled_masked_softmax_warp_backward(
|
|
output_t *gradInput,
|
|
input_t *grad,
|
|
const input_t *output,
|
|
acc_t scale,
|
|
int micro_batch_size,
|
|
int element_count)
|
|
{
|
|
// WARP_SIZE and WARP_BATCH must match the return values batches_per_warp and
|
|
// warp_size of method warp_softmax_backward_kernel.
|
|
constexpr int next_power_of_two = 1 << log2_elements;
|
|
constexpr int WARP_SIZE = (next_power_of_two < C10_WARP_SIZE) ? next_power_of_two : C10_WARP_SIZE;
|
|
constexpr int WARP_ITERATIONS = next_power_of_two / WARP_SIZE;
|
|
constexpr int WARP_BATCH = (next_power_of_two <= 128) ? 2 : 1;
|
|
constexpr int ELEMENTS_PER_LDG_STG = (WARP_ITERATIONS < 4) ? 1 : 4;
|
|
|
|
// blockDim/threadIdx = (WARP_SIZE, WARPS_PER_BLOCK, )
|
|
// gridDim/blockIdx = (seq_len, attn_heads, batches)
|
|
int first_batch = (blockDim.y * blockIdx.x + threadIdx.y) * WARP_BATCH;
|
|
|
|
// micro_batch_size might not be a multiple of WARP_BATCH. Check how
|
|
// many batches have to computed within this WARP.
|
|
int local_batches = micro_batch_size - first_batch;
|
|
if (local_batches > WARP_BATCH)
|
|
local_batches = WARP_BATCH;
|
|
|
|
// there might be multiple batches per warp. compute the index within the batch
|
|
int local_idx = threadIdx.x;
|
|
|
|
// the first element to process by the current thread
|
|
int thread_offset = first_batch * element_count + ELEMENTS_PER_LDG_STG * local_idx;
|
|
grad += thread_offset;
|
|
output += thread_offset;
|
|
gradInput += thread_offset;
|
|
|
|
// load data from global memory
|
|
acc_t grad_reg[WARP_BATCH][WARP_ITERATIONS] { 0.0f };
|
|
acc_t output_reg[WARP_BATCH][WARP_ITERATIONS] { 0.0f };
|
|
input_t temp_grad[ELEMENTS_PER_LDG_STG];
|
|
input_t temp_output[ELEMENTS_PER_LDG_STG];
|
|
#pragma unroll
|
|
for (int i = 0; i < WARP_BATCH; ++i) {
|
|
int batch_element_count = (i >= local_batches) ? 0 : element_count;
|
|
|
|
#pragma unroll
|
|
for (int it = 0; it < WARP_ITERATIONS; it+=ELEMENTS_PER_LDG_STG) {
|
|
int element_index = ELEMENTS_PER_LDG_STG * local_idx + it * WARP_SIZE;
|
|
if (element_index < batch_element_count) {
|
|
copy_vector<input_t, ELEMENTS_PER_LDG_STG>(temp_grad, grad + i * element_count + it * WARP_SIZE);
|
|
copy_vector<input_t, ELEMENTS_PER_LDG_STG>(temp_output, output + i * element_count + it * WARP_SIZE);
|
|
|
|
#pragma unroll
|
|
for (int element = 0; element < ELEMENTS_PER_LDG_STG; ++element) {
|
|
output_reg[i][it + element] = (acc_t)temp_output[element];
|
|
}
|
|
#pragma unroll
|
|
for (int element = 0; element < ELEMENTS_PER_LDG_STG; ++element) {
|
|
grad_reg[i][it + element] = (acc_t)temp_grad[element] * output_reg[i][it + element];
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
acc_t sum[WARP_BATCH];
|
|
#pragma unroll
|
|
for (int i = 0; i < WARP_BATCH; ++i) {
|
|
sum[i] = grad_reg[i][0];
|
|
#pragma unroll
|
|
for (int it = 1; it < WARP_ITERATIONS; ++it) {
|
|
sum[i] += grad_reg[i][it];
|
|
}
|
|
}
|
|
warp_reduce<acc_t, WARP_BATCH, WARP_SIZE, Add>(sum);
|
|
|
|
// store result
|
|
#pragma unroll
|
|
for (int i = 0; i < WARP_BATCH; ++i) {
|
|
if (i >= local_batches)
|
|
break;
|
|
#pragma unroll
|
|
for (int it = 0; it < WARP_ITERATIONS; it+=ELEMENTS_PER_LDG_STG) {
|
|
int element_index = ELEMENTS_PER_LDG_STG * local_idx + it * WARP_SIZE;
|
|
if (element_index < element_count) {
|
|
// compute gradients
|
|
output_t out[ELEMENTS_PER_LDG_STG];
|
|
#pragma unroll
|
|
for (int element = 0; element < ELEMENTS_PER_LDG_STG; ++element) {
|
|
out[element] = (output_t)(scale * (grad_reg[i][it + element] - output_reg[i][it + element] * sum[i]));
|
|
}
|
|
copy_vector<output_t, ELEMENTS_PER_LDG_STG>(gradInput + i * element_count + it * WARP_SIZE, out);
|
|
}
|
|
}
|
|
}
|
|
}
|
|
} // end of anonymous namespace
|
|
|
|
int get_batch_per_block(int query_seq_len, int key_seq_len, int batches, int attn_heads){
|
|
int log2_elements = log2_ceil(key_seq_len);
|
|
const int next_power_of_two = 1 << log2_elements;
|
|
|
|
int warp_size = (next_power_of_two < C10_WARP_SIZE) ? next_power_of_two : C10_WARP_SIZE;
|
|
int batches_per_warp = (next_power_of_two <= 128) ? 2 : 1;
|
|
|
|
constexpr int threads_per_block = 128;
|
|
int warps_per_block = (threads_per_block / warp_size);
|
|
int batches_per_block = warps_per_block * batches_per_warp;
|
|
|
|
return batches_per_block;
|
|
}
|
|
|
|
template<typename input_t, typename output_t, typename acc_t>
|
|
void dispatch_scaled_masked_softmax_forward(
|
|
output_t *dst,
|
|
const input_t *src,
|
|
const uint8_t *mask,
|
|
const input_t scale,
|
|
int query_seq_len,
|
|
int key_seq_len,
|
|
int batches,
|
|
int attn_heads,
|
|
int pad_batches)
|
|
{
|
|
TORCH_INTERNAL_ASSERT(key_seq_len >= 0 && key_seq_len <= 2048 );
|
|
if (key_seq_len == 0) {
|
|
return;
|
|
} else {
|
|
int log2_elements = log2_ceil(key_seq_len);
|
|
const int next_power_of_two = 1 << log2_elements;
|
|
int batch_count = batches * attn_heads * query_seq_len;
|
|
|
|
// This value must match the WARP_SIZE constexpr value computed inside softmax_warp_forward.
|
|
int warp_size = (next_power_of_two < C10_WARP_SIZE) ? next_power_of_two : C10_WARP_SIZE;
|
|
|
|
// This value must match the WARP_BATCH constexpr value computed inside softmax_warp_forward.
|
|
int batches_per_warp = (next_power_of_two <= 128) ? 2 : 1;
|
|
|
|
// use 128 threads per block to maximimize gpu utilization
|
|
constexpr int threads_per_block = 128;
|
|
|
|
int warps_per_block = (threads_per_block / warp_size);
|
|
int batches_per_block = warps_per_block * batches_per_warp;
|
|
TORCH_INTERNAL_ASSERT(query_seq_len%batches_per_block == 0);
|
|
dim3 blocks(query_seq_len/batches_per_block, attn_heads, batches);
|
|
dim3 threads(warp_size, warps_per_block, 1);
|
|
// Launch code would be more elegant if C++ supported FOR CONSTEXPR
|
|
switch (log2_elements) {
|
|
case 0: // 1
|
|
scaled_masked_softmax_warp_forward<input_t, output_t, acc_t, 0>
|
|
<<<blocks, threads, 0, at::cuda::getCurrentCUDAStream()>>>(dst, src, mask, scale, batch_count, key_seq_len, pad_batches);
|
|
break;
|
|
case 1: // 2
|
|
scaled_masked_softmax_warp_forward<input_t, output_t, acc_t, 1>
|
|
<<<blocks, threads, 0, at::cuda::getCurrentCUDAStream()>>>(dst, src, mask, scale, batch_count, key_seq_len, pad_batches);
|
|
break;
|
|
case 2: // 4
|
|
scaled_masked_softmax_warp_forward<input_t, output_t, acc_t, 2>
|
|
<<<blocks, threads, 0, at::cuda::getCurrentCUDAStream()>>>(dst, src, mask, scale, batch_count, key_seq_len, pad_batches);
|
|
break;
|
|
case 3: // 8
|
|
scaled_masked_softmax_warp_forward<input_t, output_t, acc_t, 3>
|
|
<<<blocks, threads, 0, at::cuda::getCurrentCUDAStream()>>>(dst, src, mask, scale, batch_count, key_seq_len, pad_batches);
|
|
break;
|
|
case 4: // 16
|
|
scaled_masked_softmax_warp_forward<input_t, output_t, acc_t, 4>
|
|
<<<blocks, threads, 0, at::cuda::getCurrentCUDAStream()>>>(dst, src, mask, scale, batch_count, key_seq_len, pad_batches);
|
|
break;
|
|
case 5: // 32
|
|
scaled_masked_softmax_warp_forward<input_t, output_t, acc_t, 5>
|
|
<<<blocks, threads, 0, at::cuda::getCurrentCUDAStream()>>>(dst, src, mask, scale, batch_count, key_seq_len, pad_batches);
|
|
break;
|
|
case 6: // 64
|
|
scaled_masked_softmax_warp_forward<input_t, output_t, acc_t, 6>
|
|
<<<blocks, threads, 0, at::cuda::getCurrentCUDAStream()>>>(dst, src, mask, scale, batch_count, key_seq_len, pad_batches);
|
|
break;
|
|
case 7: // 128
|
|
scaled_masked_softmax_warp_forward<input_t, output_t, acc_t, 7>
|
|
<<<blocks, threads, 0, at::cuda::getCurrentCUDAStream()>>>(dst, src, mask, scale, batch_count, key_seq_len, pad_batches);
|
|
break;
|
|
case 8: // 256
|
|
scaled_masked_softmax_warp_forward<input_t, output_t, acc_t, 8>
|
|
<<<blocks, threads, 0, at::cuda::getCurrentCUDAStream()>>>(dst, src, mask, scale, batch_count, key_seq_len, pad_batches);
|
|
break;
|
|
case 9: // 512
|
|
scaled_masked_softmax_warp_forward<input_t, output_t, acc_t, 9>
|
|
<<<blocks, threads, 0, at::cuda::getCurrentCUDAStream()>>>(dst, src, mask, scale, batch_count, key_seq_len, pad_batches);
|
|
break;
|
|
case 10: // 1024
|
|
scaled_masked_softmax_warp_forward<input_t, output_t, acc_t, 10>
|
|
<<<blocks, threads, 0, at::cuda::getCurrentCUDAStream()>>>(dst, src, mask, scale, batch_count, key_seq_len, pad_batches);
|
|
break;
|
|
case 11: // 2048
|
|
scaled_masked_softmax_warp_forward<input_t, output_t, acc_t, 11>
|
|
<<<blocks, threads, 0, at::cuda::getCurrentCUDAStream()>>>(dst, src, mask, scale, batch_count, key_seq_len, pad_batches);
|
|
break;
|
|
default:
|
|
break;
|
|
}
|
|
}
|
|
}
|
|
|
|
template<typename input_t, typename output_t, typename acc_t>
|
|
void dispatch_scaled_masked_softmax_backward(
|
|
output_t *grad_input,
|
|
input_t *grad,
|
|
const input_t *output,
|
|
const acc_t scale,
|
|
int query_seq_len,
|
|
int key_seq_len,
|
|
int batches,
|
|
int attn_heads)
|
|
{
|
|
TORCH_INTERNAL_ASSERT( key_seq_len >= 0 && key_seq_len <= 2048 );
|
|
if (key_seq_len == 0) {
|
|
return;
|
|
} else {
|
|
int log2_elements = log2_ceil(key_seq_len);
|
|
const int next_power_of_two = 1 << log2_elements;
|
|
int batch_count = batches * attn_heads * query_seq_len;
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|
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// This value must match the WARP_SIZE constexpr value computed inside softmax_warp_backward.
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int warp_size = (next_power_of_two < C10_WARP_SIZE) ? next_power_of_two : C10_WARP_SIZE;
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|
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// This value must match the WARP_BATCH constexpr value computed inside softmax_warp_backward.
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int batches_per_warp = (next_power_of_two <= 128) ? 2 : 1;
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|
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// use 128 threads per block to maximimize gpu utilization
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constexpr int threads_per_block = 128;
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|
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int warps_per_block = (threads_per_block / warp_size);
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int batches_per_block = warps_per_block * batches_per_warp;
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int blocks = batch_count/batches_per_block;
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dim3 threads(warp_size, warps_per_block, 1);
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// Launch code would be more elegant if C++ supported FOR CONSTEXPR
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|
switch (log2_elements) {
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case 0: // 1
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|
scaled_masked_softmax_warp_backward<input_t, output_t, acc_t, 0>
|
|
<<<blocks, threads, 0, at::cuda::getCurrentCUDAStream()>>>(grad_input, grad, output, scale, batch_count, key_seq_len);
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break;
|
|
case 1: // 2
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|
scaled_masked_softmax_warp_backward<input_t, output_t, acc_t, 1>
|
|
<<<blocks, threads, 0, at::cuda::getCurrentCUDAStream()>>>(grad_input, grad, output, scale, batch_count, key_seq_len);
|
|
break;
|
|
case 2: // 4
|
|
scaled_masked_softmax_warp_backward<input_t, output_t, acc_t, 2>
|
|
<<<blocks, threads, 0, at::cuda::getCurrentCUDAStream()>>>(grad_input, grad, output, scale, batch_count, key_seq_len);
|
|
break;
|
|
case 3: // 8
|
|
scaled_masked_softmax_warp_backward<input_t, output_t, acc_t, 3>
|
|
<<<blocks, threads, 0, at::cuda::getCurrentCUDAStream()>>>(grad_input, grad, output, scale, batch_count, key_seq_len);
|
|
break;
|
|
case 4: // 16
|
|
scaled_masked_softmax_warp_backward<input_t, output_t, acc_t, 4>
|
|
<<<blocks, threads, 0, at::cuda::getCurrentCUDAStream()>>>(grad_input, grad, output, scale, batch_count, key_seq_len);
|
|
break;
|
|
case 5: // 32
|
|
scaled_masked_softmax_warp_backward<input_t, output_t, acc_t, 5>
|
|
<<<blocks, threads, 0, at::cuda::getCurrentCUDAStream()>>>(grad_input, grad, output, scale, batch_count, key_seq_len);
|
|
break;
|
|
case 6: // 64
|
|
scaled_masked_softmax_warp_backward<input_t, output_t, acc_t, 6>
|
|
<<<blocks, threads, 0, at::cuda::getCurrentCUDAStream()>>>(grad_input, grad, output, scale, batch_count, key_seq_len);
|
|
break;
|
|
case 7: // 128
|
|
scaled_masked_softmax_warp_backward<input_t, output_t, acc_t, 7>
|
|
<<<blocks, threads, 0, at::cuda::getCurrentCUDAStream()>>>(grad_input, grad, output, scale, batch_count, key_seq_len);
|
|
break;
|
|
case 8: // 256
|
|
scaled_masked_softmax_warp_backward<input_t, output_t, acc_t, 8>
|
|
<<<blocks, threads, 0, at::cuda::getCurrentCUDAStream()>>>(grad_input, grad, output, scale, batch_count, key_seq_len);
|
|
break;
|
|
case 9: // 512
|
|
scaled_masked_softmax_warp_backward<input_t, output_t, acc_t, 9>
|
|
<<<blocks, threads, 0, at::cuda::getCurrentCUDAStream()>>>(grad_input, grad, output, scale, batch_count, key_seq_len);
|
|
break;
|
|
case 10: // 1024
|
|
scaled_masked_softmax_warp_backward<input_t, output_t, acc_t, 10>
|
|
<<<blocks, threads, 0, at::cuda::getCurrentCUDAStream()>>>(grad_input, grad, output, scale, batch_count, key_seq_len);
|
|
break;
|
|
case 11: // 2048
|
|
scaled_masked_softmax_warp_backward<input_t, output_t, acc_t, 11>
|
|
<<<blocks, threads, 0, at::cuda::getCurrentCUDAStream()>>>(grad_input, grad, output, scale, batch_count, key_seq_len);
|
|
break;
|
|
default:
|
|
break;
|
|
}
|
|
}
|
|
}
|