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github.com/Alibaba-NLP/VRAG
/ types & classes
Types & classes
150 in github.com/Alibaba-NLP/VRAG
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Functions
1,037
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Types & classes
150
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Endpoints
26
↓ 21 callers
Class
DataProto
A DataProto is a data structure that aims to provide a standard protocol for data exchange between functions. It contains a batch (TensorDict
VRAG-RL/verl/protocol.py:176
↓ 7 callers
Class
ParallelLlamaRMSNorm
VRAG-RL/verl/models/llama/megatron/layers/parallel_rmsnorm.py:25
↓ 7 callers
Class
ParallelQwen2RMSNorm
VRAG-RL/verl/models/qwen2/megatron/layers/parallel_rmsnorm.py:25
↓ 6 callers
Class
RayClassWithInitArgs
VRAG-RL/verl/single_controller/ray/base.py:148
↓ 4 callers
Class
FSDPUlyssesShardingManager
Sharding manager to support data resharding when using FSDP + Ulysses
VRAG-RL/verl/workers/sharding_manager/fsdp_ulysses.py:32
↓ 4 callers
Class
FlopsCounter
Used to count mfu during training loop Example: flops_counter = FlopsCounter(config) flops_achieved, flops_promised = flops_
VRAG-RL/verl/utils/flops_counter.py:54
↓ 3 callers
Class
EncoderOutput
search_engine/models/GVE/models.py:27
↓ 3 callers
Class
GenerationConfig
VRAG-RL/vrag_agent/generation.py:45
↓ 3 callers
Class
Model_Role
VRAG-RL/scripts/data_construct_pipeline.py:115
↓ 3 callers
Class
RayResourcePool
VRAG-RL/verl/single_controller/ray/base.py:69
↓ 3 callers
Class
vLLMRollout
VRAG-RL/verl/workers/rollout/vllm_rollout/vllm_rollout.py:57
↓ 2 callers
Class
DataParallelPPOActor
VRAG-RL/verl/workers/actor/dp_actor.py:39
↓ 2 callers
Class
DataProtoFuture
DataProtoFuture aims to eliminate actual data fetching on driver. By doing so, the driver doesn't have to wait for data so that asynchronous
VRAG-RL/verl/protocol.py:765
↓ 2 callers
Class
FSDPCheckpointManager
A checkpoint manager that saves and loads - model - optimizer - lr_scheduler - extra_states in a SPMD way. We save
VRAG-RL/verl/utils/checkpoint/fsdp_checkpoint_manager.py:32
↓ 2 callers
Class
LLMGenerationManager
VRAG-RL/vrag_agent/generation.py:55
↓ 2 callers
Class
MegatronPPOActor
VRAG-RL/verl/workers/actor/megatron_actor.py:53
↓ 2 callers
Class
MemoryBuffer
A memory buffer is a contiguous torch tensor that may combine multiple tensors sharing with the underlying memory. It must have a unique type
VRAG-RL/verl/utils/memory_buffer.py:24
↓ 2 callers
Class
ParallelLlamaDecoderLayerRmPad
VRAG-RL/verl/models/llama/megatron/layers/parallel_decoder.py:102
↓ 2 callers
Class
ParallelLlamaMLP
VRAG-RL/verl/models/llama/megatron/layers/parallel_mlp.py:31
↓ 2 callers
Class
ParallelQwen2DecoderLayerRmPad
VRAG-RL/verl/models/qwen2/megatron/layers/parallel_decoder.py:102
↓ 2 callers
Class
ParallelQwen2MLP
VRAG-RL/verl/models/qwen2/megatron/layers/parallel_mlp.py:31
↓ 2 callers
Class
RLHFDataset
We assume the dataset contains a column that contains prompts and other information
VRAG-RL/verl/utils/dataset/rl_dataset.py:75
↓ 2 callers
Class
RMManager
VRAG-RL/verl/workers/reward_manager/rm.py:123
↓ 2 callers
Class
SFTDataset
This is an in-memory SFTDataset
VRAG-RL/verl/utils/dataset/sft_dataset.py:34
↓ 2 callers
Class
SearchEngine
search_engine/search_engine.py:10
↓ 2 callers
Class
State
VRAG-RL/verl/utils/seqlen_balancing.py:49
↓ 2 callers
Class
Tracking
VRAG-RL/verl/utils/tracking.py:24
↓ 2 callers
Class
VRAG
demo/vrag_agent.py:14
↓ 2 callers
Class
VimRAG
VimRAG: Visual Memory RAG Agent with DAG-based reasoning.
demo/vimrag_agent.py:19
↓ 1 callers
Class
AdaptiveKLController
Adaptive KL controller described in the paper: https://arxiv.org/pdf/1909.08593.pdf
VRAG-RL/verl/trainer/ppo/core_algos.py:28
↓ 1 callers
Class
AllGatherPPModel
VRAG-RL/verl/workers/sharding_manager/megatron_vllm.py:37
↓ 1 callers
Class
AutoModelForSentenceEmbeddingTriplet
search_engine/models/GVE/models.py:209
↓ 1 callers
Class
BaseShardingManager
VRAG-RL/verl/workers/sharding_manager/base.py:21
↓ 1 callers
Class
Capturing
VRAG-RL/verl/utils/reward_score/prime_code/testing_util.py:74
↓ 1 callers
Class
DataParallelPPOCritic
VRAG-RL/verl/workers/critic/dp_critic.py:39
↓ 1 callers
Class
DistGlobalInfo
VRAG-RL/verl/single_controller/base/worker.py:31
↓ 1 callers
Class
DistRankInfo
VRAG-RL/verl/single_controller/base/worker.py:24
↓ 1 callers
Class
FSDPSFTTrainer
VRAG-RL/verl/trainer/fsdp_sft_trainer.py:78
↓ 1 callers
Class
FSDPSGLangShardingManager
VRAG-RL/verl/workers/sharding_manager/fsdp_sglang.py:47
↓ 1 callers
Class
FSDPVLLMShardingManager
VRAG-RL/verl/workers/sharding_manager/fsdp_vllm.py:37
↓ 1 callers
Class
FixedKLController
Fixed KL controller.
VRAG-RL/verl/trainer/ppo/core_algos.py:46
↓ 1 callers
Class
HFRollout
VRAG-RL/verl/workers/rollout/hf_rollout.py:35
↓ 1 callers
Class
LambdaLayer
VRAG-RL/verl/utils/model.py:28
↓ 1 callers
Class
LlamaDynamicNTKScalingRotaryEmbedding
LlamaRotaryEmbedding extended with Dynamic NTK scaling. Credits to the Reddit users /u/bloc97 and /u/emozilla
VRAG-RL/verl/models/llama/megatron/layers/parallel_attention.py:91
↓ 1 callers
Class
LlamaLinearScalingRotaryEmbedding
LlamaRotaryEmbedding extended with linear scaling. Credits to the Reddit user /u/kaiokendev
VRAG-RL/verl/models/llama/megatron/layers/parallel_attention.py:72
↓ 1 callers
Class
LlamaRotaryEmbedding
VRAG-RL/verl/models/llama/megatron/layers/parallel_attention.py:35
↓ 1 callers
Class
LocalLogger
VRAG-RL/verl/utils/logger/aggregate_logger.py:30
↓ 1 callers
Class
MMRAG
VRAG-RL/scripts/data_construct_pipeline.py:162
↓ 1 callers
Class
MegatronPPOCritic
VRAG-RL/verl/workers/critic/megatron_critic.py:43
↓ 1 callers
Class
MegatronRewardModel
VRAG-RL/verl/workers/reward_model/megatron/reward_model.py:32
↓ 1 callers
Class
MegatronVLLMShardingManager
VRAG-RL/verl/workers/sharding_manager/megatron_vllm.py:254
↓ 1 callers
Class
MergedColumnParallelLinear
VRAG-RL/verl/models/qwen2/megatron/layers/parallel_linear.py:52
↓ 1 callers
Class
MergedColumnParallelLinear
VRAG-RL/verl/models/llama/megatron/layers/parallel_linear.py:52
↓ 1 callers
Class
NestedNamespace
VRAG-RL/verl/utils/py_functional.py:48
↓ 1 callers
Class
ParallelLlamaAttention
Multi-headed attention from 'Attention Is All You Need' paper
VRAG-RL/verl/models/llama/megatron/layers/parallel_attention.py:143
↓ 1 callers
Class
ParallelLlamaAttentionRmPad
VRAG-RL/verl/models/llama/megatron/layers/parallel_attention.py:338
↓ 1 callers
Class
ParallelLlamaDecoderLayer
VRAG-RL/verl/models/llama/megatron/layers/parallel_decoder.py:35
↓ 1 callers
Class
ParallelLlamaModel
Transformer decoder consisting of *config.num_hidden_layers* layers. Each layer is a [`LlamaDecoderLayer`] Args: config: LlamaConfig
VRAG-RL/verl/models/llama/megatron/modeling_llama_megatron.py:74
↓ 1 callers
Class
ParallelLlamaModelRmPad
Transformer decoder consisting of *config.num_hidden_layers* layers. Each layer is a [`LlamaDecoderLayer`] Args: config: LlamaConfig
VRAG-RL/verl/models/llama/megatron/modeling_llama_megatron.py:219
↓ 1 callers
Class
ParallelLlamaModelRmPadPP
Transformer decoder consisting of *config.num_hidden_layers* layers. Each layer is a [`LlamaDecoderLayer`] This model definition supports pip
VRAG-RL/verl/models/llama/megatron/modeling_llama_megatron.py:405
↓ 1 callers
Class
ParallelQwen2Attention
Multi-headed attention from 'Attention Is All You Need' paper
VRAG-RL/verl/models/qwen2/megatron/layers/parallel_attention.py:143
↓ 1 callers
Class
ParallelQwen2AttentionRmPad
VRAG-RL/verl/models/qwen2/megatron/layers/parallel_attention.py:322
↓ 1 callers
Class
ParallelQwen2DecoderLayer
VRAG-RL/verl/models/qwen2/megatron/layers/parallel_decoder.py:35
↓ 1 callers
Class
ParallelQwen2Model
Transformer decoder consisting of *config.num_hidden_layers* layers. Each layer is a [`Qwen2DecoderLayer`] Args: config: Qwen2Config
VRAG-RL/verl/models/qwen2/megatron/modeling_qwen2_megatron.py:73
↓ 1 callers
Class
ParallelQwen2ModelRmPad
Transformer decoder consisting of *config.num_hidden_layers* layers. Each layer is a [`Qwen2DecoderLayer`] Args: config: Qwen2Config
VRAG-RL/verl/models/qwen2/megatron/modeling_qwen2_megatron.py:218
↓ 1 callers
Class
ParallelQwen2ModelRmPadPP
Transformer decoder consisting of *config.num_hidden_layers* layers. Each layer is a [`Qwen2DecoderLayer`] This model definition supports pip
VRAG-RL/verl/models/qwen2/megatron/modeling_qwen2_megatron.py:404
↓ 1 callers
Class
QKVParallelLinear
VRAG-RL/verl/models/qwen2/megatron/layers/parallel_linear.py:21
↓ 1 callers
Class
QKVParallelLinear
VRAG-RL/verl/models/llama/megatron/layers/parallel_linear.py:21
↓ 1 callers
Class
Qwen2RotaryEmbedding
VRAG-RL/verl/models/qwen2/megatron/layers/parallel_attention.py:35
↓ 1 callers
Class
Qwen3VLEmbedder
search_engine/models/Qwen3_VL_Embedding/qwen3_vl_embedding.py:160
↓ 1 callers
Class
Qwen3VLForEmbeddingOutput
search_engine/models/Qwen3_VL_Embedding/qwen3_vl_embedding.py:37
↓ 1 callers
Class
RayPPOTrainer
Note that this trainer runs on the driver process on a single CPU/GPU node.
VRAG-RL/verl/trainer/ppo/ray_trainer.py:248
↓ 1 callers
Class
RayWorkerGroup
VRAG-RL/verl/single_controller/ray/base.py:196
↓ 1 callers
Class
ResourcePoolManager
Define a resource pool specification. Resource pool will be initialized first. Mapping
VRAG-RL/verl/trainer/ppo/ray_trainer.py:75
↓ 1 callers
Class
SGLangRollout
VRAG-RL/verl/workers/rollout/sglang_rollout/sglang_rollout.py:84
↓ 1 callers
Class
Set
VRAG-RL/verl/utils/seqlen_balancing.py:27
↓ 1 callers
Class
TensorConfig
VRAG-RL/vrag_agent/tensor_helper.py:6
↓ 1 callers
Class
TensorHelper
VRAG-RL/vrag_agent/tensor_helper.py:9
↓ 1 callers
Class
TimeoutException
VRAG-RL/verl/utils/reward_score/prime_math/grader.py:340
↓ 1 callers
Class
UnifierMnrlLoss
search_engine/models/GVE/model_utils.py:9
↓ 1 callers
Class
VLProcessor
search_engine/models/GVE/processor.py:5
↓ 1 callers
Class
ValidationGenerationsLogger
VRAG-RL/verl/utils/tracking.py:168
↓ 1 callers
Class
WorkerMeta
VRAG-RL/verl/single_controller/base/worker.py:68
↓ 1 callers
Class
_MlflowLoggingAdapter
VRAG-RL/verl/utils/tracking.py:126
↓ 1 callers
Class
_TensorboardAdapter
VRAG-RL/verl/utils/tracking.py:108
Class
ActorRolloutRefWorker
This worker can be instantiated as a standalone actor or a standalone rollout or a standalone reference policy or a hybrid engine based on th
VRAG-RL/verl/workers/megatron_workers.py:67
Class
ActorRolloutRefWorker
This worker can be instantiated as a standalone actor or a standalone rollout or a standalone reference policy or a hybrid engine based on th
VRAG-RL/verl/workers/fsdp_workers.py:70
Class
AdvantageEstimator
Using an enumeration class to avoid spelling errors in adv_estimator
VRAG-RL/verl/trainer/ppo/ray_trainer.py:63
Class
AutoModelForSentenceEmbedding
search_engine/models/GVE/models.py:34
Class
BaseCheckpointManager
A checkpoint manager that saves and loads - model - optimizer - lr_scheduler - extra_states in a SPMD way. We save -
VRAG-RL/verl/utils/checkpoint/checkpoint_manager.py:27
Class
BasePPOActor
VRAG-RL/verl/workers/actor/base.py:26
Class
BasePPOCritic
VRAG-RL/verl/workers/critic/base.py:26
Class
BasePPORewardModel
VRAG-RL/verl/workers/reward_model/base.py:23
Class
BaseRollout
VRAG-RL/verl/workers/rollout/base.py:23
Class
CODE_TYPE
VRAG-RL/verl/utils/reward_score/prime_code/testing_util.py:50
Class
ClassWithInitArgs
This class stores a class constructor and the args/kwargs to construct the class. It is used to instantiate the remote class.
VRAG-RL/verl/single_controller/base/worker_group.py:61
Class
CriticWorker
VRAG-RL/verl/workers/megatron_workers.py:486
Class
CriticWorker
VRAG-RL/verl/workers/fsdp_workers.py:616
Class
DataProtoItem
VRAG-RL/verl/protocol.py:168
Class
Dispatch
VRAG-RL/verl/single_controller/base/decorator.py:25
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