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Types & classes46 in github.com/TencentARC/Moto

⨍ Functions 210◇ Types & classes 46
↓ 4 callersClassDataPrefetcher
common/data/datasets.py:34
↓ 2 callersClassAttention
moto_gpt/src/models/trajectory_gpt2.py:291
↓ 2 callersClassLMDBDataset_Mix
common/data/datasets.py:85
↓ 2 callersClassRGB_PreProcessor
common/processors/rgb_preprocessors.py:40
↓ 1 callersClassBlock
moto_gpt/src/models/trajectory_gpt2.py:448
↓ 1 callersClassCalvinEnvWrapperRaw
moto_gpt/evaluation/robot_manipulation_benchmarks/calvin/calvin_env_wrapper_raw.py:38
↓ 1 callersClassLMDViTEmbeddings
latent_motion_tokenizer/src/models/modeling_lmd_vit.py:13
↓ 1 callersClassLMDViTModel
latent_motion_tokenizer/src/models/modeling_lmd_vit.py:87
↓ 1 callersClassLatentMotionTokenizer_Trainer
latent_motion_tokenizer/src/trainers/latent_motion_tokenizer_trainer.py:21
↓ 1 callersClassLinearWarmup_CosineAnnealing
Construct two LR schedulers. First one is for a linear warmup. Second one is for a cosine annealing.
latent_motion_tokenizer/src/trainers/optimizer.py:39
↓ 1 callersClassMFormerEmbeddings
latent_motion_tokenizer/src/models/m_former.py:12
↓ 1 callersClassMLP
moto_gpt/src/models/trajectory_gpt2.py:418
↓ 1 callersClassMotoGPT_Inference
moto_gpt/evaluation/robot_manipulation_benchmarks/simpler/simpler_env_policy_wrapper.py:23
↓ 1 callersClassMotoGPT_PolicyWraper
moto_gpt/src/models/moto_gpt_policy_wraper.py:23
↓ 1 callersClassMotoGPT_Trainer
moto_gpt/src/trainers/moto_gpt_trainer.py:19
↓ 1 callersClassRandomShiftsAug
common/processors/rgb_preprocessors.py:9
↓ 1 callersClassTheiaOutput
latent_motion_tokenizer/src/models/theia_model.py:44
↓ 1 callersClassTimmDinoV2Output
latent_motion_tokenizer/src/models/timm_dinov2_model.py:8
↓ 1 callersClassTimmDinoV2VsionEncoder
latent_motion_tokenizer/src/models/timm_dinov2_model.py:22
↓ 1 callersClassTimmDinoV2VsionEncoder
moto_gpt/src/models/timm_dinov2_model.py:24
↓ 1 callersClassViTPooler
latent_motion_tokenizer/src/models/modeling_lmd_vit.py:72
↓ 1 callersClassViTPooler
latent_motion_tokenizer/src/models/m_former.py:61
ClassActionEncoding
Defines supported action encoding schemes for different datasets.
data_preprocessing/oxe_dataset_configs.py:29
ClassAdapterMLP
moto_gpt/src/models/trajectory_gpt2.py:433
ClassGPT2Config
This is the configuration class to store the configuration of a :class:`~transformers.GPT2Model` or a :class:`~transformers.TFGPT2Model`. It
moto_gpt/src/models/trajectory_gpt2.py:80
ClassGPT2DoubleHeadsModelOutput
Base class for outputs of models predicting if two sentences are consecutive or not. Args: loss (:obj:`torch.FloatTensor` of shape :o
moto_gpt/src/models/trajectory_gpt2.py:542
ClassGPT2Model
moto_gpt/src/models/trajectory_gpt2.py:687
ClassGPT2PreTrainedModel
An abstract class to handle weights initialization and a simple interface for downloading and loading pretrained models.
moto_gpt/src/models/trajectory_gpt2.py:514
ClassJsonDataset_for_MotoGPT_Video
common/data/datasets.py:327
ClassLMDBDataset_for_MotoGPT
common/data/datasets.py:105
ClassLMDBDataset_for_MotoGPT_CALVIN
common/data/datasets.py:289
ClassLMDBDataset_for_MotoGPT_OXE
common/data/datasets.py:260
ClassLMDBDataset_for_MotoGPT_RT1
common/data/datasets.py:270
ClassLMDBDataset_for_MotoGPT_Video
common/data/datasets.py:265
ClassLatentMotionDecoder
latent_motion_tokenizer/src/models/latent_motion_decoder.py:11
ClassLatentMotionTokenizer
latent_motion_tokenizer/src/models/latent_motion_tokenizer.py:14
ClassMFormer
latent_motion_tokenizer/src/models/m_former.py:75
ClassMaeEncoder
moto_gpt/src/models/mae_model.py:8
ClassMotoGPT
moto_gpt/src/models/moto_gpt.py:24
ClassNpzDataset_for_MotoGPT_Video
common/data/datasets.py:461
ClassProprioEncoding
Defines supported proprio encoding schemes for different datasets.
data_preprocessing/oxe_dataset_configs.py:18
ClassTheiaEncoder
latent_motion_tokenizer/src/models/theia_model.py:49
ClassTheiaEncoder
moto_gpt/src/models/theia_model.py:49
ClassTheiaOutput
moto_gpt/src/models/theia_model.py:44
ClassTimmDinoV2Output
moto_gpt/src/models/timm_dinov2_model.py:10
ClassVectorQuantizer2
Improved version over VectorQuantizer, can be used as a drop-in replacement. Mostly avoids costly matrix multiplications and allows for pos
latent_motion_tokenizer/src/models/vector_quantizer.py:8