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github.com/allenai/molmo
/ functions
Functions
893 in github.com/allenai/molmo
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Functions
893
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Types & classes
198
↓ 1 callers
Function
synchronize_flag
(flag: bool, device: torch.device)
olmo/torch_util.py:142
↓ 1 callers
Method
train_batch
(self, batch: Dict[str, Any])
olmo/train.py:811
↓ 1 callers
Method
train_step
(self, batch: Dict[str, Any], reduce_global_loss: bool = True)
olmo/train.py:909
↓ 1 callers
Method
trainer_state_dict
(self)
olmo/train.py:377
↓ 1 callers
Function
traverse_nodes
(nodes)
olmo/hf_datasets/android_control_utils.py:186
↓ 1 callers
Function
unnormalize_image
Normalizes the image to zero mean and unit variance.
olmo/html_utils.py:38
↓ 1 callers
Method
unshard_checkpoint
( self, load_path: PathOrStr, *, local_cache: Optional[PathOrStr] = None,
olmo/checkpoint.py:1743
↓ 1 callers
Method
unshard_checkpoint
( self, load_path: PathOrStr, *, local_cache: Optional[PathOrStr] = None,
olmo/checkpoint.py:1987
↓ 1 callers
Method
update_metrics
( self, batch: Dict[str, Any], eval_out: Dict[str, torch.Tensor], )
olmo/train.py:192
↓ 1 callers
Function
vqa_score
Evaluation with VQA 2 style preprocessing
olmo/eval/vqa.py:100
↓ 1 callers
Function
within_bounding_box
(coords, box)
olmo/hf_datasets/android_control_utils.py:116
Method
__call__
(self, batch: List[Dict[str, Any]])
olmo/data/collator.py:64
Method
__call__
Interleave images and text tokens into multi-modal features for the model
olmo/data/model_preprocessor.py:617
Method
__call__
(self, example, rng=np.random)
olmo/data/model_preprocessor.py:824
Method
__call__
Returns a formatted example and example metadata
olmo/data/data_formatter.py:578
Method
__call__
(self, metadatas, predictions, tokenizer, step=None)
olmo/eval/evaluators.py:147
Method
__call__
(self, metadatas, predictions, tokenizer, step=None, scores=None)
olmo/eval/evaluators.py:170
Method
__call__
(self, metadatas, predictions, tokenizer, step=None)
olmo/eval/evaluators.py:379
Method
__call__
(self, metadatas, predictions, tokenizer, step=None)
olmo/eval/evaluators.py:423
Method
__call__
(self, metadatas, predictions, tokenizer, step=None)
olmo/eval/evaluators.py:487
Method
__call__
(self, metadatas, predictions, tokenizer, step=None)
olmo/eval/evaluators.py:596
Method
__call__
(self, metadatas, predictions, tokenizer, step=None)
olmo/eval/evaluators.py:625
Method
__call__
(self, metadata, predictions, tokenizer, step=None)
olmo/eval/evaluators.py:747
Method
__call__
(self, metadatas, predictions, tokenizer, step=None)
olmo/eval/evaluators.py:823
Method
__call__
(self, inputs, predictions, tokenizer, step=None)
olmo/eval/evaluators.py:952
Method
__call__
(self, predictions, example_metadata, tokenizer, device, step=None)
olmo/eval/inf_evaluator.py:37
Method
__enter__
(self)
olmo/train.py:1586
Method
__exit__
(self, exc_type, exc_val, exc_tb)
olmo/train.py:1589
Method
__getitem__
(self, item)
olmo/data/dataset.py:23
Method
__getitem__
(self, idx)
olmo/data/dataset.py:48
Method
__getitem__
(self, item)
olmo/data/dataset.py:85
Method
__init__
( self, params, lr: float = 1e-4, betas: Tuple[float, float] = (0.9, 0.99),
olmo/optim.py:439
Method
__init__
(self, tokenizer, bos_token_id=None, adds_space=False)
olmo/tokenizer.py:33
Method
__init__
(self, config: ModelConfig, use_bias: bool = True, is_vit_layer: Optional[bool] = True)
olmo/image_vit.py:36
Method
__init__
(self, config: ModelConfig)
olmo/image_vit.py:188
Method
__init__
(self, config: ModelConfig)
olmo/image_vit.py:216
Method
__init__
(self, config: ModelConfig)
olmo/image_vit.py:244
Method
__init__
(self, config: ModelConfig)
olmo/image_vit.py:276
Method
__init__
(self, config: ModelConfig)
olmo/image_vit.py:316
Method
__init__
(self, config: ModelConfig)
olmo/image_vit.py:403
Method
__init__
(self, config: ModelConfig)
olmo/image_vit.py:476
Method
__init__
( self, temperature: float = 1.0, with_replacement: bool = False, )
olmo/beam_search.py:127
Method
__init__
( self, k: int = 1, temperature: float = 1.0, with_replacement: bool = False,
olmo/beam_search.py:161
Method
__init__
( self, p: float = 0.9, temperature: float = 1.0, with_replacement: bool = Fal
olmo/beam_search.py:226
Method
__init__
(self, temperature: float = 1.0)
olmo/beam_search.py:302
Method
__init__
(self, length_penalty: float = 1.0)
olmo/beam_search.py:474
Method
__init__
(self, ngram_size: int, **kwargs)
olmo/beam_search.py:594
Method
__init__
( self, path: PathOrStr, single_file_per_rank: bool = True, sync_files: bool =
olmo/checkpoint.py:341
Method
__init__
( self, path: PathOrStr, *, local_cache: Optional[PathOrStr] = None, thread_count: Optional[int] = Non
olmo/checkpoint.py:417
Method
__init__
(self, cfg: TrainConfig, thread_count: Optional[int] = None, use_shared_mem_impl: bool = False)
olmo/checkpoint.py:977
Method
__init__
( self, *, level: Union[int, str] = logging.NOTSET, console: Optional[Console]
olmo/util.py:234
Method
__init__
( self, num_embeddings: int, num_new_embeddings: int, features: int, d
olmo/model.py:138
Method
__init__
( self, p: float = 0.5, inplace: bool = False, mask_p: float = 0, broa
olmo/model.py:166
Method
__init__
( self, config: ModelConfig, *, size: Optional[int] = None, elementwis
olmo/model.py:211
Method
__init__
( self, config: ModelConfig, size: Optional[int] = None, low_precision: bool =
olmo/model.py:276
Method
__init__
( self, config: ModelConfig, size: Optional[int] = None, elementwise_affine: O
olmo/model.py:308
Method
__init__
(self, config: ModelConfig, cache: BufferCache)
olmo/model.py:339
Method
__init__
(self, config: ModelConfig)
olmo/model.py:430
Method
__init__
(self, layer_id: int, config: ModelConfig, cache: BufferCache)
olmo/model.py:535
Method
__init__
(self, layer_id: int, config: ModelConfig, cache: BufferCache)
olmo/model.py:785
Method
__init__
(self, layer_id: int, config: ModelConfig, cache: BufferCache)
olmo/model.py:943
Method
__init__
(self, layer_id: int, config: ModelConfig, cache: BufferCache)
olmo/model.py:1064
Method
__init__
(self, config: ModelConfig, layer_offset: int, modules: Optional[Iterable[nn.Module]] = None)
olmo/model.py:1259
Method
__init__
(self, config: ModelConfig, input_dim: int, dropout: float = 0.0)
olmo/model.py:1305
Method
__init__
(self, submodule: nn.Module)
olmo/model.py:1347
Method
__init__
(self, config: ModelConfig)
olmo/model.py:1359
Method
__init__
(self, split, sample=None, counting=False, keep_in_memory=False)
olmo/data/pixmo_datasets.py:88
Method
__init__
(self, doc_type, split, sample=None, keep_in_memory=False, v1_style=False)
olmo/data/pixmo_datasets.py:126
Method
__init__
(self, split, kind="both", counting=False, keep_in_memory=False)
olmo/data/pixmo_datasets.py:177
Method
__init__
(self, split, split_groups=True, keep_in_memory=False)
olmo/data/pixmo_datasets.py:234
Method
__init__
(self, split, prefix_how_many=True, keep_in_memory=False)
olmo/data/pixmo_datasets.py:289
Method
__init__
(self, split, mode, prefix_how_many=True, keep_in_memory=False)
olmo/data/pixmo_datasets.py:338
Method
__init__
(self, split, prefix_how_many=True, keep_in_memory=False)
olmo/data/pixmo_datasets.py:387
Method
__init__
(self, keep_in_memory=False)
olmo/data/pixmo_datasets.py:436
Method
__init__
:param max_sequence_length: truncate examples longer than this length :param include_metadata: whether to include the metadata in the
olmo/data/collator.py:49
Method
__init__
( self, datasets: List[DeterministicDataset], global_batch_size: int, mixture_
olmo/data/iterable_dataset_mixture.py:18
Method
__init__
(self, dataset: Dataset, preprocessor, seed, n_pad=0)
olmo/data/dataset.py:39
Method
__init__
(self, split, sample: int=None)
olmo/data/dataset.py:71
Method
__init__
(self, split: str, parts="both", weighted=False, keep_in_memory=False)
olmo/data/academic_datasets.py:50
Method
__init__
(self, split, direct_answer=False)
olmo/data/academic_datasets.py:139
Method
__init__
(self, split: str, multi_question=False, keep_in_memory=False)
olmo/data/academic_datasets.py:202
Method
__init__
(self, split: str, identifier=None, keep_in_memory=False)
olmo/data/academic_datasets.py:256
Method
__init__
(self, split)
olmo/data/academic_datasets.py:281
Method
__init__
(self, split, boxes="both")
olmo/data/academic_datasets.py:312
Method
__init__
(self, split)
olmo/data/academic_datasets.py:368
Method
__init__
(self, split)
olmo/data/academic_datasets.py:407
Method
__init__
(self, split: str, keep_in_memory=False, **kwargs)
olmo/data/academic_datasets.py:447
Method
__init__
(self, split)
olmo/data/academic_datasets.py:480
Method
__init__
(self)
olmo/data/academic_datasets.py:521
Method
__init__
(self, split, include_options: bool)
olmo/data/academic_datasets.py:547
Method
__init__
(self, split, in_memory=False)
olmo/data/academic_datasets.py:576
Method
__init__
(self, split, in_memory=False)
olmo/data/academic_datasets.py:598
Method
__init__
(self, split, mode="all", in_memory=False)
olmo/data/academic_datasets.py:619
Method
__init__
(self, split, in_memory=False)
olmo/data/academic_datasets.py:680
Method
__init__
(self, split, simplify_question=True, **kwargs)
olmo/data/academic_datasets.py:702
Method
__init__
(self, mode="no_mc_instruction", in_memory=False)
olmo/data/academic_datasets.py:736
Method
__init__
(self, split: str)
olmo/data/academic_datasets.py:787
Method
__init__
(self, split)
olmo/data/academic_datasets.py:822
Method
__init__
(self, split, multi_question=False)
olmo/data/academic_datasets_manual.py:130
Method
__init__
(self, split, direct_answer=False)
olmo/data/academic_datasets_manual.py:171
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