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Functions1,094 in github.com/Alpha-VLLM/LLaMA2-Accessory

⨍ Functions 1,094◇ Types & classes 182
↓ 1 callersMethodindices_and_padded_bins
( self, selected_experts: torch.Tensor )
accessory/model/LLM/mixtral_sparse_ens5.py:384
↓ 1 callersMethodindices_and_padded_bins
( self, selected_experts: torch.Tensor )
accessory/model/LLM/mixtral_sparse.py:378
↓ 1 callersMethodindices_and_padded_bins
( self, selected_experts: torch.Tensor )
accessory/model/LLM/mixtral_sparse_ens.py:382
↓ 1 callersFunctioninit_ceph_client_if_needed
()
Large-DiT-T2I/data/data_reader.py:19
↓ 1 callersFunctioninit_ceph_client_if_needed
()
accessory/data/data_reader.py:15
↓ 1 callersFunctioninit_print
(is_master)
accessory/model/multi_gpu_wrapper.py:26
↓ 1 callersFunctioninteractive_mode
(args)
accessory/tools/download.py:47
↓ 1 callersMethodis_complete
r"""Check if all the shards are loaded to the target tensor.
accessory/util/tensor_parallel.py:571
↓ 1 callersFunctionlast_boxed_only_string
(string)
light-eval/src/eval_utils/math_util.py:9
↓ 1 callersFunctionlevenshtein_distance
(s1, s2)
accessory/eval_mm/infographicsvqa_eval.py:20
↓ 1 callersFunctionload
(args)
light-eval/src/eval_math.py:54
↓ 1 callersFunctionload
(args)
light-eval/src/eval_bbh.py:68
↓ 1 callersFunctionload
(args)
light-eval/src/eval_cmmlu.py:65
↓ 1 callersFunctionload
(args)
light-eval/src/eval_humaneval.py:50
↓ 1 callersFunctionload
(args)
light-eval/src/eval_mmlu.py:82
↓ 1 callersFunctionload
(args)
light-eval/src/eval_ceval.py:59
↓ 1 callersFunctionload
(args)
light-eval/src/eval_mmvet.py:89
↓ 1 callersFunctionload
(args)
light-eval/src/eval_gsm8k.py:54
↓ 1 callersMethodloadRes
Load result file and return a result object. :param resFile (str) : file name of result file :return: res (obj) : resul
accessory/eval_mm/utils/vqa.py:168
↓ 1 callersFunctionload_and_merge_tensor_parallel_weights
( src_weights_path: List[str], torch_dtype: torch.dtype, ignore_unknown_keys: bool = False, )
accessory/tools/convert_weights_to_hf.py:92
↓ 1 callersFunctionload_diff_checkpoint
r"""This method loads model from a *_diff format checkpoint. The behavior of loading a diff checkpoint is different from loading a regular che
accessory/util/tensor_parallel.py:387
↓ 1 callersFunctionload_image
(image_path, model)
accessory/demos/multi_model_cli.py:13
↓ 1 callersMethodload_shard
r"""Load a shard into the target tensor. Args: shard_id (int): The shard id of the current value. value (``torch.Tens
accessory/util/tensor_parallel.py:558
↓ 1 callersFunctionmain
(args)
light-eval/src/eval_math.py:199
↓ 1 callersFunctionmain
(args, multiple_choice_tasks=MULTIPLE_CHOICE_TASKS, free_form_tasks=FREE_FORM_TASKS)
light-eval/src/eval_bbh.py:210
↓ 1 callersFunctionmain
(args)
light-eval/src/eval_cmmlu.py:199
↓ 1 callersFunctionmain
(args)
light-eval/src/eval_humaneval.py:168
↓ 1 callersFunctionmain
(args)
light-eval/src/eval_mmlu.py:215
↓ 1 callersFunctionmain
(args)
light-eval/src/eval_ceval.py:212
↓ 1 callersFunctionmain
(args)
light-eval/src/eval_gsm8k.py:218
↓ 1 callersFunctionmain
Trains a new DiT model.
Large-DiT-ImageNet/train.py:197
↓ 1 callersFunctionmain
(args, rank, master_port)
Large-DiT-ImageNet/sample.py:26
↓ 1 callersFunctionmain
()
SPHINX/batch_inference.py:56
↓ 1 callersFunctionmain
()
SPHINX/inference.py:8
↓ 1 callersFunctionmain
Trains a new DiT model.
Large-DiT-T2I/train.py:269
↓ 1 callersFunctionmain
()
Large-DiT-T2I/demo.py:173
↓ 1 callersFunctionmain
(args)
accessory/main_finetune.py:141
↓ 1 callersFunctionmain
(args)
accessory/main_pretrain.py:125
↓ 1 callersFunctionmain
()
accessory/tools/download.py:82
↓ 1 callersFunctionmain
()
accessory/tools/convert_weights_to_hf.py:358
↓ 1 callersFunctionmain
(model, image_path, instruction)
accessory/demos/multi_model_cli.py:19
↓ 1 callersFunctionmerge_weights_and_save
(original_model, delta_weights, num, max_num)
accessory/tools/weight_operate.py:38
↓ 1 callersFunctionmodel_worker
(port: int, rank:int, world_size: int)
accessory/model/multi_gpu_wrapper.py:49
↓ 1 callersMethodp_sample
Sample x_{t-1} from the model at the given timestep. :param model: the model to sample from. :param x: the current tensor at
Large-DiT-ImageNet/diffusion/gaussian_diffusion.py:376
↓ 1 callersMethodp_sample
Sample x_{t-1} from the model at the given timestep. :param model: the model to sample from. :param x: the current tensor at
Large-DiT-T2I/diffusion/gaussian_diffusion.py:376
↓ 1 callersMethodp_sample_loop
Generate samples from the model. :param model: the model module. :param shape: the shape of the samples, (N, C, H, W).
Large-DiT-ImageNet/diffusion/gaussian_diffusion.py:420
↓ 1 callersMethodp_sample_loop
Generate samples from the model. :param model: the model module. :param shape: the shape of the samples, (N, C, H, W).
Large-DiT-T2I/diffusion/gaussian_diffusion.py:420
↓ 1 callersMethodp_sample_loop_progressive
Generate samples from the model and yield intermediate samples from each timestep of diffusion. Arguments are the same as p_s
Large-DiT-ImageNet/diffusion/gaussian_diffusion.py:465
↓ 1 callersMethodp_sample_loop_progressive
Generate samples from the model and yield intermediate samples from each timestep of diffusion. Arguments are the same as p_s
Large-DiT-T2I/diffusion/gaussian_diffusion.py:465
↓ 1 callersMethodparameter_count
(self)
Large-DiT-ImageNet/models.py:625
↓ 1 callersMethodparameter_count
(self)
Large-DiT-T2I/models/model.py:715
↓ 1 callersFunctionparse_pred_ans
(pred_ans)
accessory/eval_mm/utils/metric.py:252
↓ 1 callersFunctionparse_score
(review)
light-eval/src/eval_llavabenchmark.py:203
↓ 1 callersMethodpatchify
(self, x: torch.Tensor)
Large-DiT-ImageNet/models.py:542
↓ 1 callersMethodpatchify_and_embed
(self, x: List[torch.Tensor] | torch.Tensor)
Large-DiT-T2I/models/model.py:599
↓ 1 callersMethodprecompute_freqs_cis
Precompute the frequency tensor for complex exponentials (cis) with given dimensions. This function calculates a frequency t
Large-DiT-ImageNet/models.py:597
↓ 1 callersMethodprecompute_freqs_cis
Precompute the frequency tensor for complex exponentials (cis) with given dimensions. This function calculates a frequency t
Large-DiT-T2I/models/model.py:686
↓ 1 callersMethodpreprocess
(self, meta_l:List[Dict], recipe: str)
accessory/data/alpaca.py:217
↓ 1 callersFunctionprobe_tokenizer_path_from_pretrained
(pretrained_path: str)
accessory/model/tokenizer.py:134
↓ 1 callersMethodprocessDigitArticle
(self, inText)
accessory/eval_mm/utils/vqa_eval.py:274
↓ 1 callersMethodprocess_item
(self, data_item, training_mode=False)
Large-DiT-T2I/data/dataset.py:31
↓ 1 callersMethodq_mean_variance
Get the distribution q(x_t | x_0). :param x_start: the [N x C x ...] tensor of noiseless inputs. :param t: the number of diff
Large-DiT-ImageNet/diffusion/gaussian_diffusion.py:203
↓ 1 callersMethodq_mean_variance
Get the distribution q(x_t | x_0). :param x_start: the [N x C x ...] tensor of noiseless inputs. :param t: the number of diff
Large-DiT-T2I/diffusion/gaussian_diffusion.py:203
↓ 1 callersFunctionrandom_seed
(seed=0)
accessory/util/misc.py:88
↓ 1 callersFunctionread_img_general
(img_path)
accessory/data/data_reader.py:6
↓ 1 callersFunctionremove_boxed
(s)
light-eval/src/eval_math.py:81
↓ 1 callersFunctionremove_right_units
(string)
light-eval/src/eval_utils/math_util.py:139
↓ 1 callersMethodreset
(self)
accessory/eval_mm/utils/metric.py:99
↓ 1 callersMethodreset
(self)
accessory/eval_mm/utils/metric.py:177
↓ 1 callersMethodreset_parameters
(self)
accessory/model/LLM/internlm.py:232
↓ 1 callersMethodreshape_for_broadcast
Reshape frequency tensor for broadcasting it with another tensor. This function reshapes the frequency tensor to have the same shape
Large-DiT-ImageNet/models.py:190
↓ 1 callersMethodreshape_for_broadcast
Reshape frequency tensor for broadcasting it with another tensor. This function reshapes the frequency tensor to have the same shape
Large-DiT-T2I/models/model.py:207
↓ 1 callersFunctionresize_prompt
(tokenizer, model_max_context, prompt)
light-eval/src/eval_math.py:119
↓ 1 callersFunctionresize_prompt
(tokenizer, model_max_context, prompt)
light-eval/src/eval_bbh.py:128
↓ 1 callersFunctionresize_prompt
(tokenizer, model_max_context, prompt)
light-eval/src/eval_cmmlu.py:143
↓ 1 callersFunctionresize_prompt
(tokenizer, model_max_context, prompt)
light-eval/src/eval_mmlu.py:128
↓ 1 callersFunctionresize_prompt
(tokenizer, model_max_context, prompt)
light-eval/src/eval_ceval.py:135
↓ 1 callersFunctionresize_prompt
(tokenizer, model_max_context, prompt)
light-eval/src/eval_gsm8k.py:138
↓ 1 callersMethodrun
(self)
accessory/eval_mm/utils/math_utils.py:55
↓ 1 callersFunctionrun_eval
(infer_path)
light-eval/src/eval_math.py:174
↓ 1 callersFunctionrun_eval
(tasks, infer_path)
light-eval/src/eval_mmlu.py:187
↓ 1 callersFunctionrun_eval
(infer_path)
light-eval/src/eval_gsm8k.py:193
↓ 1 callersFunctionrun_infer
(model, max_seq_len, data_path, infer_path, overwrite = False)
light-eval/src/eval_math.py:128
↓ 1 callersFunctionrun_infer
( model:MetaModel, infer_file: str, overwrite: bool = False, num_samples_per_task: int = 10,
light-eval/src/eval_humaneval.py:125
↓ 1 callersFunctionrun_infer
(model, max_seq_len, tasks, infer_path, ntrain=5, overwrite = False)
light-eval/src/eval_mmlu.py:137
↓ 1 callersFunctionrun_infer
(model, max_seq_len, data_path, infer_path, overwrite = False)
light-eval/src/eval_gsm8k.py:147
↓ 1 callersFunctionrun_infer_eval
(model, max_seq_len, data_path, ntrain=-1, few_shot = True)
light-eval/src/eval_cmmlu.py:152
↓ 1 callersFunctionrun_infer_eval
(model, max_seq_len, data_path, ntrain=-1, few_shot = True)
light-eval/src/eval_ceval.py:144
↓ 1 callersMethodsample
Importance-sample timesteps for a batch. :param batch_size: the number of timesteps. :param device: the torch device to save
Large-DiT-ImageNet/diffusion/timestep_sampler.py:44
↓ 1 callersFunctionsave_json
(file_path, data)
accessory/eval_mm/infographicsvqa_eval.py:14
↓ 1 callersFunctionscale_grad
(model: nn.Module, factor: float)
Large-DiT-ImageNet/grad_norm.py:55
↓ 1 callersFunctionscale_grad
(model: nn.Module, factor: float)
Large-DiT-T2I/grad_norm.py:55
↓ 1 callersMethodsetAccuracy
(self, accQA, accQuesType, accAnsType)
accessory/eval_mm/utils/vqa_eval.py:289
↓ 1 callersMethodsetEvalAnsType
(self, quesId, ansType, acc)
accessory/eval_mm/utils/vqa_eval.py:315
↓ 1 callersMethodsetEvalQA
(self, quesId, acc)
accessory/eval_mm/utils/vqa_eval.py:307
↓ 1 callersMethodsetEvalQuesType
(self, quesId, quesType, acc)
accessory/eval_mm/utils/vqa_eval.py:310
↓ 1 callersMethodset_epoch
(self, epoch)
accessory/data/falcon.py:41
↓ 1 callersFunctionsetup_dist_env_from_slurm
(args)
Large-DiT-ImageNet/train.py:137
↓ 1 callersFunctionsetup_lm_fsdp_sync
(model: nn.Module)
Large-DiT-T2I/train.py:160
↓ 1 callersFunctionsetup_mixed_precision
(args)
Large-DiT-ImageNet/train.py:183
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