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Functions226 in github.com/WillDreamer/Aurora

Functionlevel_to_args
(level)
transform/randaugment.py:203
Methodload_decompress_img_from_lmdb_value
Args: lmdb_value: image binary from with open(filepath, "rb") as f: lmdb_valu
data/vqa_dataset.py:94
Methodload_pretrained
(self, checkpoint_path, prefix='')
CP/vit.py:247
Methodno_weight_decay
(self)
CP/vit.py:224
Methodno_weight_decay
(self)
CP/med.py:493
Functionnone_level_to_args
(level)
transform/randaugment.py:241
Functionposterize_func
same output as PIL.ImageOps.posterize
transform/randaugment.py:173
Methodprepare_inputs_for_generation
(self, input_ids, past=None, attention_mask=None, **model_kwargs)
CP/med.py:1060
Functionrotate_func
like PIL, rotate by degree, not radians
transform/randaugment.py:66
Methodsave_attention_map
(self, attention_map)
CP/vit.py:86
Methodsave_attn_gradients
(self, attn_gradients)
CP/vit.py:80
Methodsave_attn_gradients
(self, attn_gradients)
CP/med.py:140
Functionsave_on_master
(*args, **kwargs)
utils.py:251
Methodset_input_embeddings
(self, value)
CP/med.py:717
Methodset_output_embeddings
(self, new_embeddings)
CP/med.py:949
Functionsharpness_func
The differences the this result and PIL are all on the 4 boundaries, the center areas are same
transform/randaugment.py:125
Functionshear_x_func
(img, factor, fill=(0, 0, 0))
transform/randaugment.py:146
Functionshear_y_func
(img, factor, fill=(0, 0, 0))
transform/randaugment.py:181
Functionsolarize_func
same output as PIL.ImageOps.posterize
transform/randaugment.py:77
Functionstep_lr_schedule
Decay the learning rate
utils.py:15
Methodsynchronize_between_processes
Warning: does not synchronize the deque!
utils.py:49
Functiontranslate_x_func
same output as PIL.Image.transform
transform/randaugment.py:153
Functiontranslate_y_func
same output as PIL.Image.transform
transform/randaugment.py:163
Functionvqa_collate_fn
(batch)
data/videovqa_dataset.py:106
Functionvqa_collate_fn
(batch)
data/vqa_dataset.py:109
Functionwarmup_lr_schedule
Warmup the learning rate
utils.py:9
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