Rainbowneko

Latest version: v1.4

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1.4

+ Fix python config bug of `_neko_cfg_`
+ Plugin hook support kwargs
+ Fix workflow runner

1.3.1

bug fix

1.3

Upgrade python config compiler.
python config file can support for full python syntax now.

python
neko_cfg compile this function
def steps_cfg():
return dict(
train_steps=1000,
save_steps=100,
)

neko_cfg
def config(low_vram=False):
if low_vram:
from bitsandbytes.optim import AdamW8bit
optimizer = AdamW8bit(_partial_=True, betas=(0.9, 0.99))
else:
import torch
optimizer = torch.optim.AdamW(_partial_=True, betas=(0.9, 0.99))


return dict(
exp_dir='exps',
**steps_cfg(), insert steps_cfg here
x=nn.Linear(1, 1),
optimizer=optimizer,
)


The compiled function:
python
def config(low_vram=False):
if low_vram:
from bitsandbytes.optim import AdamW8bit
optimizer = dict(_target_=AdamW8bit, _partial_=True, betas=(0.9, 0.99))
else:
import torch
optimizer = dict(
_target_=torch.optim.AdamW, _partial_=True, betas=(0.9, 0.99)
)
return dict(
exp_dir='exps',
_merge_1_=dict(_target_=steps_cfg),
x=dict(_target_=nn.Linear, _args_=[1, 1]),
optimizer=optimizer
)

1.2

+ webdataset support (stream dataset)
+ bugs fix

1.1

+ Add CacheableDataset
+ Add LMDB Dataset
+ key mapper skip_missing
+ workflow evaluator and previewer
+ Fix plugin loader
+ Modify EMA
+ Move `data` module out of train
+ Add resumer
+ Add contrastive bucket

1.0

First Stable Version
+ update LR schedule
+ all gradient accumulation steps as one global step. (N accumulation steps means batch_size*N, it is one step actually)
+ remake ckpt manager
* support model save/load
* support different source and format
+ onnx export/load support
+ remake model loader
+ update config of `MetricGroup` and `Handler`

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