For troubleshooting wandb

wandb_fastai_troubleshooting.py

from fastai.text import TextLMDataBunch as lmdb
from fastai.text.transform import Tokenizer
import pandas as pd
from pathlib import Path

small_df = pd.read_csv('https://storage.googleapis.com/issue_label_bot/pre_processed_data/processed_part0000.csv').head(1000)

stokenizer = Tokenizer(pre_rules=[pass_through], n_cpus=30)

spath = Path('lang_model_test/')

sdata_lm = lmdb.from_df(path=spath,
                        train_df=small_df,
                        valid_df=small_df,
                        text_cols='text',
                        tokenizer=stokenizer)

slearn = language_model_learner(data=sdata_lm,
                                arch=AWD_LSTM,
                                drop_mult=.5,
                                pretrained=False)

wandb.init()

escb = EarlyStoppingCallback(learn=slearn, patience=5)
smcb = SaveModelCallback(learn=slearn)
rpcb = ReduceLROnPlateauCallback(learn=slearn, patience=3)
sgcb = ShowGraph(learn=slearn)
wandcb = WandbCallback(learn=slearn, log='all', save_model=True, monitor='valid_loss')

scallbacks = [escb, smcb, rpcb, sgcb, wandcb]

slearn.fit_one_cycle(cyc_len=1,
                     max_lr=1e-2,
                     tot_epochs=10,
                     callbacks=scallbacks)

@lukas @raubitsj Here is the modification that I think should be made in this case to extract the criterion
borisdayma/client@d69319f

However it seems it does not affect anything (not even logged model) so I'm not exactly sure what's the purpose of graph.criterion…

criterion controls code that is effectively commented out currently. The change you provided would be helpful when we enable that feature. If you submit this as a PR it would be great to have a test for it otherwise we can capture this in an issue and address it later when the code is active.

Thanks I just created wandb/wandb#355