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)

Thanks I just created wandb/wandb#355