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Fix minor typos in train_clas

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This commit is contained in:
Nirant K
2018-11-15 18:04:15 +00:00
parent 56fc150eb1
commit 43340d03bc
2 changed files with 14 additions and 8 deletions
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fastai_contrib/utils.py
+1 -1
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@@ -67,7 +67,7 @@ def prepare_imdb(file_path: str, prepare_lm = False):
assert dir_path.exists()
print(f"Extracted to {dir_path}")
CLAS_PATH = dir_path / 'imdb_clas'
CLAS_PATH = dir_path
CLAS_PATH.mkdir(exist_ok=True)
LM_PATH = dir_path /'imdb_lm'
ulmfit/train_clas.py
+13 -7
View File
@@ -16,8 +16,9 @@ from collections import Counter
from pathlib import Path
def new_train_clas(data_dir, lang='en', cuda_id=0, pretrain_name='wt-103', model_dir='models', qrnn=True,
fine_tune=True, max_vocab=30000, bs=70, bptt=70, name='imdb-clas',
def new_train_clas(data_dir, lang='en', cuda_id=0, pretrain_name='wt103', model_dir='models',
qrnn=False,
fine_tune=True, max_vocab=30000, bs=20, bptt=70, name='imdb-clas',
dataset='imdb'):
"""
:param data_dir: The path to the `data` directory
@@ -95,13 +96,13 @@ def new_train_clas(data_dir, lang='en', cuda_id=0, pretrain_name='wt-103', model
print(f'Train size: {len(ids[TRN])}. Valid size: {len(ids[VAL])}. '
f'Test size: {len(ids[TST])}.')
data_lm = TextLMDataBunch.from_ids(path=tmp_dir, vocab=vocab, trn_ids=ids[TRN],
val_ids=ids[VAL], bs=bs, bptt=bptt)
data_lm = TextLMDataBunch.from_ids(path=tmp_dir, vocab=vocab, train_ids=ids[TRN],
valid_ids=ids[VAL], bs=bs, bptt=bptt)
# TODO TextClasDataBunch allows tst_ids as input, but not tst_lbls?
data_clas = TextClasDataBunch.from_ids(
path=tmp_dir, vocab=vocab, trn_ids=ids[TRN], val_ids=ids[VAL],
trn_lbls=lbls[TRN], val_lbls=lbls[VAL], bs=bs)
path=tmp_dir, vocab=vocab, train_ids=ids[TRN], valid_ids=ids[VAL],
train_lbls=lbls[TRN], valid_lbls=lbls[VAL], bs=bs)
if qrnn:
emb_sz, nh, nl = 400, 1550, 3
@@ -113,7 +114,7 @@ def new_train_clas(data_dir, lang='en', cuda_id=0, pretrain_name='wt-103', model
pretrained_fnames=(f'lstm_{pretrain_name}', f'itos_{pretrain_name}'),
path=model_dir.parent, model_dir=model_dir.name)
if fine_tune:
if fine_tune and not (model_dir / "enc.pth").exists():
print('Fine-tuning the language model...')
learn.unfreeze()
learn.fit(2, slice(1e-4, 1e-2))
@@ -121,16 +122,21 @@ def new_train_clas(data_dir, lang='en', cuda_id=0, pretrain_name='wt-103', model
# save encoder
learn.save_encoder('enc')
print("Starting classifier training")
learn = text_classifier_learner(data_clas, bptt=bptt, pad_token=PAD_TOKEN_ID,
path=model_dir.parent, model_dir=model_dir.name,
qrnn=qrnn, emb_sz=emb_sz, nh=nh, nl=nl)
learn.load_encoder('enc')
torch.cuda.empty_cache()
fit_one_cycle(learn, 1, 5e-3, (0.8, 0.7), wd=1e-7)
torch.cuda.empty_cache()
learn.freeze_to(-2)
fit_one_cycle(learn, 1, 5e-3, (0.8, 0.7), wd=1e-7)
torch.cuda.empty_cache()
learn.unfreeze()
fit_one_cycle(learn, 10, 5e-3, (0.8, 0.7), wd=1e-7)