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Respect batch size in training lm model.

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This commit is contained in:
Piotr Czapla committed 2018-12-06 23:29:43 +01:00
1 parent 6a899015ed
commit 4ae2a158a2
1 file changed
+6 -4
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ulmfit/pretrain_lm.py
+6 -4
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@@ -228,7 +228,7 @@ class LMHyperParams:
lm_type=self.lm_type)
elif self.tokenizer is Tokenizers.MOSES_FA:
try:
data_lm = TextLMDataBunch.load(self.cache_dir, '.', lm_type=self.lm_type)
data_lm = TextLMDataBunch.load(self.cache_dir, '.', lm_type=self.lm_type, bs=self.bs)
print("Tokenized data loaded")
except FileNotFoundError:
print("Running tokenization")
@@ -238,16 +238,18 @@ class LMHyperParams:
data_lm = TextLMDataBunch.from_df(path=self.cache_dir, train_df=read_file(trn_path),
valid_df=read_file(val_path), tokenizer=pretokenized,
test_df=read_file(tst_path), classes=None, lm_type=self.lm_type,
max_vocab=self.max_vocab)
max_vocab=self.max_vocab, bs=self.bs)
data_lm.save('.')
elif self.tokenizer is Tokenizers.FASTAI:
try:
data_lm = TextLMDataBunch.load(self.cache_dir, '.', lm_type=self.lm_type)
data_lm = TextLMDataBunch.load(self.cache_dir, '.', lm_type=self.lm_type, bs=self.bs)
print("Tokenized data loaded")
except FileNotFoundError:
print("Running tokenization")
data_lm = TextLMDataBunch.from_df(path=self.cache_dir, train_df=read_file(trn_path), valid_df=read_file(val_path),
test_df=read_file(tst_path), classes=None, lm_type=self.lm_type, max_vocab=self.max_vocab,)
test_df=read_file(tst_path), classes=None, lm_type=self.lm_type,
max_vocab=self.max_vocab,bs=self.bs,
)
data_lm.save('.')
else:
raise ValueError(f"self.tokenizer has wrong value {self.tokenizer}, Allowed values are taken from {Tokenizers}")