Fix AutoModel not loading model correctly due to config_class inconsistency
Browse filesThis fixes an issue when using AutoModel to instantiate the model where the config class instantiated with the model is from the transformers library instead of the model's module. This causes the instantiation to fail with the error below. See [this Github issue](https://github.com/huggingface/transformers/issues/31068) for more details.
```
Traceback (most recent call last):
model = AutoModel.from_pretrained("zhihan1996/DNA_bert_6", trust_remote_code=True)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File ".../lib/python3.11/site-packages/transformers/models/auto/auto_factory.py", line 560, in from_pretrained
cls.register(config.__class__, model_class, exist_ok=True)
File ".../lib/python3.11/site-packages/transformers/models/auto/auto_factory.py", line 586, in register
raise ValueError(
ValueError: The model class you are passing has a `config_class` attribute that is not consistent with the config class you passed (model has <class 'transformers.models.bert.configuration_bert.BertConfig'> and you passed <class 'transformers_modules.zhihan1996.DNA_bert_6.55e0c0eb7b734c8b9b77bc083bf89eb6fbda1341.configuration_bert.BertConfig'>. Fix one of those so they match!
```
- dnabert_layer.py +16 -0
@@ -9,22 +9,38 @@ from transformers.models.bert.modeling_bert import BertForPreTraining as Transfo
|
|
9 |
from transformers.models.bert.modeling_bert import BertPreTrainedModel
|
10 |
from transformers.modeling_outputs import SequenceClassifierOutput
|
11 |
|
|
|
|
|
12 |
|
13 |
class BertModel(TransformersBertModel):
|
|
|
|
|
|
|
14 |
def __init__(self, config):
|
15 |
super().__init__(config)
|
|
|
16 |
|
17 |
class BertForMaskedLM(TransformersBertForMaskedLM):
|
|
|
|
|
|
|
18 |
def __init__(self, config):
|
19 |
super().__init__(config)
|
|
|
20 |
|
21 |
class BertForPreTraining(TransformersBertForPreTraining):
|
|
|
|
|
|
|
22 |
def __init__(self, config):
|
23 |
super().__init__(config)
|
24 |
|
25 |
|
26 |
|
27 |
class DNABertForSequenceClassification(BertPreTrainedModel):
|
|
|
|
|
|
|
28 |
def __init__(self, config):
|
29 |
super().__init__(config)
|
30 |
self.num_labels = config.num_labels
|
|
|
9 |
from transformers.models.bert.modeling_bert import BertPreTrainedModel
|
10 |
from transformers.modeling_outputs import SequenceClassifierOutput
|
11 |
|
12 |
+
from .configuration_bert import BertConfig
|
13 |
+
|
14 |
|
15 |
class BertModel(TransformersBertModel):
|
16 |
+
|
17 |
+
config_class = BertConfig
|
18 |
+
|
19 |
def __init__(self, config):
|
20 |
super().__init__(config)
|
21 |
+
|
22 |
|
23 |
class BertForMaskedLM(TransformersBertForMaskedLM):
|
24 |
+
|
25 |
+
config_class = BertConfig
|
26 |
+
|
27 |
def __init__(self, config):
|
28 |
super().__init__(config)
|
29 |
+
|
30 |
|
31 |
class BertForPreTraining(TransformersBertForPreTraining):
|
32 |
+
|
33 |
+
config_class = BertConfig
|
34 |
+
|
35 |
def __init__(self, config):
|
36 |
super().__init__(config)
|
37 |
|
38 |
|
39 |
|
40 |
class DNABertForSequenceClassification(BertPreTrainedModel):
|
41 |
+
|
42 |
+
config_class = BertConfig
|
43 |
+
|
44 |
def __init__(self, config):
|
45 |
super().__init__(config)
|
46 |
self.num_labels = config.num_labels
|