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class RecurrentGemmaPreTrainedModel(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,586 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class ReformerForMaskedLM(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,587 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class ReformerForQuestionAnswering(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,588 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class ReformerForSequenceClassification(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,589 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class ReformerModel(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,590 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class ReformerModelWithLMHead(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,591 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class ReformerPreTrainedModel(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,592 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class RegNetForImageClassification(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,593 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class RegNetModel(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,594 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class RegNetPreTrainedModel(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,595 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class RemBertForCausalLM(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,596 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class RemBertForMaskedLM(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,597 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class RemBertForMultipleChoice(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,598 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class RemBertForQuestionAnswering(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,599 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class RemBertForSequenceClassification(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,600 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class RemBertForTokenClassification(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,601 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class RemBertModel(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,602 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class RemBertPreTrainedModel(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,603 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class ResNetBackbone(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,604 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class ResNetForImageClassification(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,605 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class ResNetModel(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,606 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class ResNetPreTrainedModel(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,607 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class RobertaForCausalLM(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,608 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class RobertaForMaskedLM(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,609 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class RobertaForMultipleChoice(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,610 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class RobertaForQuestionAnswering(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,611 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class RobertaForSequenceClassification(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,612 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class RobertaForTokenClassification(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,613 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class RobertaModel(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,614 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class RobertaPreTrainedModel(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,615 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class RobertaPreLayerNormForCausalLM(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,616 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class RobertaPreLayerNormForMaskedLM(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,617 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class RobertaPreLayerNormForMultipleChoice(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,618 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class RobertaPreLayerNormForQuestionAnswering(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,619 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class RobertaPreLayerNormForSequenceClassification(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,620 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class RobertaPreLayerNormForTokenClassification(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,621 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class RobertaPreLayerNormModel(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,622 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class RobertaPreLayerNormPreTrainedModel(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,623 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class RoCBertForCausalLM(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,624 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class RoCBertForMaskedLM(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,625 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class RoCBertForMultipleChoice(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,626 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class RoCBertForPreTraining(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,627 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class RoCBertForQuestionAnswering(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,628 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class RoCBertForSequenceClassification(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,629 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class RoCBertForTokenClassification(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,630 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class RoCBertModel(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,631 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class RoCBertPreTrainedModel(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,632 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class RoFormerForCausalLM(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,633 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class RoFormerForMaskedLM(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,634 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class RoFormerForMultipleChoice(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,635 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class RoFormerForQuestionAnswering(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,636 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class RoFormerForSequenceClassification(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,637 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class RoFormerForTokenClassification(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,638 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class RoFormerModel(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,639 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class RoFormerPreTrainedModel(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,640 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class RTDetrForObjectDetection(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,641 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class RTDetrModel(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,642 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class RTDetrPreTrainedModel(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,643 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class RTDetrResNetBackbone(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,644 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class RTDetrResNetPreTrainedModel(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,645 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class RwkvForCausalLM(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,646 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class RwkvModel(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,647 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class RwkvPreTrainedModel(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,648 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class SamModel(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,649 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class SamPreTrainedModel(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,650 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class SeamlessM4TCodeHifiGan(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,651 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class SeamlessM4TForSpeechToSpeech(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,652 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class SeamlessM4TForSpeechToText(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,653 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class SeamlessM4TForTextToSpeech(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,654 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class SeamlessM4TForTextToText(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,655 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class SeamlessM4THifiGan(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,656 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class SeamlessM4TModel(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,657 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class SeamlessM4TPreTrainedModel(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,658 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class SeamlessM4TTextToUnitForConditionalGeneration(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,659 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class SeamlessM4TTextToUnitModel(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,660 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class SeamlessM4Tv2ForSpeechToSpeech(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,661 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class SeamlessM4Tv2ForSpeechToText(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,662 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class SeamlessM4Tv2ForTextToSpeech(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,663 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class SeamlessM4Tv2ForTextToText(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,664 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class SeamlessM4Tv2Model(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,665 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class SeamlessM4Tv2PreTrainedModel(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,666 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class SegformerDecodeHead(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,667 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class SegformerForImageClassification(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,668 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class SegformerForSemanticSegmentation(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,669 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class SegformerModel(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,670 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class SegformerPreTrainedModel(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,671 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class SegGptForImageSegmentation(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,672 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class SegGptModel(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,673 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class SegGptPreTrainedModel(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,674 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class SEWForCTC(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,675 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class SEWForSequenceClassification(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,676 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class SEWModel(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,677 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class SEWPreTrainedModel(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,678 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class SEWDForCTC(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,679 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class SEWDForSequenceClassification(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,680 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class SEWDModel(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,681 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class SEWDPreTrainedModel(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,682 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class SiglipForImageClassification(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,683 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class SiglipModel(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,684 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
class SiglipPreTrainedModel(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
| 1,685 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
|
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