text stringlengths 1 1.02k | class_index int64 0 10.8k | source stringlengths 85 188 |
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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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