text stringlengths 1 1.02k | class_index int64 0 10.8k | source stringlengths 85 188 |
|---|---|---|
class TFRobertaPreLayerNormForCausalLM(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,379 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFRobertaPreLayerNormForMaskedLM(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,380 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFRobertaPreLayerNormForMultipleChoice(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,381 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFRobertaPreLayerNormForQuestionAnswering(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,382 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFRobertaPreLayerNormForSequenceClassification(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,383 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFRobertaPreLayerNormForTokenClassification(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,384 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFRobertaPreLayerNormMainLayer(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,385 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFRobertaPreLayerNormModel(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,386 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFRobertaPreLayerNormPreTrainedModel(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,387 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFRoFormerForCausalLM(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,388 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFRoFormerForMaskedLM(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,389 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFRoFormerForMultipleChoice(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,390 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFRoFormerForQuestionAnswering(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,391 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFRoFormerForSequenceClassification(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,392 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFRoFormerForTokenClassification(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,393 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFRoFormerModel(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,394 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFRoFormerPreTrainedModel(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,395 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFSamModel(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,396 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFSamPreTrainedModel(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,397 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFSegformerDecodeHead(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,398 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFSegformerForImageClassification(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,399 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFSegformerForSemanticSegmentation(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,400 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFSegformerModel(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,401 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFSegformerPreTrainedModel(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,402 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFSpeech2TextForConditionalGeneration(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,403 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFSpeech2TextModel(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,404 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFSpeech2TextPreTrainedModel(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,405 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFSwiftFormerForImageClassification(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,406 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFSwiftFormerModel(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,407 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFSwiftFormerPreTrainedModel(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,408 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFSwinForImageClassification(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,409 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFSwinForMaskedImageModeling(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,410 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFSwinModel(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,411 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFSwinPreTrainedModel(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,412 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFT5EncoderModel(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,413 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFT5ForConditionalGeneration(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,414 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFT5Model(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,415 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFT5PreTrainedModel(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,416 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFTapasForMaskedLM(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,417 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFTapasForQuestionAnswering(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,418 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFTapasForSequenceClassification(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,419 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFTapasModel(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,420 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFTapasPreTrainedModel(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,421 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFVisionEncoderDecoderModel(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,422 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFVisionTextDualEncoderModel(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,423 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFViTForImageClassification(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,424 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFViTModel(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,425 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFViTPreTrainedModel(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,426 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFViTMAEForPreTraining(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,427 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFViTMAEModel(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,428 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFViTMAEPreTrainedModel(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,429 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFWav2Vec2ForCTC(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,430 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFWav2Vec2ForSequenceClassification(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,431 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFWav2Vec2Model(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,432 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFWav2Vec2PreTrainedModel(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,433 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFWhisperForConditionalGeneration(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,434 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFWhisperModel(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,435 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFWhisperPreTrainedModel(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,436 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFXGLMForCausalLM(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,437 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFXGLMModel(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,438 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFXGLMPreTrainedModel(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,439 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFXLMForMultipleChoice(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,440 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFXLMForQuestionAnsweringSimple(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,441 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFXLMForSequenceClassification(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,442 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFXLMForTokenClassification(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,443 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFXLMMainLayer(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,444 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFXLMModel(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,445 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFXLMPreTrainedModel(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,446 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFXLMWithLMHeadModel(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,447 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFXLMRobertaForCausalLM(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,448 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFXLMRobertaForMaskedLM(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,449 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFXLMRobertaForMultipleChoice(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,450 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFXLMRobertaForQuestionAnswering(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,451 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFXLMRobertaForSequenceClassification(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,452 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFXLMRobertaForTokenClassification(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,453 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFXLMRobertaModel(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,454 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFXLMRobertaPreTrainedModel(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,455 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFXLNetForMultipleChoice(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,456 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFXLNetForQuestionAnsweringSimple(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,457 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFXLNetForSequenceClassification(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,458 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFXLNetForTokenClassification(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,459 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFXLNetLMHeadModel(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,460 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFXLNetMainLayer(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,461 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFXLNetModel(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,462 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TFXLNetPreTrainedModel(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,463 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class AdamWeightDecay(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,464 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class GradientAccumulator(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,465 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class WarmUp(metaclass=DummyObject):
_backends = ["tf"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tf"]) | 2,466 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_tf_objects.py |
class TypeHintParsingException(Exception):
"""Exception raised for errors in parsing type hints to generate JSON schemas"""
pass | 2,467 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/chat_template_utils.py |
class DocstringParsingException(Exception):
"""Exception raised for errors in parsing docstrings to generate JSON schemas"""
pass | 2,468 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/chat_template_utils.py |
class AssistantTracker(Extension):
# This extension is used to track the indices of assistant-generated tokens in the rendered chat
tags = {"generation"}
def __init__(self, environment: ImmutableSandboxedEnvironment):
# The class is only initiated by jinja.
super().__init__(environment)
environment.extend(activate_tracker=self.activate_tracker)
self._rendered_blocks = None
self._generation_indices = None
def parse(self, parser: jinja2.parser.Parser) -> jinja2.nodes.CallBlock:
lineno = next(parser.stream).lineno
body = parser.parse_statements(["name:endgeneration"], drop_needle=True)
return jinja2.nodes.CallBlock(self.call_method("_generation_support"), [], [], body).set_lineno(lineno) | 2,469 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/chat_template_utils.py |
@jinja2.pass_eval_context
def _generation_support(self, context: jinja2.nodes.EvalContext, caller: jinja2.runtime.Macro) -> str:
rv = caller()
if self.is_active():
# Only track generation indices if the tracker is active
start_index = len("".join(self._rendered_blocks))
end_index = start_index + len(rv)
self._generation_indices.append((start_index, end_index))
return rv
def is_active(self) -> bool:
return self._rendered_blocks or self._generation_indices
@contextmanager
def activate_tracker(self, rendered_blocks: List[int], generation_indices: List[int]):
try:
if self.is_active():
raise ValueError("AssistantTracker should not be reused before closed")
self._rendered_blocks = rendered_blocks
self._generation_indices = generation_indices | 2,469 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/chat_template_utils.py |
yield
finally:
self._rendered_blocks = None
self._generation_indices = None | 2,469 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/chat_template_utils.py |
class PushToHubMixin:
"""
A Mixin containing the functionality to push a model or tokenizer to the hub.
""" | 2,470 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/hub.py |
def _create_repo(
self,
repo_id: str,
private: Optional[bool] = None,
token: Optional[Union[bool, str]] = None,
repo_url: Optional[str] = None,
organization: Optional[str] = None,
) -> str:
"""
Create the repo if needed, cleans up repo_id with deprecated kwargs `repo_url` and `organization`, retrieves
the token.
"""
if repo_url is not None:
warnings.warn(
"The `repo_url` argument is deprecated and will be removed in v5 of Transformers. Use `repo_id` "
"instead."
)
if repo_id is not None:
raise ValueError(
"`repo_id` and `repo_url` are both specified. Please set only the argument `repo_id`."
)
repo_id = repo_url.replace(f"{HUGGINGFACE_CO_RESOLVE_ENDPOINT}/", "")
if organization is not None:
warnings.warn( | 2,470 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/hub.py |
"The `organization` argument is deprecated and will be removed in v5 of Transformers. Set your "
"organization directly in the `repo_id` passed instead (`repo_id={organization}/{model_id}`)."
)
if not repo_id.startswith(organization):
if "/" in repo_id:
repo_id = repo_id.split("/")[-1]
repo_id = f"{organization}/{repo_id}" | 2,470 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/hub.py |
url = create_repo(repo_id=repo_id, token=token, private=private, exist_ok=True)
return url.repo_id
def _get_files_timestamps(self, working_dir: Union[str, os.PathLike]):
"""
Returns the list of files with their last modification timestamp.
"""
return {f: os.path.getmtime(os.path.join(working_dir, f)) for f in os.listdir(working_dir)} | 2,470 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/hub.py |
def _upload_modified_files(
self,
working_dir: Union[str, os.PathLike],
repo_id: str,
files_timestamps: Dict[str, float],
commit_message: Optional[str] = None,
token: Optional[Union[bool, str]] = None,
create_pr: bool = False,
revision: str = None,
commit_description: str = None,
):
"""
Uploads all modified files in `working_dir` to `repo_id`, based on `files_timestamps`.
"""
if commit_message is None:
if "Model" in self.__class__.__name__:
commit_message = "Upload model"
elif "Config" in self.__class__.__name__:
commit_message = "Upload config"
elif "Tokenizer" in self.__class__.__name__:
commit_message = "Upload tokenizer"
elif "FeatureExtractor" in self.__class__.__name__:
commit_message = "Upload feature extractor"
elif "Processor" in self.__class__.__name__: | 2,470 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/hub.py |
commit_message = "Upload processor"
else:
commit_message = f"Upload {self.__class__.__name__}"
modified_files = [
f
for f in os.listdir(working_dir)
if f not in files_timestamps or os.path.getmtime(os.path.join(working_dir, f)) > files_timestamps[f]
] | 2,470 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/hub.py |
# filter for actual files + folders at the root level
modified_files = [
f
for f in modified_files
if os.path.isfile(os.path.join(working_dir, f)) or os.path.isdir(os.path.join(working_dir, f))
]
operations = []
# upload standalone files
for file in modified_files:
if os.path.isdir(os.path.join(working_dir, file)):
# go over individual files of folder
for f in os.listdir(os.path.join(working_dir, file)):
operations.append(
CommitOperationAdd(
path_or_fileobj=os.path.join(working_dir, file, f), path_in_repo=os.path.join(file, f)
)
)
else:
operations.append(
CommitOperationAdd(path_or_fileobj=os.path.join(working_dir, file), path_in_repo=file)
) | 2,470 | /Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/hub.py |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.