| |
| from ..utils import DummyObject, requires_backends |
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| class TFForcedBOSTokenLogitsProcessor(metaclass=DummyObject): |
| _backends = ["tf"] |
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|
| def __init__(self, *args, **kwargs): |
| requires_backends(self, ["tf"]) |
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|
| class TFForcedEOSTokenLogitsProcessor(metaclass=DummyObject): |
| _backends = ["tf"] |
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| def __init__(self, *args, **kwargs): |
| requires_backends(self, ["tf"]) |
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|
| class TFForceTokensLogitsProcessor(metaclass=DummyObject): |
| _backends = ["tf"] |
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| def __init__(self, *args, **kwargs): |
| requires_backends(self, ["tf"]) |
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|
| class TFGenerationMixin(metaclass=DummyObject): |
| _backends = ["tf"] |
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| def __init__(self, *args, **kwargs): |
| requires_backends(self, ["tf"]) |
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|
| class TFLogitsProcessor(metaclass=DummyObject): |
| _backends = ["tf"] |
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| def __init__(self, *args, **kwargs): |
| requires_backends(self, ["tf"]) |
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|
| class TFLogitsProcessorList(metaclass=DummyObject): |
| _backends = ["tf"] |
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| def __init__(self, *args, **kwargs): |
| requires_backends(self, ["tf"]) |
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|
|
| class TFLogitsWarper(metaclass=DummyObject): |
| _backends = ["tf"] |
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| def __init__(self, *args, **kwargs): |
| requires_backends(self, ["tf"]) |
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|
|
| class TFMinLengthLogitsProcessor(metaclass=DummyObject): |
| _backends = ["tf"] |
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|
| def __init__(self, *args, **kwargs): |
| requires_backends(self, ["tf"]) |
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|
|
| class TFNoBadWordsLogitsProcessor(metaclass=DummyObject): |
| _backends = ["tf"] |
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| def __init__(self, *args, **kwargs): |
| requires_backends(self, ["tf"]) |
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|
|
| class TFNoRepeatNGramLogitsProcessor(metaclass=DummyObject): |
| _backends = ["tf"] |
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|
| def __init__(self, *args, **kwargs): |
| requires_backends(self, ["tf"]) |
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|
|
| class TFRepetitionPenaltyLogitsProcessor(metaclass=DummyObject): |
| _backends = ["tf"] |
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|
| def __init__(self, *args, **kwargs): |
| requires_backends(self, ["tf"]) |
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|
|
| class TFSuppressTokensAtBeginLogitsProcessor(metaclass=DummyObject): |
| _backends = ["tf"] |
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|
| def __init__(self, *args, **kwargs): |
| requires_backends(self, ["tf"]) |
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|
|
| class TFSuppressTokensLogitsProcessor(metaclass=DummyObject): |
| _backends = ["tf"] |
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|
| def __init__(self, *args, **kwargs): |
| requires_backends(self, ["tf"]) |
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|
|
| class TFTemperatureLogitsWarper(metaclass=DummyObject): |
| _backends = ["tf"] |
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|
| def __init__(self, *args, **kwargs): |
| requires_backends(self, ["tf"]) |
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|
|
| class TFTopKLogitsWarper(metaclass=DummyObject): |
| _backends = ["tf"] |
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|
| def __init__(self, *args, **kwargs): |
| requires_backends(self, ["tf"]) |
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|
|
| class TFTopPLogitsWarper(metaclass=DummyObject): |
| _backends = ["tf"] |
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|
| def __init__(self, *args, **kwargs): |
| requires_backends(self, ["tf"]) |
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|
|
| class KerasMetricCallback(metaclass=DummyObject): |
| _backends = ["tf"] |
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|
| def __init__(self, *args, **kwargs): |
| requires_backends(self, ["tf"]) |
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|
|
| class PushToHubCallback(metaclass=DummyObject): |
| _backends = ["tf"] |
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|
| def __init__(self, *args, **kwargs): |
| requires_backends(self, ["tf"]) |
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|
|
| class TFPreTrainedModel(metaclass=DummyObject): |
| _backends = ["tf"] |
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|
| def __init__(self, *args, **kwargs): |
| requires_backends(self, ["tf"]) |
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|
|
| class TFSequenceSummary(metaclass=DummyObject): |
| _backends = ["tf"] |
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|
| def __init__(self, *args, **kwargs): |
| requires_backends(self, ["tf"]) |
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|
|
| class TFSharedEmbeddings(metaclass=DummyObject): |
| _backends = ["tf"] |
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|
| def __init__(self, *args, **kwargs): |
| requires_backends(self, ["tf"]) |
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|
|
| def shape_list(*args, **kwargs): |
| requires_backends(shape_list, ["tf"]) |
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|
|
| class AdamWeightDecay(metaclass=DummyObject): |
| _backends = ["tf"] |
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|
| def __init__(self, *args, **kwargs): |
| requires_backends(self, ["tf"]) |
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|
|
| class GradientAccumulator(metaclass=DummyObject): |
| _backends = ["tf"] |
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|
| def __init__(self, *args, **kwargs): |
| requires_backends(self, ["tf"]) |
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|
|
| class WarmUp(metaclass=DummyObject): |
| _backends = ["tf"] |
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|
| def __init__(self, *args, **kwargs): |
| requires_backends(self, ["tf"]) |
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|
|
| def create_optimizer(*args, **kwargs): |
| requires_backends(create_optimizer, ["tf"]) |
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|
