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class XLMRobertaForMaskedLM(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
|
class_definition
| 242,426 | 242,588 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
| null | 1,900 |
class XLMRobertaForMultipleChoice(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
|
class_definition
| 242,591 | 242,759 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
| null | 1,901 |
class XLMRobertaForQuestionAnswering(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
|
class_definition
| 242,762 | 242,933 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
| null | 1,902 |
class XLMRobertaForSequenceClassification(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
|
class_definition
| 242,936 | 243,112 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
| null | 1,903 |
class XLMRobertaForTokenClassification(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
|
class_definition
| 243,115 | 243,288 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
| null | 1,904 |
class XLMRobertaModel(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
|
class_definition
| 243,291 | 243,447 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
| null | 1,905 |
class XLMRobertaPreTrainedModel(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
|
class_definition
| 243,450 | 243,616 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
| null | 1,906 |
class XLMRobertaXLForCausalLM(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
|
class_definition
| 243,619 | 243,783 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
| null | 1,907 |
class XLMRobertaXLForMaskedLM(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
|
class_definition
| 243,786 | 243,950 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
| null | 1,908 |
class XLMRobertaXLForMultipleChoice(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
|
class_definition
| 243,953 | 244,123 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
| null | 1,909 |
class XLMRobertaXLForQuestionAnswering(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
|
class_definition
| 244,126 | 244,299 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
| null | 1,910 |
class XLMRobertaXLForSequenceClassification(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
|
class_definition
| 244,302 | 244,480 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
| null | 1,911 |
class XLMRobertaXLForTokenClassification(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
|
class_definition
| 244,483 | 244,658 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
| null | 1,912 |
class XLMRobertaXLModel(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
|
class_definition
| 244,661 | 244,819 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
| null | 1,913 |
class XLMRobertaXLPreTrainedModel(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
|
class_definition
| 244,822 | 244,990 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
| null | 1,914 |
class XLNetForMultipleChoice(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
|
class_definition
| 244,993 | 245,156 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
| null | 1,915 |
class XLNetForQuestionAnswering(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
|
class_definition
| 245,159 | 245,325 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
| null | 1,916 |
class XLNetForQuestionAnsweringSimple(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
|
class_definition
| 245,328 | 245,500 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
| null | 1,917 |
class XLNetForSequenceClassification(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
|
class_definition
| 245,503 | 245,674 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
| null | 1,918 |
class XLNetForTokenClassification(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
|
class_definition
| 245,677 | 245,845 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
| null | 1,919 |
class XLNetLMHeadModel(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
|
class_definition
| 245,848 | 246,005 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
| null | 1,920 |
class XLNetModel(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
|
class_definition
| 246,008 | 246,159 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
| null | 1,921 |
class XLNetPreTrainedModel(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
|
class_definition
| 246,162 | 246,323 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
| null | 1,922 |
class XmodForCausalLM(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
|
class_definition
| 246,434 | 246,590 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
| null | 1,923 |
class XmodForMaskedLM(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
|
class_definition
| 246,593 | 246,749 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
| null | 1,924 |
class XmodForMultipleChoice(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
|
class_definition
| 246,752 | 246,914 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
| null | 1,925 |
class XmodForQuestionAnswering(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
|
class_definition
| 246,917 | 247,082 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
| null | 1,926 |
class XmodForSequenceClassification(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
|
class_definition
| 247,085 | 247,255 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
| null | 1,927 |
class XmodForTokenClassification(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
|
class_definition
| 247,258 | 247,425 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
| null | 1,928 |
class XmodModel(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
|
class_definition
| 247,428 | 247,578 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
| null | 1,929 |
class XmodPreTrainedModel(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
|
class_definition
| 247,581 | 247,741 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
| null | 1,930 |
class YolosForObjectDetection(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
|
class_definition
| 247,744 | 247,908 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
| null | 1,931 |
class YolosModel(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
|
class_definition
| 247,911 | 248,062 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
| null | 1,932 |
class YolosPreTrainedModel(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
|
class_definition
| 248,065 | 248,226 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
| null | 1,933 |
class YosoForMaskedLM(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
|
class_definition
| 248,229 | 248,385 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
| null | 1,934 |
class YosoForMultipleChoice(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
|
class_definition
| 248,388 | 248,550 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
| null | 1,935 |
class YosoForQuestionAnswering(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
|
class_definition
| 248,553 | 248,718 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
| null | 1,936 |
class YosoForSequenceClassification(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
|
class_definition
| 248,721 | 248,891 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
| null | 1,937 |
class YosoForTokenClassification(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
|
class_definition
| 248,894 | 249,061 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
| null | 1,938 |
class YosoModel(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
|
class_definition
| 249,064 | 249,214 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
| null | 1,939 |
class YosoPreTrainedModel(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
|
class_definition
| 249,217 | 249,377 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
| null | 1,940 |
class ZambaForCausalLM(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
|
class_definition
| 249,380 | 249,537 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
| null | 1,941 |
class ZambaForSequenceClassification(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
|
class_definition
| 249,540 | 249,711 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
| null | 1,942 |
class ZambaModel(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
|
class_definition
| 249,714 | 249,865 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
| null | 1,943 |
class ZambaPreTrainedModel(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
|
class_definition
| 249,868 | 250,029 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
| null | 1,944 |
class ZoeDepthForDepthEstimation(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
|
class_definition
| 250,032 | 250,199 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
| null | 1,945 |
class ZoeDepthPreTrainedModel(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
|
class_definition
| 250,202 | 250,366 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
| null | 1,946 |
class Adafactor(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
|
class_definition
| 250,369 | 250,519 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
| null | 1,947 |
class AdamW(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
|
class_definition
| 250,522 | 250,668 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
| null | 1,948 |
class Conv1D(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
|
class_definition
| 251,733 | 251,880 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
| null | 1,949 |
class Trainer(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
|
class_definition
| 252,075 | 252,223 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
| null | 1,950 |
class Seq2SeqTrainer(metaclass=DummyObject):
_backends = ["torch"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torch"])
|
class_definition
| 252,342 | 252,497 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_pt_objects.py
| null | 1,951 |
class TFGPT2Tokenizer(metaclass=DummyObject):
_backends = ["keras_nlp"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["keras_nlp"])
|
class_definition
| 129 | 293 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_keras_nlp_objects.py
| null | 1,952 |
class MusicgenMelodyFeatureExtractor(metaclass=DummyObject):
_backends = ["torchaudio"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torchaudio"])
|
class_definition
| 129 | 310 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_torchaudio_objects.py
| null | 1,953 |
class MusicgenMelodyProcessor(metaclass=DummyObject):
_backends = ["torchaudio"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["torchaudio"])
|
class_definition
| 313 | 487 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_torchaudio_objects.py
| null | 1,954 |
class cached_property(property):
"""
Descriptor that mimics @property but caches output in member variable.
From tensorflow_datasets
Built-in in functools from Python 3.8.
"""
def __get__(self, obj, objtype=None):
# See docs.python.org/3/howto/descriptor.html#properties
if obj is None:
return self
if self.fget is None:
raise AttributeError("unreadable attribute")
attr = "__cached_" + self.fget.__name__
cached = getattr(obj, attr, None)
if cached is None:
cached = self.fget(obj)
setattr(obj, attr, cached)
return cached
|
class_definition
| 1,252 | 1,906 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/generic.py
| null | 1,955 |
class ModelOutput(OrderedDict):
"""
Base class for all model outputs as dataclass. Has a `__getitem__` that allows indexing by integer or slice (like a
tuple) or strings (like a dictionary) that will ignore the `None` attributes. Otherwise behaves like a regular
python dictionary.
<Tip warning={true}>
You can't unpack a `ModelOutput` directly. Use the [`~utils.ModelOutput.to_tuple`] method to convert it to a tuple
before.
</Tip>
"""
def __init_subclass__(cls) -> None:
"""Register subclasses as pytree nodes.
This is necessary to synchronize gradients when using `torch.nn.parallel.DistributedDataParallel` with
`static_graph=True` with modules that output `ModelOutput` subclasses.
"""
if is_torch_available():
if version.parse(get_torch_version()) >= version.parse("2.2"):
_torch_pytree.register_pytree_node(
cls,
_model_output_flatten,
partial(_model_output_unflatten, output_type=cls),
serialized_type_name=f"{cls.__module__}.{cls.__name__}",
)
else:
_torch_pytree._register_pytree_node(
cls,
_model_output_flatten,
partial(_model_output_unflatten, output_type=cls),
)
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
# Subclasses of ModelOutput must use the @dataclass decorator
# This check is done in __init__ because the @dataclass decorator operates after __init_subclass__
# issubclass() would return True for issubclass(ModelOutput, ModelOutput) when False is needed
# Just need to check that the current class is not ModelOutput
is_modeloutput_subclass = self.__class__ != ModelOutput
if is_modeloutput_subclass and not is_dataclass(self):
raise TypeError(
f"{self.__module__}.{self.__class__.__name__} is not a dataclasss."
" This is a subclass of ModelOutput and so must use the @dataclass decorator."
)
def __post_init__(self):
"""Check the ModelOutput dataclass.
Only occurs if @dataclass decorator has been used.
"""
class_fields = fields(self)
# Safety and consistency checks
if not len(class_fields):
raise ValueError(f"{self.__class__.__name__} has no fields.")
if not all(field.default is None for field in class_fields[1:]):
raise ValueError(f"{self.__class__.__name__} should not have more than one required field.")
first_field = getattr(self, class_fields[0].name)
other_fields_are_none = all(getattr(self, field.name) is None for field in class_fields[1:])
if other_fields_are_none and not is_tensor(first_field):
if isinstance(first_field, dict):
iterator = first_field.items()
first_field_iterator = True
else:
try:
iterator = iter(first_field)
first_field_iterator = True
except TypeError:
first_field_iterator = False
# if we provided an iterator as first field and the iterator is a (key, value) iterator
# set the associated fields
if first_field_iterator:
for idx, element in enumerate(iterator):
if (
not isinstance(element, (list, tuple))
or not len(element) == 2
or not isinstance(element[0], str)
):
if idx == 0:
# If we do not have an iterator of key/values, set it as attribute
self[class_fields[0].name] = first_field
else:
# If we have a mixed iterator, raise an error
raise ValueError(
f"Cannot set key/value for {element}. It needs to be a tuple (key, value)."
)
break
setattr(self, element[0], element[1])
if element[1] is not None:
self[element[0]] = element[1]
elif first_field is not None:
self[class_fields[0].name] = first_field
else:
for field in class_fields:
v = getattr(self, field.name)
if v is not None:
self[field.name] = v
def __delitem__(self, *args, **kwargs):
raise Exception(f"You cannot use ``__delitem__`` on a {self.__class__.__name__} instance.")
def setdefault(self, *args, **kwargs):
raise Exception(f"You cannot use ``setdefault`` on a {self.__class__.__name__} instance.")
def pop(self, *args, **kwargs):
raise Exception(f"You cannot use ``pop`` on a {self.__class__.__name__} instance.")
def update(self, *args, **kwargs):
raise Exception(f"You cannot use ``update`` on a {self.__class__.__name__} instance.")
def __getitem__(self, k):
if isinstance(k, str):
inner_dict = dict(self.items())
return inner_dict[k]
else:
return self.to_tuple()[k]
def __setattr__(self, name, value):
if name in self.keys() and value is not None:
# Don't call self.__setitem__ to avoid recursion errors
super().__setitem__(name, value)
super().__setattr__(name, value)
def __setitem__(self, key, value):
# Will raise a KeyException if needed
super().__setitem__(key, value)
# Don't call self.__setattr__ to avoid recursion errors
super().__setattr__(key, value)
def __reduce__(self):
if not is_dataclass(self):
return super().__reduce__()
callable, _args, *remaining = super().__reduce__()
args = tuple(getattr(self, field.name) for field in fields(self))
return callable, args, *remaining
def to_tuple(self) -> Tuple[Any]:
"""
Convert self to a tuple containing all the attributes/keys that are not `None`.
"""
return tuple(self[k] for k in self.keys())
|
class_definition
| 8,842 | 15,214 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/generic.py
| null | 1,956 |
class ExplicitEnum(str, Enum):
"""
Enum with more explicit error message for missing values.
"""
@classmethod
def _missing_(cls, value):
raise ValueError(
f"{value} is not a valid {cls.__name__}, please select one of {list(cls._value2member_map_.keys())}"
)
|
class_definition
| 16,194 | 16,500 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/generic.py
| null | 1,957 |
class PaddingStrategy(ExplicitEnum):
"""
Possible values for the `padding` argument in [`PreTrainedTokenizerBase.__call__`]. Useful for tab-completion in an
IDE.
"""
LONGEST = "longest"
MAX_LENGTH = "max_length"
DO_NOT_PAD = "do_not_pad"
|
class_definition
| 16,503 | 16,769 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/generic.py
| null | 1,958 |
class TensorType(ExplicitEnum):
"""
Possible values for the `return_tensors` argument in [`PreTrainedTokenizerBase.__call__`]. Useful for
tab-completion in an IDE.
"""
PYTORCH = "pt"
TENSORFLOW = "tf"
NUMPY = "np"
JAX = "jax"
MLX = "mlx"
|
class_definition
| 16,772 | 17,046 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/generic.py
| null | 1,959 |
class ContextManagers:
"""
Wrapper for `contextlib.ExitStack` which enters a collection of context managers. Adaptation of `ContextManagers`
in the `fastcore` library.
"""
def __init__(self, context_managers: List[ContextManager]):
self.context_managers = context_managers
self.stack = ExitStack()
def __enter__(self):
for context_manager in self.context_managers:
self.stack.enter_context(context_manager)
def __exit__(self, *args, **kwargs):
self.stack.__exit__(*args, **kwargs)
|
class_definition
| 17,049 | 17,604 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/generic.py
| null | 1,960 |
class LossKwargs(TypedDict, total=False):
"""
Keyword arguments to be passed to the loss function
Attributes:
num_items_in_batch (`int`, *optional*):
Number of items in the batch. It is recommended to pass it when
you are doing gradient accumulation.
"""
num_items_in_batch: Optional[int]
|
class_definition
| 28,105 | 28,447 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/generic.py
| null | 1,961 |
class ImageProcessingMixin(metaclass=DummyObject):
_backends = ["vision"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["vision"])
|
class_definition
| 129 | 292 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_vision_objects.py
| null | 1,962 |
class BaseImageProcessor(metaclass=DummyObject):
_backends = ["vision"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["vision"])
|
class_definition
| 295 | 456 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_vision_objects.py
| null | 1,963 |
class ImageFeatureExtractionMixin(metaclass=DummyObject):
_backends = ["vision"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["vision"])
|
class_definition
| 459 | 629 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_vision_objects.py
| null | 1,964 |
class AriaImageProcessor(metaclass=DummyObject):
_backends = ["vision"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["vision"])
|
class_definition
| 632 | 793 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_vision_objects.py
| null | 1,965 |
class BeitFeatureExtractor(metaclass=DummyObject):
_backends = ["vision"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["vision"])
|
class_definition
| 796 | 959 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_vision_objects.py
| null | 1,966 |
class BeitImageProcessor(metaclass=DummyObject):
_backends = ["vision"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["vision"])
|
class_definition
| 962 | 1,123 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_vision_objects.py
| null | 1,967 |
class BitImageProcessor(metaclass=DummyObject):
_backends = ["vision"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["vision"])
|
class_definition
| 1,126 | 1,286 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_vision_objects.py
| null | 1,968 |
class BlipImageProcessor(metaclass=DummyObject):
_backends = ["vision"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["vision"])
|
class_definition
| 1,289 | 1,450 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_vision_objects.py
| null | 1,969 |
class BridgeTowerImageProcessor(metaclass=DummyObject):
_backends = ["vision"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["vision"])
|
class_definition
| 1,453 | 1,621 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_vision_objects.py
| null | 1,970 |
class ChameleonImageProcessor(metaclass=DummyObject):
_backends = ["vision"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["vision"])
|
class_definition
| 1,624 | 1,790 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_vision_objects.py
| null | 1,971 |
class ChineseCLIPFeatureExtractor(metaclass=DummyObject):
_backends = ["vision"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["vision"])
|
class_definition
| 1,793 | 1,963 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_vision_objects.py
| null | 1,972 |
class ChineseCLIPImageProcessor(metaclass=DummyObject):
_backends = ["vision"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["vision"])
|
class_definition
| 1,966 | 2,134 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_vision_objects.py
| null | 1,973 |
class CLIPFeatureExtractor(metaclass=DummyObject):
_backends = ["vision"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["vision"])
|
class_definition
| 2,137 | 2,300 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_vision_objects.py
| null | 1,974 |
class CLIPImageProcessor(metaclass=DummyObject):
_backends = ["vision"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["vision"])
|
class_definition
| 2,303 | 2,464 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_vision_objects.py
| null | 1,975 |
class ConditionalDetrFeatureExtractor(metaclass=DummyObject):
_backends = ["vision"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["vision"])
|
class_definition
| 2,467 | 2,641 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_vision_objects.py
| null | 1,976 |
class ConditionalDetrImageProcessor(metaclass=DummyObject):
_backends = ["vision"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["vision"])
|
class_definition
| 2,644 | 2,816 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_vision_objects.py
| null | 1,977 |
class ConvNextFeatureExtractor(metaclass=DummyObject):
_backends = ["vision"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["vision"])
|
class_definition
| 2,819 | 2,986 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_vision_objects.py
| null | 1,978 |
class ConvNextImageProcessor(metaclass=DummyObject):
_backends = ["vision"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["vision"])
|
class_definition
| 2,989 | 3,154 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_vision_objects.py
| null | 1,979 |
class DeformableDetrFeatureExtractor(metaclass=DummyObject):
_backends = ["vision"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["vision"])
|
class_definition
| 3,157 | 3,330 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_vision_objects.py
| null | 1,980 |
class DeformableDetrImageProcessor(metaclass=DummyObject):
_backends = ["vision"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["vision"])
|
class_definition
| 3,333 | 3,504 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_vision_objects.py
| null | 1,981 |
class DeiTFeatureExtractor(metaclass=DummyObject):
_backends = ["vision"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["vision"])
|
class_definition
| 3,507 | 3,670 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_vision_objects.py
| null | 1,982 |
class DeiTImageProcessor(metaclass=DummyObject):
_backends = ["vision"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["vision"])
|
class_definition
| 3,673 | 3,834 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_vision_objects.py
| null | 1,983 |
class DetaImageProcessor(metaclass=DummyObject):
_backends = ["vision"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["vision"])
|
class_definition
| 3,837 | 3,998 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_vision_objects.py
| null | 1,984 |
class EfficientFormerImageProcessor(metaclass=DummyObject):
_backends = ["vision"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["vision"])
|
class_definition
| 4,001 | 4,173 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_vision_objects.py
| null | 1,985 |
class TvltImageProcessor(metaclass=DummyObject):
_backends = ["vision"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["vision"])
|
class_definition
| 4,176 | 4,337 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_vision_objects.py
| null | 1,986 |
class ViTHybridImageProcessor(metaclass=DummyObject):
_backends = ["vision"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["vision"])
|
class_definition
| 4,340 | 4,506 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_vision_objects.py
| null | 1,987 |
class DetrFeatureExtractor(metaclass=DummyObject):
_backends = ["vision"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["vision"])
|
class_definition
| 4,509 | 4,672 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_vision_objects.py
| null | 1,988 |
class DetrImageProcessor(metaclass=DummyObject):
_backends = ["vision"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["vision"])
|
class_definition
| 4,675 | 4,836 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_vision_objects.py
| null | 1,989 |
class DonutFeatureExtractor(metaclass=DummyObject):
_backends = ["vision"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["vision"])
|
class_definition
| 4,839 | 5,003 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_vision_objects.py
| null | 1,990 |
class DonutImageProcessor(metaclass=DummyObject):
_backends = ["vision"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["vision"])
|
class_definition
| 5,006 | 5,168 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_vision_objects.py
| null | 1,991 |
class DPTFeatureExtractor(metaclass=DummyObject):
_backends = ["vision"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["vision"])
|
class_definition
| 5,171 | 5,333 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_vision_objects.py
| null | 1,992 |
class DPTImageProcessor(metaclass=DummyObject):
_backends = ["vision"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["vision"])
|
class_definition
| 5,336 | 5,496 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_vision_objects.py
| null | 1,993 |
class EfficientNetImageProcessor(metaclass=DummyObject):
_backends = ["vision"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["vision"])
|
class_definition
| 5,499 | 5,668 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_vision_objects.py
| null | 1,994 |
class Emu3ImageProcessor(metaclass=DummyObject):
_backends = ["vision"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["vision"])
|
class_definition
| 5,671 | 5,832 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_vision_objects.py
| null | 1,995 |
class FlavaFeatureExtractor(metaclass=DummyObject):
_backends = ["vision"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["vision"])
|
class_definition
| 5,835 | 5,999 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_vision_objects.py
| null | 1,996 |
class FlavaImageProcessor(metaclass=DummyObject):
_backends = ["vision"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["vision"])
|
class_definition
| 6,002 | 6,164 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_vision_objects.py
| null | 1,997 |
class FlavaProcessor(metaclass=DummyObject):
_backends = ["vision"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["vision"])
|
class_definition
| 6,167 | 6,324 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_vision_objects.py
| null | 1,998 |
class FuyuImageProcessor(metaclass=DummyObject):
_backends = ["vision"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["vision"])
|
class_definition
| 6,327 | 6,488 | 0 |
/Users/nielsrogge/Documents/python_projecten/transformers/src/transformers/utils/dummy_vision_objects.py
| null | 1,999 |
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