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Generic utilities
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Tests if `x` is a `torch.Tensor` or `np.ndarray`.
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BaseOutput( a
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.
You can't unpack a [`BaseOutput`] directly. Use the [`~utils.BaseOutput.to_tuple`] method to convert it to a tuple
first.
r Nc ^ ^ [ 5 ( a SSKm[ SS5 ( aK TR R R T TR R R U U4S j5 gTR R R T TR R R U U4S jT R ST R 3S9 gg) zRegister 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.
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!S 2 &D%**-='(D$ &r c H [ SU R R S35 e)Nz$You cannot use ``__delitem__`` on a
instance. ExceptionrB r1 r= argskwargss r __delitem__BaseOutput.__delitem__` s# >t~~?V?V>WWabccr c H [ SU R R S35 e)Nz#You cannot use ``setdefault`` on a rO rP rR s r
setdefaultBaseOutput.setdefaultc s# =dnn>U>U=VV`abbr c H [ SU R R S35 e)Nz You cannot use ``pop`` on a rO rP rR s r popBaseOutput.popf s" 6t~~7N7N6OzZ[[r c H [ SU R R S35 e)Nz You cannot use ``update`` on a rO rP rR s r updateBaseOutput.updatei s# 9$..:Q:Q9RR\]^^r kc [ U[ 5 ( a [ U R 5 5 nX! $ U R 5 U $ r6 )r strrD rE to_tuple)r= r`
inner_dicts r __getitem__BaseOutput.__getitem__l s8 a djjl+J = ==?1% %r r9 rJ c n > XR 5 ; a Ub [ TU ] X5 [ TU ]
X5 g r6 )keyssuper __setitem__ __setattr__)r= r9 rJ rB s r rk BaseOutput.__setattr__s s. 99; 5#4 G ,
D(r c B > [ TU ] X5 [ TU ] X5 g r6 )ri rj rk )r= rI rJ rB s r rj BaseOutput.__setitem__y s
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Convert self to a tuple containing all the attributes/keys that are not `None`.
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