Transformers documentation

時系列ユーティリティ

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時系列ユーティリティ

このページには、時系列ベースのモデルに使用できるすべてのユーティリティ関数とクラスがリストされます。

これらのほとんどは、時系列モデルのコードを研究している場合、または分散出力クラスのコレクションに追加したい場合にのみ役立ちます。

Distributional Output

class transformers.time_series_utils.NormalOutput

< >

( dim: int = 1 )

Normal distribution output class.

Normal

( *args**kwargs )

A mock value for a dotted path (e.g. torch.float32): attribute access chains, calls behave as pass-through decorators, repr is the dotted path, and using it as a base class substitutes a plain-type base (PEP 560 __mro_entries__), so real subclasses keep a normal metaclass and inspect.signature reads their real __init__ instead of a mock’s.

class transformers.time_series_utils.StudentTOutput

< >

( dim: int = 1 )

Student-T distribution output class.

StudentT

( *args**kwargs )

A mock value for a dotted path (e.g. torch.float32): attribute access chains, calls behave as pass-through decorators, repr is the dotted path, and using it as a base class substitutes a plain-type base (PEP 560 __mro_entries__), so real subclasses keep a normal metaclass and inspect.signature reads their real __init__ instead of a mock’s.

class transformers.time_series_utils.NegativeBinomialOutput

< >

( dim: int = 1 )

Negative Binomial distribution output class.

NegativeBinomial

( *args**kwargs )

A mock value for a dotted path (e.g. torch.float32): attribute access chains, calls behave as pass-through decorators, repr is the dotted path, and using it as a base class substitutes a plain-type base (PEP 560 __mro_entries__), so real subclasses keep a normal metaclass and inspect.signature reads their real __init__ instead of a mock’s.

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