# 模型输出 所有模型的输出都是 [`~utils.ModelOutput`] 的子类的实例。这些是包含模型返回的所有信息的数据结构，但也可以用作元组或字典。 让我们看一个例子： ```python from transformers import BertTokenizer, BertForSequenceClassification import torch tokenizer = BertTokenizer.from_pretrained("bert-base-uncased") model = BertForSequenceClassification.from_pretrained("bert-base-uncased") inputs = tokenizer("Hello, my dog is cute", return_tensors="pt") labels = torch.tensor([1]).unsqueeze(0) # Batch size 1 outputs = model(**inputs, labels=labels) ``` `outputs` 对象是 [`~modeling_outputs.SequenceClassifierOutput`]，如下面该类的文档中所示，它表示它有一个可选的 `loss`，一个 `logits`，一个可选的 `hidden_states` 和一个可选的 `attentions` 属性。在这里，我们有 `loss`，因为我们传递了 `labels`，但我们没有 `hidden_states` 和 `attentions`，因为我们没有传递 `output_hidden_states=True` 或 `output_attentions=True`。 当传递 `output_hidden_states=True` 时，您可能希望 `outputs.hidden_states[-1]` 与 `outputs.last_hidden_states` 完全匹配。然而，这并不总是成立。一些模型在返回最后的 hidden state时对其应用归一化或其他后续处理。 您可以像往常一样访问每个属性，如果模型未返回该属性，您将得到 `None`。在这里，例如，`outputs.loss` 是模型计算的损失，而 `outputs.attentions` 是 `None`。 当将我们的 `outputs` 对象视为元组时，它仅考虑那些没有 `None` 值的属性。例如这里它有两个元素，`loss` 和 `logits`，所以 ```python outputs[:2] ``` 将返回元组 `(outputs.loss, outputs.logits)`。 将我们的 `outputs` 对象视为字典时，它仅考虑那些没有 `None` 值的属性。例如在这里它有两个键，分别是 `loss` 和 `logits`。 我们在这里记录了被多个类型模型使用的通用模型输出。特定输出类型在其相应的模型页面上有文档。 ## ModelOutput [[autodoc]] utils.ModelOutput - to_tuple ## BaseModelOutput [[autodoc]] modeling_outputs.BaseModelOutput ## BaseModelOutputWithPooling [[autodoc]] modeling_outputs.BaseModelOutputWithPooling ## BaseModelOutputWithCrossAttentions [[autodoc]] modeling_outputs.BaseModelOutputWithCrossAttentions ## BaseModelOutputWithPoolingAndCrossAttentions [[autodoc]] modeling_outputs.BaseModelOutputWithPoolingAndCrossAttentions ## BaseModelOutputWithPast [[autodoc]] modeling_outputs.BaseModelOutputWithPast ## BaseModelOutputWithPastAndCrossAttentions [[autodoc]] modeling_outputs.BaseModelOutputWithPastAndCrossAttentions ## Seq2SeqModelOutput [[autodoc]] modeling_outputs.Seq2SeqModelOutput ## CausalLMOutput [[autodoc]] modeling_outputs.CausalLMOutput ## CausalLMOutputWithCrossAttentions [[autodoc]] modeling_outputs.CausalLMOutputWithCrossAttentions ## CausalLMOutputWithPast [[autodoc]] modeling_outputs.CausalLMOutputWithPast ## MaskedLMOutput [[autodoc]] modeling_outputs.MaskedLMOutput ## Seq2SeqLMOutput [[autodoc]] modeling_outputs.Seq2SeqLMOutput ## NextSentencePredictorOutput [[autodoc]] modeling_outputs.NextSentencePredictorOutput ## SequenceClassifierOutput [[autodoc]] modeling_outputs.SequenceClassifierOutput ## Seq2SeqSequenceClassifierOutput [[autodoc]] modeling_outputs.Seq2SeqSequenceClassifierOutput ## MultipleChoiceModelOutput [[autodoc]] modeling_outputs.MultipleChoiceModelOutput ## TokenClassifierOutput [[autodoc]] modeling_outputs.TokenClassifierOutput ## QuestionAnsweringModelOutput [[autodoc]] modeling_outputs.QuestionAnsweringModelOutput ## Seq2SeqQuestionAnsweringModelOutput [[autodoc]] modeling_outputs.Seq2SeqQuestionAnsweringModelOutput ## Seq2SeqSpectrogramOutput [[autodoc]] modeling_outputs.Seq2SeqSpectrogramOutput ## SemanticSegmenterOutput [[autodoc]] modeling_outputs.SemanticSegmenterOutput ## ImageClassifierOutput [[autodoc]] modeling_outputs.ImageClassifierOutput ## ImageClassifierOutputWithNoAttention [[autodoc]] modeling_outputs.ImageClassifierOutputWithNoAttention ## DepthEstimatorOutput [[autodoc]] modeling_outputs.DepthEstimatorOutput ## Wav2Vec2BaseModelOutput [[autodoc]] modeling_outputs.Wav2Vec2BaseModelOutput ## XVectorOutput [[autodoc]] modeling_outputs.XVectorOutput ## Seq2SeqTSModelOutput [[autodoc]] modeling_outputs.Seq2SeqTSModelOutput ## Seq2SeqTSPredictionOutput [[autodoc]] modeling_outputs.Seq2SeqTSPredictionOutput ## SampleTSPredictionOutput [[autodoc]] modeling_outputs.SampleTSPredictionOutput ## TFBaseModelOutput [[autodoc]] modeling_tf_outputs.TFBaseModelOutput ## TFBaseModelOutputWithPooling [[autodoc]] modeling_tf_outputs.TFBaseModelOutputWithPooling ## TFBaseModelOutputWithPoolingAndCrossAttentions [[autodoc]] modeling_tf_outputs.TFBaseModelOutputWithPoolingAndCrossAttentions ## TFBaseModelOutputWithPast [[autodoc]] modeling_tf_outputs.TFBaseModelOutputWithPast ## TFBaseModelOutputWithPastAndCrossAttentions [[autodoc]] modeling_tf_outputs.TFBaseModelOutputWithPastAndCrossAttentions ## TFSeq2SeqModelOutput [[autodoc]] modeling_tf_outputs.TFSeq2SeqModelOutput ## TFCausalLMOutput [[autodoc]] modeling_tf_outputs.TFCausalLMOutput ## TFCausalLMOutputWithCrossAttentions [[autodoc]] modeling_tf_outputs.TFCausalLMOutputWithCrossAttentions ## TFCausalLMOutputWithPast [[autodoc]] modeling_tf_outputs.TFCausalLMOutputWithPast ## TFMaskedLMOutput [[autodoc]] modeling_tf_outputs.TFMaskedLMOutput ## TFSeq2SeqLMOutput [[autodoc]] modeling_tf_outputs.TFSeq2SeqLMOutput ## TFNextSentencePredictorOutput [[autodoc]] modeling_tf_outputs.TFNextSentencePredictorOutput ## TFSequenceClassifierOutput [[autodoc]] modeling_tf_outputs.TFSequenceClassifierOutput ## TFSeq2SeqSequenceClassifierOutput [[autodoc]] modeling_tf_outputs.TFSeq2SeqSequenceClassifierOutput ## TFMultipleChoiceModelOutput [[autodoc]] modeling_tf_outputs.TFMultipleChoiceModelOutput ## TFTokenClassifierOutput [[autodoc]] modeling_tf_outputs.TFTokenClassifierOutput ## TFQuestionAnsweringModelOutput [[autodoc]] modeling_tf_outputs.TFQuestionAnsweringModelOutput ## TFSeq2SeqQuestionAnsweringModelOutput [[autodoc]] modeling_tf_outputs.TFSeq2SeqQuestionAnsweringModelOutput ## FlaxBaseModelOutput [[autodoc]] modeling_flax_outputs.FlaxBaseModelOutput ## FlaxBaseModelOutputWithPast [[autodoc]] modeling_flax_outputs.FlaxBaseModelOutputWithPast ## FlaxBaseModelOutputWithPooling [[autodoc]] modeling_flax_outputs.FlaxBaseModelOutputWithPooling ## FlaxBaseModelOutputWithPastAndCrossAttentions [[autodoc]] modeling_flax_outputs.FlaxBaseModelOutputWithPastAndCrossAttentions ## FlaxSeq2SeqModelOutput [[autodoc]] modeling_flax_outputs.FlaxSeq2SeqModelOutput ## FlaxCausalLMOutputWithCrossAttentions [[autodoc]] modeling_flax_outputs.FlaxCausalLMOutputWithCrossAttentions ## FlaxMaskedLMOutput [[autodoc]] modeling_flax_outputs.FlaxMaskedLMOutput ## FlaxSeq2SeqLMOutput [[autodoc]] modeling_flax_outputs.FlaxSeq2SeqLMOutput ## FlaxNextSentencePredictorOutput [[autodoc]] modeling_flax_outputs.FlaxNextSentencePredictorOutput ## FlaxSequenceClassifierOutput [[autodoc]] modeling_flax_outputs.FlaxSequenceClassifierOutput ## FlaxSeq2SeqSequenceClassifierOutput [[autodoc]] modeling_flax_outputs.FlaxSeq2SeqSequenceClassifierOutput ## FlaxMultipleChoiceModelOutput [[autodoc]] modeling_flax_outputs.FlaxMultipleChoiceModelOutput ## FlaxTokenClassifierOutput [[autodoc]] modeling_flax_outputs.FlaxTokenClassifierOutput ## FlaxQuestionAnsweringModelOutput [[autodoc]] modeling_flax_outputs.FlaxQuestionAnsweringModelOutput ## FlaxSeq2SeqQuestionAnsweringModelOutput [[autodoc]] modeling_flax_outputs.FlaxSeq2SeqQuestionAnsweringModelOutput