transformers/docs/source/en/main_classes/output.md

Model outputs

All models have outputs that are instances of subclasses of [~utils.ModelOutput]. Those are data structures containing all the information returned by the model, but that can also be used as tuples or dictionaries.

Let's see how this looks in an example:

from transformers import BertTokenizer, BertForSequenceClassification
import torch

tokenizer = BertTokenizer.from_pretrained("google-bert/bert-base-uncased")
model = BertForSequenceClassification.from_pretrained("google-bert/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)

The outputs object is a [~modeling_outputs.SequenceClassifierOutput], as we can see in the documentation of that class below, it means it has an optional loss, a logits, an optional hidden_states and an optional attentions attribute. Here we have the loss since we passed along labels, but we don't have hidden_states and attentions because we didn't pass output_hidden_states=True or output_attentions=True.

When passing output_hidden_states=True you may expect the outputs.hidden_states[-1] to match outputs.last_hidden_states exactly. However, this is not always the case. Some models apply normalization or subsequent process to the last hidden state when it's returned.

You can access each attribute as you would usually do, and if that attribute has not been returned by the model, you will get None. Here for instance outputs.loss is the loss computed by the model, and outputs.attentions is None.

When considering our outputs object as tuple, it only considers the attributes that don't have None values. Here for instance, it has two elements, loss then logits, so

outputs[:2]

will return the tuple (outputs.loss, outputs.logits) for instance.

When considering our outputs object as dictionary, it only considers the attributes that don't have None values. Here for instance, it has two keys that are loss and logits.

We document here the generic model outputs that are used by more than one model type. Specific output types are documented on their corresponding model page.

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