Model outputs¶
PyTorch models have outputs that are instances of subclasses of 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 of this looks on an example:
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)
The outputs object is a 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.
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¶
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class
transformers.file_utils.ModelOutput[source]¶ 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 theNoneattributes. Otherwise behaves like a regular python dictionary.Warning
You can’t unpack a
ModelOutputdirectly. Use theto_tuple()method to convert it to a tuple before.-
pop(k[, d]) → v, remove specified key and return the corresponding[source]¶ value. If key is not found, d is returned if given, otherwise KeyError is raised.
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