scvi.module.base.LossRecorder

class scvi.module.base.LossRecorder(loss, reconstruction_loss=None, kl_local=None, kl_global=None, **kwargs)

Bases: object

Loss signature for models.

This class provides an organized way to record the model loss, as well as the components of the ELBO. This may also be used in MLE, MAP, EM methods. The loss is used for backpropagation during inference. The other parameters are used for logging/early stopping during inference.

Parameters:

• loss (Union[Dict[str, Union[Tensor, Array]], Tensor, Array]) – Tensor with loss for minibatch. Should be one dimensional with one value. Note that loss should be a Tensor and not the result of .item().

• reconstruction_loss (Union[Dict[str, Union[Tensor, Array]], Tensor, Array, None] (default: None)) – Reconstruction loss for each observation in the minibatch. If a tensor, converted to a dictionary with key “reconstruction_loss” and value as tensor

• kl_local (Union[Dict[str, Union[Tensor, Array]], Tensor, Array, None] (default: None)) – KL divergence associated with each observation in the minibatch. If a tensor, converted to a dictionary with key “kl_local” and value as tensor

• kl_global (Union[Dict[str, Union[Tensor, Array]], Tensor, Array, None] (default: None)) – Global kl divergence term. Should be one dimensional with one value. If a tensor, converted to a dictionary with key “kl_global” and value as tensor

• **kwargs – Additional metrics can be passed as keyword arguments and will be available as attributes of the object.

Attributes table

kl_global	rtype: Union[Tensor, Array]
kl_global_sum	rtype: Union[Tensor, Array]
kl_local	rtype: Union[Tensor, Array]
kl_local_sum	rtype: Union[Tensor, Array]
loss	rtype: Union[Tensor, Array]
reconstruction_loss	rtype: Union[Tensor, Array]
reconstruction_loss_sum	rtype: Union[Tensor, Array]

Methods table

dict_sum(x)

Wrapper of LossOutput.dict_sum.

Attributes

kl_global

LossRecorder.kl_global

Return type:

Union[Tensor, Array]

kl_global_sum

LossRecorder.kl_global_sum

Return type:

Union[Tensor, Array]

kl_local

LossRecorder.kl_local

Return type:

Union[Tensor, Array]

kl_local_sum

LossRecorder.kl_local_sum

Return type:

Union[Tensor, Array]

loss

LossRecorder.loss

Return type:

Union[Tensor, Array]

reconstruction_loss

LossRecorder.reconstruction_loss

Return type:

Union[Tensor, Array]

reconstruction_loss_sum

LossRecorder.reconstruction_loss_sum

Return type:

Union[Tensor, Array]

Methods

dict_sum

LossRecorder.dict_sum(x)

Wrapper of LossOutput.dict_sum.