o }oi @spddlmZddlZddlmZddlmZmZmZddlm Z m Z m Z m Z m Z dgZGdddejeeZdS))ListN)nn) SerializationTyping typecheck) LabelsType LogitsTypeLossTypeMaskType NeuralTypeBCEWithLogitsLossc seZdZdZeddZeddZ    dd ed ej d e d ej ffd d Z e dde deedej ffdd ZZS)r zi BCEWithLogitsLoss https://pytorch.org/docs/1.9.1/generated/torch.nn.BCEWithLogitsLoss.html cCs`tdgdg|jdttdgdg|jdtgtdgdg|jdtdddS)z3Returns definitions of module input ports. BANYT)optional)logitslabels loss_mask)r _logits_dimrrr selfrb/home/ubuntu/.local/lib/python3.10/site-packages/nemo/collections/common/losses/bce_logits_loss.py input_types!s zBCEWithLogitsLoss.input_typescCsdttdiS)z4Returns definitions of module output ports. loss) elements_type)r r rrrr output_types+szBCEWithLogitsLoss.output_typesrNmean logits_ndimweight reduction pos_weightcs8|durt|st|}tj|||d||_dS)a Args: logits_ndim: number of dimensions (or rank) of the logits tensor weight: list of rescaling weight given to each class reduction: type of the reduction over the batch pos_weight: weight given to positive samples N)r r"r!)torch is_tensor FloatTensorsuper__init__r)rrr r!r" __class__rrr'1s  zBCEWithLogitsLoss.__init__rrrcs$t|}|}t||S)zl Args: logits: output of the classifier labels: ground truth labels )r#stacktfloatr&forward)rrrrr(rrr-Es  zBCEWithLogitsLoss.forward)rNrN)N)__name__ __module__ __qualname____doc__propertyrrintr#Tensorstrr'rr,rr- __classcell__rrr(rr s*  ,)typingrr#rnemo.core.classesrrrnemo.core.neural_typesrrr r r __all__r rrrrs