def parse_batch(self: TrainerType, batch: List[torch.Tensor]) -> Tuple[torch.Tensor, ...]: inputs = to_device(batch[0], device=self.device, non_blocking=self.non_blocking) targets = to_device(batch[1], device=self.device, non_blocking=self.non_blocking) return inputs, targets
def parse_batch(self, batch: List[torch.Tensor]) -> Tuple[torch.Tensor, ...]: inputs = to_device(batch[0], device=self.device, non_blocking=self.non_blocking) lengths = to_device(batch[1], device=self.device, non_blocking=self.non_blocking) return inputs, inputs, lengths
def parse_batch(self, batch: List[torch.Tensor]) -> Tuple[torch.Tensor, ...]: inputs = to_device(batch[0], device=self.device, non_blocking=self.non_blocking) target = to_device(batch[1], device=self.device, non_blocking=self.non_blocking) domain = to_device(batch[2], device=self.device, non_blocking=self.non_blocking) return inputs, target, domain
def parse_batch(self, batch: List[torch.Tensor]) -> Tuple[torch.Tensor, ...]: inputs = to_device(batch[0], device=self.device, non_blocking=self.non_blocking) target = to_device(batch[1], device=self.device, non_blocking=self.non_blocking) segms = to_device(batch[2], device=self.device, non_blocking=self.non_blocking) attention_masks = to_device(batch[3], device=self.device, non_blocking=self.non_blocking) return inputs, target, segms, attention_masks
def parse_batch( self, batch: List[torch.Tensor]) -> Tuple[torch.Tensor, ...]: inputs, input_lengths, targets, target_lengths = map( lambda b: to_device(b, device=self.device, non_blocking=self.non_blocking), batch) return inputs, input_lengths, targets, target_lengths
def parse_batch(self, batch: List[torch.Tensor]) -> Tuple[torch.Tensor, ...]: inputs = to_device(batch[0], device=self.device, non_blocking=self.non_blocking) titles = to_device(batch[1], device=self.device, non_blocking=self.non_blocking) targets = to_device(batch[2], device=self.device, non_blocking=self.non_blocking) len_inputs = to_device(batch[3], device=self.device, non_blocking=self.non_blocking) len_titles = to_device(batch[4], device=self.device, non_blocking=self.non_blocking) return inputs, titles, targets, len_inputs, len_titles
def parse_batch( self, batch: List[torch.Tensor]) -> Tuple[torch.Tensor, ...]: inputs1 = to_device(batch[0], device=self.device) lengths1 = to_device(batch[1], device=self.device) inputs2 = to_device(batch[2], device=self.device) lengths2 = to_device(batch[3], device=self.device) inputs3 = to_device(batch[4], device=self.device) lengths3 = to_device(batch[5], device=self.device) return inputs1, lengths1, inputs2, lengths2, inputs3, lengths3