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
