| | |
| | | float_pad_value: Union[float, int] = 0.0, |
| | | int_pad_value: int = -32768, |
| | | not_sequence: Collection[str] = (), |
| | | max_sample_size=None |
| | | max_sample_size=None, |
| | | ): |
| | | self.float_pad_value = float_pad_value |
| | | self.int_pad_value = int_pad_value |
| | |
| | | int_pad_value: int = -32768, |
| | | not_sequence: Collection[str] = (), |
| | | ) -> Tuple[List[str], Dict[str, torch.Tensor]]: |
| | | """Concatenate ndarray-list to an array and convert to torch.Tensor. |
| | | """ |
| | | """Concatenate ndarray-list to an array and convert to torch.Tensor.""" |
| | | uttids = [u for u, _ in data] |
| | | data = [d for _, d in data] |
| | | |
| | |
| | | float_pad_value: Union[float, int] = 0.0, |
| | | int_pad_value: int = -32768, |
| | | not_sequence: Collection[str] = (), |
| | | max_sample_size=None |
| | | max_sample_size=None, |
| | | ): |
| | | self.float_pad_value = float_pad_value |
| | | self.int_pad_value = int_pad_value |
| | |
| | | int_pad_value: int = -32768, |
| | | not_sequence: Collection[str] = (), |
| | | ) -> Tuple[List[str], Dict[str, torch.Tensor]]: |
| | | """Concatenate ndarray-list to an array and convert to torch.Tensor. |
| | | """ |
| | | """Concatenate ndarray-list to an array and convert to torch.Tensor.""" |
| | | uttids = [u for u, _ in data] |
| | | data = [d for _, d in data] |
| | | |