Computes an output mask tensor. Arguments: inputs: Tensor or list of tensors. mask: Tensor or list of tensors. Returns: None or a tensor (or list of tensors, one per output tensor of the layer).
(self, inputs, mask=None)
| 704 | |
| 705 | @base_layer_utils.default |
| 706 | def compute_mask(self, inputs, mask=None): # pylint: disable=unused-argument |
| 707 | """Computes an output mask tensor. |
| 708 | |
| 709 | Arguments: |
| 710 | inputs: Tensor or list of tensors. |
| 711 | mask: Tensor or list of tensors. |
| 712 | |
| 713 | Returns: |
| 714 | None or a tensor (or list of tensors, |
| 715 | one per output tensor of the layer). |
| 716 | """ |
| 717 | if not self.supports_masking: |
| 718 | if any(m is not None for m in nest.flatten(mask)): |
| 719 | raise TypeError('Layer ' + self.name + ' does not support masking, ' |
| 720 | 'but was passed an input_mask: ' + str(mask)) |
| 721 | # masking not explicitly supported: return None as mask. |
| 722 | return None |
| 723 | # if masking is explicitly supported, by default |
| 724 | # carry over the input mask |
| 725 | return mask |
| 726 | |
| 727 | def __call__(self, inputs, *args, **kwargs): |
| 728 | """Wraps `call`, applying pre- and post-processing steps. |
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