(self, inputs)
| 53 | return inputs |
| 54 | |
| 55 | def __call__(self, inputs): |
| 56 | input_shapes = None |
| 57 | if all(hasattr(x, 'shape') for x in nest.flatten(inputs)): |
| 58 | input_shapes = nest.map_structure(lambda x: x.shape, inputs) |
| 59 | |
| 60 | with tf.variable_scope(self._name): |
| 61 | if not self.built: |
| 62 | self.build(input_shapes) |
| 63 | outputs = self.call(inputs) |
| 64 | return outputs |
| 65 | |
| 66 | def compute_output_shape(self, input_shape): |
| 67 | raise NotImplementedError() |