(self, all_inputs, target, orig_inputs, orig_target)
| 2622 | return processed_inputs, targets, is_dict_inputs |
| 2623 | |
| 2624 | def _compile_from_inputs(self, all_inputs, target, orig_inputs, orig_target): |
| 2625 | if target is not None: |
| 2626 | # We need to use `y` to set the model targets. |
| 2627 | if training_utils.has_tensors(target): |
| 2628 | target = training_utils.cast_if_floating_dtype_and_mismatch( |
| 2629 | target, self.outputs) |
| 2630 | training_utils.validate_input_types(target, orig_target, |
| 2631 | allow_dict=False, field_name='target') |
| 2632 | if isinstance(target, (list, tuple)): |
| 2633 | all_inputs += list(target) |
| 2634 | else: |
| 2635 | all_inputs.append(target) |
| 2636 | # Type check that all inputs are *either* value *or* symbolic. |
| 2637 | # TODO(fchollet): this check could be removed in Eager mode? |
| 2638 | if any(tensor_util.is_tensor(v) for v in all_inputs): |
| 2639 | if not all(tensor_util.is_tensor(v) for v in all_inputs): |
| 2640 | raise ValueError('Do not pass inputs that mix Numpy arrays and ' |
| 2641 | 'TensorFlow tensors. ' |
| 2642 | 'You passed: x=' + str(orig_inputs) + |
| 2643 | '; y=' + str(orig_target)) |
| 2644 | is_dataset = isinstance(orig_inputs, (dataset_ops.DatasetV1, |
| 2645 | dataset_ops.DatasetV2, |
| 2646 | iterator_ops.Iterator)) |
| 2647 | if is_dataset or context.executing_eagerly(): |
| 2648 | target_tensors = None |
| 2649 | else: |
| 2650 | # Handle target tensors if any passed. |
| 2651 | if target is not None: |
| 2652 | if not isinstance(target, (list, tuple)): |
| 2653 | target = [target] |
| 2654 | target_tensors = [v for v in target if _is_symbolic_tensor(v)] |
| 2655 | else: |
| 2656 | target_tensors = None |
| 2657 | |
| 2658 | self.compile( |
| 2659 | optimizer=self.optimizer, |
| 2660 | loss=self.loss, |
| 2661 | metrics=self._compile_metrics, |
| 2662 | weighted_metrics=self._compile_weighted_metrics, |
| 2663 | loss_weights=self.loss_weights, |
| 2664 | target_tensors=target_tensors, |
| 2665 | sample_weight_mode=self.sample_weight_mode, |
| 2666 | run_eagerly=self.run_eagerly, |
| 2667 | experimental_run_tf_function=self._experimental_run_tf_function) |
| 2668 | |
| 2669 | # TODO(omalleyt): Consider changing to a more descriptive function name. |
| 2670 | def _set_inputs(self, inputs, outputs=None, training=None): |
no test coverage detected