their input and output keys silently ignored and rewritten to 'inputs' and
    'outputs'. If a model was exported with different names before 1.2, and is
    now served with tensorflow/serving, it will accept requests using 'inputs'
    and 'outputs'. Starting at 1.2, such a model will accept the keys specified
    during export. Therefore, inference requests using 'inputs' and 'outputs'

            // * if single date picker mode, and time picker isn't enabled, apply the selection immediately
            // * if one of the inputs above the calendars was focused, cancel that manual input
            //

            if (this.endDate || date.isBefore(this.startDate, 'day')) { //picking start
                if (this.timePicker) {

            None if separate_input_output_schemas else "validation"
        )
        inputs = [
            (field, override_mode or field.mode, field._type_adapter.core_schema)
            for field in fields
        ]
        field_mapping, definitions = schema_generator.generate_definitions(
            inputs=inputs
        )
        return field_mapping, definitions  # type: ignore[return-value]

  // existing and given constraints will be performed.
  virtual absl::Status SetDeviceName(const char* name) = 0;

  virtual absl::Status AddInput(AbstractTensorHandle* input) = 0;
  virtual absl::Status AddInputList(
      absl::Span<AbstractTensorHandle* const> inputs) = 0;
  virtual absl::Status Execute(absl::Span<AbstractTensorHandle*> retvals,
                               int* num_retvals) = 0;

```json
{
    "detail": [
        {
            "type": "extra_forbidden",
            "loc": ["cookie", "santa_tracker"],
            "msg": "Extra inputs are not permitted",
            "input": "good-list-please",
        }
    ]
}
```

## Summary

    private final String[] inputs;

    private final String output;

    private String[] newInputs;

    private String newOutput;

    public CharMappingItem(final long id, final String[] inputs, final String output) {
        this.id = id;
        this.inputs = inputs;
        this.output = output == null ? null : output.replace("\n", " ");
        Arrays.sort(inputs);

        if (id == 0) {

public class SynonymItem extends DictionaryItem {
    private final String[] inputs;

    private final String[] outputs;

    private String[] newInputs;

    private String[] newOutputs;

    public SynonymItem(final long id, final String[] inputs, final String[] outputs) {
        this.id = id;
        this.inputs = inputs;
        this.outputs = outputs;

        if (id == 0) {
            // create

					Signature: [4]byte{2, 1, 1, 1},
					Type:      ObjectType,
					Flags:     0,
				}},
			},
		},
	}
	inputSerialized := make([]metaCacheEntry, len(inputs))
	for i, xl := range inputs {
		xl.sortByModTime()
		var err error
		entry := metaCacheEntry{
			name: "testobject",
		}
		entry.metadata, err = xl.AppendTo(nil)
		if err != nil {
			t.Fatal(err)
		}

                    inputs = new String[inputStrings.size()];
                    for (int i = 0; i < inputs.length; i++) {
                        inputs[i] = unescape(inputStrings.get(i)).trim();
                    }

                    if (inputs.length > 0) {
                        id++;
                        final SynonymItem item = new SynonymItem(id, inputs, inputs);

    std::vector<TFE_TensorHandle*> device_inputs;
    device_inputs.reserve(inputs.size());
    for (int input_index = 0; input_index < inputs.size(); ++input_index) {
      // Parallel tensors are divided between operations by device.
      device_inputs.push_back(inputs[input_index]->tensor(device_index));
    }
    device_thread->StartExecute(