<th style="width: 25%"><la:message
                                                key="labels.dict_protwords_source"/></th>
                                        <td>${f:h(input)}<la:hidden property="input"/></td>
                                    </tr>
                                    </tbody>
                                </table>
                            </div>

            final VaErrorHook hook) {
        return getEntity(form).map(entity -> {
            final String newInput = form.input;
            validateProtwordsString(action, newInput, "input", hook);
            entity.setNewInput(newInput);
            return entity;
        });
    }

# Response Model - Return Type

You can declare the type used for the response by annotating the *path operation function* **return type**.

You can use **type annotations** the same way you would for input data in function **parameters**, you can use Pydantic models, lists, dictionaries, scalar values like integers, booleans, etc.

//// tab | Python 3.10+

```Python hl_lines="16  21"
{!> ../../docs_src/response_model/tutorial001_01_py310.py!}
```

  forward_op_->attrs.Reset(op);
  return op_->Reset(op, raw_device_name);
}
absl::Status AddInput(AbstractOperation* op_, AbstractTensorHandle* input,
                      ForwardOperation* forward_op_) {
  TF_RETURN_IF_ERROR(op_->AddInput(input));
  forward_op_->inputs.push_back(input);
  return absl::OkStatus();
}
absl::Status AddInputList(AbstractOperation* op_,

                    "loc": ["header", "x-token"],
                    "msg": "Field required",
                    "input": None,
                },
                {
                    "type": "missing",
                    "loc": ["header", "x-key"],
                    "msg": "Field required",
                    "input": None,
                },
            ]
        }
    ) | IsDict(

        {
            "detail": [
                {
                    "type": "enum",
                    "loc": ["path", "model_name"],
                    "msg": "Input should be 'alexnet', 'resnet' or 'lenet'",
                    "input": "foo",
                    "ctx": {"expected": "'alexnet', 'resnet' or 'lenet'"},
                }
            ]
        }
    ) | IsDict(

		Enable spectre mitigations in list (all, ret).
	-trimpath prefix
		Remove prefix from recorded source file paths.
	-v
		Print debug output.

Input language:

The assembler uses mostly the same syntax for all architectures,
the main variation having to do with addressing modes. Input is
run through a simplified C preprocessor that implements #include,
#define, #ifdef/endif, but not #if or ##.

			metaMap[formCanonicalName] = policy.Value
		}
	}
	// Check if any extra metadata field is passed as input
	for key := range formValues {
		if strings.HasPrefix(key, "X-Amz-Meta-") {
			if _, ok := metaMap[key]; !ok {
				return fmt.Errorf("Invalid according to Policy: Extra input fields: %s", key)
			}
		}
	}

	// Flag to indicate if all policies conditions are satisfied
	var condPassed bool

case "${VERSION}" in
devtoolset-7)
mv "/${TARGET}/usr/lib/libstdc++.so.${LIBSTDCXX_VERSION}" \
   "/${TARGET}/usr/lib/libstdc++.so.${LIBSTDCXX_VERSION}.backup"
echo -e "OUTPUT_FORMAT(elf64-x86-64)\nINPUT ( libstdc++.so.6.0.13 -lstdc++_nonshared44 )" \
   > "/${TARGET}/usr/lib/libstdc++.so.${LIBSTDCXX_VERSION}"
cp "./x86_64-pc-linux-gnu/libstdc++-v3/src/.libs/libstdc++_nonshared44.a" \
   "/${TARGET}/usr/lib"
  ;;

        {
            "detail": [
                {
                    "type": "greater_than",
                    "loc": ["body", "item", "price"],
                    "msg": "Input should be greater than 0",
                    "input": -3.0,
                    "ctx": {"gt": 0.0},
                }
            ]
        }
    ) | IsDict(
        # TODO: remove when deprecating Pydantic v1
        {