assert response.json() == {
        "detail": [
            {
                "type": "extra_forbidden",
                "loc": ["body", "extra"],
                "msg": "Extra inputs are not permitted",
                "input": "extra",
            }
        ]
    }


@needs_pydanticv2
@needs_py39
def test_post_body_form_no_password(client: TestClient):

                        "msg": "Input should be less than or equal to 100",
                        "input": "150",
                        "ctx": {"le": 100},
                    },
                    {
                        "type": "greater_than_equal",
                        "loc": ["query", "offset"],
                        "msg": "Input should be greater than or equal to 0",

   */
  HashCode hashBytes(byte[] input, int off, int len);

  /**
   * Shortcut for {@code newHasher().putBytes(input).hash()}. The implementation <i>might</i>
   * perform better than its longhand equivalent, but should not perform worse.
   *
   * @since 23.0
   */
  HashCode hashBytes(ByteBuffer input);

  /**
   * Shortcut for {@code newHasher().putUnencodedChars(input).hash()}. The implementation

   */
  HashCode hashBytes(byte[] input, int off, int len);

  /**
   * Shortcut for {@code newHasher().putBytes(input).hash()}. The implementation <i>might</i>
   * perform better than its longhand equivalent, but should not perform worse.
   *
   * @since 23.0
   */
  HashCode hashBytes(ByteBuffer input);

  /**
   * Shortcut for {@code newHasher().putUnencodedChars(input).hash()}. The implementation

                                             const char* prefix2 = nullptr) {
    TF_Output inputs[2];
    TF_Output outputs[1];
    TF_Output grad_outputs[2];

    BuildSuccessGraph(inputs, outputs);

    AddGradients(false, prefix1, inputs, 2, outputs, 1, grad_outputs);
    if (prefix2 != nullptr) {
      AddGradients(false, prefix2, inputs, 2, outputs, 1, grad_outputs);
    }
  }

  TF_Status* s_;

void TF_AddInput(TF_OperationDescription* desc, TF_Output input) {
  desc->node_builder.Input(&input.oper->node, input.index);
}

void TF_AddInputList(TF_OperationDescription* desc, const TF_Output* inputs,
                     int num_inputs) {
  std::vector<NodeBuilder::NodeOut> input_list;
  input_list.reserve(num_inputs);
  for (int i = 0; i < num_inputs; ++i) {
    input_list.emplace_back(&inputs[i].oper->node, inputs[i].index);
  }

  private static void assertMacHashing(
      byte[] input, String algorithm, SecretKey key, HashFunction hashFunc) throws Exception {
    Mac mac = Mac.getInstance(algorithm);
    mac.init(key);
    mac.update(input);

    assertEquals(HashCode.fromBytes(mac.doFinal()), hashFunc.hashBytes(input));
    assertEquals(HashCode.fromBytes(mac.doFinal(input)), hashFunc.hashBytes(input));
  }

    inputs.property('acceptedViolations', acceptedViolations.toAcceptedChangesMap())
    inputs.property("baseline.version", compatibilityBaselineVersion)
    inputs.property("currentVersion", baseVersion)
    def apiSourceFolders = configurations.currentSources.incoming.artifactView { lenient(true) }.files
    inputs.files("apiSourceFolders", apiSourceFolders)
    inputs.files(currentClasspath)

        return false;
      }
    }
  }
  return found_t && found_n;
}

bool IsNeg(const tensorflow::NodeDef& node_def, const string& input) {
  return node_def.op() == "Neg" && node_def.name() == "neg" &&
         node_def.input_size() == 1 && node_def.input(0) == input;
}

bool GetGraphDef(TF_Graph* graph, tensorflow::GraphDef* graph_def) {
  TF_Status* s = TF_NewStatus();
  TF_Buffer* buffer = TF_NewBuffer();

  @SafeVarargs
  public static <T extends @Nullable Object> Iterable<T> concat(Iterable<? extends T>... inputs) {
    return FluentIterable.concat(inputs);
  }

  /**
   * Combines multiple iterables into a single iterable. The returned iterable has an iterator that
   * traverses the elements of each iterable in {@code inputs}. The input iterators are not polled
   * until necessary.
   *