graph_->graph.NodeType(output_.oper->node.name(), &ft);
    if (ft == nullptr) {
      return FullTypeDef();
    } else {
      return *ft;
    }
  }

  TF_Output output_;

  // For LLVM style RTTI.
  static bool classof(const AbstractTensorHandle* ptr) {
    return ptr->getKind() == kGraph;
  }

 private:
  TF_Graph* graph_;  // For shape inference.
};

  // Return the collected RunMetadata. This method will transfer the ownership
  // to the caller.
  virtual std::unique_ptr<RunMetadata> ExportRunMetadata() = 0;

  // For LLVM style RTTI.
  static bool classof(const AbstractContext* ptr) {
    return ptr->getKind() == kEager || ptr->getKind() == kTfrt;
  }

  //===--------------------------------------------------------------------===//

Burada *path operation function* password içeren aynı input user’ı döndürüyor olsa bile:

{* ../../docs_src/response_model/tutorial003_py310.py hl[24] *}

...`response_model` olarak, password’ü içermeyen `UserOut` modelimizi declare ettik:

{* ../../docs_src/response_model/tutorial003_py310.py hl[22] *}

Dolayısıyla **FastAPI**, output model’de declare edilmemiş tüm verileri (Pydantic kullanarak) filtrelemekle ilgilenir.

            "graph_function.h",
            "graph_function.cc",
            "gradient_checker.cc",
            "gradient_checker.h",
            "gradients.cc",  # Uses RTTI.
            "tracing_utils.h",
            "tracing_utils.cc",
            "*test*",
            "*dlpack*",
        ],
    ),
    visibility = ["//visibility:public"],

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