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  1. okhttp-idna-mapping-table/src/main/resources/okhttp3/internal/idna/IdnaMappingTable.txt

    2166          ; mapped                 ; 0076 0069 0069 #1.1  ROMAN NUMERAL SEVEN
    2167          ; mapped                 ; 0076 0069 0069 0069 #1.1 ROMAN NUMERAL EIGHT
    2168          ; mapped                 ; 0069 0078     # 1.1  ROMAN NUMERAL NINE
    2169          ; mapped                 ; 0078          # 1.1  ROMAN NUMERAL TEN
    216A          ; mapped                 ; 0078 0069     # 1.1  ROMAN NUMERAL ELEVEN
    Plain Text
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  2. docs/de/docs/tutorial/path-params-numeric-validations.md

        ```Python hl_lines="1  3"
        {!> ../../../docs_src/path_params_numeric_validations/tutorial001_an_py310.py!}
        ```
    
    === "Python 3.9+"
    
        ```Python hl_lines="1  3"
        {!> ../../../docs_src/path_params_numeric_validations/tutorial001_an_py39.py!}
        ```
    
    === "Python 3.8+"
    
        ```Python hl_lines="3-4"
        {!> ../../../docs_src/path_params_numeric_validations/tutorial001_an.py!}
        ```
    
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  3. docs/zh/docs/tutorial/path-params-numeric-validations.md

        ```Python hl_lines="1  3"
        {!> ../../../docs_src/path_params_numeric_validations/tutorial001_an_py310.py!}
        ```
    
    === "Python 3.9+"
    
        ```Python hl_lines="1  3"
        {!> ../../../docs_src/path_params_numeric_validations/tutorial001_an_py39.py!}
        ```
    
    === "Python 3.8+"
    
        ```Python hl_lines="3-4"
        {!> ../../../docs_src/path_params_numeric_validations/tutorial001_an.py!}
        ```
    
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  4. docs/en/docs/tutorial/path-params-numeric-validations.md

        ```Python hl_lines="10"
        {!> ../../../docs_src/path_params_numeric_validations/tutorial001_an_py310.py!}
        ```
    
    === "Python 3.9+"
    
        ```Python hl_lines="10"
        {!> ../../../docs_src/path_params_numeric_validations/tutorial001_an_py39.py!}
        ```
    
    === "Python 3.8+"
    
        ```Python hl_lines="11"
        {!> ../../../docs_src/path_params_numeric_validations/tutorial001_an.py!}
        ```
    
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  5. docs/ru/docs/tutorial/path-params-numeric-validations.md

        ```Python hl_lines="1  3"
        {!> ../../../docs_src/path_params_numeric_validations/tutorial001_an_py310.py!}
        ```
    
    === "Python 3.9+"
    
        ```Python hl_lines="1  3"
        {!> ../../../docs_src/path_params_numeric_validations/tutorial001_an_py39.py!}
        ```
    
    === "Python 3.8+"
    
        ```Python hl_lines="3-4"
        {!> ../../../docs_src/path_params_numeric_validations/tutorial001_an.py!}
        ```
    
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  6. docs/pt/docs/tutorial/path-params-numeric-validations.md

    ## Importe `Path`
    
    Primeiro, importe `Path` de `fastapi`:
    
    === "Python 3.10+"
    
        ```Python hl_lines="1"
        {!> ../../../docs_src/path_params_numeric_validations/tutorial001_py310.py!}
        ```
    
    === "Python 3.8+"
    
        ```Python hl_lines="3"
        {!> ../../../docs_src/path_params_numeric_validations/tutorial001.py!}
        ```
    
    ## Declare metadados
    
    Você pode declarar todos os parâmetros da mesma maneira que na `Query`.
    
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  7. docs/ja/docs/tutorial/path-params-numeric-validations.md

    ## Pathのインポート
    
    まず初めに、`fastapi`から`Path`をインポートします:
    
    ```Python hl_lines="1"
    {!../../../docs_src/path_params_numeric_validations/tutorial001.py!}
    ```
    
    ## メタデータの宣言
    
    パラメータは`Query`と同じものを宣言することができます。
    
    例えば、パスパラメータ`item_id`に対して`title`のメタデータを宣言するには以下のようにします:
    
    ```Python hl_lines="8"
    {!../../../docs_src/path_params_numeric_validations/tutorial001.py!}
    ```
    
    !!! note "備考"
        パスの一部でなければならないので、パスパラメータは常に必須です。
    
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  8. tensorflow/c/experimental/gradients/grad_test_helper.cc

        if (!outputs[i]) continue;
    
        AbstractTensorHandlePtr numerical_grad;
        {
          AbstractTensorHandle* numerical_grad_raw;
          s = CalcNumericalGrad(ctx, model, inputs,
                                /*input_index=*/i, use_function,
                                &numerical_grad_raw);
          ASSERT_EQ(errors::OK, s.code()) << s.message();
          numerical_grad.reset(numerical_grad_raw);
        }
    
        TF_Tensor* numerical_tensor;
    C++
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  9. tensorflow/c/eager/gradient_checker.cc

        TF_DeleteTensor(grad_tensor);
        dtheta_approx[i] = grad_data[0];
      }
    
      // Populate *numerical_grad with the data from dtheta_approx.
      TF_RETURN_IF_ERROR(TestTensorHandleWithDims<float, TF_FLOAT>(
          ctx, dtheta_approx.data(), theta_dims.data(), num_dims, numerical_grad));
      TF_DeleteTensor(theta_tensor);
      return absl::OkStatus();
    }
    
    }  // namespace gradients
    C++
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  10. android/guava/src/com/google/common/math/Stats.java

       *
       * <p>This is guaranteed to return zero if the dataset contains only exactly one finite value. It
       * is not guaranteed to return zero when the dataset consists of the same value multiple times,
       * due to numerical errors. However, it is guaranteed never to return a negative result.
       *
       * <h3>Non-finite values</h3>
       *
       * <p>If the dataset contains any non-finite values ({@link Double#POSITIVE_INFINITY}, {@link
    Java
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