然後它會轉換並驗證資料。因此，當你使用該 `settings` 物件時，你會得到你宣告的型別的資料（例如 `items_per_user` 會是 `int`）。

### 使用 `settings` { #use-the-settings }

接著你可以在應用程式中使用新的 `settings` 物件：

{* ../../docs_src/settings/tutorial001_py310.py hl[18:20] *}

### 執行伺服器 { #run-the-server }

接下來，你可以在啟動伺服器時，將設定以環境變數傳入。舉例來說，你可以設定 `ADMIN_EMAIL` 與 `APP_NAME`：

<div class="termy">

```console

  // `TF_AttrBuilderCheckCanRunOnDevice()` call(s) on the same `builder`.
  std::set<std::string> attr_names;
};

TF_AttrBuilder* TF_NewAttrBuilder(const char* op_name) {
  return new TF_AttrBuilder(op_name);
}

void TF_DeleteAttrBuilder(TF_AttrBuilder* builder) { delete builder; }

void TF_AttrBuilderSetType(TF_AttrBuilder* builder, const char* attr_name,

  <uses-permission android:name="android.permission.INTERNET" />

  <application
    android:allowBackup="true"
    android:label="@string/app_name"
    android:supportsRtl="true"
    android:name=".TestApplication"
  >
    <activity
      android:name=".MainActivity"
      android:exported="true">
      <intent-filter>

  // least one input of the op is watched and has a trainable dtype.
  // op_name is optional and is used for debugging only.
  void RecordOperation(absl::Span<AbstractTensorHandle* const> inputs,
                       absl::Span<AbstractTensorHandle* const> outputs,
                       GradientFunction* gradient_function,
                       const string& op_name = "");
  // Returns whether any tensor in a list of tensors is being watched and has

<resources>
  <string name="app_name">android-test</string>

<resources>
  <string name="app_name">regression-test</string>

from pydantic_settings import BaseSettings


class Settings(BaseSettings):
    app_name: str = "Awesome API"
    admin_email: str
    items_per_user: int = 50

from pydantic_settings import BaseSettings, SettingsConfigDict


class Settings(BaseSettings):
    app_name: str = "Awesome API"
    admin_email: str
    items_per_user: int = 50

  tsl::Set_TF_Status_from_Status(
      s, unwrap(op)->Reset(op_type,
                           /*raw_device_name=*/nullptr));
}

void TF_AbstractOpSetOpName(TF_AbstractOp* op, const char* const op_name,
                            TF_Status* s) {
  TracingOperation* tracing_op = dyn_cast<TracingOperation>(unwrap(op));
  if (!tracing_op) {
    tsl::Set_TF_Status_from_Status(

// needs to be updated with the argument length of the input list.
// Returns nullptr if there is any problem like op_name is not found, or the
// argument does not support this attribute type.
TF_CAPI_EXPORT extern const char* TF_GetNumberAttrForOpListInput(
    const char* op_name, int input_index, TF_Status* status);

// Returns 1 if the op is stateful, 0 otherwise. The return value is undefined