CacheTesting.checkValidState(cache);
  }

  /**
   * With an unlimited-size cache with maxWeight of 0, entries weighing 0 should still be cached.
   * Entries with positive weight should not be cached (nor dump existing cache).
   */
  public void testEviction_maxWeight_zero() {
    CountingRemovalListener<Integer, Integer> removalListener = countingRemovalListener();
    IdentityLoader<Integer> loader = identityLoader();

{* ../../docs_src/extra_models/tutorial001_py310.py hl[7,9,14,20,22,27:28,31:33,38:39] *}

### `**user_in.model_dump()` 에 대하여 { #about-user-in-model-dump }

#### Pydantic의 `.model_dump()` { #pydantics-model-dump }

`user_in`은 Pydantic 모델 클래스인 `UserIn`입니다.

Pydantic 모델은 모델 데이터를 포함한 `dict`를 반환하는 `.model_dump()` 메서드를 제공합니다.

따라서, 다음과 같이 Pydantic 객체 `user_in`을 생성할 수 있습니다:

```Python

        final long freeMemory = Runtime.getRuntime().freeMemory();
        final String msg = String.format(
                "%d words from %d %s: {\"time\":{\"parse\":%d,\"index\":%d},\"cpu\":%f,\"mem\":{\"heap\":\"%dmb\",\"used\":\"%dmb\"}}",
                items.length, size, type, parseTime, indexTime, cpuLoad, maxMemory / (1024 * 1024),
                (maxMemory - freeMemory) / (1024 * 1024));
        logger.info(msg);

errors.could_not_delete_logged_in_user=You cannot delete a user who is logged in.
errors.unauthorized_request=Unauthorized request.
errors.failed_to_print_thread_dump=Failed to print a thread dump.
errors.file_is_not_supported={0} is not supported.
errors.plugin_file_is_not_found={0} is not found.
errors.failed_to_install_plugin=Failed to install {0}.
errors.failed_to_find_plugins=Could not find available plugins.

errors.could_not_delete_logged_in_user=You cannot delete a user who is logged in.
errors.unauthorized_request=Unauthorized request.
errors.failed_to_print_thread_dump=Failed to print a thread dump.
errors.file_is_not_supported={0} is not supported.
errors.plugin_file_is_not_found={0} is not found.
errors.failed_to_install_plugin=Failed to install {0}.
errors.failed_to_find_plugins=Could not find available plugins.

            String domA = ntlm.getUserDomain() != null ? ntlm.getUserDomain().toUpperCase() : null;
            String domB = this.getUserDomain() != null ? this.getUserDomain().toUpperCase() : null;
            return ntlm.type == this.type && Objects.equals(domA, domB) && ntlm.getUsername().equalsIgnoreCase(this.getUsername())
                    && constantTimeEquals(getPasswordAsCharArray(), ntlm.getPasswordAsCharArray());

                nonTransitiveDependencyScopes));
        return result;
    }

    // ===

    public static void main(String... args) {
        ScopeManagerDump.dump(Maven3ScopeManagerConfiguration.INSTANCE);
    }

ここでは、パスワードフィールドをもつモデルがどのように見えるのか、また、どこで使われるのか、大まかなイメージを紹介します:

{* ../../docs_src/extra_models/tutorial001_py310.py hl[7,9,14,20,22,27:28,31:33,38:39] *}

### `**user_in.model_dump()` について { #about-user-in-model-dump }

#### Pydanticの`.model_dump()` { #pydantics-model-dump }

`user_in`は`UserIn`クラスのPydanticモデルです。

Pydanticモデルには、モデルのデータを含む`dict`を返す`.model_dump()`メソッドがあります。

そこで、以下のようなPydanticオブジェクト`user_in`を作成すると:

```Python

        logger.error("  failure marker exists: ${failureMarker.exists()}")
        logger.error("  pid file exists: ${pidFile.exists()}")
        logger.error("  ports file exists: ${portsFile.exists()}")
        // also dump the log file for the startup script (which will include ES logging output to stdout)
        if (runLog.exists()) {
            logger.error("\n  [log]")
            runLog.eachLine { line -> logger.error("    ${line}") }

      output_tensors, output_names_vec, control_output_nodes,
      control_output_names_vec, description, &fdef);
  if (TF_GetCode(status) != TF_OK) {
    return nullptr;
  }

  // Dump the op creation stacktraces for debugging purpose.
  DEBUG_DATA_DUMPER()->DumpOpCreationStackTraces(
      fn_name, kDebugGroupOpStacktrace, "initial", &fn_body->graph);

  tensorflow::StackTracesMap stack_traces;