==============================================================================*/
#ifndef TENSORFLOW_C_EAGER_IMMEDIATE_EXECUTION_TENSOR_HANDLE_H_
#define TENSORFLOW_C_EAGER_IMMEDIATE_EXECUTION_TENSOR_HANDLE_H_

#include "tensorflow/c/eager/abstract_tensor_handle.h"
#include "tensorflow/c/tensor_interface.h"
#include "tensorflow/core/framework/types.pb.h"
#include "tensorflow/core/platform/status.h"

namespace tensorflow {

								<li class="nav-item" data-toggle="tooltip" data-placement="left" title="<la:message key="labels.eol_error" />">
									<a class="nav-link active" href="${eolLink}" target="_olh"><em class="fas fa-times-circle text-danger"></a>
								</li>
							</c:if>
							<c:if test="${developmentMode}">
								<li class="nav-item" data-toggle="tooltip" data-placement="left"
									title="<la:message key="labels.development_mode_warning" />"

    <img src="https://github.com/fastapi/fastapi/workflows/Test/badge.svg?event=push&branch=master" alt="Test">
</a>
<a href="https://coverage-badge.samuelcolvin.workers.dev/redirect/fastapi/fastapi" target="_blank">
    <img src="https://coverage-badge.samuelcolvin.workers.dev/fastapi/fastapi.svg" alt="Coverage">
</a>
<a href="https://pypi.org/project/fastapi" target="_blank">

 * use a framework. Frameworks automate the process, often adding features like monitoring,
 * debugging, and cancellation. Examples of frameworks include:
 *
 * <ul>
 *   <li><a href="https://dagger.dev/producers.html">Dagger Producers</a>
 * </ul>
 *
 * <h4>{@link java.util.concurrent.CompletableFuture} / {@link java.util.concurrent.CompletionStage}
 * </h4>
 *

#ifndef TENSORFLOW_C_EAGER_ABSTRACT_OPERATION_H_
#define TENSORFLOW_C_EAGER_ABSTRACT_OPERATION_H_

#include <memory>

#include "absl/types/span.h"
#include "tensorflow/c/eager/abstract_tensor_handle.h"
#include "tensorflow/c/tensor_interface.h"
#include "tensorflow/core/framework/tensor_shape.h"
#include "tensorflow/core/framework/types.pb.h"
#include "tensorflow/core/platform/status.h"

    <img src="https://github.com/fastapi/fastapi/workflows/Test/badge.svg?event=push&branch=master" alt="Test">
</a>
<a href="https://coverage-badge.samuelcolvin.workers.dev/redirect/fastapi/fastapi" target="_blank">
    <img src="https://coverage-badge.samuelcolvin.workers.dev/fastapi/fastapi.svg" alt="Coverage">
</a>
<a href="https://pypi.org/project/fastapi" target="_blank">

var errSignatureMismatch = errors.New("Signature does not match")

// When upload object size is greater than 5G in a single PUT/POST operation.
var errDataTooLarge = errors.New("Object size larger than allowed limit")

// When upload object size is less than what was expected.
var errDataTooSmall = errors.New("Object size smaller than expected")

// errServerNotInitialized - server not initialized.

		bs.XferRateLrg.addSize(sz, duration)
	} else {
		bs.XferRateSml.addSize(sz, duration)
	}
}

// RMetricName - name of replication metric
type RMetricName string

const (
	// Large - objects larger than 128MiB
	Large RMetricName = "Large"
	// Small - objects smaller than 128MiB
	Small RMetricName = "Small"
	// Total - metric pertaining to totals
	Total RMetricName = "Total"
)

  /*
   * Cache the size for efficiency. Using a long lets us avoid the need for
   * overflow checking and ensures that size() will function correctly even if
   * the multiset had once been larger than Integer.MAX_VALUE.
   */
  private transient long size;

  /** Standard constructor. */
  protected AbstractMapBasedMultiset(Map<E, Count> backingMap) {
    checkArgument(backingMap.isEmpty());

# 更多模型

书接上文，多个关联模型这种情况很常见。

特别是用户模型，因为：

* **输入模型**应该含密码
* **输出模型**不应含密码
* **数据库模型**需要加密的密码

/// danger | "危险"

千万不要存储用户的明文密码。始终存储可以进行验证的**安全哈希值**。

如果不了解这方面的知识，请参阅[安全性中的章节](security/simple-oauth2.md#password-hashing){.internal-link target=_blank}，了解什么是**密码哈希**。

///

## 多个模型

下面的代码展示了不同模型处理密码字段的方式，及使用位置的大致思路：

//// tab | Python 3.10+

```Python hl_lines="7  9  14  20  22  27-28  31-33  38-39"