* `tf.types.experimental.TraceType` now allows custom tf.function inputs to declare Tensor decomposition and type casting support.

### 現代的なPython

FastAPIの機能はすべて、標準のPython 3.8型宣言に基づいています（Pydanticの功績）。新しい構文はありません。ただの現代的な標準のPythonです。

（FastAPIを使用しない場合でも）Pythonの型の使用方法について簡単な復習が必要な場合は、短いチュートリアル（[Python Types](python-types.md){.internal-link target=_blank}）を参照してください。

型を使用した標準的なPythonを記述します:

```Python
from datetime import date

from pydantic import BaseModel

# Declare a variable as a str

  // Pack 3 variable handles into one TFE_TensorHandle.
  // When remote is false, function device is placed on task0. Handle types are
  // REMOTE, REMOTE, LOCAL on task0. When remote is true, function device is
  // placed on task1, Handle types are LOCAL, REMOTE, LOCAL on task1.
  int num_replicas = 3;
  std::vector<TFE_TensorHandle*> handles = {h0, h1, h2};
  TFE_TensorHandle* packed_handle =

 * Range}, this allows the use of an arbitrary comparator. This is designed for use in the
 * implementation of subcollections of sorted collection types.
 *
 * <p>Whenever possible, use {@code Range} instead, which is better supported.
 *
 * @author Louis Wasserman
 */
@GwtCompatible(serializable = true)
@ElementTypesAreNonnullByDefault

   * <p><b>Note:</b> coalescing requires calling {@code .equals()} on any connected values, which
   * may be expensive depending on the value type. Using this method on range maps with large values
   * such as {@link Collection} types is discouraged.
   *
   * @since 22.0
   */
  void putCoalescing(Range<K> range, V value);

  /** Puts all the associations from {@code rangeMap} into this range map (optional operation). */

为此，请使用 Python 标准类型提示 <a href="https://docs.python.org/3/library/typing.html#typing.Union" class="external-link" target="_blank">`typing.Union`</a>：

/// note | "笔记"

定义 <a href="https://docs.pydantic.dev/latest/concepts/types/#unions" class="external-link" target="_blank">`Union`</a> 类型时，要把详细的类型写在前面，然后是不太详细的类型。下例中，更详细的 `PlaneItem` 位于 `Union[PlaneItem，CarItem]` 中的 `CarItem` 之前。

///

//// tab | Python 3.10+

import (
	"encoding/xml"
	"io"
	"net/http"

	xhttp "github.com/minio/minio/internal/http"
	"github.com/minio/minio/internal/logger"
	"github.com/minio/mux"
	"github.com/minio/pkg/v3/policy"
)

// Data types used for returning dummy access control
// policy XML, these variables shouldn't be used elsewhere
// they are only defined to be used in this file alone.
type grantee struct {
	XMLNS       string `xml:"xmlns:xsi,attr"`

		"Please contact MinIO at https://slack.min.io",
		"",
	)

	ErrInvalidCompressionIncludesValue = newErrFn(
		"Invalid compression include value",
		"Please check the passed value",
		"Compress extensions/mime-types are delimited by `,`. For eg, MINIO_COMPRESS_MIME_TYPES=\"A,B,C\"",
	)

	ErrInvalidReplicationWorkersValue = newErrFn(
		"Invalid value for replication workers",
		"",

limitations under the License.
==============================================================================*/

#include "tensorflow/c/c_api_experimental.h"

#include "absl/types/optional.h"
#include "tensorflow/c/c_api.h"
#include "tensorflow/c/c_api_internal.h"
#include "tensorflow/c/c_test_util.h"
#include "tensorflow/c/eager/c_api.h"
#include "tensorflow/c/eager/c_api_test_util.h"

But in this case, the same **FastAPI** application will handle the API and the authentication.

So, let's review it from that simplified point of view:

* The user types the `username` and `password` in the frontend, and hits `Enter`.
* The frontend (running in the user's browser) sends that `username` and `password` to a specific URL in our API (declared with `tokenUrl="token"`).