Це означатиме, що  **FastAPI**  очікуватиме тіло запиту такого вигляду:

```JSON
{
    "name": "Foo",
    "description": "The pretender",
    "price": 42.0,
    "tax": 3.2,
    "tags": ["rock", "metal", "bar"],
    "image": {
        "url": "http://example.com/baz.jpg",
        "name": "The Foo live"
    }
}
```

Завдяки такій декларації у **FastAPI** Ви отримуєте:

Это означает, что **FastAPI** будет ожидать тело запроса, аналогичное этому:

```JSON
{
    "name": "Foo",
    "description": "The pretender",
    "price": 42.0,
    "tax": 3.2,
    "tags": ["rock", "metal", "bar"],
    "image": {
        "url": "http://example.com/baz.jpg",
        "name": "The Foo live"
    }
}
```

Ещё раз: сделав такое объявление, с помощью **FastAPI** вы получите:

    // US region agents have name "EC2-XXX"
    doesNotContain("teamcity.agent.name", "EC2")
}

/**
 * We have some "shared" host where a Linux build agent and a Windows build agent
 * both run on the same bare metal. Some builds require exclusive access to the
 * hardware resources (e.g. performance test).
 */
fun Requirements.requiresNotSharedHost() {
    doesNotContain("agent.host.type", "shared")
}

/**

To install the current release, which includes support for
[CUDA-enabled GPU cards](https://www.tensorflow.org/install/gpu) *(Ubuntu and
Windows)*:

```
$ pip install tensorflow
```

Other devices (DirectX and MacOS-metal) are supported using
[Device Plugins](https://www.tensorflow.org/install/gpu_plugins#available_devices).

A smaller CPU-only package is also available:

```
$ pip install tensorflow-cpu
```

🔹 High Performance – Ideal for demanding storage workloads.

AI storage documentation  (https://min.io/solutions/object-storage-for-ai).

This README provides quickstart instructions on running MinIO on bare metal hardware, including container-based installations. For Kubernetes environments, use the [MinIO Kubernetes Operator](https://github.com/minio/operator/blob/master/README.md).

## Container Installation

v3.0. It is API compatible with Amazon S3 cloud storage service. Use MinIO to build high performance infrastructure for machine learning, analytics and application data workloads. This README provides quickstart instructions on running MinIO on bare metal hardware, including container-based installations. For Kubernetes environments, use the [MinIO Kubernetes Operator](https://github.com/minio/operator/blob/master/README.md). ## Container Installation Use the following commands to run a standalone MinIO...

		if len(e.cached.versions) == 0 {
			return true
		}
		return e.cached.versions[0].header.Type == DeleteType
	}
	if !isXL2V1Format(e.metadata) {
		return false
	}
	if meta, _, err := isIndexedMetaV2(e.metadata); meta != nil {
		return meta.IsLatestDeleteMarker()
	} else if err != nil {
		return true
	}
	// Fall back...
	xlMeta, err := e.xlmeta()
	if err != nil || len(xlMeta.versions) == 0 {
		return true
	}

	case bucketPolicyConfig:
		meta.PolicyConfigJSON = configData
		meta.PolicyConfigUpdatedAt = updatedAt
	case bucketNotificationConfig:
		meta.NotificationConfigXML = configData
		meta.NotificationConfigUpdatedAt = updatedAt
	case bucketLifecycleConfig:
		meta.LifecycleConfigXML = configData
		meta.LifecycleConfigUpdatedAt = updatedAt
	case bucketSSEConfig:
		meta.EncryptionConfigXML = configData

		}

		// Always check data, if we got it.
		if (len(meta.Data) > 0 || meta.Size == 0) && len(meta.Parts) > 0 {
			checksumInfo := meta.Erasure.GetChecksumInfo(meta.Parts[0].Number)
			verifyErr := bitrotVerify(bytes.NewReader(meta.Data),
				int64(len(meta.Data)),
				meta.Erasure.ShardFileSize(meta.Size),
				checksumInfo.Algorithm,
				checksumInfo.Hash, meta.Erasure.ShardSize())
			dataErrsByPart[0][i] = convPartErrToInt(verifyErr)

		}
		if len(meta.metadata) == 0 {
			metaDataPoolPut(meta.metadata)
			meta.metadata = nil
		}
		if !inclDirs && (meta.isDir() || (!inclVersions && meta.isObjectDir() && meta.isLatestDeletemarker())) {
			continue
		}
		if !inclDeleted && meta.isLatestDeletemarker() && meta.isObject() && !meta.isObjectDir() {
			continue
		}
		res = append(res, meta)
	}