package logger

import (
	"context"
	"encoding/hex"
	"errors"
	"fmt"
	"go/build"
	"path/filepath"
	"reflect"
	"runtime"
	"sort"
	"strings"
	"time"

	"github.com/minio/highwayhash"
	"github.com/minio/madmin-go/v3"
	xhttp "github.com/minio/minio/internal/http"
	"github.com/minio/pkg/v2/logger/message/log"
)

```Python hl_lines="1  3" title="app/routers/users.py"
{!../../../docs_src/bigger_applications/app/routers/users.py!}
```

### *➡ 🛠️* ⏮️ `APIRouter`

& ⤴️ 👆 ⚙️ ⚫️ 📣 👆 *➡ 🛠️*.

⚙️ ⚫️ 🎏 🌌 👆 🔜 ⚙️ `FastAPI` 🎓:

```Python hl_lines="6  11  16" title="app/routers/users.py"
{!../../../docs_src/bigger_applications/app/routers/users.py!}
```

👆 💪 💭 `APIRouter` "🐩 `FastAPI`" 🎓.

```Python hl_lines="1  3" title="app/routers/users.py"
{!../../../docs_src/bigger_applications/app/routers/users.py!}
```

### *Path operations* with `APIRouter`

And then you use it to declare your *path operations*.

Use it the same way you would use the `FastAPI` class:

```Python hl_lines="6  11  16" title="app/routers/users.py"
{!../../../docs_src/bigger_applications/app/routers/users.py!}
```

你可以导入它并通过与 `FastAPI` 类相同的方式创建一个「实例」：

```Python hl_lines="1  3" title="app/routers/users.py"
{!../../../docs_src/bigger_applications/app/routers/users.py!}
```

### 使用 `APIRouter` 的*路径操作*

然后你可以使用它来声明*路径操作*。

使用方式与 `FastAPI` 类相同：

```Python hl_lines="6  11  16" title="app/routers/users.py"
{!../../../docs_src/bigger_applications/app/routers/users.py!}
```

你可以将 `APIRouter` 视为一个「迷你 `FastAPI`」类。

所有相同的选项都得到支持。

package storageclass

import (
	"context"
	"encoding/json"
	"fmt"
	"strconv"
	"strings"
	"sync"

	"github.com/dustin/go-humanize"
	"github.com/minio/minio/internal/config"
	"github.com/minio/minio/internal/logger"
	"github.com/minio/pkg/v2/env"
)

// Standard constants for all storage class
const (
	// Reduced redundancy storage class
	RRS = "REDUCED_REDUNDANCY"
	// Standard storage class
	STANDARD = "STANDARD"
)

	"github.com/minio/minio/internal/logger"
)

func replLogIf(ctx context.Context, err error, errKind ...interface{}) {
	logger.LogIf(ctx, "replication", err, errKind...)
}

func replLogOnceIf(ctx context.Context, err error, id string, errKind ...interface{}) {
	logger.LogOnceIf(ctx, "replication", err, id, errKind...)
}

func iamLogIf(ctx context.Context, err error, errKind ...interface{}) {
	logger.LogIf(ctx, "iam", err, errKind...)
}

* **Machine Learning**: it normally requires lots of "matrix" and "vector" multiplications. Think of a huge spreadsheet with numbers and multiplying all of them together at the same time.
* **Deep Learning**: this is a sub-field of Machine Learning, so, the same applies. It's just that there is not a single spreadsheet of numbers to multiply, but a huge set of them, and in many cases, you use a special processor to build and / or use those models.

		SSHHandshakeDeadline: 2 * time.Minute,
		Logger:               new(sftpLogger),
		SSHConfig:            sshConfig,
		HandleSFTPSession:    handleSFTPSession,
	})
	if err != nil {
		logger.Fatal(err, "Unable to start SFTP Server")
	}

	err = sftpServer.Listen()
	if err != nil {
		logger.Fatal(err, "SFTP Server had an unrecoverable error while accepting connections")
	}

			g.errs[index].Err = nil
			if err := f(); err != nil {
				g.errs[index].Err = err
				// Last iteration log the error.
				if i == g.retryCount-1 {
					reqInfo := (&logger.ReqInfo{}).AppendTags("peerAddress", addr.String())
					ctx := logger.SetReqInfo(ctx, reqInfo)
					peersLogOnceIf(ctx, err, addr.String())
				}
				// Wait for a minimum of 100ms and dynamically increase this based on number of attempts.

                logger.info("Copying from {} to {}", oldIndex, index);
                if (!client.reindex(oldIndex, index, false)) {
                    logger.warn("Failed to copy from {} to {}", oldIndex, index);
                }
            } else if (logger.isDebugEnabled()) {
                if (!client.existsIndex(oldIndex)) {
                    logger.debug("{} does not exist.", oldIndex);