# sections in the ELF binary are too large, errors can occur. See
# https://github.com/tensorflow/tensorflow/issues/48919.
# Users can still include debug info for a specific kernel, e.g. with:
#     --config=dbg --per_file_copt=+tensorflow/core/kernels/identity_op.*@-g
# Since this .bazelrc file is synced between the tensorflow/tensorflow repo and

///

Çıktı olarak şöyle bir satır ile karşılaşacaksınız:

```hl_lines="4"
INFO:     Uvicorn running on http://127.0.0.1:8000 (Press CTRL+C to quit)
```

Bu satır, yerel makinenizde uygulamanızın çalıştığı bağlantıyı gösterir.

### Kontrol Edelim

Tarayıcınızı açıp <a href="http://127.0.0.1:8000" class="external-link" target="_blank">http://127.0.0.1:8000</a> bağlantısına gidin.

| `minio_system_process_syscall_read_total`          | Total read SysCalls to the kernel. /proc/[pid]/io syscr. <br><br>Type: counter                                                        | `server` |
| `minio_system_process_syscall_write_total`         | Total write SysCalls to the kernel. /proc/[pid]/io syscw. <br><br>Type: counter                                                       | `server` |

#### Docker runtime Known Issues

- Kernel crash with Aufs storage driver on Debian Jessie ([#27885](https://github.com/kubernetes/kubernetes/issues/27885))
  - Consider running the *new* [kubernetes node problem detector](https://github.com/kubernetes/node-problem-detector) to identify this (and other) kernel issues automatically.

Each node is responsible of healing its local drives; Each drive will have multiple heal workers which is the quarter of the number of CPU cores of the node or the quarter of the configured nr_requests of the drive (https://www.kernel.org/doc/Documentation/block/queue-sysfs.txt). It is also possible to provide a custom number of workers by using this command: `mc admin config set alias/ heal drive_workers=100` .


```
~ mc admin config set alias/ heal

  // scheduled on that same threadpool, causing a deadlock in cases where the
  // caller of event_mgr->ThenExecute() blocks on the completion of the callback
  // (as in the case of ConstOp kernel creation on GPU, which involves copying a
  // CPU tensor to GPU).
  // Setting a larger thread pool does not help with the Swift caller, as we use
  // a different TFE context for each thread of execution (for running graph

Próbáld kicserélni a következő sorban:

```Python
    return {"item_name": item.name, "item_id": item_id}
```

...ezt:

```Python
        ... "item_name": item.name ...
```

...erre:

```Python
        ... "item_price": item.price ...
```

... És figyeld meg hogy a szerkesztő automatikusan tudni fogja a típusokat és kiegészíti azokat:

  gci-beta-55-8872-47-0:
  Date:           Nov 11, 2016
  Kernel:         ChromiumOS-4.4
  Kubernetes:     v1.4.5
  Docker:         v1.11.2
  Changelog (vs 55-8872-18-0)
    * Cherry-pick runc PR#608: Eliminate redundant parsing of mountinfo
    * Updated kubernetes to v1.4.5

debugging information with `--config=dbg`, as issues occur on Linux if
there is too much debug info (see [this GitHub
issue](https://github.com/tensorflow/tensorflow/issues/48919) for context). If
you want to debug a kernel, you can compile specific files with `-g` using the
`--per_file_copt` bazel option. For example, if you want to debug the Identity
op, which are in files starting with `identity_op`, you can run

```bash

    * Date:           Nov 03, 2016
    * Kernel:         ChromiumOS-4.4
    * Kubernetes:     v1.4.5
    * Docker:         v1.11.2
    * Changelog (vs 55-8872-18-0)
            * Updated kubernetes to v1.4.5
            * Fixed a bug in e2fsprogs that caused mke2fs to take a very long time. Upstream fix: http://git.kernel.org/cgit/fs/ext2/e2fsprogs.git/commit/?h=next&id=d33e690fe7a6cbeb51349d9f2c7fb16a6ebec9c2