## 1. Prerequisites

* Familiarity with [Docker Compose](https://docs.docker.com/compose/overview/).
* Docker installed on your machine. Download the relevant installer from [here](https://www.docker.com/community-edition#/download).

## 2. Run Distributed MinIO on Docker Compose

app = FastAPI()


class CustomORJSONResponse(Response):
    media_type = "application/json"

    def render(self, content: Any) -> bytes:
        assert orjson is not None, "orjson must be installed"
        return orjson.dumps(content, option=orjson.OPT_INDENT_2)


@app.get("/", response_class=CustomORJSONResponse)
async def main():

This container branches off from
/tensorflow/tools/tf_sig_build_dockerfiles/. However, since
hermetic CUDA and hermetic Python is now available for Tensorflow, a lot of the
requirements installed on the original container can be removed to reduce the
footprint of the container and make it more reusable across different ML

                }
                getLogger().debug(message);
            } else {
                // Locally installed file is newer, don't use the resolved version
                getLogger().debug(artifact.getArtifactId() + ": using locally installed snapshot");
            }
        }
        return version;
    }

## Prerequisites

Please make sure the following packages are already installed via `dnf` or `apt`: 

- `tuned`
- `curl`

### Install `tuned.conf` performance profile

#### Step 1 - download `tuned.conf` from the referenced link
```
wget https://raw.githubusercontent.com/minio/minio/master/docs/tuning/tuned.conf
```

#### Step 2 - install tuned.conf as supported performance profile on all nodes
```

downloads/
eggs/
.eggs/
lib/
lib64/
parts/
sdist/
var/
wheels/
*.egg-info/
.installed.cfg
*.egg
MANIFEST

# PyInstaller
#  Usually these files are written by a python script from a template
#  before PyInstaller builds the exe, so as to inject date/other infos into it.
*.manifest
*.spec

# Installer logs
pip-log.txt
pip-delete-this-directory.txt

# Unit test / coverage reports
htmlcov/

- Chroot installed on your machine.

## 2. Install MinIO in Chroot

> **Note:** MinIO community edition is now distributed as source code only. Pre-compiled binaries are no longer provided for new releases.

Build MinIO from source and install it in the chroot directory:

```sh
# Build MinIO from source
go install github.com/minio/minio@latest

RUN Add-Content -Path C:\tools\msys64\etc\pacman.d\mirrorlist.msys -Value 'SigLevel = Never'

# Install pacman packages.
RUN C:\tools\msys64\usr\bin\bash.exe -lc \
  'pacman --noconfirm -Syy curl git patch vim unzip zip'

# Install multiple Pythons, but only add one of them to PATH.
RUN function Install-Python { \
        param( \
            [string]$version, \
            [int]$prependPath \
        ) \

    ```bash
    python tf_doctest.py --file=<file_path>
    ```

    This will run it using your installed version of TensorFlow. To be sure
    you're running the same code that you're testing:

    *   Use an up to date [tf-nightly](https://pypi.org/project/tf-nightly/)
        `pip install -U tf-nightly`
    *   Rebase your pull request onto a recent pull from

about: Use this template for reporting Lite ops you are using or missing
labels: 'comp:lite'

---

**System information**
- OS Platform and Distribution (e.g., Linux Ubuntu 16.04):
- TensorFlow installed from (source or binary):
- TensorFlow version (or github SHA if from source):


**Provide the text output from tflite_convert**

```
# Copy and paste here
```

**Standalone code to reproduce the issue**