# license that can be found in the LICENSE file.

SOURCE="${BASH_SOURCE[0]}"
while [ -h "$SOURCE" ]; do
	DIR="$( cd -P "$( dirname "$SOURCE" )" && pwd )"
	SOURCE="$(readlink "$SOURCE")"
	[[ $SOURCE != /* ]] && SOURCE="$DIR/$SOURCE"
done
DIR="$( cd -P "$( dirname "$SOURCE" )" && pwd )"

# Increase the V8 stack size from the default of 984K
# to 8192K to ensure all tests can pass without hitting
# stack size limits.

If you've found a bug, please contribute a failing test case so we can study and fix it.

If you have a new feature idea, please build it in an external library. There are
[many libraries][works_with_okhttp] that sit on top or hook in via existing APIs. If you build
something that integrates with OkHttp, tell us so that we can link it!

Before code can be accepted all contributors must complete our

If you've found a bug, please contribute a failing test case so we can study and fix it.

If you have a new feature idea, please build it in an external library. There are
[many libraries][works_with_okhttp] that sit on top or hook in via existing APIs. If you build
something that integrates with OkHttp, tell us so that we can link it!

Before code can be accepted all contributors must complete our

### 자동으로 생성된 API 문서 확인

이제, `uvicorn`으로 메인 응용프로그램을 실행하십시오. 당신의 파일이 `main.py`라면, 이렇게 실행합니다:

<div class="termy">

```console
$ uvicorn main:app --reload

<span style="color: green;">INFO</span>:     Uvicorn running on http://127.0.0.1:8000 (Press CTRL+C to quit)
```

</div>

그리고 <a href="http://127.0.0.1:8000/docs" class="external-link" target="_blank">http://127.0.0.1:8000/docs</a>에서 문서를 여십시오.

   
   Apparently, your CPU model does not support AVX instruction sets. You can still use TensorFlow with the alternatives given below:
   
      * Try Google Colab to use TensorFlow.
         * The easiest way to use TF will be to switch to [google colab](https://colab.sandbox.google.com/notebooks/welcome.ipynb#recent=true). You get pre-installed latest stable TF version. Also you can use ```pip install```  to install any other preferred TF version.

* searching
* inspections

///

## Use the model { #use-the-model }

Inside of the function, you can access all the attributes of the model object directly:

{* ../../docs_src/body/tutorial002_py310.py *}

## Request body + path parameters { #request-body-path-parameters }

You can declare path parameters and request body at the same time.

        companies, or even industries — utilities useful for a sizable proportion of all Java
        programmers everywhere. If you can give enough detail such that any of us can imagine coming
        across a similar need in our own work, that's extremely helpful in studying how broadly
        useful the proposed change will be.

  - type: textarea
    attributes:

## How to access to files inside a ZIP archive

Accessing to contents inside an archive can be done using regular S3 API with a modified request path. You just need to append the path of the content inside the archive to the path of the archive itself.

e.g.:
To download `2021/taxes.csv` archived in `financial.zip` and stored under a bucket named `company-data`, you can issue a GET request using the following path 'company-data/financial.zip/2021/taxes.csv`

  ) {
  }

  /**
   * Invoked just prior to initiating a socket connection.
   *
   * This method will be invoked if no existing connection in the [ConnectionPool] can be reused.
   *
   * This can be invoked more than 1 time for a single [Call]. For example, if the response to the
   * [Call.request] is a redirect to a different address, or a connection is retried.
   */
  open fun connectStart(

# ==============================================================================
cat <<EOF
IMPORTANT: These tests ran under docker. This script does not clean up the
container for you! You can delete the container with:

$ docker rm -f tf

You can also execute more commands within the container with e.g.:

$ docker exec tf bazel clean
$ docker exec -it tf bash
EOF