build:mkl --define=build_with_mkl=true --define=enable_mkl=true
build:mkl --define=tensorflow_mkldnn_contraction_kernel=0
build:mkl --define=build_with_openmp=true
build:mkl -c opt

# config to build OneDNN backend with a user specified threadpool.
build:mkl_threadpool --define=build_with_mkl=true --define=enable_mkl=true
build:mkl_threadpool --define=tensorflow_mkldnn_contraction_kernel=0

This is normally called a **webhook**.

## Webhooks steps

The process normally is that **you define** in your code what is the message that you will send, the **body of the request**.

You also define in some way at which **moments** your app will send those requests or events.

And **your users** define in some way (for example in a web dashboard somewhere) the **URL** where your app should send those requests.

Isso normalmente é chamado de **webhook**.

## Etapas dos Webhooks

Normalmente, o processo é que **você define** em seu código qual é a mensagem que você irá mandar, o **corpo da sua requisição**.

Você também define de alguma maneira em quais **momentos** a sua aplicação mandará essas requisições ou eventos.

E os **seus usuários** definem de alguma forma (em algum painel por exemplo) a **URL** que a sua aplicação deve enviar essas requisições.

    inline semantics, unless -fgnu89-inline is used.  */
-#if (!defined __cplusplus || __GNUC_PREREQ (4,3)) && defined __GNUC__
+#if (!defined __cplusplus || __GNUC_PREREQ (4,3) || defined __clang__) && defined __GNUC__
 # if defined __GNUC_STDC_INLINE__ || defined __cplusplus
 #  define __extern_inline extern __inline __attribute__ ((__gnu_inline__))

		switch in.Stack.Text() {
		case "else", "endif", "ifdef", "ifndef", "line":
			// Press on.
		default:
			return false
		}
	}
	switch in.Stack.Text() {
	case "define":
		in.define()
	case "else":
		in.else_()
	case "endif":
		in.endif()
	case "ifdef":
		in.ifdef(true)
	case "ifndef":
		in.ifdef(false)
	case "include":
		in.include()
	case "line":

# where fields are strings separated by whitespace.
export TF_VER_MAJOR=$(awk '/#define TF_MAJOR_VERSION/ {print $3}' tensorflow/core/public/version.h)
export TF_VER_MINOR=$(awk '/#define TF_MINOR_VERSION/ {print $3}' tensorflow/core/public/version.h)
export TF_VER_PATCH=$(awk '/#define TF_PATCH_VERSION/ {print $3}' tensorflow/core/public/version.h)

You can import it directly from `fastapi`:

```python
from fastapi import Request
```

/// tip

When you want to define dependencies that should be compatible with both HTTP and WebSockets, you can define a parameter that takes an `HTTPConnection` instead of a `Request` or a `WebSocket`.

///

# Lifespan Events

You can define logic (code) that should be executed before the application **starts up**. This means that this code will be executed **once**, **before** the application **starts receiving requests**.

The same way, you can define logic (code) that should be executed when the application is **shutting down**. In this case, this code will be executed **once**, **after** having handled possibly **many requests**.

${includes} = ?"${maven.user.conf}/maven.properties", \
              ?"${maven.project.conf}/maven.properties"

#
# Settings
#
# Define the default three levels for settings.
# The '-is' flag will override the 'maven.installation.settings' property.
# The '-ps' flag will override the 'maven.project.settings' property.

            if it should exclude from the output the fields that had the same default
            value, even when they were explicitly set.
            """
        ),
    ] = False,
    exclude_none: Annotated[
        bool,
        Doc(
            """
            Pydantic's `exclude_none` parameter, passed to Pydantic models to define