api(libs.conscrypt.openjdk)
  api(libs.openjsse)

  api(libs.junit.jupiter.engine)

  // This runs Corretto on macOS (aarch64) and Linux (x86_64). We don't test Corretto on other
  // operating systems or architectures.
  api(
    variantOf(libs.amazon.corretto) {
      classifier(
        when {
          OperatingSystem.current().isMacOsX -> "osx-aarch_64"
          OperatingSystem.current().isLinux -> "linux-x86_64"

#!/bin/bash

set -ex

function _init() {
	## All binaries are static make sure to disable CGO.
	export CGO_ENABLED=0
	export CRED_DIR="/media/${USER}/minio"

	## List of architectures and OS to test coss compilation.
	SUPPORTED_OSARCH="linux/ppc64le linux/amd64 linux/arm64"

	remote=$(git remote get-url upstream)
	if test "$remote" != "******@****.***:minio/minio.git"; then

the offsets being used to access them are correct.
</p>

<h2 id="architectures">Architecture-specific details</h2>

<p>
It is impractical to list all the instructions and other details for each machine.
To see what instructions are defined for a given machine, say ARM,
look in the source for the <code>obj</code> support library for
that architecture, located in the directory <code>src/cmd/internal/obj/arm</code>.

### Container Images

All container images are available as manifest lists and support the described
architectures. It is also possible to pull a specific architecture directly by
adding the "-$ARCH" suffix  to the container image name.

name | architectures
---- | -------------

### Container Images

All container images are available as manifest lists and support the described
architectures. It is also possible to pull a specific architecture directly by
adding the "-$ARCH" suffix  to the container image name.

name | architectures
---- | -------------

### Container Images

All container images are available as manifest lists and support the described
architectures. It is also possible to pull a specific architecture directly by
adding the "-$ARCH" suffix  to the container image name.

name | architectures
---- | -------------

### Container Images

All container images are available as manifest lists and support the described
architectures. It is also possible to pull a specific architecture directly by
adding the "-$ARCH" suffix  to the container image name.

name | architectures
---- | -------------

### Container Images

All container images are available as manifest lists and support the described
architectures. It is also possible to pull a specific architecture directly by
adding the "-$ARCH" suffix  to the container image name.

name | architectures
---- | -------------

{* ../../docs_src/path_params/tutorial005_py310.py hl[1,6:9] *}

/// tip

If you are wondering, "AlexNet", "ResNet", and "LeNet" are just names of Machine Learning <dfn title="Technically, Deep Learning model architectures">models</dfn>.

///

### Declare a *path parameter* { #declare-a-path-parameter }

Then create a *path parameter* with a type annotation using the enum class you created (`ModelName`):

### Container Images

All container images are available as manifest lists and support the described
architectures. It is also possible to pull a specific architecture directly by
adding the "-$ARCH" suffix  to the container image name.

name | architectures
---- | -------------