For now we just have this global repository of ADRs.
If we see fit, we can break these out to per-platform ones, or keep a hybrid approach to having global and platform-specific ADSs.

Our aim is to keep the process lightweight and approachable.

import org.junit.jupiter.params.provider.ArgumentsSource

/** Runs the web platform URL tests against Java URL models.  */
class WebPlatformUrlTest {
  class TestDataParamProvider : SimpleProvider() {
    override fun arguments() = ArrayList<Any>(loadTests())
  }

  /** Test how [HttpUrl] does against the web platform test suite.  */
  @ArgumentsSource(TestDataParamProvider::class)
  @ParameterizedTest

#include <vector>

#include "tensorflow/c/eager/c_api.h"
#include "tensorflow/c/eager/c_api_experimental.h"
#include "tensorflow/c/tf_datatype.h"
#include "tensorflow/core/platform/logging.h"
#include "tensorflow/core/platform/tstring.h"
#include "tensorflow/core/platform/types.h"
#include "tensorflow/core/protobuf/tensorflow_server.pb.h"

// Return a tensor handle containing a float scalar

#include "tensorflow/core/framework/device_attributes.pb.h"
#include "tensorflow/core/framework/op_def.pb.h"
#include "tensorflow/core/framework/types.pb.h"
#include "tensorflow/core/platform/casts.h"
#include "tensorflow/core/platform/status.h"
#include "tensorflow/core/util/managed_stack_trace.h"

struct TFE_Op;

namespace tensorflow {

class ImmediateExecutionContext;
class AbstractOpAttrs;

    id("gradlebuild.ci-reporting")
    id("gradlebuild.test-retry")
    id("gradlebuild.private-javadoc")
}

val testLibs = project.versionCatalogs.named("testLibs")

dependencies {
    api(platform("gradlebuild:build-platform"))
    implementation("gradlebuild:gradle-plugin")

    testImplementation(testLibs.findLibrary("junit5Vintage").get())

    testRuntimeOnly(testLibs.findLibrary("junitPlatform").get())
}

## Architecture overview

### Platform architecture

Gradle is arranged into several coarse-grained components called "platforms".
Each platform provides support for some kind of automation, such as building JVM software or building Gradle plugins.

    "functionalTests": true,
    "crossVersionTests": false
  },
  {
    "name": "platform-base",
    "path": "platforms/software/platform-base",
    "unitTests": true,
    "functionalTests": true,
    "crossVersionTests": false
  },
  {
    "name": "platform-jvm",
    "path": "platforms/jvm/platform-jvm",
    "unitTests": true,
    "functionalTests": true,
    "crossVersionTests": false

import org.bouncycastle.jsse.BCSSLSocket
import org.bouncycastle.jsse.provider.BouncyCastleJsseProvider

/**
 * Platform using BouncyCastle if installed as the first Security Provider.
 *
 * Requires org.bouncycastle:bctls-jdk15on on the classpath.
 */
class BouncyCastlePlatform private constructor() : Platform() {
  private val provider: Provider = BouncyCastleJsseProvider()

   
     * If you have above configuration and using _**Windows**_ platform -
       * Try adding the CUDA, CUPTI, and cuDNN installation directories to the %PATH% environment variable.
       * Refer [windows setup guide](https://www.tensorflow.org/install/gpu#windows_setup).
     * If you have above configuration and using _**Ubuntu/Linux**_ platform -

			<scope>test</scope>
		</dependency>
		<dependency>
			<groupId>org.junit.platform</groupId>
			<artifactId>junit-platform-suite</artifactId>
			<version>1.10.3</version>
			<scope>test</scope>
		</dependency>
		<dependency>
			<groupId>org.junit.platform</groupId>
			<artifactId>junit-platform-runner</artifactId>
			<version>1.10.3</version>
			<scope>test</scope>
			<exclusions>