## 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.

  private val serverProviderClass: Class<*>,
) : Platform() {
  override fun configureTlsExtensions(
    sslSocket: SSLSocket,
    hostname: String?,
    protocols: List<Protocol>,
  ) {
    val names = alpnProtocolNames(protocols)

    try {
      val alpnProvider =
        Proxy.newProxyInstance(
          Platform::class.java.classLoader,
          arrayOf(clientProviderClass, serverProviderClass),

    "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>

        implementation(projects.okhttpTestingSupport)
        implementation(projects.okhttpTls)
        implementation(projects.okhttpUrlconnection)

        if (platform == "conscrypt") {
          implementation(libs.conscrypt.openjdk)
        } else if (platform == "openjsse") {
          implementation(libs.openjsse)
        }
      }
    }

    if (testJavaVersion >= 17) {
      val androidHostTest by getting {

#include "tensorflow/c/eager/c_api_experimental_reader.h"

#include <cstdint>

#include "tensorflow/c/eager/c_api_experimental.h"
#include "tensorflow/core/platform/logging.h"
#include "tensorflow/core/platform/test.h"

namespace tensorflow {
namespace {

TFE_MonitoringCounter0* CreateCounter0(const char* counter_name);
TFE_MonitoringCounter1* CreateCounter1(const char* counter_name,

TF_CAPI_EXPORT extern int TF_OpIsStateful(const char* op_type,
                                          TF_Status* status);

// Platform specific initialization routine. Very few platforms actually require
// this to be called.
TF_CAPI_EXPORT void TF_InitMain(const char* usage, int* argc, char*** argv);

// Platform-specific implementation to return an unused port. (This should used
// in tests only.)

#include <memory>
#include <string>

#include "tensorflow/c/tf_status_helper.h"
#include "tensorflow/core/framework/tensor_shape.h"
#include "tensorflow/core/platform/status.h"
#include "tensorflow/core/platform/types.h"
#include "tensorflow/core/util/tensor_bundle/tensor_bundle.h"
#include "tensorflow/core/util/tensor_slice_reader.h"

namespace tensorflow {
namespace checkpoint {