If you have an old FastAPI app, you might be using Pydantic version 1.

FastAPI version 0.100.0 had support for either Pydantic v1 or v2. It would use whichever you had installed.

FastAPI version 0.119.0 introduced partial support for Pydantic v1 from inside of Pydantic v2 (as `pydantic.v1`), to facilitate the migration to v2.

   * MyTag myTag = original.tag(MyTag.class);
   * if (myTag != null) {
   *   copy.tag(MyTag.class, () -> myTag);
   * }
   * ```
   *
   * If any event listeners were installed on this call with [addEventListener], they will not be
   * installed on this copy.
   */
  public override fun clone(): Call

  fun interface Factory {
    fun newCall(request: Request): Call
  }

            descriptor.language === Language.SWIFT -> {
                "* An installed Swift compiler. See which link:{userManualPath}/building_swift_projects.html#sec:swift_supported_tool_chain[Swift tool chains] are supported by Gradle."
            }
            descriptor.language === Language.CPP -> {

    int ERROR_NO_DATA = 232;
    /** No process is on the other end of the pipe */
    int ERROR_PIPE_NOT_CONNECTED = 233;
    /** More data is available */
    int ERROR_MORE_DATA = 234;
    /** The service is not installed */
    int ERROR_SERVICE_NOT_INSTALLED = 2184;
    /** The list of servers for this workgroup is not currently available */
    int ERROR_NO_BROWSER_SERVERS_FOUND = 6118;

    /** Array of Windows error codes */

## Prerequisites

- Prometheus and MinIO configured as explained in [document here](https://github.com/minio/minio/blob/master/docs/metrics/prometheus/README.md).
- Grafana installed as explained [here](https://grafana.com/grafana/download).

## MinIO Grafana Dashboard

-   type: dropdown id: source attributes: label: Source description: Tensorflow
    installed from options: - source - binary validations: required: true

-   type: input id: tfversion attributes: label: Tensorflow Version description:
    placeholder: ex,. tf 2.8 validations: required: true

   
      * 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.

import javax.net.ssl.SSLSocketFactory
import javax.net.ssl.TrustManagerFactory
import javax.net.ssl.X509TrustManager
import okhttp3.Protocol

/**
 * Platform using OpenJSSE (https://github.com/openjsse/openjsse) if installed as the first
 * Security Provider.
 *
 * Requires org.openjsse:openjsse >= 1.1.0 on the classpath.
 */
class OpenJSSEPlatform private constructor() : Platform() {
  private val provider: Provider =

import javax.net.ssl.X509TrustManager
import okhttp3.Protocol
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() {

	mv bin/*_*/* bin
	rmdir bin/*_*
	rm -rf "pkg/${gohostos}_${gohostarch}" "pkg/tool/${gohostos}_${gohostarch}"
fi

rm -rf pkg/bootstrap pkg/obj .git

echo ----
echo Bootstrap toolchain for "$GOOS/$GOARCH" installed in "$(pwd)".
echo Building tbz.
cd ..
tar cf - "go-${GOOS}-${GOARCH}-bootstrap" | bzip2 -9 >"go-${GOOS}-${GOARCH}-bootstrap.tbz"
ls -l "$(pwd)/go-${GOOS}-${GOARCH}-bootstrap.tbz"