TFE_TensorHandle* h, TF_Status* status) {
  tensorflow::TensorHandle* handle =
      TensorHandleFromInterface(tensorflow::unwrap(h));
  const tensorflow::Tensor* tensor;
  status->status = handle->Tensor(&tensor);
  if (!status->status.ok()) {
    return nullptr;
  }

  std::vector<int64_t> dev_dims = TensorShapeAsVector(*handle, &status->status);
  if (!status->status.ok()) {
    return nullptr;

  ASSERT_EQ(errors::OK, s.code()) << s.message();

  TF_Tensor* result_tensor;
  s = GetValue(outputs[0], &result_tensor);
  ASSERT_EQ(errors::OK, s.code()) << s.message();
  auto result_value = static_cast<float*>(TF_TensorData(result_tensor));
  EXPECT_EQ(*result_value, 1.0);
  outputs[0]->Unref();
  TF_DeleteTensor(result_tensor);
  result_tensor = nullptr;
}

INSTANTIATE_TEST_SUITE_P(

  }

  /**
   * Send a close frame with optional code and reason.
   *
   * @param code Status code as defined by
   *     [Section 7.4 of RFC 6455](http://tools.ietf.org/html/rfc6455#section-7.4) or `0`.
   * @param reason Reason for shutting down or `null`.
   */
  @Throws(IOException::class)
  fun writeClose(
    code: Int,
    reason: ByteString?,
  ) {
    var payload = ByteString.EMPTY

	person := Person{Name: "person", Addresses: []Address{address1, address2}}
	DB.Create(&person)

	var addresses1 []Address
	if err := DB.Model(&person).Association("Addresses").Find(&addresses1); err != nil || len(addresses1) != 2 {
		t.Fatalf("Failed to find address, got error %v, length: %v", err, len(addresses1))
	}

	if err := DB.Model(&person).Association("Addresses").Delete(&person.Addresses[0]); err != nil {

                """
            ),
        ],
        reason: Annotated[
            Union[str, None],
            Doc(
                """
                The reason to close the WebSocket connection.

                It is UTF-8-encoded data. The interpretation of the reason is up to the
                application, it is not specified by the WebSocket specification.

        .`when`(
          request().withPath("/person")
            .withQueryStringParameter("name", "peter"),
        )
        .respond(response().withBody("Peter the person!"))

      val response = client.newCall(Request((mockServer.endpoint + "/person?name=peter").toHttpUrl())).execute()

      assertThat(response.body.string()).contains("Peter the person")
    }
  }

  @Test
  fun testHttpsRequest() {

		if info.Person == nil {
			t.Fatalf("Failed, expected not nil, got person nil")
		}
		if info.Address == nil {
			t.Fatalf("Failed, expected not nil, got address nil")
		}
		if info.Person.ID == person1.ID {
			personMatched = true
			if info.Person.Name != person1.Name {
				t.Errorf("Failed, expected %v, got %v", person1.Name, info.Person.Name)
			}
		}

        .`when`(
          request().withPath("/person")
            .withQueryStringParameter("name", "peter"),
        )
        .respond(response().withBody("Peter the person!"))

      val results =
        (1..20).map {
          executor.submit {
            val response =
              client.newCall(Request((mockServer.secureEndpoint + "/person?name=peter").toHttpUrl())).execute()

#ifndef TENSORFLOW_C_EAGER_DLPACK_H_
#define TENSORFLOW_C_EAGER_DLPACK_H_

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

namespace tensorflow {

// PyCapsule name for DLPack Tensor
const char* const kDlTensorCapsuleName = "dltensor";

// Converts eager tensor handle to DLPack (DLManagedTensor*), and return the
// void* for further PyCapsule construction.
TF_CAPI_EXPORT extern void* TFE_HandleToDLPack(TFE_TensorHandle* h,

from .utils import needs_pydanticv1, needs_pydanticv2


class Person:
    def __init__(self, name: str):
        self.name = name


class Pet:
    def __init__(self, owner: Person, name: str):
        self.owner = owner
        self.name = name


@dataclass
class Item:
    name: str
    count: int


class DictablePerson(Person):
    def __iter__(self):