assertTrue(multimap().remove(k0(), v0()));

    assertFalse(multimap().containsEntry(k0(), v0()));
    expectMissing(e0());
    assertEquals(getNumElements() - 1, multimap().size());
    assertGet(k0(), ImmutableList.<V>of());
  }

  @CollectionSize.Require(absent = ZERO)
  @MapFeature.Require({SUPPORTS_REMOVE, ALLOWS_NULL_KEYS})
  public void testRemoveNullKeyPresent() {
    initMultimapWithNullKey();

    TF_EXPECT_OK(status);
    ASSERT_NE(nullptr, kernel.get());

    p.op_kernel = kernel.get();
    OpKernelContext ctx(&p);
    kernel->Compute(&ctx);

    ASSERT_EQ(2, num_inputs);
    ASSERT_EQ(1, num_outputs);
    ASSERT_EQ(123, ctx.mutable_output(0)->scalar<tensorflow::uint8>()());
  }
}

TEST(TestKernel, DeleteKernelBuilderIsOkOnNull) {
  TF_DeleteKernelBuilder(nullptr);
}

 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

package org.gradle.test.fixtures.server

interface ServerExpectation {
    void assertMet()

  TF_OperationDescription* desc = TF_NewOperation(graph, "Const", name);
  TF_SetAttrTensor(desc, "value", t, s);
  ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);
  TF_SetAttrType(desc, "dtype", TF_TensorType(t));
  *op = TF_FinishOperation(desc, s);
  ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);
  ASSERT_NE(*op, nullptr);
}

TF_Operation* Const(TF_Tensor* t, TF_Graph* graph, TF_Status* s,

 */

package org.gradle.test.fixtures.server

import groovy.transform.CompileStatic

@CompileStatic
abstract class ForbidOne extends OneRequestServerExpectation {

    void assertMet() {
        if (run) {
            throw new AssertionError(notMetMessage as Object)
        }
    }

    abstract String getNotMetMessage()

 */

package org.gradle.test.fixtures.server

import groovy.transform.CompileStatic

@CompileStatic
abstract class ExpectOne extends OneRequestServerExpectation {

    @Override
    void assertMet() {
        if (!run) {
            throw new AssertionError(notMetMessage as Object)
        }
    }

    abstract String getNotMetMessage()

#include "tensorflow/cc/experimental/libtf/impl/scalars.h"

#include "tensorflow/core/platform/test.h"

namespace tf {
namespace libtf {
namespace impl {

TEST(ScalarsTest, TestHeterogeneousAddition) {
  ASSERT_EQ((Int64(1) + Float32(0.375)).get(), 1.375);
}

}  // namespace impl
}  // namespace libtf

      << "], strides=[" << absl::StrJoin(strides, ",") << "])";

  auto* dlm_out =
      static_cast<DLManagedTensor*>(TFE_HandleToDLPack(handle, status));
  ASSERT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
  const DLTensor* dltensor_out = &dlm_out->dl_tensor;
  EXPECT_EQ(dltensor_out->device.device_type, dltensor_in->device.device_type);

      TFE_NewOp(context.get(), "Identity", status.get()), TFE_DeleteOp);
  TFE_OpReset(reused_op.get(), "Identity", custom_device_name, status.get());
  ASSERT_TRUE(TF_GetCode(status.get()) == TF_OK) << TF_Message(status.get());
  ASSERT_EQ(tensorflow::string(TFE_OpGetDevice(reused_op.get(), status.get())),
            tensorflow::string(custom_device_name));
  ASSERT_TRUE(TF_GetCode(status.get()) == TF_OK) << TF_Message(status.get());

    std::string first_device =
        TFE_TensorHandleBackingDeviceName(components[0].get(), status.get());
    ASSERT_EQ(underlying_devices[0], first_device);
    std::string second_device =
        TFE_TensorHandleBackingDeviceName(components[1].get(), status.get());
    ASSERT_EQ(underlying_devices[1], second_device);
  }

  // Add a parallel tensor with different values on each device to the variable.
  {