int num_retvals = 1;
  TFE_Execute(matmul, &retvals[0], &num_retvals, status);
  TFE_DeleteOp(matmul);
  if (!async) {
    EXPECT_NE(TF_OK, TF_GetCode(status));
  } else {
    TF_Tensor* t = TFE_TensorHandleResolve(retvals[0], status);
    EXPECT_NE(TF_OK, TF_GetCode(status));
    EXPECT_EQ(nullptr, t);
    const char* msg = "Matrix size-incompatible: In[0]: [2,2], In[1]: [3,2]";

  dltensor_in->dtype = {kDLFloat, 32, 1};
  dltensor_in->shape = shape.data();
  dltensor_in->strides = strides.data();
  TFE_TensorHandle* handle = TFE_HandleFromDLPack(&dlm_in, status, ctx);
  ASSERT_NE(handle, nullptr)
      << TF_Message(status) << " (shape=[" << absl::StrJoin(shape, ",")
      << "], strides=[" << absl::StrJoin(strides, ",") << "])";

  auto* dlm_out =

  TF_Tensor* a =
      TF_AllocateTensor(TF_UINT64, dims, 2, 6 * TF_DataTypeSize(TF_UINT64));
  TF_Tensor* b =
      TF_AllocateTensor(TF_UINT64, nullptr, 0, TF_DataTypeSize(TF_UINT64));
  EXPECT_NE(a, nullptr);
  EXPECT_NE(b, nullptr);

  EXPECT_EQ(6, TF_TensorElementCount(a));
  EXPECT_EQ(1, TF_TensorElementCount(b));
  EXPECT_EQ(6 * TF_DataTypeSize(TF_UINT64), TF_TensorByteSize(a));

  ASSERT_NE(func_, nullptr);

  // Verify that FunctionDef ArgDef has attributes.
  ASSERT_EQ(func_->record->fdef().arg_attr_size(), 1);
  auto arg_attrs = func_->record->fdef().arg_attr().find(0);
  ASSERT_NE(arg_attrs, func_->record->fdef().arg_attr().end());
  auto iter = arg_attrs->second.attr().find("_test_attr");
  ASSERT_NE(iter, arg_attrs->second.attr().end());

  ASSERT_EQ(TF_OK, TF_GetCode(status.get())) << TF_Message(status.get());

  // Test that full type information can be accessed.
  auto outs = unwrap(add_outputs);
  auto h = outs->outputs[0];
  ASSERT_NE(h, nullptr);
  ASSERT_EQ(h->FullType().type_id(), TFT_UNSET);
  ASSERT_EQ(unwrap(inputs[0])->FullType().type_id(), TFT_UNSET);

  // Clean up operation and inputs.
  TF_DeleteAbstractOp(add_op);

  do
    docker build \
    --build-arg REQUIREMENTS_FILE=jax.requirements.txt \
    --target=$target \
    --cache-from "$IMAGE" \
    -t "$IMAGE"  . && break
  done
  final=$?
  if [ $final -ne 0 ]; then
    exit $final
  fi
  set -e

  if [[ -n "$KOKORO_BUILD_ID" ]]; then
    gcloud auth configure-docker
    docker push "$IMAGE"
  fi

  TFE_ContextSetServerDef(ctx, 0, serialized.data(), serialized.size(), status);
  EXPECT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);

  TFE_TensorHandle* var_handle = TestVariable(ctx, 2.0, dev2_name);
  EXPECT_NE(var_handle, nullptr);
  TFE_ContextAsyncWait(ctx, status);
  EXPECT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);

  const string function_def = VariableAddFunction();

    previous behavior.

*   Performing equality operations on Tensors or Variables with incompatible
    shapes an exception is no longer thrown. Instead `__eq__` returns False and
    `__ne__` returns True.

*   Removed `tf.string_split` from v2 API.

*   Deprecated the use of `constraint=` and `.constraint` with ResourceVariable.