TFE_DeleteExecutor(executor);
    TFE_DeleteContext(ctx);
  }
  TF_DeleteStatus(status);
}

TEST(CAPI, Function_ident_CPU) {
  // First create a simple identity function.
  TF_Graph* function_graph = TF_NewGraph();
  TF_OperationDescription* arg_descr =
      TF_NewOperation(function_graph, "Placeholder", "arg");
  TF_SetAttrType(arg_descr, "dtype", TF_INT32);

you want to debug a kernel, you can compile specific files with `-g` using the
`--per_file_copt` bazel option. For example, if you want to debug the Identity
op, which are in files starting with `identity_op`, you can run

```bash
bazel build --config=dbg --per_file_copt=+tensorflow/core/kernels/identity_op.*@-g //tensorflow/tools/pip_package:build_pip_package
```

  ASSERT_TRUE(TF_GetCode(status.get()) == TF_OK) << TF_Message(status.get());

  std::unique_ptr<TFE_Op, decltype(&TFE_DeleteOp)> reused_op(
      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())),

         "        value {"
         "          type: DT_FLOAT"
         "        }"
         "      }"
         "    }"
         "    node_def {"
         "      name: 'identity'"
         "      op: 'Identity'"
         "      input: 'add:z:0'"
         "      device: '/job:localhost/task:0/device:CPU:0'"
         "      attr {"
         "        key: 'T'"
         "        value {"

                       AbstractTensorHandle** output, const char* name) {
  auto dtype = input->DataType();
  if (DataTypeIsFloating(BaseType(dtype)) ||
      DataTypeIsInteger(BaseType(dtype))) {
    return tensorflow::ops::Identity(ctx, input, output, name);
  } else if (!DataTypeIsComplex(BaseType(dtype)) &&
             BaseType(dtype) != DT_VARIANT) {
    return errors::InvalidArgument(
        "Expected numeric or variant tensor, got dtype ", dtype);

  int assign = TF_OpIsStateful("AssignAddVariableOp", status.get());
  ASSERT_EQ(TF_OK, TF_GetCode(status.get())) << TF_Message(status.get());
  EXPECT_EQ(assign, 1);
  int id = TF_OpIsStateful("Identity", status.get());
  ASSERT_EQ(TF_OK, TF_GetCode(status.get())) << TF_Message(status.get());
  EXPECT_EQ(id, 0);
}

class ShapeInferenceTest : public ::testing::Test {
 protected:
  ShapeInferenceTest()

  TFE_OpSetAttrType(op, "T", TFE_TensorHandleDataType(a));

  return op;
}

TFE_Op* IdentityOp(TFE_Context* ctx, TFE_TensorHandle* a) {
  TF_Status* status = TF_NewStatus();

  TFE_Op* op = TFE_NewOp(ctx, "Identity", status);
  CHECK_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
  TFE_OpAddInput(op, a, status);
  CHECK_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
  TF_DeleteStatus(status);

// nodes. This may cause incorrectness in graph analyses, but is useful for
// simulation or scheduling.
// If aggressive_shape_inference is true, nodes are executed on the host to
// identify output values when possible and does other aggressive strategies.
// This may cause incorrectness in graph analyses, but is useful for simulation
// or scheduling.
// If include_input_tensor_values is true, the values of constant

      "Licensor" shall mean the copyright owner or entity authorized by
      the copyright owner that is granting the License.

      "Legal Entity" shall mean the union of the acting entity and all
      other entities that control, are controlled by, or are under common
      control with that entity. For the purposes of this definition,
      "control" means (i) the power, direct or indirect, to cause the