checker_->FindUncompilableNodes(*uncompilable_op, flib_runtime);
  ASSERT_EQ(1, uncompilable_nodes.size());
  auto node_info_it =
      uncompilable_nodes.find(NameAttrList().ShortDebugString());
  ASSERT_NE(uncompilable_nodes.end(), node_info_it);
  const auto& uncompilable_nodes_inside_function = node_info_it->second.second;
  ASSERT_EQ(1, uncompilable_nodes_inside_function.size());

  public void testGetMultiple() {
    resetContainer(
        Helpers.mapEntry(k0(), v0()), Helpers.mapEntry(k0(), v1()), Helpers.mapEntry(k0(), v2()));
    assertGet(k0(), v0(), v1(), v2());
  }

  public void testGetAbsentKey() {
    assertGet(k4());
  }

  @CollectionSize.Require(SEVERAL)
  @MapFeature.Require(SUPPORTS_REMOVE)
  public void testPropagatesRemoveToMultimap() {
    resetContainer(

          tensorflow::unwrap(saved_model));
  tensorflow::Variable* uninitialized_variable;
  ASSERT_EQ(absl::OkStatus(), model_api->GetVariable("uninitialized_variable",
                                                     &uninitialized_variable));
  ASSERT_EQ(tensorflow::DT_FLOAT, uninitialized_variable->dtype());

  ASSERT_EQ(absl::OkStatus(),
            model_api->GetVariable("sub_module.uninitialized_variable",

  TF_GraphCopyFunction(func_graph_, func_, nullptr, s_);
  ASSERT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_);

  EXPECT_EQ(TF_GraphNumFunctions(func_graph_), 1);
  EXPECT_EQ(TF_GraphGetFunctions(func_graph_, funcs, 1, s_), 1);
  ASSERT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_);

  TF_GraphRemoveFunction(func_graph_, func_name_, s_);
  ASSERT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_);

        List<V> values = multimap().get(key);
        List<V> expectedValues = Helpers.copyToList(values);

        assertTrue(multimap().put(key, value));
        expectedValues.add(value);

        assertGet(key, expectedValues);
        assertEquals(value, values.get(values.size() - 1));
      }
    }
  }

  @MapFeature.Require(SUPPORTS_PUT)
  @CollectionSize.Require(absent = ZERO)

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

namespace mlir {
namespace TFL {
namespace {

TEST(SizeUtilTest, TestConvertsSize) {
  ASSERT_EQ(ConvertToTfliteSize(1), 1);
  ASSERT_EQ(ConvertToTfliteSize(-1), -1);
  ASSERT_EQ(ConvertToTfliteSize(mlir::ShapedType::kDynamic), -1);
}

}  // namespace
}  // namespace TFL

  /**
   * @see AbstractContainerTester#resetContainer()
   */
  protected void resetCollection() {
    resetContainer();
  }

  protected void assertGet(K key, V... values) {
    assertGet(key, Arrays.asList(values));
  }

  protected void assertGet(K key, Collection<? extends V> values) {
    assertEqualIgnoringOrder(values, multimap().get(key));

    if (!values.isEmpty()) {

  TFE_Op* op = TFE_NewOp(ctx, "ReadVariableOp", status);
  ASSERT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
  TFE_OpSetAttrType(op, "dtype", TF_FLOAT);
  TFE_OpAddInput(op, var, status);
  ASSERT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
  int num_retvals = 1;
  TFE_Execute(op, out_value, &num_retvals, status);
  ASSERT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
  TFE_DeleteOp(op);

  (*module_ref)->setAttr("tf.devices", device_dict);

  mlir::TF::RuntimeDevices devices;
  EXPECT_TRUE(mlir::succeeded(GetDevicesFromOp(*module_ref, &devices)));

  ASSERT_EQ(devices.NumDevices(), 1);
  ASSERT_EQ(devices.device_names().size(), 1);
  ASSERT_EQ(DeviceNameUtils::ParsedNameToString(devices.device_names()[0]),
            "/job:worker/replica:0/task:0/device:CPU:0");
}

TEST(DeviceUtilTest, GetGpuDeviceMetadata) {

      }));

  ASSERT_EQ(inputs.size(), 1);
  EXPECT_EQ(inputs[0], "x");
  ASSERT_EQ(outputs.size(), 1);
  EXPECT_EQ(outputs[0], "r");

  ASSERT_EQ(in_specs.size(), 1);
  ASSERT_EQ(in_specs[0].first, tensorflow::DT_INT32);
  ASSERT_TRUE(in_specs[0].second.IsIdenticalTo(PartialTensorShape({1, 3})));

  ASSERT_EQ(out_specs.size(), 1);
  ASSERT_EQ(out_specs[0].first, tensorflow::DT_INT32);