auto s = GetValue(t, &analytical_tensor);
  ASSERT_EQ(errors::OK, s.code()) << s.message();

  int64_t num_elem_analytical = 1;
  auto num_dims_analytical = TF_NumDims(analytical_tensor);
  ASSERT_EQ(dims.size(), num_dims_analytical);
  for (int j = 0; j < num_dims_analytical; j++) {
    auto dim_analytical = TF_Dim(analytical_tensor, j);
    ASSERT_EQ(dims[j], dim_analytical);
    num_elem_analytical *= dim_analytical;

    status_ = StatusFromTF_Status(status.get());
    ASSERT_EQ(errors::OK, status_.code()) << status_.message();

    {
      AbstractContext* ctx_raw = nullptr;
      status_ =
          BuildImmediateExecutionContext(std::get<1>(GetParam()), &ctx_raw);
      ASSERT_EQ(errors::OK, status_.code()) << status_.message();
      immediate_execution_ctx_.reset(ctx_raw);
    }

  std::stringstream stream;
  stream << x;
  ASSERT_EQ(stream.str(), "42");
}

TEST(OStreamTest, TestFloat32) {
  Float32 x(0.375);  // Exactly representable as a float.
  std::stringstream stream;
  stream << x;
  ASSERT_EQ(stream.str(), "0.375");
}

TEST(OStreamTest, TestString) {
  String s("foo");
  std::stringstream stream;
  stream << s;
  ASSERT_EQ(stream.str(), "foo");
}

                  }
                }));
    assertGet(k0(), v0(), v3(), v4());
  }

  @CollectionSize.Require(absent = ZERO)
  @MapFeature.Require(SUPPORTS_PUT)
  public void testPutAllNonEmptyCollectionOnPresentKey() {
    assertTrue(multimap().putAll(k0(), Lists.newArrayList(v3(), v4())));
    assertGet(k0(), v0(), v3(), v4());
  }

  @MapFeature.Require(SUPPORTS_PUT)

                  }
                }));
    assertGet(k0(), v0(), v3(), v4());
  }

  @CollectionSize.Require(absent = ZERO)
  @MapFeature.Require(SUPPORTS_PUT)
  public void testPutAllNonEmptyCollectionOnPresentKey() {
    assertTrue(multimap().putAll(k0(), Lists.newArrayList(v3(), v4())));
    assertGet(k0(), v0(), v3(), v4());
  }

  @MapFeature.Require(SUPPORTS_PUT)

                          &numerical_grad_raw);
    ASSERT_EQ(errors::OK, s.code()) << s.message();
    numerical_grad.reset(numerical_grad_raw);
  }

  TF_Tensor* numerical_tensor;
  s = GetValue(numerical_grad.get(), &numerical_tensor);
  ASSERT_EQ(errors::OK, s.code()) << s.message();
  auto num_elem_numerical = TF_TensorElementCount(numerical_tensor);
  ASSERT_EQ(num_elem_numerical, num_grad);

    multimap().replaceValues(k0(), values);
    assertGet(k0(), values);
  }

  @MapFeature.Require({SUPPORTS_PUT, SUPPORTS_REMOVE, ALLOWS_NULL_KEYS})
  public void testReplaceValuesWithNullKey() {
    List<V> values = Arrays.asList(v0(), v2(), v3());
    multimap().replaceValues(null, values);
    assertGet(null, values);
  }

  @MapFeature.Require({SUPPORTS_PUT, SUPPORTS_REMOVE})

#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

    int size = getNumElements();

    assertGet(k3(), ImmutableList.<V>of());

    assertTrue(multimap().put(k3(), v3()));

    assertGet(k3(), v3());
    assertEquals(size + 1, multimap().size());
  }

  @MapFeature.Require(SUPPORTS_PUT)
  @CollectionSize.Require(absent = ZERO)
  public void testPutPresent() {
    int size = getNumElements();

    assertGet(k0(), v0());

    int size = getNumElements();

    assertGet(k3(), ImmutableList.<V>of());

    assertTrue(multimap().put(k3(), v3()));

    assertGet(k3(), v3());
    assertEquals(size + 1, multimap().size());
  }

  @MapFeature.Require(SUPPORTS_PUT)
  @CollectionSize.Require(absent = ZERO)
  public void testPutPresent() {
    int size = getNumElements();

    assertGet(k0(), v0());