TF_DeleteTensor(t);

  for (int i = 0; i < expected_values.size(); i++) {
    EXPECT_EQ(expected_values[i], actual_values[i])
        << "Mismatch in expected values at (zero-based) index " << i;
  }
}

void CheckRemoteMatMulExecutesOK(TFE_Context* ctx,
                                 const char* remote_device_name,
                                 const char* local_device_name) {

#include "tensorflow/core/protobuf/config.pb.h"

using tensorflow::string;

namespace tensorflow {
namespace {

static bool HasSubstr(absl::string_view base, absl::string_view substr) {
  bool ok = absl::StrContains(base, substr);
  EXPECT_TRUE(ok) << base << ", expected substring " << substr;
  return ok;
}

TEST(CAPI, MonitoringCounter0) {
  TF_Status* status = TF_NewStatus();
  auto* counter =

  const uint32 block_count = 2;
  tf_gcs_filesystem::RamFileBlockCache cache(
      block_size, block_count * block_size, 0, fetcher);
  std::vector<char> out;
  // Read blocks from the cache, and verify the LRU behavior based on the
  // fetcher calls that the cache makes.
  calls.push_back(0);
  // Cache miss - drains an element from `calls`.
  TF_EXPECT_OK(ReadCache(&cache, "", 0, 1, &out));

  TF_Operation* neg = TF_GraphOperationByName(graph, "imported/neg");
  ASSERT_TRUE(scalar != nullptr);
  ASSERT_TRUE(feed != nullptr);
  ASSERT_TRUE(neg != nullptr);

  // Test basic structure of the imported graph.
  EXPECT_EQ(0, TF_OperationNumInputs(scalar));
  EXPECT_EQ(0, TF_OperationNumInputs(feed));
  ASSERT_EQ(1, TF_OperationNumInputs(neg));
  TF_Output neg_input = TF_OperationInput({neg, 0});

  executed = false;
  TFE_Execute(matmul.get(), &retval, &num_retvals, status.get());
  EXPECT_FALSE(executed);
  ASSERT_FALSE(TF_GetCode(status.get()) == TF_OK);

  // Custom devices can refuse to do type-based dispatch (as hcustom1 is
  // configured to do)
  matmul.reset(MatMulOp(context.get(), hcustom1.get(), hcpu.get()));
  num_retvals = 1;
  executed = false;
  TFE_Execute(matmul.get(), &retval, &num_retvals, status.get());

See the License for the specific language governing permissions and
limitations under the License.
==============================================================================*/
// This file extends/implements core graph optimizer base classes in terms of
// the C API defined in grappler.h. A class "CSomething" represents a
// "Something" that can be manipulated via calls in the C interface and a C
// struct called "TP_Something".

  ASSERT_TF_OK(status_);
  const std::string base = GetURIForPath("GetChildren");
  tf_gcs_filesystem::CreateDir(filesystem_, base.c_str(), status_);
  EXPECT_TF_OK(status_);

  const std::string file = io::JoinPath(base, "TestFile.csv");
  WriteString(file, "test");
  EXPECT_TF_OK(status_);

  const std::string subdir = io::JoinPath(base, "SubDir");

  bool* arrived_flag;
  // Set to true whenever an operation is executed
  bool* executed_flag;
  // If true, only explicit op placements are accepted. If false, uses
  // type-based dispatch.
  bool strict_scope_placement;
};

struct LoggedTensor {
  TFE_TensorHandle* tensor;
  LoggedTensor() = delete;
  explicit LoggedTensor(TFE_TensorHandle* tensor) : tensor(tensor) {}

  stat->generation_number = metadata->generation();
  stat->base.length = metadata->size();
  stat->base.mtime_nsec =
      metadata->time_storage_class_updated().time_since_epoch().count();
  stat->base.is_directory = object.back() == '/';
  TF_VLog(1,
          "Stat of: gs://%s/%s --  length: %u generation: %u; mtime_nsec: %u;",
          bucket.c_str(), object.c_str(), stat->base.length,

TEST_F(CApiFunctionTest, AppendHash) {
  DefineFunction("func_name_base", &func_, "Return something",
                 /*append_hash=*/true);
  tensorflow::FunctionDef fdef;
  ASSERT_TRUE(GetFunctionDef(func_, &fdef));
#if (__BYTE_ORDER__ == __ORDER_BIG_ENDIAN__)
  ASSERT_EQ(string("func_name_base_ZpgUD4x8oqk"), fdef.signature().name());
#else
  ASSERT_EQ(string("func_name_base_qaJ8jA8UmGY"), fdef.signature().name());
#endif
}