EXPECT_TRUE(TFE_CancellationManagerRegisterCallback(c_mgr, token2, &callback2,
                                                      "callback2"));

  TFE_CancellationToken token3 = TFE_CancellationManagerGetToken(c_mgr);
  EXPECT_TRUE(TFE_CancellationManagerRegisterCallback(c_mgr, token3, &callback1,
                                                      "callback3"));

static bool register_tracing = [] {
  RegisterTracingEngineFactory("graphdef", GraphTracingFactory);
  SetDefaultTracingEngine("graphdef").IgnoreError();
  return true;
}();

}  // namespace graph
}  // namespace tracing

      found_scalar_const = true;
    } else if (IsAddN(n, 2)) {
      EXPECT_FALSE(found_add);
      found_add = true;
    } else {
      ADD_FAILURE() << "Unexpected NodeDef: " << n.DebugString();
    }
  }
  EXPECT_TRUE(found_placeholder);
  EXPECT_TRUE(found_scalar_const);
  EXPECT_TRUE(found_add);

  // Add another oper to the graph.
  TF_Operation* neg = Neg(add, graph, s);

    ASSERT_TRUE(TF_GetCode(status) == TF_OK) << TF_Message(status);
    const char* device_name = TFE_OpGetDevice(matmul, status);
    ASSERT_TRUE(strstr(device_name, "GPU:0") != nullptr);

    TFE_OpSetDevice(matmul, "CPU:0", status);
    ASSERT_TRUE(TF_GetCode(status) == TF_OK) << TF_Message(status);
    device_name = TFE_OpGetDevice(matmul, status);
    ASSERT_TRUE(strstr(device_name, "CPU:0") != nullptr);
  }

    if (dev_type == device_type) {
      *device_name = dev_name;
      LOG(INFO) << "Found " << device_type << " device " << *device_name;
      TF_DeleteDeviceList(devices);
      return true;
    }
  }
  TF_DeleteDeviceList(devices);
  return false;
}

tensorflow::ServerDef GetServerDef(const string& job_name, int num_tasks) {
  tensorflow::ServerDef server_def;

    TF_SetStatus(status, TF_INVALID_ARGUMENT,
                 "op_to_reset should not be nullptr");
  }
}

void TFE_ContextEnableGraphCollection(TFE_Context* ctx) {
  tensorflow::unwrap(ctx)->SetShouldStoreGraphs(true);
}

void TFE_ContextDisableGraphCollection(TFE_Context* ctx) {
  tensorflow::unwrap(ctx)->SetShouldStoreGraphs(false);
}

uint64_t TFE_GetContextId(TFE_Context* ctx) {
  tensorflow::EagerContext* context =

  tf_gcs_filesystem::RamFileBlockCache cache(16, 32, 0, fetcher);
  std::vector<char> out;

  // First read.
  EXPECT_TRUE(cache.ValidateAndUpdateFileSignature(filename, 123));
  TF_EXPECT_OK(ReadCache(&cache, filename, 0, 16, &out));
  EXPECT_EQ(calls, 1);

  // Second read. Hit cache.
  EXPECT_TRUE(cache.ValidateAndUpdateFileSignature(filename, 123));
  TF_EXPECT_OK(ReadCache(&cache, filename, 0, 16, &out));
  EXPECT_EQ(calls, 1);

                                   " dimensions which is over the limit of ",
                                   TensorShape::MaxDimensions(), ".");
  }
  TensorShapeProto proto;
  if (num_dims < 0) {
    proto.set_unknown_rank(true);
  } else {
    for (int d = 0; d < num_dims; ++d) {
      proto.add_dim()->set_size(dims[d]);
    }
  }

  forward_op_.attrs.Set(attr_name, proto);

                       /*use_function*/ ::testing::Values(true, false)));
#else
INSTANTIATE_TEST_SUITE_P(
    UnifiedCAPI, CppGradients,
    ::testing::Combine(::testing::Values("graphdef", "mlir"),
                       /*tfrt*/ ::testing::Values(false),
                       /*use_function*/ ::testing::Values(true, false)));
#endif
}  // namespace
}  // namespace internal

}

TEST_P(ModularFileSystemTest, TestFilesExistsNoFiles) {
  const std::vector<std::string> filenames = {};
  EXPECT_TRUE(env_->FilesExist(filenames, /*status=*/nullptr));

  std::vector<Status> statuses;
  EXPECT_TRUE(env_->FilesExist(filenames, &statuses));
  EXPECT_TRUE(statuses.empty());
}

TEST_P(ModularFileSystemTest, TestStatEmptyFile) {
  const std::string filepath = GetURIForPath("a_file");