// Fetch and see that the new value is returned.
  TF_GraphGetTensorShape(graph, feed_out_0, returned_dims, num_dims, s);
  ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);
  EXPECT_EQ(2, num_dims);
  EXPECT_EQ(2, returned_dims[0]);
  EXPECT_EQ(3, returned_dims[1]);

  // Try to fetch a shape with the wrong num_dims
  TF_GraphGetTensorShape(graph, feed_out_0, returned_dims, 5, s);

        << entry.InitializationErrorString();
    string key(v2_reader_->key());
    (*var_to_shape_map)[key] = TensorShape(entry.shape());
    (*var_to_data_type_map)[key] = DataType(entry.dtype());
  }
  // The returned pointers are owned by the caller.
  return std::make_pair(std::move(var_to_shape_map),
                        std::move(var_to_data_type_map));
}

}  // namespace checkpoint

    add_output2 = TF_OutputListGet(add_outputs, 0);
    TF_DeleteOutputList(add_outputs);
  }

  TF_DeleteAbstractTensor(arg0);
  TF_DeleteAbstractTensor(arg1);

  // Finalize the function by providing the returned values.
  TF_AbstractFunction* func;
  {
    // We want to return the output of both add operations, create a new list
    // and populate it.
    TF_OutputList* func_outputs = TF_NewOutputList();

  if (ops_->translate_name == nullptr) return FileSystem::TranslateName(name);

  char* p = ops_->translate_name(filesystem_.get(), name.c_str());
  CHECK(p != nullptr) << "TranslateName(" << name << ") returned nullptr";

  std::string ret(p);
  // Since `p` is allocated by plugin, free it using plugin's method.
  plugin_memory_free_(p);
  return ret;
}

  TFE_TensorHandle* input2 = TestMatrixTensorHandle(ctx);
  TFE_Op* identityOp = TFE_NewOp(ctx, "IdentityN", status);
  CHECK_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);

  // Try to retrieve lengths before building the attributes (should fail)
  EXPECT_EQ(-1, TFE_OpGetInputLength(identityOp, "input", status));
  CHECK_NE(TF_OK, TF_GetCode(status)) << TF_Message(status);

int ModularFileSystemTest::rng_val_;
std::string ModularFileSystemTest::cloud_path_;
std::string ModularFileSystemTest::tmp_dir_;

// As some of the implementations might be missing, the tests should still pass
// if the returned `Status` signals the unimplemented state.
bool UnimplementedOrReturnsCode(Status actual_status, Code expected_code) {
  Code actual_code = actual_status.code();

// with `h`. On success, `status` is set to OK. On failure, `status` reflects
// the error and a nullptr is returned.
TF_CAPI_EXPORT extern TFE_TensorHandle* TFE_TensorHandleCopySharingTensor(
    TFE_TensorHandle* h, TF_Status* status);

// This function will block till the operation that produces `h` has
// completed. The memory returned might alias the internal memory used by

  // Returns the operation's device name.
  //
  // The value returned may be different from the one set by SetDeviceName, but
  // it will be compatible with it: the name will be updated by device placement
  // logic to refer to the specific device chosen.
  //
  // Example: If one calls `op->SetDeviceName("/device:GPU")`, the value
  // returned by DeviceName should be "/device:GPU:*" until a particular GPU is

  virtual Status SetOrUpdateServerDef(const ServerDef& server_def,
                                      bool reset_context, int keep_alive_secs,
                                      int64_t init_timeout_in_ms, int retries,
                                      bool clear_existing_contexts = false) = 0;

  // Initializes context for the local worker and no contexts will be created

    TFE_Context* ctx, int keep_alive_secs, const void* proto, size_t proto_len,
    int64_t init_timeout_in_ms, TF_Status* status,
    bool clear_existing_contexts);

// Set server def with retries and timeout. This is helpful for fault-tolerant
// initial connection in high-preemption environments, such as
// ParameterServerStrategy training.
// This API is for experimental usage and may be subject to change.