if (TF_GetCode(status) == TF_OK) {
    // This modification only updates the destination node for
    // the purposes of running this graph in a session. Thus, we don't
    // record the source node as being modified.
    RecordMutation(graph, *dst.oper, "updating input tensor");
  }
}

// Apis that are corresponding to python c api. --------------------------

    size_t requested_read_length;
    if (n > INT32_MAX)
      requested_read_length = INT32_MAX;
    else
      requested_read_length = n;

    // `pread` returns a `ssize_t` on POSIX, but due to interface being
    // cross-platform, return type of `Read` is `int64_t`.
    int64_t r = int64_t{pread(posix_file->fd, dst, requested_read_length,
                              static_cast<off_t>(offset))};
    if (r > 0) {
      dst += r;

          EXPECT_EQ(out, x);
        }));
  }
  // The `threads` destructor blocks until the threads can be joined, once their
  // respective reads finish (which happens once they are all concurrently being
  // executed, or 10 seconds have passed).
}

TEST(RamFileBlockCacheTest, CoalesceConcurrentReads) {
  // Concurrent reads to the same file blocks should be de-duplicated.
  const size_t block_size = 16;

  return schemes;
}

// `INSTANTIATE_TEST_SUITE_P` is called once for every `TEST_P`. However, we
// only want to analyze the user provided schemes and those that are registered
// only once. Hence, this function keeping another static pointer to a vector
// which contains only the schemes under test.
//
// Without this additional step, when there are schemes available but the user

      EXPECT_EQ(orig_ptr, TF_TensorData(t));
    } else {
      // In sync mode, forwarding can't really happen since the client code will
      // have a reference count on the input tensor while the kernel is being
      // executed and thus it cannot be re-used for the return tensor.
      EXPECT_NE(orig_ptr, TF_TensorData(t));
    }
  }

  ASSERT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);

int64_t TapeVSpace::NumElements(AbstractTensorHandle* tensor) const {
  // TODO(srbs): It seems like this is used only for performance optimization
  // and not for correctness. The only downside of keeping this 1 seems to be
  // that the gradient accumulation is unbounded and we will never
  // aggressively aggregate accumulated gradients to recover memory.
  // Revisit and fix.
  return 1;
}

  }

  const char* func_name_ = "MyFunc";
  const char* func_node_name_ = "MyFunc_0";
  TF_Status* s_;
  TF_Graph* func_graph_;
  TF_Graph* host_graph_;
  TF_Function* func_;

  // Workaround for not being able to initialize empty map using {}
  std::unordered_set<string> empty_;
};

TEST_F(CApiFunctionTest, OneOp_ZeroInputs_OneOutput) {
  /*
   *                constant
   *                   |