delete reinterpret_cast<tensorflow::grappler::GraphProperties*>(
      graph_properties);
}

void TF_InferStatically(TF_GraphProperties* graph_properties,
                        TF_Bool assume_valid_feeds,
                        TF_Bool aggressive_shape_inference,
                        TF_Bool include_input_tensor_values,
                        TF_Bool include_output_tensor_values,

// Implementation of a filesystem for GCS environments.
// This filesystem will support `gs://` URI schemes.
namespace gcs = google::cloud::storage;

// The environment variable that overrides the block size for aligned reads from
// GCS. Specified in MB (e.g. "16" = 16 x 1024 x 1024 = 16777216 bytes).
constexpr char kBlockSize[] = "GCS_READ_CACHE_BLOCK_SIZE_MB";
constexpr size_t kDefaultBlockSize = 64 * 1024 * 1024;

        }));
  }
  // 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;
  int num_requests = 0;

    return errors::Unimplemented(
        "Filesystem does not support SetConfiguration()");
  }
  if (values.empty()) {
    return errors::InvalidArgument(
        "SetConfiguration() needs number of values > 0");
  }

  TF_Filesystem_Option option;
  memset(&option, 0, sizeof(option));
  option.name = const_cast<char*>(name.c_str());
  TF_Filesystem_Option_Value option_value;

  // in the cache, and our current block is not block size, this likely means
  // we have inconsistent state within the cache. Note: it's possible some
  // incomplete reads may still go undetected.
  if (block->data.size() < block_size_) {
    Key fmax = std::make_pair(key.first, std::numeric_limits<size_t>::max());
    auto fcmp = block_map_.upper_bound(fmax);

  TF_Session* sess = TF_NewSession(graph, opts, s);
  TF_DeleteSessionOptions(opts);

  TF_Output feeds[] = {TF_Output{a, 0}, TF_Output{b, 0}};
  TF_Output fetches[] = {TF_Output{plus2, 0}, TF_Output{plusB, 0}};

  const char* handle = nullptr;
  TF_SessionPRunSetup(sess, feeds, TF_ARRAYSIZE(feeds), fetches,
                      TF_ARRAYSIZE(fetches), nullptr, 0, &handle, s);

// become available after a shared object with a filesystem implementation is
// loaded, we can only check for availability after all arguments have been
// parsed.
//
// Furthermore, as `INSTANTIATE_TEST_SUITE_P` needs to be at global level and we
// don't want to have a `std::vector<std::string>` at global level, we use a
// static pointer to such a vector: we construct it via `SchemeVector()` below

  EXPECT_EQ(tensorflow::DT_INT64, attr_values.find("dtype")->second.type());

  TF_DeleteStatus(status);
  TFE_DeleteOp(var_op);
  TFE_DeleteOp(var_op_2);
  TFE_DeleteContext(ctx);
}

// Needs to work with a const TFE_Op since custom devices should not modify the
// op they are called with.
TFE_Op* CloneOp(const TFE_Op* other) {
  TF_Status* status = TF_NewStatus();