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#ifndef TENSORFLOW_STREAM_EXECUTOR_EXECUTOR_CACHE_H_
#define TENSORFLOW_STREAM_EXECUTOR_EXECUTOR_CACHE_H_
#include "tensorflow/stream_executor/lib/status.h"
#include "tensorflow/stream_executor/lib/statusor.h"
#include "tensorflow/stream_executor/stream_executor_pimpl.h"
namespace perftools {
namespace gputools {
// Utility class to allow Platform objects to manage cached StreamExecutors.
class ExecutorCache {
public:
ExecutorCache() {}
// Inserts a new StreamExecutor with the given configuration into the cache.
// Will not overwrite if called when a matching element is already present.
port::Status Insert(const StreamExecutorConfig& config,
std::unique_ptr<StreamExecutor> executor);
// Returns a pointer to the described executor (if one with a matching config
// has been created), or a NOT_FOUND status.
port::StatusOr<StreamExecutor*> Get(const StreamExecutorConfig& config);
// Destroys all Executors and clears the cache.
// Performs no synchronization - undefined behavior may occur if any executors
// are active!
void DestroyAllExecutors();
private:
typedef std::pair<StreamExecutorConfig, std::unique_ptr<StreamExecutor>>
Entry;
// Maps ordinal number to a list of cached executors for that ordinal.
// We key off of ordinal (instead of just looking up all fields in the
// StreamExecutorConfig) for a slight improvement in lookup time.
std::map<int, std::vector<Entry>> cache_;
SE_DISALLOW_COPY_AND_ASSIGN(ExecutorCache);
};
} // namespace gputools
} // namespace perftools
#endif // TENSORFLOW_STREAM_EXECUTOR_EXECUTOR_CACHE_H_
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