| /* Copyright 2019 The TensorFlow Authors. All Rights Reserved. |
| |
| Licensed under the Apache License, Version 2.0 (the "License"); |
| you may not use this file except in compliance with the License. |
| You may obtain a copy of the License at |
| |
| http://www.apache.org/licenses/LICENSE-2.0 |
| |
| Unless required by applicable law or agreed to in writing, software |
| distributed under the License is distributed on an "AS IS" BASIS, |
| WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
| See the License for the specific language governing permissions and |
| limitations under the License. |
| ==============================================================================*/ |
| |
| #ifndef TENSORFLOW_LITE_DELEGATES_GPU_CL_ENVIRONMENT_H_ |
| #define TENSORFLOW_LITE_DELEGATES_GPU_CL_ENVIRONMENT_H_ |
| |
| #include "tensorflow/lite/delegates/gpu/cl/cl_command_queue.h" |
| #include "tensorflow/lite/delegates/gpu/cl/cl_context.h" |
| #include "tensorflow/lite/delegates/gpu/cl/cl_device.h" |
| #include "tensorflow/lite/delegates/gpu/cl/program_cache.h" |
| #include "tensorflow/lite/delegates/gpu/common/data_type.h" |
| #include "tensorflow/lite/delegates/gpu/common/gpu_info.h" |
| #include "tensorflow/lite/delegates/gpu/common/precision.h" |
| #include "tensorflow/lite/delegates/gpu/common/status.h" |
| #include "tensorflow/lite/delegates/gpu/common/task/tensor_desc.h" |
| #include "tensorflow/lite/delegates/gpu/common/tensor.h" |
| |
| namespace tflite { |
| namespace gpu { |
| namespace cl { |
| |
| class Environment { |
| public: |
| Environment() = default; |
| explicit Environment(CLDevice&& device, CLContext&& context, |
| CLCommandQueue&& queue, |
| ProfilingCommandQueue&& profiling_queue); |
| // Move only |
| Environment(Environment&& environment); |
| Environment& operator=(Environment&& environment); |
| Environment(const Environment&) = delete; |
| Environment& operator=(const Environment&) = delete; |
| |
| const CLDevice& device() const { return device_; } |
| CLDevice* GetDevicePtr() { return &device_; } |
| const CLDevice* GetDevicePtr() const { return &device_; } |
| CLContext& context() { return context_; } |
| CLCommandQueue* queue() { return &queue_; } |
| ProfilingCommandQueue* profiling_queue() { return &profiling_queue_; } |
| ProgramCache* program_cache() { return &program_cache_; } |
| const ProgramCache* program_cache() const { return &program_cache_; } |
| |
| std::vector<CalculationsPrecision> GetSupportedPrecisions() const; |
| bool IsSupported(CalculationsPrecision precision) const; |
| std::vector<TensorStorageType> GetSupportedStorages() const; |
| // returns storage types that support zero clamping when reading OOB in HW |
| // (Height/Width) dimensions. |
| std::vector<TensorStorageType> GetSupportedStoragesWithHWZeroClampSupport() |
| const; |
| bool IsSupported(TensorStorageType storage_type) const; |
| |
| absl::Status Init(); |
| |
| void SetHighPerformance() const; |
| void SetDefaultPerformance() const; |
| void SetLowPerformance() const; // for energy saving |
| |
| private: |
| CLDevice device_; |
| CLContext context_; |
| CLCommandQueue queue_; |
| ProfilingCommandQueue profiling_queue_; |
| ProgramCache program_cache_; |
| }; |
| |
| TensorStorageType GetFastestStorageType(const GpuInfo& gpu_info); |
| TensorStorageType GetStorageTypeWithMinimalMemoryConsumption( |
| const GpuInfo& gpu_info); |
| |
| // Checks if image 2D creation from sub-buffer is supported. |
| bool CanUseSubBufferForImage2d(const GpuInfo& gpu_info); |
| |
| absl::Status CreateEnvironment(Environment* result); |
| |
| } // namespace cl |
| } // namespace gpu |
| } // namespace tflite |
| |
| #endif // TENSORFLOW_LITE_DELEGATES_GPU_CL_ENVIRONMENT_H_ |