00afb9f75f
BufferDesc moved to gpu/common/task/ PiperOrigin-RevId: 340496591 Change-Id: I7d2ea7b2e68c1c56afb489b069634ac526031bf7
64 lines
2.2 KiB
C++
64 lines
2.2 KiB
C++
/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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==============================================================================*/
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#ifndef TENSORFLOW_LITE_DELEGATES_GPU_CL_UTIL_H_
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#define TENSORFLOW_LITE_DELEGATES_GPU_CL_UTIL_H_
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#include <string>
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#include "absl/types/span.h"
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#include "tensorflow/lite/delegates/gpu/cl/opencl_wrapper.h"
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#include "tensorflow/lite/delegates/gpu/common/data_type.h"
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#include "tensorflow/lite/delegates/gpu/common/status.h"
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#include "tensorflow/lite/delegates/gpu/common/tensor.h"
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#include "tensorflow/lite/delegates/gpu/common/util.h"
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namespace tflite {
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namespace gpu {
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namespace cl {
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std::string CLErrorCodeToString(cl_int error_code);
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int ChannelTypeToSizeInBytes(cl_channel_type type);
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bool OpenCLSupported();
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template <DataType S, typename T>
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void CopyLinearFLT4(const tflite::gpu::Tensor<Linear, S>& src,
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absl::Span<T> dst) {
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const int dst_depth = dst.size();
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for (int d = 0; d < dst_depth; ++d) {
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T val;
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for (int i = 0; i < 4; ++i) {
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const int dst_ch = d * 4 + i;
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val[i] = dst_ch >= src.shape.v ? 0.0f : src.data[dst_ch];
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}
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dst[d] = val;
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}
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}
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absl::Status CreateCLBuffer(cl_context context, int size_in_bytes,
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bool read_only, void* data, cl_mem* result);
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cl_channel_type DataTypeToChannelType(DataType type, bool normalized = false);
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absl::Status CreateRGBAImage2D(cl_context context, int width, int height,
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cl_channel_type channel_type, void* data,
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cl_mem* result);
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} // namespace cl
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} // namespace gpu
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} // namespace tflite
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#endif // TENSORFLOW_LITE_DELEGATES_GPU_CL_UTIL_H_
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