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https://github.com/vee1e/tflite-micro.git
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3323a41d69
The TFLM kernels use the MicroContext and MicroGraph interfaces to fetch eval tensors and access other parts of the graph. Since codegen does not have the MicroInterpreter and related objects to serve those, this PR introduces a new MicroCodegenContext class that serves as both the MicroContext and MicroGraph. The MicroCodegenContext is configured with a span of Subgraphs, each of which includes the inputs, outputs, nodes, tensors and an invocation function. The code generator will create the data and functions needed for each Subgraph and initialize the MicroCodegenContext with it. By having the re-usable MicroCodegenContext, the code generator won't have to generate nearly as much code. BUG=b/295174086
90 lines
3.1 KiB
C++
90 lines
3.1 KiB
C++
/* Copyright 2023 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 CODEGEN_RUNTIME_MICRO_CODEGEN_CONTEXT_H_
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#define CODEGEN_RUNTIME_MICRO_CODEGEN_CONTEXT_H_
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#include "tensorflow/lite/c/common.h"
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#include "tensorflow/lite/micro/micro_context.h"
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#include "tensorflow/lite/micro/micro_graph.h"
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namespace tflite {
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// A poor man's std::span, we should consider using the Pigweed span instead.
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template <typename T>
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class Span {
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public:
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constexpr Span(T* data, size_t size) noexcept : data_(data), size_(size) {}
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constexpr T& operator[](size_t idx) const noexcept { return *(data_ + idx); }
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constexpr T* data() const noexcept { return data_; }
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constexpr size_t size() const noexcept { return size_; }
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private:
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T* data_;
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size_t size_;
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};
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struct Subgraph {
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Span<const size_t> inputs;
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Span<const size_t> outputs;
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Span<TfLiteNode> nodes;
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Span<TfLiteEvalTensor> tensors;
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TfLiteStatus (*invoke)(TfLiteContext*, Span<TfLiteNode>);
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};
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class MicroCodegenContext : public MicroContext, MicroGraph {
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public:
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MicroCodegenContext(TfLiteContext* context, Span<Subgraph> subgraphs);
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~MicroCodegenContext() = default;
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// MicroContext API
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void* AllocatePersistentBuffer(size_t bytes) override;
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TfLiteStatus RequestScratchBufferInArena(size_t bytes,
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int* buffer_idx) override;
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void* GetScratchBuffer(int buffer_idx) override;
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TfLiteTensor* AllocateTempTfLiteTensor(int tensor_idx) override;
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void DeallocateTempTfLiteTensor(TfLiteTensor* tensor) override;
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uint8_t* AllocateTempBuffer(size_t size, size_t alignment) override;
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void DeallocateTempBuffer(uint8_t* buffer) override;
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TfLiteEvalTensor* GetEvalTensor(int tensor_idx) override;
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TfLiteStatus set_external_context(void* external_context_payload) override;
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void* external_context() override;
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MicroGraph& graph() override;
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// MicroGraph API
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TfLiteStatus InvokeSubgraph(int subgraph_idx) override;
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size_t NumSubgraphInputs(int subgraph_idx) override;
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TfLiteEvalTensor* GetSubgraphInput(int subgraph_idx, int input_idx) override;
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size_t NumSubgraphOutputs(int subgraph_idx) override;
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TfLiteEvalTensor* GetSubgraphOutput(int subgraph_idx,
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int output_idx) override;
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int NumSubgraphs() override;
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MicroResourceVariables* GetResourceVariables() override;
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private:
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TfLiteContext* context_;
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Span<Subgraph> subgraphs_;
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size_t current_subgraph_idx_ = 0;
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void* external_context_payload_ = nullptr;
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TF_LITE_REMOVE_VIRTUAL_DELETE
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};
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} // namespace tflite
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#endif // CODEGEN_RUNTIME_MICRO_CODEGEN_CONTEXT_H_
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