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Implement MicroContext/Graph for codegen (#2218)
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
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| /* Copyright 2023 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. | ||
| ==============================================================================*/ | ||
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| #include "codegen/runtime/micro_codegen_context.h" | ||
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| #include "tensorflow/lite/c/common.h" | ||
| #include "tensorflow/lite/kernels/internal/compatibility.h" | ||
| #include "tensorflow/lite/kernels/op_macros.h" | ||
| #include "tensorflow/lite/micro/micro_log.h" | ||
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| namespace tflite { | ||
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| MicroCodegenContext::MicroCodegenContext(TfLiteContext* context, | ||
| Span<Subgraph> subgraphs) | ||
| : context_(context), subgraphs_(subgraphs) {} | ||
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| void* MicroCodegenContext::GetScratchBuffer(int buffer_idx) { | ||
| // TODO(rjascani): Implement scratch buffers | ||
| return nullptr; | ||
| } | ||
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| TfLiteEvalTensor* MicroCodegenContext::GetEvalTensor(int tensor_idx) { | ||
| TFLITE_DCHECK(static_cast<size_t>(tensor_idx) < | ||
| subgraphs_[current_subgraph_idx_].tensors.size()); | ||
| return &subgraphs_[current_subgraph_idx_].tensors[tensor_idx]; | ||
| } | ||
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| TfLiteStatus MicroCodegenContext::set_external_context( | ||
| void* external_context_payload) { | ||
| if (external_context_payload == nullptr || | ||
| external_context_payload_ != nullptr) { | ||
| MicroPrintf( | ||
| "Attempting to set external context to %x but it was %x already", | ||
| external_context_payload, external_context_payload_); | ||
| return kTfLiteError; | ||
| } | ||
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| external_context_payload_ = external_context_payload; | ||
| return kTfLiteOk; | ||
| } | ||
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| void* MicroCodegenContext::external_context() { | ||
| return external_context_payload_; | ||
| } | ||
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| MicroGraph& MicroCodegenContext::graph() { return *this; } | ||
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| void* MicroCodegenContext::AllocatePersistentBuffer(size_t) { | ||
| // Not allowed at Eval | ||
| TFLITE_ABORT; | ||
| return nullptr; | ||
| } | ||
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| TfLiteStatus MicroCodegenContext::RequestScratchBufferInArena(size_t, int*) { | ||
| // Not allowed at Eval | ||
| TFLITE_ABORT; | ||
| return kTfLiteError; | ||
| } | ||
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| TfLiteTensor* MicroCodegenContext::AllocateTempTfLiteTensor(int) { | ||
| // Not allowed at Eval | ||
| TFLITE_ABORT; | ||
| return nullptr; | ||
| } | ||
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| void MicroCodegenContext::DeallocateTempTfLiteTensor(TfLiteTensor*) { | ||
| // Not allowed at Eval | ||
| TFLITE_ABORT; | ||
| } | ||
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| uint8_t* MicroCodegenContext::AllocateTempBuffer(size_t, size_t) { | ||
| // Not allowed at Eval | ||
| TFLITE_ABORT; | ||
| return nullptr; | ||
| } | ||
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| void MicroCodegenContext::DeallocateTempBuffer(uint8_t*) { | ||
| // Not allowed at Eval | ||
| TFLITE_ABORT; | ||
| } | ||
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| TfLiteStatus MicroCodegenContext::InvokeSubgraph(int subgraph_idx) { | ||
| TF_LITE_ENSURE(context_, | ||
| static_cast<size_t>(subgraph_idx) < subgraphs_.size()); | ||
| size_t previous_subgraph_idx = current_subgraph_idx_; | ||
| current_subgraph_idx_ = subgraph_idx; | ||
| TfLiteStatus status = | ||
| subgraphs_[subgraph_idx].invoke(context_, subgraphs_[subgraph_idx].nodes); | ||
| current_subgraph_idx_ = previous_subgraph_idx; | ||
| return status; | ||
| } | ||
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| size_t MicroCodegenContext::NumSubgraphInputs(int subgraph_idx) { | ||
| TFLITE_DCHECK(static_cast<size_t>(subgraph_idx) < subgraphs_.size()); | ||
| return subgraphs_[subgraph_idx].inputs.size(); | ||
| } | ||
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| TfLiteEvalTensor* MicroCodegenContext::GetSubgraphInput(int subgraph_idx, | ||
| int input_idx) { | ||
| TFLITE_DCHECK(static_cast<size_t>(subgraph_idx) < subgraphs_.size()); | ||
| TFLITE_DCHECK(static_cast<size_t>(input_idx) < | ||
| subgraphs_[subgraph_idx].inputs.size()); | ||
| const size_t tensor_idx = subgraphs_[subgraph_idx].inputs[input_idx]; | ||
| return &subgraphs_[subgraph_idx].tensors[tensor_idx]; | ||
| } | ||
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| size_t MicroCodegenContext::NumSubgraphOutputs(int subgraph_idx) { | ||
| TFLITE_DCHECK(static_cast<size_t>(subgraph_idx) < subgraphs_.size()); | ||
| return subgraphs_[subgraph_idx].outputs.size(); | ||
| } | ||
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| TfLiteEvalTensor* MicroCodegenContext::GetSubgraphOutput(int subgraph_idx, | ||
| int output_idx) { | ||
| TFLITE_DCHECK(static_cast<size_t>(subgraph_idx) < subgraphs_.size()); | ||
| TFLITE_DCHECK(static_cast<size_t>(output_idx) < | ||
| subgraphs_[subgraph_idx].outputs.size()); | ||
| const size_t tensor_idx = subgraphs_[subgraph_idx].outputs[output_idx]; | ||
| return &subgraphs_[subgraph_idx].tensors[tensor_idx]; | ||
| } | ||
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| int MicroCodegenContext::NumSubgraphs() { return subgraphs_.size(); } | ||
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| MicroResourceVariables* MicroCodegenContext::GetResourceVariables() { | ||
| return nullptr; | ||
| } | ||
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| } // namespace tflite |
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