mirror of
https://github.com/vee1e/tflite-micro.git
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8f1f3b2623
@tensorflow/micro Remove extraneous tensor copy operation after first invocation of condition subgraph. Move copy of operator inputs to outputs, such that it occurs before the first invocation of the condition subgraph. This preserves the operator inputs when one or more of them is the output of DECODE, and alternate decompression memory is in use. This is because the output of DECODE is for immediate consumption by the next operator in the graph (WHILE), yet it is possible for the WHILE subgraph invocations to share memory with the original DECODE output. Update the unit test for multiple invocations of the condition and body subgraphs. When copying tensors between operator inputs/outputs and subgraph inputs/outputs, check if the source and destination tensors share memory. bug=fixes #3632
133 lines
5 KiB
C++
133 lines
5 KiB
C++
/* Copyright 2022 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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#include <stddef.h>
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#include <cstring>
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#include "tensorflow/lite/c/builtin_op_data.h"
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#include "tensorflow/lite/c/common.h"
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#include "tensorflow/lite/kernels/internal/compatibility.h"
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#include "tensorflow/lite/kernels/kernel_util.h"
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#include "tensorflow/lite/micro/kernels/kernel_util.h"
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#include "tensorflow/lite/micro/memory_helpers.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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#include "tensorflow/lite/micro/micro_utils.h"
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namespace tflite {
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namespace {
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struct OpData {
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int cond_subgraph_index;
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int body_subgraph_index;
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};
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void* WhileInit(TfLiteContext* context, const char* buffer, size_t length) {
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TFLITE_DCHECK(context->AllocatePersistentBuffer != nullptr);
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return context->AllocatePersistentBuffer(context, sizeof(OpData));
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}
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TfLiteStatus WhilePrepare(TfLiteContext* context, TfLiteNode* node) {
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OpData* op_data = reinterpret_cast<OpData*>(node->user_data);
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const auto* params =
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reinterpret_cast<const TfLiteWhileParams*>(node->builtin_data);
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op_data->cond_subgraph_index = params->cond_subgraph_index;
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op_data->body_subgraph_index = params->body_subgraph_index;
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// The first input is the condition.
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tflite::MicroContext* micro_context = tflite::GetMicroContext(context);
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size_t num_inputs = node->inputs->size;
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size_t num_outputs = node->outputs->size;
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MicroGraph& graph_info = micro_context->graph();
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TF_LITE_ENSURE(context,
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op_data->cond_subgraph_index < graph_info.NumSubgraphs());
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TF_LITE_ENSURE(context,
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op_data->body_subgraph_index < graph_info.NumSubgraphs());
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TF_LITE_ENSURE_EQ(context, num_inputs,
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graph_info.NumSubgraphInputs(op_data->cond_subgraph_index));
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TF_LITE_ENSURE_EQ(context, num_inputs,
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graph_info.NumSubgraphInputs(op_data->body_subgraph_index));
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TF_LITE_ENSURE_EQ(context, num_inputs, num_outputs);
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TF_LITE_ENSURE_EQ(
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context, num_outputs,
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graph_info.NumSubgraphOutputs(op_data->body_subgraph_index));
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return kTfLiteOk;
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}
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TfLiteStatus WhileEval(TfLiteContext* context, TfLiteNode* node) {
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const OpData* op_data = reinterpret_cast<OpData*>(node->user_data);
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tflite::MicroContext* micro_context = tflite::GetMicroContext(context);
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MicroGraph* graph_info = µ_context->graph();
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TF_LITE_ENSURE_OK(context,
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tflite::micro::CopyOpInputsToSubgraphInputs(
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context, node, graph_info, op_data->cond_subgraph_index,
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/*first_tensor_idx=*/0));
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// Preserve the op inputs by copying to op outputs, prior to invoking
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// a subgraph which could invalidate the memory of one or more op inputs.
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// This is possible when using the output of the DECODE operator as input to
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// the WHILE op, in the presence of alternate decompression memory.
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TF_LITE_ENSURE_OK(context,
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tflite::micro::CopyOpInputsToOpOutputs(context, node));
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TF_LITE_ENSURE_OK(context,
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graph_info->InvokeSubgraph(op_data->cond_subgraph_index));
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TfLiteEvalTensor* cond_subgraph_output = graph_info->GetSubgraphOutput(
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op_data->cond_subgraph_index, /*tensor_idx=*/0);
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bool cond_value = cond_subgraph_output->data.b[0];
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while (cond_value == true) {
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// Copy output of this iteration back to the body input.
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TF_LITE_ENSURE_OK(
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context, tflite::micro::CopyOpOutputsToSubgraphInputs(
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context, node, graph_info, op_data->body_subgraph_index));
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TF_LITE_ENSURE_OK(context,
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graph_info->InvokeSubgraph(op_data->body_subgraph_index));
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TF_LITE_ENSURE_OK(
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context, tflite::micro::CopySubgraphOutputsToOpOutputs(
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context, node, graph_info, op_data->body_subgraph_index));
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TF_LITE_ENSURE_OK(
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context, tflite::micro::CopyOpOutputsToSubgraphInputs(
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context, node, graph_info, op_data->cond_subgraph_index));
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TF_LITE_ENSURE_OK(context,
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graph_info->InvokeSubgraph(op_data->cond_subgraph_index));
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cond_subgraph_output = graph_info->GetSubgraphOutput(
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op_data->cond_subgraph_index, /*tensor_idx=*/0);
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cond_value = cond_subgraph_output->data.b[0];
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}
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return kTfLiteOk;
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}
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} // namespace.
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TFLMRegistration Register_WHILE() {
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return tflite::micro::RegisterOp(WhileInit, WhilePrepare, WhileEval);
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}
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} // namespace tflite
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