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vikramdattuvikramdattu
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Added python_ops_resolver from latest tflite-micro
 - all_ops_resolver is removed from latest tflite-micro sources. - Created `openmv-libtf-updated.cpp` from `openmv-libtf.cpp` and used python_ops_resolver instead of all_ops_resolver Signed-off-by: Vikram <[email protected]>
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‎micropython-modules/microlite/openmv-libtf-updated.cpp‎

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/* This file is part of the OpenMV project.
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* Copyright (c) 2013-2019 Ibrahim Abdelkader <[email protected]> & Kwabena W. Agyeman <[email protected]>
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* This work is licensed under the MIT license, see the file LICENSE for details.
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*/
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// Copied and modified for using with newer tflite-micro sources
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#include "python_ops_resolver.h"
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#include "tensorflow/lite/micro/tflite_bridge/micro_error_reporter.h"
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#include "tensorflow/lite/micro/micro_interpreter.h"
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#include "tensorflow/lite/schema/schema_generated.h"
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#include "tensorflow-microlite.h"
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#include "openmv-libtf.h"
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#include "micropython-error-reporter.h"
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#include <stdio.h>
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extern "C" {
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STATIC microlite::MicropythonErrorReporter micro_error_reporter;
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/*
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Return the index'th tensor
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*/
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TfLiteTensor *libtf_interpreter_get_input_tensor(microlite_interpreter_obj_t *microlite_interpreter, mp_uint_t index) {
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tflite::MicroInterpreter *interpreter = (tflite::MicroInterpreter *)microlite_interpreter->tf_interpreter;
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return interpreter->input((size_t)index);
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}
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TfLiteTensor *libtf_interpreter_get_output_tensor(microlite_interpreter_obj_t *microlite_interpreter, mp_uint_t index) {
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tflite::MicroInterpreter *interpreter = (tflite::MicroInterpreter *)microlite_interpreter->tf_interpreter;
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return interpreter->output((size_t)index);
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}
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// static int libtf_align_tensor_arena(uint8_t **tensor_arena, size_t *tensor_arena_size)
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// {
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// tflite::ErrorReporter *error_reporter = &micro_error_reporter;
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// error_reporter->Report("Performing Alignment");
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// uint8_t alignment = ((uint8_t) (*tensor_arena)) % 16;
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// if (alignment) {
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// unsigned int fix = 16 - alignment;
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// if ((*tensor_arena_size) < fix) {
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// return 1;
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// }
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// (*tensor_arena) += fix;
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// (*tensor_arena_size) -= fix;
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// }
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// return 0;
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// }
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int libtf_interpreter_init(microlite_interpreter_obj_t *microlite_interpreter) {
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tflite::ErrorReporter *error_reporter = &micro_error_reporter;
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const tflite::Model *model = tflite::GetModel(microlite_interpreter->model_data->items);
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// if (model->version() != TFLITE_SCHEMA_VERSION) {
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// error_reporter->Report("Model provided is schema version is not equal to supported version!");
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// return 1;
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// }
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// if (libtf_align_tensor_arena((uint8_t **)microlite_interpreter->tensor_area->items, &microlite_interpreter->tensor_area->len)) {
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// error_reporter->Report("Align failed!");
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// return 1;
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// }
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microlite_interpreter->tf_error_reporter = (mp_obj_t)error_reporter;
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microlite_interpreter->tf_model = (mp_obj_t)model;
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// tflite::MicroAllocator *allocator = tflite::MicroAllocator::Create(
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// (uint8_t*)microlite_interpreter->tensor_area->items,
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// microlite_interpreter->tensor_area->len, error_reporter);
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tflite::PythonOpsResolver op_resolver;
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tflite::MicroInterpreter *interpreter = new tflite::MicroInterpreter(model,
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op_resolver,
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(uint8_t*)microlite_interpreter->tensor_area->items,
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microlite_interpreter->tensor_area->len);
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if (interpreter->AllocateTensors() != kTfLiteOk) {
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MicroPrintf("AllocateTensors() failed!");
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return 1;
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}
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microlite_interpreter->tf_interpreter = (mp_obj_t)interpreter;
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return 0;
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}
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int libtf_interpreter_invoke(microlite_interpreter_obj_t *microlite_interpreter)
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{
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tflite::MicroInterpreter *interpreter = (tflite::MicroInterpreter *)microlite_interpreter->tf_interpreter;
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mp_call_function_1(microlite_interpreter->input_callback, microlite_interpreter);
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if (interpreter->Invoke() != kTfLiteOk) {
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MicroPrintf("Invoke() failed!");
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return 1;
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}
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mp_call_function_1(microlite_interpreter->output_callback, microlite_interpreter);
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return 0;
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}
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}

‎micropython-modules/microlite/python_ops_resolver.cc‎

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/* 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 "python_ops_resolver.h"
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#include "tensorflow/lite/micro/kernels/micro_ops.h"
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namespace tflite {
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PythonOpsResolver::PythonOpsResolver() {
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// Please keep this list of Builtin Operators in alphabetical order.
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AddAbs();
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AddAdd();
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AddAddN();
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AddArgMax();
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AddArgMin();
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AddAssignVariable();
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AddAveragePool2D();
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AddBatchToSpaceNd();
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AddBroadcastArgs();
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AddBroadcastTo();
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AddCallOnce();
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AddCast();
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AddCeil();
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AddCircularBuffer();
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AddConcatenation();
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AddConv2D();
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AddCos();
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AddCumSum();
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AddDepthToSpace();
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AddDepthwiseConv2D();
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AddDequantize();
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AddDetectionPostprocess();
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AddDiv();
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AddElu();
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AddEqual();
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AddEthosU();
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AddExp();
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AddExpandDims();
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AddFill();
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AddFloor();
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AddFloorDiv();
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AddFloorMod();
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AddFullyConnected();
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AddGather();
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AddGatherNd();
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AddGreater();
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AddGreaterEqual();
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AddHardSwish();
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AddIf();
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AddL2Normalization();
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AddL2Pool2D();
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AddLeakyRelu();
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AddLess();
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AddLessEqual();
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AddLog();
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AddLogicalAnd();
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AddLogicalNot();
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AddLogicalOr();
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AddLogistic();
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AddLogSoftmax();
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AddMaxPool2D();
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AddMaximum();
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AddMean();
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AddMinimum();
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AddMirrorPad();
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AddMul();
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AddNeg();
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AddNotEqual();
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AddPack();
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AddPad();
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AddPadV2();
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AddPrelu();
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AddQuantize();
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AddReadVariable();
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AddReduceMax();
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AddRelu();
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AddRelu6();
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AddReshape();
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AddResizeBilinear();
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AddResizeNearestNeighbor();
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AddRound();
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AddRsqrt();
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AddSelectV2();
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AddShape();
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AddSin();
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AddSlice();
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AddSoftmax();
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AddSpaceToBatchNd();
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AddSpaceToDepth();
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AddSplit();
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AddSplitV();
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AddSqrt();
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AddSquare();
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AddSquaredDifference();
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AddSqueeze();
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AddStridedSlice();
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AddSub();
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AddSum();
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AddSvdf();
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AddTanh();
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AddTranspose();
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AddTransposeConv();
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AddUnidirectionalSequenceLSTM();
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AddUnpack();
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AddVarHandle();
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AddWhile();
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AddZerosLike();
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}
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} // namespace tflite

‎micropython-modules/microlite/python_ops_resolver.h‎

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/* Copyright 2018 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_MICRO_PYTHON_OPS_RESOLVER_H_
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#define TENSORFLOW_LITE_MICRO_PYTHON_OPS_RESOLVER_H_
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#include "tensorflow/lite/micro/compatibility.h"
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#include "tensorflow/lite/micro/micro_mutable_op_resolver.h"
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namespace tflite {
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// PythonOpsResolver is used to register all the Ops for the TFLM Python
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// interpreter. This is ok since code size is not a concern from Python and
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// the goal is to be able to run any model supported by TFLM in a flexible way
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class PythonOpsResolver : public MicroMutableOpResolver<200> {
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public:
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PythonOpsResolver();
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private:
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TF_LITE_REMOVE_VIRTUAL_DELETE
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};
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} // namespace tflite
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#endif // TENSORFLOW_LITE_MICRO_PYTHON_OPS_RESOLVER_H_

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