MLECO-3710: Fix for freshly updated submodule build issue.
TensorFlow Lite Micro can have stale third party components downloaded
by an older version. On a submodule update, our recommendation to users
would be to use `-DTENSORFLOW_LITE_MICRO_CLEAN_DOWNLOADS=ON` to clean
the older downloads. Moving the triggered cleaning and refresh to CMake
configuration stage (with no parallel build option). This should have a
better chance of success with the subsequent build step.
Change-Id: I305439c09658f49765ecc15eb1ce0c8b914dd30a
diff --git a/scripts/cmake/tensorflow.cmake b/scripts/cmake/tensorflow.cmake
index d807416..29d5bce 100644
--- a/scripts/cmake/tensorflow.cmake
+++ b/scripts/cmake/tensorflow.cmake
@@ -71,7 +71,16 @@
endif()
if (TENSORFLOW_LITE_MICRO_CLEAN_DOWNLOADS)
- list(APPEND MAKE_TARGETS_LIST "clean_downloads")
+ message(STATUS "Refreshing TensorFlow Lite Micro's third party downloads...")
+ execute_process(
+ COMMAND make -f ${TENSORFLOW_LITE_MICRO_PATH}/tools/make/Makefile clean_downloads third_party_downloads
+ RESULT_VARIABLE return_code
+ WORKING_DIRECTORY ${TENSORFLOW_SRC_PATH})
+ if (NOT return_code EQUAL "0")
+ message(FATAL_ERROR "Failed to clean TensorFlow Lite Micro's third party downloads.")
+ else()
+ message(STATUS "Refresh completed.")
+ endif ()
endif()
if (TENSORFLOW_LITE_MICRO_CLEAN_BUILD)
diff --git a/scripts/py/setup_hooks.py b/scripts/py/setup_hooks.py
index 97a2861..178765c 100644
--- a/scripts/py/setup_hooks.py
+++ b/scripts/py/setup_hooks.py
@@ -55,25 +55,25 @@
while read local_ref local_sha remote_ref remote_sha
do
# We should pass only added or modified C/C++ source files to cppcheck.
- changed_files=$(git diff --name-only HEAD~1 HEAD | grep -E "*\.(c|cpp|cc|cxx)" | cut -f 2)
- if [ -n "$changed_files" ]; then
- clang-format -style=file --dry-run --Werror $changed_files
+ changed_files=$(git diff --name-only HEAD~1 HEAD | grep -iE "\.(c|cpp|cxx|cc|h|hpp|hxx)$" | cut -f 2)
+ if [ -n "$changed_files" ]; then
+ clang-format -style=file --dry-run --Werror $changed_files
- exitcode1=$?
- if [ $exitcode1 -ne 0 ]; then
- echo "Formatting errors found in file: $changed_files.
- \nPlease run:\n\ \"clang-format -style=file -i $changed_files\"
- \nto correct these errors"
- exit $exitcode1
- fi
+ exitcode1=$?
+ if [ $exitcode1 -ne 0 ]; then
+ echo "Formatting errors found in file: $changed_files.
+ \nPlease run:\n\ \"clang-format -style=file -i $changed_files\"
+ \nto correct these errors"
+ exit $exitcode1
+ fi
- cppcheck --enable=performance,portability --error-exitcode=1 $changed_files
- exitcode2=$?
- if [ $exitcode2 -ne 0 ]; then
- exit $exitcode2
- fi
- fi
- exit 0
+ cppcheck --enable=performance,portability --error-exitcode=1 $changed_files
+ exitcode2=$?
+ if [ $exitcode2 -ne 0 ]; then
+ exit $exitcode2
+ fi
+ fi
+ exit 0
done
exit 0'''
diff --git a/source/application/api/common/source/Model.cc b/source/application/api/common/source/Model.cc
index 8467d71..7de6fde 100644
--- a/source/application/api/common/source/Model.cc
+++ b/source/application/api/common/source/Model.cc
@@ -1,6 +1,6 @@
/*
- * SPDX-FileCopyrightText: Copyright 2021-2022 Arm Limited and/or its affiliates <open-source-office@arm.com>
- * SPDX-License-Identifier: Apache-2.0
+ * SPDX-FileCopyrightText: Copyright 2021-2022 Arm Limited and/or its affiliates
+ * <open-source-office@arm.com> SPDX-License-Identifier: Apache-2.0
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
@@ -22,16 +22,13 @@
/* Initialise the model */
arm::app::Model::~Model()
{
- delete this->m_pInterpreter;
+ delete this->m_pInterpreter;
/**
* No clean-up function available for allocator in TensorFlow Lite Micro yet.
**/
}
-arm::app::Model::Model() :
- m_inited (false),
- m_type(kTfLiteNoType)
-{}
+arm::app::Model::Model() : m_inited(false), m_type(kTfLiteNoType) {}
bool arm::app::Model::Init(uint8_t* tensorArenaAddr,
uint32_t tensorArenaSize,
@@ -48,10 +45,10 @@
this->m_pModel = ::tflite::GetModel(nnModelAddr);
if (this->m_pModel->version() != TFLITE_SCHEMA_VERSION) {
- printf_err(
- "Model's schema version %d is not equal "
- "to supported version %d.",
- this->m_pModel->version(), TFLITE_SCHEMA_VERSION);
+ printf_err("Model's schema version %" PRIu32 " is not equal "
+ "to supported version %d.",
+ this->m_pModel->version(),
+ TFLITE_SCHEMA_VERSION);
return false;
}
@@ -75,9 +72,7 @@
/* Create an allocator instance */
info("Creating allocator using tensor arena at 0x%p\n", tensorArenaAddr);
- this->m_pAllocator = tflite::MicroAllocator::Create(
- tensorArenaAddr,
- tensorArenaSize);
+ this->m_pAllocator = tflite::MicroAllocator::Create(tensorArenaAddr, tensorArenaSize);
if (!this->m_pAllocator) {
printf_err("Failed to create allocator\n");
@@ -88,9 +83,8 @@
debug("Using existing allocator @ 0x%p\n", this->m_pAllocator);
}
- this->m_pInterpreter = new ::tflite::MicroInterpreter(
- this->m_pModel, this->GetOpResolver(),
- this->m_pAllocator);
+ this->m_pInterpreter =
+ new ::tflite::MicroInterpreter(this->m_pModel, this->GetOpResolver(), this->m_pAllocator);
if (!this->m_pInterpreter) {
printf_err("Failed to allocate interpreter\n");
@@ -120,7 +114,7 @@
printf_err("failed to get tensors\n");
return false;
} else {
- this->m_type = this->m_input[0]->type; /* Input 0 should be the main input */
+ this->m_type = this->m_input[0]->type; /* Input 0 should be the main input */
/* Clear the input & output tensors */
for (size_t inIndex = 0; inIndex < this->GetNumInputs(); inIndex++) {
@@ -155,10 +149,9 @@
debug("\ttensor is assigned to 0x%p\n", tensor);
info("\ttensor type is %s\n", TfLiteTypeGetName(tensor->type));
- info("\ttensor occupies %zu bytes with dimensions\n",
- tensor->bytes);
- for (int i = 0 ; i < tensor->dims->size; ++i) {
- info ("\t\t%d: %3d\n", i, tensor->dims->data[i]);
+ info("\ttensor occupies %zu bytes with dimensions\n", tensor->bytes);
+ for (int i = 0; i < tensor->dims->size; ++i) {
+ info("\t\t%d: %3d\n", i, tensor->dims->data[i]);
}
TfLiteQuantization quant = tensor->quantization;
@@ -192,7 +185,7 @@
}
info("Activation buffer (a.k.a tensor arena) size used: %zu\n",
- this->m_pInterpreter->arena_used_bytes());
+ this->m_pInterpreter->arena_used_bytes());
/* We expect there to be only one subgraph. */
const uint32_t nOperators = tflite::NumSubgraphOperators(this->m_pModel, 0);
@@ -203,10 +196,10 @@
auto* opcodes = this->m_pModel->operator_codes();
/* For each operator, display registration information. */
- for (size_t i = 0 ; i < nOperators; ++i) {
- const tflite::Operator* op = subgraph->operators()->Get(i);
+ for (size_t i = 0; i < nOperators; ++i) {
+ const tflite::Operator* op = subgraph->operators()->Get(i);
const tflite::OperatorCode* opcode = opcodes->Get(op->opcode_index());
- const TfLiteRegistration* reg = nullptr;
+ const TfLiteRegistration* reg = nullptr;
tflite::GetRegistrationFromOpCode(opcode, this->GetOpResolver(), ®);
std::string opName;
@@ -215,8 +208,8 @@
if (tflite::BuiltinOperator_CUSTOM == reg->builtin_code) {
opName = std::string(reg->custom_name);
} else {
- opName = std::string(EnumNameBuiltinOperator(
- tflite::BuiltinOperator(reg->builtin_code)));
+ opName = std::string(
+ EnumNameBuiltinOperator(tflite::BuiltinOperator(reg->builtin_code)));
}
}
info("\tOperator %zu: %s\n", i, opName.c_str());
@@ -236,21 +229,19 @@
bool arm::app::Model::ContainsEthosUOperator() const
{
/* We expect there to be only one subgraph. */
- const uint32_t nOperators = tflite::NumSubgraphOperators(this->m_pModel, 0);
+ const uint32_t nOperators = tflite::NumSubgraphOperators(this->m_pModel, 0);
const tflite::SubGraph* subgraph = this->m_pModel->subgraphs()->Get(0);
- const auto* opcodes = this->m_pModel->operator_codes();
+ const auto* opcodes = this->m_pModel->operator_codes();
/* check for custom operators */
- for (size_t i = 0; (i < nOperators); ++i)
- {
- const tflite::Operator* op = subgraph->operators()->Get(i);
+ for (size_t i = 0; (i < nOperators); ++i) {
+ const tflite::Operator* op = subgraph->operators()->Get(i);
const tflite::OperatorCode* opcode = opcodes->Get(op->opcode_index());
auto builtin_code = tflite::GetBuiltinCode(opcode);
if ((builtin_code == tflite::BuiltinOperator_CUSTOM) &&
- ( nullptr != opcode->custom_code()) &&
- ( "ethos-u" == std::string(opcode->custom_code()->c_str())))
- {
+ (nullptr != opcode->custom_code()) &&
+ ("ethos-u" == std::string(opcode->custom_code()->c_str()))) {
return true;
}
}
@@ -304,7 +295,6 @@
return 0;
}
-
TfLiteType arm::app::Model::GetType() const
{
return this->m_type;
@@ -339,7 +329,8 @@
info("Model info:\n");
this->LogInterpreterInfo();
- info("The model is optimised for Ethos-U NPU: %s.\n", this->ContainsEthosUOperator()? "yes": "no");
+ info("The model is optimised for Ethos-U NPU: %s.\n",
+ this->ContainsEthosUOperator() ? "yes" : "no");
return true;
}