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samples: add tensorflow hello world sample

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Adds Tensorflow Hello World sample to tree.

Signed-off-by: Lauren Murphy <lauren.murphy@intel.com>
This commit is contained in:
Lauren Murphy 2021-04-26 22:01:30 -05:00 • committed by Anas Nashif
commit cb4d28a066
16 changed files with 769 additions and 0 deletions
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samples/modules/tensorflow/hello_world/CMakeLists.txt Normal file
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cmake_minimum_required(VERSION 3.13.1)
find_package(Zephyr REQUIRED HINTS $ENV{ZEPHYR_BASE})
project(tensorflow_hello_world)
# Required for TensorFlow to compile properly
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -fno-threadsafe-statics")
target_sources(app PRIVATE
src/assert.cc
src/main.c
src/main_functions.cc
src/constants.c
src/output_handler.cc
src/model.cc
src/model.h
src/output_handler.h
src/constants.h
src/main_functions.h
)

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.. _tensorflow_hello_world:
TensorFlow Hello World sample
#############################
Overview
********
This sample TensorFlow application replicates a sine wave and
demonstrates the absolute basics of using TensorFlow Lite Micro.
The model included with the sample is trained to replicate a
sine function and generates x values to print alongside the
y values predicted by the model. The x values iterate from 0 to
an approximation of 2π.
The sample also includes a full end-to-end workflow of training
a model and converting it for use with TensorFlow Lite Micro for
running inference on a microcontroller.
.. Note::
This README and sample have been modified from
`the TensorFlow Hello World sample for Zephyr`_.
.. _the TensorFlow Hello World sample for Zephyr:
https://github.com/tensorflow/tensorflow/tree/master/tensorflow/lite/micro/examples/hello_world
Building and Running
********************
This sample should work on most boards since it does not rely
on any sensors.
This application can be built and executed on QEMU as follows:
.. zephyr-app-commands::
:zephyr-app: samples/tensorflow/hello_world
:host-os: unix
:board: qemu_x86
:goals: run
:compact:
Exit QEMU by pressing :kbd:`CTRL+A` :kbd:`x`.
Sample Output
=============
.. code-block:: console
...
x_value: 1.0995567*2^1, y_value: 1.6951603*2^-1
x_value: 1.2566366*2^1, y_value: 1.1527088*2^-1
x_value: 1.4137159*2^1, y_value: 1.1527088*2^-2
x_value: 1.5707957*2^1, y_value: -1.0849024*2^-6
x_value: 1.7278753*2^1, y_value: -1.0509993*2^-2
...
The modified sample prints 50 generated-x-and-predicted-y pairs.
Modifying Sample for Your Own Project
*************************************
It is recommended that you copy and modify one of the two TensorFlow
samples when creating your own TensorFlow project. To build with
TensorFlow, you must enable the below Kconfig options in your :file:`prj.conf`
and set a flag in your :file:`CMakeLists.txt`.
:file:`prj.conf`:
.. code-block:: console
CONFIG_CPLUSPLUS=y
CONFIG_NEWLIB_LIBC=y
CONFIG_TENSORFLOW_LITE_MICRO=y
:file:`CMakeLists.txt`:
.. code-block:: console
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -fno-threadsafe-statics")
Training
********
Follow the instructions in the :file:`train/` directory to train your
own model for use in the sample.

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samples/modules/tensorflow/hello_world/prj.conf Normal file
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# Copyright 2019 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.
# ==============================================================================s
CONFIG_CPLUSPLUS=y
CONFIG_NEWLIB_LIBC=y
CONFIG_TENSORFLOW_LITE_MICRO=y

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samples/modules/tensorflow/hello_world/sample.yaml Normal file
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sample:
description: Hello World TensorFlow sample
name: hello world tensorflow
common:
tags: tensorflow
harness: console
harness_config:
type: multi_line
ordered: false
regex:
- "x_value:.*, y_value:.*"
- ""
tests:
sample.tensorflow.helloworld:
platform_allow: qemu_x86 qemu_x86_64
tags: tensorflow

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/*
* Copyright 2020 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.
*/
extern "C" {
void __assert_func(const char *, int, const char *, const char *)
{
}
}

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/*
* Copyright 2020 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.
*/
#include "constants.h"
/* This is a small number so that it's easy to read the logs */
const int kInferencesPerCycle = 20;

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samples/modules/tensorflow/hello_world/src/constants.h Normal file
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/*
* Copyright 2020 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.
*/
#ifndef TENSORFLOW_LITE_MICRO_EXAMPLES_HELLO_WORLD_CONSTANTS_H_
#define TENSORFLOW_LITE_MICRO_EXAMPLES_HELLO_WORLD_CONSTANTS_H_
/* This constant represents the range of x values our model was trained on,
* which is from 0 to (2 * Pi). We approximate Pi to avoid requiring additional
* libraries.
*/
const float kXrange = 2.f * 3.14159265359f;
/* This constant determines the number of inferences to perform across the range
* of x values defined above. Since each inference takes time, the higher this
* number, the more time it will take to run through the entire range. The value
* of this constant can be tuned so that one full cycle takes a desired amount
* of time. Since different devices take different amounts of time to perform
* inference, this value should be defined per-device.
*/
extern const int kInferencesPerCycle;
#endif /* TENSORFLOW_LITE_MICRO_EXAMPLES_HELLO_WORLD_CONSTANTS_H_ */

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/*
* Copyright 2020 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.
*/
#include "main_functions.h"
#define NUM_LOOPS 50
/* This is the default main used on systems that have the standard C entry
* point. Other devices (for example FreeRTOS or ESP32) that have different
* requirements for entry code (like an app_main function) should specialize
* this main.cc file in a target-specific subfolder.
*/
int main(int argc, char *argv[])
{
setup();
/* Note: Modified from original while(true) to accommodate CI */
for (int i = 0; i < NUM_LOOPS; i++) {
loop();
}
return 0;
}

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/*
* Copyright 2020 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.
*/
#include "main_functions.h"
#include <tensorflow/lite/micro/all_ops_resolver.h>
#include "constants.h"
#include "model.h"
#include "output_handler.h"
#include <tensorflow/lite/micro/micro_error_reporter.h>
#include <tensorflow/lite/micro/micro_interpreter.h>
#include <tensorflow/lite/schema/schema_generated.h>
#include <tensorflow/lite/version.h>
/* Globals, used for compatibility with Arduino-style sketches. */
namespace {
tflite::ErrorReporter *error_reporter = nullptr;
const tflite::Model *model = nullptr;
tflite::MicroInterpreter *interpreter = nullptr;
TfLiteTensor *input = nullptr;
TfLiteTensor *output = nullptr;
int inference_count = 0;
/* Create an area of memory to use for input, output, and intermediate arrays.
* Minimum arena size, at the time of writing. After allocating tensors
* you can retrieve this value by invoking interpreter.arena_used_bytes().
*/
const int kModelArenaSize = 2468;
/* Extra headroom for model + alignment + future interpreter changes. */
const int kExtraArenaSize = 560 + 16 + 100;
const int kTensorArenaSize = kModelArenaSize + kExtraArenaSize;
uint8_t tensor_arena[kTensorArenaSize];
} /* namespace */
/* The name of this function is important for Arduino compatibility. */
void setup(void)
{
/* Set up logging. Google style is to avoid globals or statics because of
* lifetime uncertainty, but since this has a trivial destructor it's okay.
* NOLINTNEXTLINE(runtime-global-variables)
*/
static tflite::MicroErrorReporter micro_error_reporter;
error_reporter = &micro_error_reporter;
/* Map the model into a usable data structure. This doesn't involve any
* copying or parsing, it's a very lightweight operation.
*/
model = tflite::GetModel(g_model);
if (model->version() != TFLITE_SCHEMA_VERSION) {
TF_LITE_REPORT_ERROR(error_reporter,
"Model provided is schema version %d not equal "
"to supported version %d.",
model->version(), TFLITE_SCHEMA_VERSION);
return;
}
/* This pulls in all the operation implementations we need.
* NOLINTNEXTLINE(runtime-global-variables)
*/
static tflite::AllOpsResolver resolver;
/* Build an interpreter to run the model with. */
static tflite::MicroInterpreter static_interpreter(
model, resolver, tensor_arena, kTensorArenaSize, error_reporter);
interpreter = &static_interpreter;
/* Allocate memory from the tensor_arena for the model's tensors. */
TfLiteStatus allocate_status = interpreter->AllocateTensors();
if (allocate_status != kTfLiteOk) {
TF_LITE_REPORT_ERROR(error_reporter, "AllocateTensors() failed");
return;
}
/* Obtain pointers to the model's input and output tensors. */
input = interpreter->input(0);
output = interpreter->output(0);
/* Keep track of how many inferences we have performed. */
inference_count = 0;
}
/* The name of this function is important for Arduino compatibility. */
void loop(void)
{
/* Calculate an x value to feed into the model. We compare the current
* inference_count to the number of inferences per cycle to determine
* our position within the range of possible x values the model was
* trained on, and use this to calculate a value.
*/
float position = static_cast < float > (inference_count) /
static_cast < float > (kInferencesPerCycle);
float x_val = position * kXrange;
/* Place our calculated x value in the model's input tensor */
input->data.f[0] = x_val;
/* Run inference, and report any error */
TfLiteStatus invoke_status = interpreter->Invoke();
if (invoke_status != kTfLiteOk) {
TF_LITE_REPORT_ERROR(error_reporter, "Invoke failed on x_val: %f\n",
static_cast < double > (x_val));
return;
}
/* Read the predicted y value from the model's output tensor */
float y_val = output->data.f[0];
/* Output the results. A custom HandleOutput function can be implemented
* for each supported hardware target.
*/
HandleOutput(error_reporter, x_val, y_val);
/* Increment the inference_counter, and reset it if we have reached
* the total number per cycle
*/
inference_count += 1;
if (inference_count >= kInferencesPerCycle) {
inference_count = 0;
}
}

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/*
* Copyright 2020 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.
*/
#ifndef TENSORFLOW_LITE_MICRO_EXAMPLES_HELLO_WORLD_MAIN_FUNCTIONS_H_
#define TENSORFLOW_LITE_MICRO_EXAMPLES_HELLO_WORLD_MAIN_FUNCTIONS_H_
/* Expose a C friendly interface for main functions. */
#ifdef __cplusplus
extern "C" {
#endif
/* Initializes all data needed for the example. The name is important, and needs
* to be setup() for Arduino compatibility.
*/
void setup(void);
/* Runs one iteration of data gathering and inference. This should be called
* repeatedly from the application code. The name needs to be loop() for Arduino
* compatibility.
*/
void loop(void);
#ifdef __cplusplus
}
#endif
#endif /* TENSORFLOW_LITE_MICRO_EXAMPLES_HELLO_WORLD_MAIN_FUNCTIONS_H_ */

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/*
* Copyright 2020 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.
*/
/* Automatically created from a TensorFlow Lite flatbuffer using the command:
* xxd -i model.tflite > model.cc
*
* This is a standard TensorFlow Lite model file that has been converted into a
* C data array, so it can be easily compiled into a binary for devices that
* don't have a file system.
*
* See train/README.md for a full description of the creation process.
*/
#include "model.h"
/* Keep model aligned to 8 bytes to guarantee aligned 64-bit accesses. */
alignas(8) const unsigned char g_model[] = {
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0x10, 0x00, 0x14, 0x00, 0x0e, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x09,
0x6c, 0x00, 0x00, 0x00, 0x0a, 0x00, 0x00, 0x00, 0x50, 0x00, 0x00, 0x00,
0x10, 0x00, 0x00, 0x00, 0x0c, 0x00, 0x14, 0x00, 0x04, 0x00, 0x08, 0x00,
0x0c, 0x00, 0x10, 0x00, 0x0c, 0x00, 0x00, 0x00, 0x30, 0x00, 0x00, 0x00,
0x24, 0x00, 0x00, 0x00, 0x18, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00,
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0x00, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x1a, 0xde, 0x0a, 0x3c,
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0x03, 0x00, 0x00, 0x00, 0x3c, 0x00, 0x00, 0x00, 0x28, 0x00, 0x00, 0x00,
0x10, 0x00, 0x00, 0x00, 0x00, 0x00, 0x0a, 0x00, 0x0e, 0x00, 0x07, 0x00,
0x00, 0x00, 0x08, 0x00, 0x0a, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x06,
0x02, 0x00, 0x00, 0x00, 0x00, 0x00, 0x06, 0x00, 0x06, 0x00, 0x05, 0x00,
0x06, 0x00, 0x00, 0x00, 0x00, 0x72, 0x0a, 0x00, 0x0c, 0x00, 0x07, 0x00,
0x00, 0x00, 0x08, 0x00, 0x0a, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x09,
0x04, 0x00, 0x00, 0x00
};
const int g_model_len = 2512;

33
samples/modules/tensorflow/hello_world/src/model.h Normal file
View file

@ -0,0 +1,33 @@
/*
* Copyright 2020 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.
*/
/* Automatically created from a TensorFlow Lite flatbuffer using the command:
* xxd -i model.tflite > model.cc
*
* This is a standard TensorFlow Lite model file that has been converted into a
* C data array, so it can be easily compiled into a binary for devices that
* don't have a file system.
*
* See train/README.md for a full description of the creation process.
*/
#ifndef TENSORFLOW_LITE_MICRO_EXAMPLES_HELLO_WORLD_MODEL_H_
#define TENSORFLOW_LITE_MICRO_EXAMPLES_HELLO_WORLD_MODEL_H_
extern const unsigned char g_model[];
extern const int g_model_len;
#endif /* TENSORFLOW_LITE_MICRO_EXAMPLES_HELLO_WORLD_MODEL_H_ */

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/*
* Copyright 2020 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.
*/
#include "output_handler.h"
void HandleOutput(tflite::ErrorReporter *error_reporter, float x_value,
float y_value)
{
/* Log the current X and Y values */
TF_LITE_REPORT_ERROR(error_reporter, "x_value: %f, y_value: %f\n",
static_cast < double > (x_value),
static_cast < double > (y_value));
}

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/*
* Copyright 2020 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.
*/
#ifndef TENSORFLOW_LITE_MICRO_EXAMPLES_HELLO_WORLD_OUTPUT_HANDLER_H_
#define TENSORFLOW_LITE_MICRO_EXAMPLES_HELLO_WORLD_OUTPUT_HANDLER_H_
#include <tensorflow/lite/c/common.h>
#include <tensorflow/lite/micro/micro_error_reporter.h>
/* Called by the main loop to produce some output based on the x and y values */
void HandleOutput(tflite::ErrorReporter *error_reporter, float x_value,
float y_value);
#endif /* TENSORFLOW_LITE_MICRO_EXAMPLES_HELLO_WORLD_OUTPUT_HANDLER_H_ */

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.. _tensorflow-samples:
TensorFlow Samples
##################
.. toctree::
:maxdepth: 1
:glob:
**/*