From bca497ef47c8ba6cafe2ce38360c3fcdf2ff12a8 Mon Sep 17 00:00:00 2001
From: Pete Warden <petewarden@google.com>
Date: Fri, 8 May 2020 15:41:25 -0700
Subject: [PATCH] Convert speech training to produce an int8-quantized model
PiperOrigin-RevId: 310642639
Change-Id: I9178e0d17079dd4ef4727f018b1a32f6b06fc91c
---
.../train/train_micro_speech_model.ipynb | 2021 +----------------
1 file changed, 1 insertion(+), 2020 deletions(-)
diff --git a/tensorflow/lite/micro/examples/micro_speech/train/train_micro_speech_model.ipynb b/tensorflow/lite/micro/examples/micro_speech/train/train_micro_speech_model.ipynb
index 40f56f8012b..2a64ecd7078 100644
--- a/tensorflow/lite/micro/examples/micro_speech/train/train_micro_speech_model.ipynb
+++ b/tensorflow/lite/micro/examples/micro_speech/train/train_micro_speech_model.ipynb
@@ -1,2020 +1 @@
-{
- "nbformat": 4,
- "nbformat_minor": 0,
- "metadata": {
- "colab": {
- "name": "train_micro_speech_model.ipynb",
- "provenance": [],
- "collapsed_sections": []
- },
- "kernelspec": {
- "name": "python3",
- "display_name": "Python 3"
- },
- "accelerator": "GPU"
- },
- "cells": [
- {
- "cell_type": "markdown",
- "metadata": {
- "id": "pO4-CY_TCZZS",
- "colab_type": "text"
- },
- "source": [
- "# Train a Simple Audio Recognition Model"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "id": "BaFfr7DHRmGF",
- "colab_type": "text"
- },
- "source": [
- "This notebook demonstrates how to train a 20 kB [Simple Audio Recognition](https://www.tensorflow.org/tutorials/sequences/audio_recognition) model to recognize keywords in speech.\n",
- "\n",
- "The model created in this notebook is used in the [micro_speech](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/lite/micro/examples/micro_speech) example for [TensorFlow Lite for MicroControllers](https://www.tensorflow.org/lite/microcontrollers/overview).\n",
- "\n",
- "<table class=\"tfo-notebook-buttons\" align=\"left\">\n",
- " <td>\n",
- " <a target=\"_blank\" href=\"https://colab.research.google.com/github/tensorflow/tensorflow/blob/master/tensorflow/lite/micro/examples/micro_speech/train/train_micro_speech_model.ipynb\"><img src=\"https://www.tensorflow.org/images/colab_logo_32px.png\" />Run in Google Colab</a>\n",
- " </td>\n",
- " <td>\n",
- " <a target=\"_blank\" href=\"https://github.com/tensorflow/tensorflow/blob/master/tensorflow/lite/micro/examples/micro_speech/train/train_micro_speech_model.ipynb\"><img src=\"https://www.tensorflow.org/images/GitHub-Mark-32px.png\" />View source on GitHub</a>\n",
- " </td>\n",
- "</table>\n"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "id": "XaVtYN4nlCft",
- "colab_type": "text"
- },
- "source": [
- "**Training is much faster using GPU acceleration.** Before you proceed, ensure you are using a GPU runtime by going to **Runtime -> Change runtime type** and set **Hardware accelerator: GPU**. Training 15,000 iterations will take 1.5 - 2 hours on a GPU runtime.\n",
- "\n",
- "## Configure Defaults\n",
- "\n",
- "**MODIFY** the following constants for your specific use case."
- ]
- },
- {
- "cell_type": "code",
- "metadata": {
- "id": "ludfxbNIaegy",
- "colab_type": "code",
- "colab": {}
- },
- "source": [
- "# A comma-delimited list of the words you want to train for.\n",
- "# The options are: yes,no,up,down,left,right,on,off,stop,go\n",
- "# All the other words will be used to train an \"unknown\" label and silent\n",
- "# audio data with no spoken words will be used to train a \"silence\" label.\n",
- "WANTED_WORDS = \"yes,no\"\n",
- "\n",
- "# The number of steps and learning rates can be specified as comma-separated\n",
- "# lists to define the rate at each stage. For example,\n",
- "# TRAINING_STEPS=12000,3000 and LEARNING_RATE=0.001,0.0001\n",
- "# will run 12,000 training loops in total, with a rate of 0.001 for the first\n",
- "# 8,000, and 0.0001 for the final 3,000.\n",
- "TRAINING_STEPS = \"12000,3000\"\n",
- "LEARNING_RATE = \"0.001,0.0001\"\n",
- "\n",
- "# Calculate the total number of steps, which is used to identify the checkpoint\n",
- "# file name.\n",
- "TOTAL_STEPS = str(sum(map(lambda string: int(string), TRAINING_STEPS.split(\",\"))))\n",
- "\n",
- "# Print the configuration to confirm it\n",
- "!echo \"Training these words:\" $WANTED_WORDS\n",
- "!echo \"Training steps in each stage:\" $TRAINING_STEPS\n",
- "!echo \"Learning rate in each stage:\" $LEARNING_RATE\n",
- "!echo \"Total number of training steps:\" $TOTAL_STEPS"
- ],
- "execution_count": 1,
- "outputs": [
- {
- "output_type": "stream",
- "text": [
- "Training these words: yes,no\n",
- "Training steps in each stage: 12000,3000\n",
- "Learning rate in each stage: 0.001,0.0001\n",
- "Total number of training steps: 15000\n"
- ],
- "name": "stdout"
- }
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "id": "gCgeOpvY9pAi",
- "colab_type": "text"
- },
- "source": [
- "**DO NOT MODIFY** the following constants as they include filepaths used in this notebook and data that is shared during training and inference."
- ]
- },
- {
- "cell_type": "code",
- "metadata": {
- "id": "Nd1iM1o2ymvA",
- "colab_type": "code",
- "colab": {}
- },
- "source": [
- "# Calculate the percentage of 'silence' and 'unknown' training samples required\n",
- "# to ensure that we have equal number of samples for each label.\n",
- "number_of_labels = WANTED_WORDS.count(',') + 1\n",
- "number_of_total_labels = number_of_labels + 2 # for 'silence' and 'unknown' label\n",
- "equal_percentage_of_training_samples = int(100.0/(number_of_total_labels))\n",
- "SILENT_PERCENTAGE = equal_percentage_of_training_samples\n",
- "UNKNOWN_PERCENTAGE = equal_percentage_of_training_samples\n",
- "\n",
- "# Constants which are shared during training and inference\n",
- "PREPROCESS = 'micro'\n",
- "WINDOW_STRIDE ='20'\n",
- "MODEL_ARCHITECTURE = 'tiny_conv' # Other options include: single_fc, conv,\n",
- " # low_latency_conv, low_latency_svdf, tiny_embedding_conv\n",
- "QUANTIZE = '1' # For booleans, we provide 1 or 0 (instead of True or False)\n",
- "\n",
- "# Constants used during training only\n",
- "VERBOSITY = 'WARN'\n",
- "EVAL_STEP_INTERVAL = '1000'\n",
- "SAVE_STEP_INTERVAL = '5000'\n",
- "\n",
- "# Constants for training directories and filepaths\n",
- "DATASET_DIR = 'dataset/'\n",
- "LOGS_DIR = 'logs/'\n",
- "TRAIN_DIR = 'train/' # for training checkpoints and other files.\n",
- "\n",
- "# Constants for inference directories and filepaths\n",
- "import os\n",
- "MODELS_DIR = 'models/'\n",
- "os.mkdir(MODELS_DIR)\n",
- "MODEL_TF = MODELS_DIR + 'model.pb'\n",
- "MODEL_TFLITE = MODELS_DIR + 'model.tflite'\n",
- "MODEL_TFLITE_MICRO = MODELS_DIR + 'model.cc'"
- ],
- "execution_count": 2,
- "outputs": []
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "id": "6rLYpvtg9P4o",
- "colab_type": "text"
- },
- "source": [
- "## Setup Environment\n",
- "\n",
- "Install Dependencies"
- ]
- },
- {
- "cell_type": "code",
- "metadata": {
- "id": "ed_XpUrU5DvY",
- "colab_type": "code",
- "colab": {}
- },
- "source": [
- "%tensorflow_version 1.x\n",
- "import tensorflow as tf"
- ],
- "execution_count": 3,
- "outputs": [
- {
- "output_type": "stream",
- "text": [
- "TensorFlow 1.x selected.\n"
- ],
- "name": "stdout"
- }
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "id": "T9Ty5mR58E4i",
- "colab_type": "text"
- },
- "source": [
- "**DELETE** any old data from previous runs\n"
- ]
- },
- {
- "cell_type": "code",
- "metadata": {
- "id": "APGx0fEh7hFF",
- "colab_type": "code",
- "colab": {}
- },
- "source": [
- "!rm -rf {DATASET_DIR} {LOGS_DIR} {TRAIN_DIR} {MODELS_DIR}"
- ],
- "execution_count": 5,
- "outputs": []
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "id": "GfEUlfFBizio",
- "colab_type": "text"
- },
- "source": [
- "Clone the TensorFlow Github Repository, which contains the relevant code required to run this tutorial."
- ]
- },
- {
- "cell_type": "code",
- "metadata": {
- "id": "yZArmzT85SLq",
- "colab_type": "code",
- "colab": {}
- },
- "source": [
- "!git clone -q https://github.com/tensorflow/tensorflow"
- ],
- "execution_count": 6,
- "outputs": []
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "id": "nS9swHLSi7Bi",
- "colab_type": "text"
- },
- "source": [
- "Load TensorBoard to visualize the accuracy and loss as training proceeds.\n"
- ]
- },
- {
- "cell_type": "code",
- "metadata": {
- "id": "q4qF1VxP3UE4",
- "colab_type": "code",
- "colab": {}
- },
- "source": [
- "%load_ext tensorboard\n",
- "%tensorboard --logdir {LOGS_DIR}"
- ],
- "execution_count": 7,
- "outputs": []
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "id": "x1J96Ron-O4R",
- "colab_type": "text"
- },
- "source": [
- "## Training\n",
- "\n",
- "The following script downloads the dataset and begin training."
- ]
- },
- {
- "cell_type": "code",
- "metadata": {
- "id": "VJsEZx6lynbY",
- "colab_type": "code",
- "colab": {}
- },
- "source": [
- "!python tensorflow/tensorflow/examples/speech_commands/train.py \\\n",
- "--data_dir={DATASET_DIR} \\\n",
- "--wanted_words={WANTED_WORDS} \\\n",
- "--silence_percentage={SILENT_PERCENTAGE} \\\n",
- "--unknown_percentage={UNKNOWN_PERCENTAGE} \\\n",
- "--preprocess={PREPROCESS} \\\n",
- "--window_stride={WINDOW_STRIDE} \\\n",
- "--model_architecture={MODEL_ARCHITECTURE} \\\n",
- "--quantize={QUANTIZE} \\\n",
- "--how_many_training_steps={TRAINING_STEPS} \\\n",
- "--learning_rate={LEARNING_RATE} \\\n",
- "--train_dir={TRAIN_DIR} \\\n",
- "--summaries_dir={LOGS_DIR} \\\n",
- "--verbosity={VERBOSITY} \\\n",
- "--eval_step_interval={EVAL_STEP_INTERVAL} \\\n",
- "--save_step_interval={SAVE_STEP_INTERVAL} \\"
- ],
- "execution_count": 8,
- "outputs": [
- {
- "output_type": "stream",
- "text": [
- "..\n",
- "..\n",
- "..\n",
- "..\n",
- "WARNING:tensorflow:Confusion Matrix:\n",
- " [[205 0 0 1]\n",
- " [ 3 162 13 28]\n",
- " [ 3 9 401 6]\n",
- " [ 2 22 6 375]]\n",
- "W0402 00:25:28.115174 139938153863040 train.py:320] Confusion Matrix:\n",
- " [[205 0 0 1]\n",
- " [ 3 162 13 28]\n",
- " [ 3 9 401 6]\n",
- " [ 2 22 6 375]]\n",
- "WARNING:tensorflow:Final test accuracy = 92.5% (N=1236)\n",
- "W0402 00:25:28.115574 139938153863040 train.py:322] Final test accuracy = 92.5% (N=1236)\n"
- ],
- "name": "stdout"
- }
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "id": "XQUJLrdS-ftl",
- "colab_type": "text"
- },
- "source": [
- "## Generate a TensorFlow Model for Inference\n",
- "\n",
- "Combine relevant training results (graph, weights, etc) into a single file for inference. This process is known as freezing a model and the resulting model is known as a frozen model/graph, as it cannot be further re-trained after this process."
- ]
- },
- {
- "cell_type": "code",
- "metadata": {
- "id": "xyc3_eLh9sAg",
- "colab_type": "code",
- "colab": {}
- },
- "source": [
- "!python tensorflow/tensorflow/examples/speech_commands/freeze.py \\\n",
- "--wanted_words=$WANTED_WORDS \\\n",
- "--window_stride_ms=$WINDOW_STRIDE \\\n",
- "--preprocess=$PREPROCESS \\\n",
- "--model_architecture=$MODEL_ARCHITECTURE \\\n",
- "--quantize=$QUANTIZE \\\n",
- "--start_checkpoint=$TRAIN_DIR$MODEL_ARCHITECTURE'.ckpt-'$TOTAL_STEPS \\\n",
- "--output_file=$MODEL_TF \\"
- ],
- "execution_count": 9,
- "outputs": [
- {
- "output_type": "stream",
- "text": [
- "..\n",
- "..\n",
- "..\n",
- "..\n",
- "INFO:tensorflow:Restoring parameters from /content/train/tiny_conv.ckpt-15000\n",
- "I0402 00:25:47.086113 140352379615104 saver.py:1284] Restoring parameters from /content/train/tiny_conv.ckpt-15000\n",
- "INFO:tensorflow:Froze 12 variables.\n",
- "I0402 00:25:47.663757 140352379615104 graph_util_impl.py:334] Froze 12 variables.\n",
- "INFO:tensorflow:Converted 12 variables to const ops.\n",
- "I0402 00:25:47.665771 140352379615104 graph_util_impl.py:394] Converted 12 variables to const ops.\n",
- "INFO:tensorflow:Saved frozen graph to /content/models/model.pb\n",
- "I0402 00:25:47.667117 140352379615104 freeze.py:186] Saved frozen graph to /content/models/model.pb\n"
- ],
- "name": "stdout"
- }
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "id": "_DBGDxVI-nKG",
- "colab_type": "text"
- },
- "source": [
- "## Generate a TensorFlow Lite Model\n",
- "\n",
- "Convert the frozen graph into a TensorFlow Lite model, which is fully quantized for use with embedded devices.\n",
- "\n",
- "The following cell will also print the model size, which will be under 20 kilobytes."
- ]
- },
- {
- "cell_type": "code",
- "metadata": {
- "id": "lBj_AyCh1cC0",
- "colab_type": "code",
- "colab": {}
- },
- "source": [
- "input_tensor = 'Reshape_2'\n",
- "output_tensor = 'labels_softmax'\n",
- "\n",
- "converter = tf.lite.TFLiteConverter.from_frozen_graph(\n",
- " MODEL_TF, [input_tensor], [output_tensor])\n",
- "converter.inference_type = tf.uint8\n",
- "converter.quantized_input_stats = {input_tensor: (0.0, 9.8077)} # (mean, standard deviation)\n",
- "tflite_model = converter.convert()\n",
- "\n",
- "tflite_model_size = open(MODEL_TFLITE, \"wb\").write(tflite_model)\n",
- "print(\"Model is %d bytes\" % tflite_model_size)\n"
- ],
- "execution_count": 10,
- "outputs": [
- {
- "output_type": "stream",
- "text": [
- "Model is 18288 bytes\n"
- ],
- "name": "stdout"
- }
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "id": "dt6Zqbxu-wIi",
- "colab_type": "text"
- },
- "source": [
- "## Generate a TensorFlow Lite for MicroControllers Model\n",
- "Convert the TensorFlow Lite model into a C source file that can be loaded by TensorFlow Lite for Microcontrollers."
- ]
- },
- {
- "cell_type": "code",
- "metadata": {
- "id": "XohZOTjR8ZyE",
- "colab_type": "code",
- "colab": {}
- },
- "source": [
- "# Install xxd if it is not available\n",
- "!apt-get update && apt-get -qq install xxd\n",
- "# Convert to a C source file\n",
- "!xxd -i {MODEL_TFLITE} > {MODEL_TFLITE_MICRO}\n",
- "# Update variable names\n",
- "REPLACE_TEXT = MODEL_TFLITE.replace('/', '_').replace('.', '_')\n",
- "!sed -i 's/'{REPLACE_TEXT}'/g_model/g' {MODEL_TFLITE_MICRO}"
- ],
- "execution_count": 11,
- "outputs": []
- },
- {
- "cell_type": "markdown",
- "metadata": {
- "id": "2pQnN0i_-0L2",
- "colab_type": "text"
- },
- "source": [
- "## Deploy to a Microcontroller\n",
- "\n",
- "Follow the instructions in the [micro_speech](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/lite/micro/examples/micro_speech) README.md for [TensorFlow Lite for MicroControllers](https://www.tensorflow.org/lite/microcontrollers/overview) to deploy this model on a specific microcontroller.\n",
- "\n",
- "**Reference Model:** If you have not modified this notebook, you can follow the instructions as is, to deploy the model. Refer to the [`micro_speech/train/models`](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/lite/micro/examples/micro_speech/train/models) directory to access the models generated in this notebook. \n",
- "\n",
- "**New Model:** If you have generated a new model to identify different words: (i) Update `kCategoryCount` and `kCategoryLabels` in [`micro_speech/micro_features/micro_model_settings.h`](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/lite/micro/examples/micro_speech/micro_features/micro_model_settings.h) and (ii) Update the values assigned to the variables defined in [`micro_speech/micro_features/model.cc`](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/lite/micro/examples/micro_speech/micro_features/model.cc) with values displayed after running the following cell."
- ]
- },
- {
- "cell_type": "code",
- "metadata": {
- "id": "eoYyh0VU8pca",
- "colab_type": "code",
- "colab": {}
- },
- "source": [
- "# Print the C source file\n",
- "!cat {MODEL_TFLITE_MICRO}"
- ],
- "execution_count": 12,
- "outputs": [
- {
- "output_type": "stream",
- "text": [
- "unsigned char g_model[] = {\n",
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- "};\n",
- "unsigned int g_model_len = 18288;\n"
- ],
- "name": "stdout"
- }
- ]
- }
- ]
-}
\ No newline at end of file
+{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"name":"train_micro_speech_model.ipynb","provenance":[{"file_id":"https://github.com/tensorflow/tensorflow/blob/master/tensorflow/lite/micro/examples/micro_speech/train/train_micro_speech_model.ipynb","timestamp":1587690382292}],"collapsed_sections":[],"toc_visible":true},"kernelspec":{"name":"python3","display_name":"Python 3"},"accelerator":"GPU"},"cells":[{"cell_type":"markdown","metadata":{"id":"pO4-CY_TCZZS","colab_type":"text"},"source":["# Train a Simple Audio Recognition Model"]},{"cell_type":"markdown","metadata":{"id":"BaFfr7DHRmGF","colab_type":"text"},"source":["This notebook demonstrates how to train a 20 kB [Simple Audio Recognition](https://www.tensorflow.org/tutorials/sequences/audio_recognition) model to recognize keywords in speech.\n","\n","The model created in this notebook is used in the [micro_speech](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/lite/micro/examples/micro_speech) example for [TensorFlow Lite for MicroControllers](https://www.tensorflow.org/lite/microcontrollers/overview).\n","\n","<table class=\"tfo-notebook-buttons\" align=\"left\">\n"," <td>\n"," <a target=\"_blank\" href=\"https://colab.research.google.com/github/tensorflow/tensorflow/blob/master/tensorflow/lite/micro/examples/micro_speech/train/train_micro_speech_model.ipynb\"><img src=\"https://www.tensorflow.org/images/colab_logo_32px.png\" />Run in Google Colab</a>\n"," </td>\n"," <td>\n"," <a target=\"_blank\" href=\"https://github.com/tensorflow/tensorflow/blob/master/tensorflow/lite/micro/examples/micro_speech/train/train_micro_speech_model.ipynb\"><img src=\"https://www.tensorflow.org/images/GitHub-Mark-32px.png\" />View source on GitHub</a>\n"," </td>\n","</table>\n"]},{"cell_type":"markdown","metadata":{"id":"XaVtYN4nlCft","colab_type":"text"},"source":["**Training is much faster using GPU acceleration.** Before you proceed, ensure you are using a GPU runtime by going to **Runtime -> Change runtime type** and set **Hardware accelerator: GPU**. Training 15,000 iterations will take 1.5 - 2 hours on a GPU runtime.\n","\n","## Configure Defaults\n","\n","**MODIFY** the following constants for your specific use case."]},{"cell_type":"code","metadata":{"id":"ludfxbNIaegy","colab_type":"code","outputId":"1667d949-267c-4588-fe25-c0674d1dd074","executionInfo":{"status":"ok","timestamp":1588895159583,"user_tz":420,"elapsed":3711,"user":{"displayName":"Pete Warden","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gg9RGhKK9hlUJPY0U8OJIEUEeTc3V08ZIBIs175=s64","userId":"17073007660171926128"}},"colab":{"base_uri":"https://localhost:8080/","height":85}},"source":["# A comma-delimited list of the words you want to train for.\n","# The options are: yes,no,up,down,left,right,on,off,stop,go\n","# All the other words will be used to train an \"unknown\" label and silent\n","# audio data with no spoken words will be used to train a \"silence\" label.\n","WANTED_WORDS = \"yes,no\"\n","\n","# The number of steps and learning rates can be specified as comma-separated\n","# lists to define the rate at each stage. For example,\n","# TRAINING_STEPS=12000,3000 and LEARNING_RATE=0.001,0.0001\n","# will run 12,000 training loops in total, with a rate of 0.001 for the first\n","# 8,000, and 0.0001 for the final 3,000.\n","TRAINING_STEPS = \"12000,3000\"\n","LEARNING_RATE = \"0.001,0.0001\"\n","\n","# Calculate the total number of steps, which is used to identify the checkpoint\n","# file name.\n","TOTAL_STEPS = str(sum(map(lambda string: int(string), TRAINING_STEPS.split(\",\"))))\n","\n","# Print the configuration to confirm it\n","!echo \"Training these words:\" $WANTED_WORDS\n","!echo \"Training steps in each stage:\" $TRAINING_STEPS\n","!echo \"Learning rate in each stage:\" $LEARNING_RATE\n","!echo \"Total number of training steps:\" $TOTAL_STEPS"],"execution_count":1,"outputs":[{"output_type":"stream","text":["Training these words: yes,no\n","Training steps in each stage: 12000,3000\n","Learning rate in each stage: 0.001,0.0001\n","Total number of training steps: 15000\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"id":"gCgeOpvY9pAi","colab_type":"text"},"source":["**DO NOT MODIFY** the following constants as they include filepaths used in this notebook and data that is shared during training and inference."]},{"cell_type":"code","metadata":{"id":"Nd1iM1o2ymvA","colab_type":"code","colab":{}},"source":["# Calculate the percentage of 'silence' and 'unknown' training samples required\n","# to ensure that we have equal number of samples for each label.\n","number_of_labels = WANTED_WORDS.count(',') + 1\n","number_of_total_labels = number_of_labels + 2 # for 'silence' and 'unknown' label\n","equal_percentage_of_training_samples = int(100.0/(number_of_total_labels))\n","SILENT_PERCENTAGE = equal_percentage_of_training_samples\n","UNKNOWN_PERCENTAGE = equal_percentage_of_training_samples\n","\n","# Constants which are shared during training and inference\n","PREPROCESS = 'micro'\n","WINDOW_STRIDE =20\n","MODEL_ARCHITECTURE = 'tiny_conv' # Other options include: single_fc, conv,\n"," # low_latency_conv, low_latency_svdf, tiny_embedding_conv\n","\n","# Constants used during training only\n","VERBOSITY = 'WARN'\n","EVAL_STEP_INTERVAL = '1000'\n","SAVE_STEP_INTERVAL = '1000'\n","\n","# Constants for training directories and filepaths\n","DATASET_DIR = 'dataset/'\n","LOGS_DIR = 'logs/'\n","TRAIN_DIR = 'train/' # for training checkpoints and other files.\n","\n","# Constants for inference directories and filepaths\n","import os\n","MODELS_DIR = 'models'\n","if not os.path.exists(MODELS_DIR):\n"," os.mkdir(MODELS_DIR)\n","MODEL_TF = os.path.join(MODELS_DIR, 'model.pb')\n","MODEL_TFLITE = os.path.join(MODELS_DIR, 'model.tflite')\n","FLOAT_MODEL_TFLITE = os.path.join(MODELS_DIR, 'float_model.tflite')\n","MODEL_TFLITE_MICRO = os.path.join(MODELS_DIR, 'model.cc')\n","SAVED_MODEL = os.path.join(MODELS_DIR, 'saved_model')\n","\n","QUANT_INPUT_MIN = 0.0\n","QUANT_INPUT_MAX = 9.8077\n","QUANT_INPUT_RANGE = QUANT_INPUT_MAX - QUANT_INPUT_MIN"],"execution_count":0,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"6rLYpvtg9P4o","colab_type":"text"},"source":["## Setup Environment\n","\n","Install Dependencies"]},{"cell_type":"code","metadata":{"id":"ed_XpUrU5DvY","colab_type":"code","colab":{}},"source":["%tensorflow_version 1.x\n","import tensorflow as tf"],"execution_count":0,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"T9Ty5mR58E4i","colab_type":"text"},"source":["**DELETE** any old data from previous runs\n"]},{"cell_type":"code","metadata":{"id":"APGx0fEh7hFF","colab_type":"code","colab":{}},"source":["!rm -rf {DATASET_DIR} {LOGS_DIR} {TRAIN_DIR} {MODELS_DIR}"],"execution_count":0,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"GfEUlfFBizio","colab_type":"text"},"source":["Clone the TensorFlow Github Repository, which contains the relevant code required to run this tutorial."]},{"cell_type":"code","metadata":{"id":"yZArmzT85SLq","colab_type":"code","colab":{}},"source":["!git clone -q --depth 1 https://github.com/tensorflow/tensorflow"],"execution_count":0,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"nS9swHLSi7Bi","colab_type":"text"},"source":["Load TensorBoard to visualize the accuracy and loss as training proceeds.\n"]},{"cell_type":"code","metadata":{"id":"q4qF1VxP3UE4","colab_type":"code","colab":{}},"source":["%load_ext tensorboard\n","%tensorboard --logdir {LOGS_DIR}"],"execution_count":0,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"x1J96Ron-O4R","colab_type":"text"},"source":["## Training\n","\n","The following script downloads the dataset and begin training."]},{"cell_type":"code","metadata":{"id":"VJsEZx6lynbY","colab_type":"code","colab":{}},"source":["!python tensorflow/tensorflow/examples/speech_commands/train.py \\\n","--data_dir={DATASET_DIR} \\\n","--wanted_words={WANTED_WORDS} \\\n","--silence_percentage={SILENT_PERCENTAGE} \\\n","--unknown_percentage={UNKNOWN_PERCENTAGE} \\\n","--preprocess={PREPROCESS} \\\n","--window_stride={WINDOW_STRIDE} \\\n","--model_architecture={MODEL_ARCHITECTURE} \\\n","--how_many_training_steps={TRAINING_STEPS} \\\n","--learning_rate={LEARNING_RATE} \\\n","--train_dir={TRAIN_DIR} \\\n","--summaries_dir={LOGS_DIR} \\\n","--verbosity={VERBOSITY} \\\n","--eval_step_interval={EVAL_STEP_INTERVAL} \\\n","--save_step_interval={SAVE_STEP_INTERVAL}"],"execution_count":0,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"XQUJLrdS-ftl","colab_type":"text"},"source":["## Generate a TensorFlow Model for Inference\n","\n","Combine relevant training results (graph, weights, etc) into a single file for inference. This process is known as freezing a model and the resulting model is known as a frozen model/graph, as it cannot be further re-trained after this process."]},{"cell_type":"code","metadata":{"id":"xyc3_eLh9sAg","colab_type":"code","colab":{}},"source":["!rm -rf {SAVED_MODEL}\n","!python tensorflow/tensorflow/examples/speech_commands/freeze.py \\\n","--wanted_words=$WANTED_WORDS \\\n","--window_stride_ms=$WINDOW_STRIDE \\\n","--preprocess=$PREPROCESS \\\n","--model_architecture=$MODEL_ARCHITECTURE \\\n","--start_checkpoint=$TRAIN_DIR$MODEL_ARCHITECTURE'.ckpt-'$TOTAL_STEPS \\\n","--save_format=saved_model \\\n","--output_file={SAVED_MODEL}"],"execution_count":0,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"_DBGDxVI-nKG","colab_type":"text"},"source":["## Generate a TensorFlow Lite Model\n","\n","Convert the frozen graph into a TensorFlow Lite model, which is fully quantized for use with embedded devices.\n","\n","The following cell will also print the model size, which will be under 20 kilobytes."]},{"cell_type":"code","metadata":{"id":"RIitkqvGWmre","colab_type":"code","colab":{}},"source":["import sys\n","# We add this path so we can import the speech processing modules.\n","sys.path.append(\"/content/tensorflow/tensorflow/examples/speech_commands/\")\n","import input_data\n","import models\n","import numpy as np"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"kzqECqMxgBh4","colab_type":"code","colab":{}},"source":["SAMPLE_RATE = 16000\n","CLIP_DURATION_MS = 1000\n","WINDOW_SIZE_MS = 30.0\n","FEATURE_BIN_COUNT = 40\n","BACKGROUND_FREQUENCY = 0.8\n","BACKGROUND_VOLUME_RANGE = 0.1\n","TIME_SHIFT_MS = 100.0\n","\n","DATA_URL = 'https://storage.googleapis.com/download.tensorflow.org/data/speech_commands_v0.02.tar.gz'\n","VALIDATION_PERCENTAGE = 10\n","TESTING_PERCENTAGE = 10"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"rNQdAplJV1fz","colab_type":"code","colab":{}},"source":["model_settings = models.prepare_model_settings(\n"," len(input_data.prepare_words_list(WANTED_WORDS.split(','))),\n"," SAMPLE_RATE, CLIP_DURATION_MS, WINDOW_SIZE_MS,\n"," WINDOW_STRIDE, FEATURE_BIN_COUNT, PREPROCESS)\n","audio_processor = input_data.AudioProcessor(\n"," DATA_URL, DATASET_DIR,\n"," SILENT_PERCENTAGE, UNKNOWN_PERCENTAGE,\n"," WANTED_WORDS.split(','), VALIDATION_PERCENTAGE,\n"," TESTING_PERCENTAGE, model_settings, LOGS_DIR)"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"lBj_AyCh1cC0","colab_type":"code","colab":{}},"source":["with tf.Session() as sess:\n"," float_converter = tf.lite.TFLiteConverter.from_saved_model(SAVED_MODEL)\n"," float_tflite_model = float_converter.convert()\n"," float_tflite_model_size = open(FLOAT_MODEL_TFLITE, \"wb\").write(float_tflite_model)\n"," print(\"Float model is %d bytes\" % float_tflite_model_size)\n","\n"," converter = tf.lite.TFLiteConverter.from_saved_model(SAVED_MODEL)\n"," converter.optimizations = [tf.lite.Optimize.DEFAULT]\n"," converter.quantized_input_stats = {\"Reshape_1\": (QUANT_INPUT_MIN, QUANT_INPUT_MAX)}\n"," def representative_dataset_gen():\n"," for i in range(100):\n"," data, _ = audio_processor.get_data(1, i*1, model_settings,\n"," BACKGROUND_FREQUENCY, \n"," BACKGROUND_VOLUME_RANGE,\n"," TIME_SHIFT_MS,\n"," 'testing',\n"," sess)\n"," flattened_data = np.array(data.flatten(), dtype=np.float32).reshape(1, 1960)\n"," yield [flattened_data]\n"," converter.representative_dataset = representative_dataset_gen\n"," tflite_model = converter.convert()\n"," tflite_model_size = open(MODEL_TFLITE, \"wb\").write(tflite_model)\n"," print(\"Quantized model is %d bytes\" % tflite_model_size)\n"],"execution_count":0,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"EeLiDZTbLkzv","colab_type":"text"},"source":["# Testing the TensorFlow Lite model's accuracy\n","\n","Verify that the model we've exported is still accurate, using the TF Lite Python API and our test set."]},{"cell_type":"code","metadata":{"id":"wQsEteKRLryJ","colab_type":"code","outputId":"d4a7c3eb-3d74-40e6-9eb5-7d2ffc5e3b6d","executionInfo":{"status":"ok","timestamp":1588901109389,"user_tz":420,"elapsed":9673,"user":{"displayName":"Pete Warden","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gg9RGhKK9hlUJPY0U8OJIEUEeTc3V08ZIBIs175=s64","userId":"17073007660171926128"}},"colab":{"base_uri":"https://localhost:8080/","height":51}},"source":["with tf.Session() as sess:\n"," test_data, test_labels = audio_processor.get_data(\n"," -1, 0, model_settings, BACKGROUND_FREQUENCY, BACKGROUND_VOLUME_RANGE,\n"," TIME_SHIFT_MS, 'testing', sess)\n","\n","float_interpreter = tf.lite.Interpreter(FLOAT_MODEL_TFLITE)\n","float_interpreter.allocate_tensors()\n","\n","float_input_index = float_interpreter.get_input_details()[0][\"index\"]\n","\n","float_output_index = float_interpreter.get_output_details()[0][\"index\"]\n","float_model_output = float_interpreter.tensor(float_output_index)\n","\n","float_correct_predictions = 0\n","for i in range(len(test_data)):\n"," current_input = test_data[i]\n"," current_label = test_labels[i]\n"," flattened_input = np.array(current_input.flatten(), dtype=np.float32).reshape(1, 1960)\n"," float_interpreter.set_tensor(float_input_index, flattened_input)\n"," float_interpreter.invoke()\n"," top_prediction = float_model_output()[0].argmax()\n"," if top_prediction == current_label:\n"," float_correct_predictions += 1\n","\n","print('Float accuracy is %f%% (N=%d)' % ((float_correct_predictions * 100) / len(test_data), len(test_data)))\n","\n","interpreter = tf.lite.Interpreter(MODEL_TFLITE)\n","interpreter.allocate_tensors()\n","\n","input_index = interpreter.get_input_details()[0][\"index\"]\n","\n","output_index = interpreter.get_output_details()[0][\"index\"]\n","model_output = interpreter.tensor(output_index)\n","\n","with tf.Session() as sess:\n"," test_data, test_labels = audio_processor.get_data(\n"," -1, 0, model_settings, BACKGROUND_FREQUENCY, BACKGROUND_VOLUME_RANGE,\n"," TIME_SHIFT_MS, 'testing', sess)\n","\n","correct_predictions = 0\n","for i in range(len(test_data)):\n"," current_input = test_data[i]\n"," current_label = test_labels[i]\n"," flattened_input = np.array(current_input.flatten(), dtype=np.float32).reshape(1, 1960)\n"," interpreter.set_tensor(input_index, flattened_input)\n"," interpreter.invoke()\n"," top_prediction = model_output()[0].argmax()\n"," if top_prediction == current_label:\n"," correct_predictions += 1\n","\n","print('Quantized accuracy is %f%% (N=%d)' % ((correct_predictions * 100) / len(test_data), len(test_data)))\n"],"execution_count":15,"outputs":[{"output_type":"stream","text":["Float accuracy is 91.343042% (N=1236)\n","Quantized accuracy is 90.857605% (N=1236)\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"id":"dt6Zqbxu-wIi","colab_type":"text"},"source":["## Generate a TensorFlow Lite for MicroControllers Model\n","Convert the TensorFlow Lite model into a C source file that can be loaded by TensorFlow Lite for Microcontrollers."]},{"cell_type":"code","metadata":{"id":"XohZOTjR8ZyE","colab_type":"code","colab":{"base_uri":"https://localhost:8080/","height":442},"outputId":"415d733c-86c4-4f19-9aa0-edc4112e6efb","executionInfo":{"status":"ok","timestamp":1588901187730,"user_tz":420,"elapsed":11964,"user":{"displayName":"Pete Warden","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gg9RGhKK9hlUJPY0U8OJIEUEeTc3V08ZIBIs175=s64","userId":"17073007660171926128"}}},"source":["# Install xxd if it is not available\n","!apt-get update && apt-get -qq install xxd\n","# Convert to a C source file\n","!xxd -i {MODEL_TFLITE} > {MODEL_TFLITE_MICRO}\n","# Update variable names\n","REPLACE_TEXT = MODEL_TFLITE.replace('/', '_').replace('.', '_')\n","!sed -i 's/'{REPLACE_TEXT}'/g_model/g' {MODEL_TFLITE_MICRO}"],"execution_count":16,"outputs":[{"output_type":"stream","text":["Get:1 http://security.ubuntu.com/ubuntu bionic-security InRelease [88.7 kB]\n","Ign:2 https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64 InRelease\n","Get:3 https://cloud.r-project.org/bin/linux/ubuntu bionic-cran35/ InRelease [3,626 B]\n","Hit:4 http://archive.ubuntu.com/ubuntu bionic InRelease\n","Hit:5 http://ppa.launchpad.net/graphics-drivers/ppa/ubuntu bionic InRelease\n","Ign:6 https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64 InRelease\n","Hit:7 https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64 Release\n","Hit:8 https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64 Release\n","Get:9 http://archive.ubuntu.com/ubuntu bionic-updates InRelease [88.7 kB]\n","Get:10 http://ppa.launchpad.net/marutter/c2d4u3.5/ubuntu bionic InRelease [15.4 kB]\n","Get:11 http://security.ubuntu.com/ubuntu bionic-security/main amd64 Packages [908 kB]\n","Get:12 http://security.ubuntu.com/ubuntu bionic-security/universe amd64 Packages [844 kB]\n","Get:13 http://archive.ubuntu.com/ubuntu bionic-backports InRelease [74.6 kB]\n","Get:16 http://ppa.launchpad.net/marutter/c2d4u3.5/ubuntu bionic/main Sources [1,814 kB]\n","Get:17 http://archive.ubuntu.com/ubuntu bionic-updates/universe amd64 Packages [1,376 kB]\n","Get:18 http://archive.ubuntu.com/ubuntu bionic-updates/main amd64 Packages [1,205 kB]\n","Get:19 http://ppa.launchpad.net/marutter/c2d4u3.5/ubuntu bionic/main amd64 Packages [875 kB]\n","Fetched 7,294 kB in 3s (2,429 kB/s)\n","Reading package lists... Done\n","Selecting previously unselected package xxd.\n","(Reading database ... 144429 files and directories currently installed.)\n","Preparing to unpack .../xxd_2%3a8.0.1453-1ubuntu1.3_amd64.deb ...\n","Unpacking xxd (2:8.0.1453-1ubuntu1.3) ...\n","Setting up xxd (2:8.0.1453-1ubuntu1.3) ...\n","Processing triggers for man-db (2.8.3-2ubuntu0.1) ...\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"id":"2pQnN0i_-0L2","colab_type":"text"},"source":["## Deploy to a Microcontroller\n","\n","Follow the instructions in the [micro_speech](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/lite/micro/examples/micro_speech) README.md for [TensorFlow Lite for MicroControllers](https://www.tensorflow.org/lite/microcontrollers/overview) to deploy this model on a specific microcontroller.\n","\n","**Reference Model:** If you have not modified this notebook, you can follow the instructions as is, to deploy the model. Refer to the [`micro_speech/train/models`](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/lite/micro/examples/micro_speech/train/models) directory to access the models generated in this notebook. \n","\n","**New Model:** If you have generated a new model to identify different words: (i) Update `kCategoryCount` and `kCategoryLabels` in [`micro_speech/micro_features/micro_model_settings.h`](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/lite/micro/examples/micro_speech/micro_features/micro_model_settings.h) and (ii) Update the values assigned to the variables defined in [`micro_speech/micro_features/model.cc`](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/lite/micro/examples/micro_speech/micro_features/model.cc) with values displayed after running the following cell."]},{"cell_type":"code","metadata":{"id":"eoYyh0VU8pca","colab_type":"code","outputId":"dbaba37d-8a8d-4e11-d780-478971d9ee95","colab":{"base_uri":"https://localhost:8080/","height":1000},"executionInfo":{"status":"ok","timestamp":1588901241295,"user_tz":420,"elapsed":1288,"user":{"displayName":"Pete Warden","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gg9RGhKK9hlUJPY0U8OJIEUEeTc3V08ZIBIs175=s64","userId":"17073007660171926128"}}},"source":["# Print the C source file\n","!cat {MODEL_TFLITE_MICRO}"],"execution_count":17,"outputs":[{"output_type":"stream","text":["unsigned char g_model[] = {\n"," 0x1c, 0x00, 0x00, 0x00, 0x54, 0x46, 0x4c, 0x33, 0x00, 0x00, 0x12, 0x00,\n"," 0x1c, 0x00, 0x04, 0x00, 0x08, 0x00, 0x0c, 0x00, 0x10, 0x00, 0x14, 0x00,\n"," 0x00, 0x00, 0x18, 0x00, 0x12, 0x00, 0x00, 0x00, 0x03, 0x00, 0x00, 0x00,\n"," 0x64, 0x49, 0x00, 0x00, 0x34, 0x42, 0x00, 0x00, 0x1c, 0x42, 0x00, 0x00,\n"," 0x3c, 0x00, 0x00, 0x00, 0x04, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00,\n"," 0x0c, 0x00, 0x00, 0x00, 0x08, 0x00, 0x0c, 0x00, 0x04, 0x00, 0x08, 0x00,\n"," 0x08, 0x00, 0x00, 0x00, 0x08, 0x00, 0x00, 0x00, 0x0b, 0x00, 0x00, 0x00,\n"," 0x13, 0x00, 0x00, 0x00, 0x6d, 0x69, 0x6e, 0x5f, 0x72, 0x75, 0x6e, 0x74,\n"," 0x69, 0x6d, 0x65, 0x5f, 0x76, 0x65, 0x72, 0x73, 0x69, 0x6f, 0x6e, 0x00,\n"," 0x0c, 0x00, 0x00, 0x00, 0xd4, 0x41, 0x00, 0x00, 0xb4, 0x41, 0x00, 0x00,\n"," 0x24, 0x03, 0x00, 0x00, 0xf4, 0x02, 0x00, 0x00, 0xec, 0x02, 0x00, 0x00,\n"," 0xe4, 0x02, 0x00, 0x00, 0xc4, 0x02, 0x00, 0x00, 0xbc, 0x02, 0x00, 0x00,\n"," 0x2c, 0x00, 0x00, 0x00, 0x24, 0x00, 0x00, 0x00, 0x1c, 0x00, 0x00, 0x00,\n"," 0x04, 0x00, 0x00, 0x00, 0xee, 0xbc, 0xff, 0xff, 0x04, 0x00, 0x00, 0x00,\n"," 0x05, 0x00, 0x00, 0x00, 0x31, 0x2e, 0x35, 0x2e, 0x30, 0x00, 0x00, 0x00,\n"," 0xd0, 0xb9, 0xff, 0xff, 0xd4, 0xb9, 0xff, 0xff, 0x0a, 0xbd, 0xff, 0xff,\n"," 0x04, 0x00, 0x00, 0x00, 0x80, 0x02, 0x00, 0x00, 0xd4, 0x3e, 0x2e, 0xa6,\n"," 0xd9, 0x4c, 0x23, 0x25, 0xd3, 0x2f, 0x09, 0xcb, 0xf6, 0x04, 0xc4, 0x1d,\n"," 0xe5, 0x46, 0xf2, 0xcf, 0xd5, 0x53, 0x0c, 0x2b, 0x28, 0x06, 0xf8, 0xe9,\n"," 0xe1, 0xdb, 0xdd, 0xf0, 0xbe, 0x0c, 0xfc, 0xa5, 0xb9, 0x1b, 0xca, 0x13,\n"," 0x0d, 0xed, 0x0b, 0xd3, 0xff, 0xc8, 0x0d, 0xee, 0x04, 0xfe, 0xe1, 0x08,\n"," 0xd9, 0xec, 0x26, 0x06, 0x0c, 0xcb, 0x1b, 0xc3, 0xf8, 0x81, 0xd5, 0xbc,\n"," 0xc8, 0x48, 0xe6, 0x46, 0x0e, 0x34, 0x09, 0x0c, 0xea, 0x23, 0xe0, 0x14,\n"," 0x17, 0xf5, 0xe0, 0x07, 0xe2, 0x3a, 0xaa, 0xea, 0x05, 0x5f, 0x26, 0x31,\n"," 0x4e, 0xf6, 0xce, 0xe6, 0x0b, 0xed, 0xa7, 0xea, 0xbe, 0x08, 0xa4, 0x1b,\n"," 0xd0, 0x50, 0x11, 0x2a, 0x16, 0xd3, 0xca, 0x11, 0xeb, 0xd8, 0xcb, 0xeb,\n"," 0xfc, 0xee, 0xa5, 0x12, 0xda, 0x19, 0xfd, 0x1e, 0x1e, 0xc1, 0xc8, 0xe7,\n"," 0xfc, 0x99, 0xae, 0xca, 0xe9, 0x57, 0x19, 0xe8, 0x1e, 0xff, 0xc4, 0xef,\n"," 0xdc, 0x0d, 0x25, 0xef, 0x1c, 0xef, 0x2e, 0xed, 0xf3, 0x39, 0xd6, 0x76,\n"," 0xe5, 0x4b, 0xb2, 0x2d, 0x4a, 0xf0, 0xf5, 0xcb, 0xc7, 0xf4, 0xbe, 0xea,\n"," 0xcb, 0xed, 0xce, 0x0a, 0xa4, 0x69, 0x1a, 0x34, 0x0a, 0xdc, 0xca, 0x37,\n"," 0xd4, 0xdf, 0x34, 0xe6, 0xf1, 0xd2, 0xb9, 0x1d, 0xb1, 0x42, 0xa3, 0x3a,\n"," 0x0f, 0xc0, 0xc3, 0x0a, 0xcf, 0xc4, 0xe7, 0xd2, 0xfa, 0x62, 0x14, 0x18,\n"," 0x49, 0xe1, 0x07, 0xe2, 0xec, 0x29, 0x4c, 0xd0, 0x53, 0xda, 0xdb, 0xe8,\n"," 0xf9, 0x2f, 0x0e, 0xf6, 0x17, 0x2a, 0x23, 0x29, 0x7d, 0xec, 0x04, 0x2b,\n"," 0x27, 0xf8, 0xb2, 0xdc, 0xbf, 0xec, 0xec, 0xb0, 0xe4, 0x62, 0x01, 0x42,\n"," 0x28, 0xe2, 0x13, 0xe7, 0x13, 0xf3, 0xd3, 0xe1, 0xf7, 0xc3, 0xee, 0xf9,\n"," 0xc4, 0x62, 0xfc, 0x58, 0x12, 0xc5, 0x02, 0x19, 0xe3, 0xe1, 0xf0, 0xe8,\n"," 0xc4, 0x5e, 0xf9, 0xf3, 0x31, 0xce, 0xf0, 0xc0, 0xf8, 0x2e, 0x34, 0x37,\n"," 0x7f, 0xc7, 0xa1, 0xdf, 0xf3, 0x31, 0xf8, 0xed, 0x27, 0x11, 0xc9, 0x19,\n"," 0x72, 0xf3, 0x18, 0x1b, 0x2b, 0xe6, 0xef, 0xd8, 0xd1, 0xd4, 0x14, 0xf8,\n"," 0xd5, 0x51, 0x40, 0x42, 0x2d, 0xe5, 0x0b, 0x94, 0x03, 0xf4, 0xde, 0xdf,\n"," 0xf1, 0xc0, 0x08, 0xf9, 0xc4, 0x71, 0xf5, 0x75, 0x20, 0xc8, 0xf9, 0xcb,\n"," 0xe0, 0x0c, 0x81, 0xf5, 0xc2, 0x6f, 0x25, 0xe3, 0x15, 0xca, 0x40, 0xac,\n"," 0xe6, 0x37, 0x60, 0xb4, 0x30, 0xb8, 0x19, 0xdb, 0xf1, 0x22, 0x56, 0xfe,\n"," 0x02, 0xf7, 0xfb, 0x0e, 0x68, 0xe6, 0x5e, 0x81, 0x15, 0xe4, 0xc5, 0xd9,\n"," 0xc3, 0xbd, 0x42, 0xe5, 0xbe, 0x2f, 0xde, 0x3d, 0x04, 0xe3, 0x4a, 0x97,\n"," 0xdb, 0xf6, 0xb1, 0xdf, 0xe5, 0xb2, 0x4b, 0xf2, 0xbc, 0x5e, 0x22, 0x7f,\n"," 0xfd, 0xd7, 0x37, 0xda, 0xd2, 0x1a, 0x22, 0xf8, 0xbf, 0x69, 0x1b, 0x22,\n"," 0x07, 0xcc, 0x11, 0xa3, 0xf8, 0x2c, 0x35, 0xdf, 0x60, 0xc8, 0xc9, 0xd9,\n"," 0xeb, 0x0c, 0x4e, 0x2e, 0x28, 0xe4, 0x44, 0x02, 0x7f, 0xda, 0x62, 0x25,\n"," 0x14, 0xe6, 0xbd, 0xe1, 0xcf, 0x9c, 0x50, 0x17, 0xff, 0x1e, 0xc3, 0x3c,\n"," 0x25, 0xde, 0x4c, 0x14, 0xf7, 0xfc, 0x02, 0xe1, 0xdd, 0xd3, 0x3d, 0xf8,\n"," 0xef, 0x49, 0x0c, 0x7b, 0x0a, 0xff, 0x24, 0x34, 0xfe, 0x2b, 0x14, 0x0b,\n"," 0xb6, 0x4f, 0xc5, 0x23, 0xe6, 0xe2, 0x12, 0x9f, 0xeb, 0x21, 0xc9, 0x45,\n"," 0x35, 0xcc, 0xbf, 0xea, 0x01, 0xf4, 0xe0, 0x15, 0x0e, 0xe8, 0x9d, 0xff,\n"," 0x54, 0xc7, 0xec, 0x27, 0x32, 0xed, 0xe3, 0xef, 0xd6, 0xa7, 0xf5, 0xea,\n"," 0xfa, 0x09, 0xc3, 0x32, 0x1d, 0xfd, 0x05, 0x19, 0x03, 0xf6, 0x05, 0xe9,\n"," 0xed, 0xe6, 0x05, 0x64, 0xf0, 0x35, 0xdc, 0x61, 0x12, 0x1d, 0x20, 0x3c,\n"," 0x0f, 0x33, 0xf8, 0x12, 0xa1, 0x1c, 0x81, 0x1d, 0xdc, 0xe1, 0x0a, 0x99,\n"," 0xd1, 0xf7, 0x9f, 0xc9, 0x1b, 0xd8, 0x32, 0xf2, 0xee, 0xb3, 0xaf, 0x0f,\n"," 0x01, 0xdd, 0x49, 0xf8, 0x7c, 0xa6, 0xbd, 0xac, 0x36, 0xeb, 0x0f, 0x01,\n"," 0xdb, 0xca, 0xb8, 0xb8, 0xf8, 0xf6, 0xf9, 0x27, 0x32, 0xf8, 0xde, 0xef,\n"," 0x19, 0xff, 0xf9, 0xf7, 0xf3, 0xde, 0xc7, 0x93, 0xfb, 0x1e, 0x1d, 0x50,\n"," 0xf3, 0x31, 0xc5, 0x00, 0x18, 0x27, 0xb8, 0x1a, 0x9e, 0xdf, 0xd0, 0x2c,\n"," 0xce, 0xe0, 0xa3, 0xa9, 0x9d, 0xb8, 0xaf, 0x67, 0x13, 0xd3, 0x19, 0xf7,\n"," 0xed, 0x81, 0xb1, 0x3d, 0xe9, 0xd5, 0x00, 0xf4, 0x45, 0x93, 0xcd, 0x62,\n"," 0x1e, 0xd6, 0x3a, 0x08, 0xd9, 0xb9, 0xd2, 0x1e, 0xeb, 0xe9, 0xbb, 0x1e,\n"," 0x1f, 0xf9, 0xe0, 0x20, 0xf6, 0xf2, 0x30, 0xf9, 0xfe, 0xfb, 0xe9, 0x66,\n"," 0xeb, 0xf5, 0x13, 0x40, 0xcf, 0x2d, 0xce, 0x0f, 0xe9, 0x06, 0x9a, 0x0c,\n"," 0x64, 0xbc, 0xff, 0xff, 0x9a, 0xbf, 0xff, 0xff, 0x04, 0x00, 0x00, 0x00,\n"," 0x10, 0x00, 0x00, 0x00, 0xff, 0xff, 0xff, 0xff, 0x31, 0x00, 0x00, 0x00,\n"," 0x28, 0x00, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x84, 0xbc, 0xff, 0xff,\n"," 0x88, 0xbc, 0xff, 0xff, 0xbe, 0xbf, 0xff, 0xff, 0x04, 0x00, 0x00, 0x00,\n"," 0x20, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xe1, 0xfe, 0xff, 0xff,\n"," 0x78, 0x00, 0x00, 0x00, 0xb1, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00,\n"," 0x43, 0xfd, 0xff, 0xff, 0xa9, 0xff, 0xff, 0xff, 0x97, 0xfc, 0xff, 0xff,\n"," 0xea, 0xbf, 0xff, 0xff, 0x04, 0x00, 0x00, 0x00, 0x80, 0x3e, 0x00, 0x00,\n"," 0xf5, 0xf9, 0xff, 0x08, 0xea, 0x05, 0x0f, 0x0c, 0xf3, 0x0e, 0xf6, 0x0f,\n"," 0xfa, 0x01, 0x11, 0xf1, 0xf6, 0xea, 0xfc, 0x0f, 0xfc, 0xf1, 0xdd, 0x0e,\n"," 0x1c, 0xef, 0xe6, 0xff, 0x05, 0xe8, 0x03, 0x11, 0xf6, 0xf1, 0x11, 0x0c,\n"," 0xd7, 0x08, 0xf5, 0x30, 0xd9, 0x10, 0x14, 0x11, 0x10, 0x17, 0xee, 0x23,\n"," 0x0c, 0xeb, 0x00, 0x06, 0xf6, 0xf7, 0x18, 0x0e, 0x18, 0x13, 0xfe, 0xfa,\n"," 0xf3, 0xdd, 0xfa, 0xfb, 0x01, 0xfd, 0xe5, 0xe4, 0x00, 0x0d, 0xfe, 0x09,\n"," 0xe9, 0x0a, 0x10, 0x1d, 0xf8, 0xf4, 0x0a, 0x1a, 0x10, 0x12, 0x18, 0xf1,\n"," 0xfc, 0x1d, 0x00, 0x25, 0xd8, 0x08, 0xf8, 0xff, 0x06, 0x19, 0xf5, 0x0f,\n"," 0x1c, 0x17, 0x0c, 0x16, 0xf3, 0x29, 0x20, 0x32, 0xfe, 0x19, 0xfb, 0x02,\n"," 0x04, 0x15, 0xf3, 0x2b, 0x06, 0x14, 0x0e, 0xde, 0x04, 0x0e, 0xfc, 0x2d,\n"," 0x1b, 0xdb, 0xec, 0xee, 0x00, 0xf6, 0x01, 0x33, 0x02, 0xe7, 0x06, 0xdd,\n"," 0xf9, 0x03, 0x13, 0x03, 0xf8, 0xec, 0x14, 0xe4, 0x0f, 0xfa, 0xd4, 0x22,\n"," 0x00, 0x11, 0x09, 0x02, 0x0e, 0xf4, 0x05, 0xfb, 0x04, 0x15, 0x04, 0x03,\n"," 0xff, 0x0f, 0x09, 0xf2, 0xeb, 0xfc, 0x06, 0x00, 0xe5, 0x0a, 0xf2, 0xfc,\n"," 0xfd, 0x12, 0xee, 0xe9, 0xf2, 0xfd, 0xf9, 0xf3, 0xce, 0x0f, 0xe9, 0xee,\n"," 0xff, 0x14, 0x15, 0x0b, 0xcb, 0x03, 0xf2, 0x1b, 0xdb, 0x09, 0x1d, 0x07,\n"," 0xd8, 0xde, 0xe6, 0x13, 0xd8, 0xf0, 0xe6, 0x00, 0xe7, 0xec, 0xd3, 0x00,\n"," 0xc5, 0x25, 0xdb, 0x0a, 0xde, 0x1f, 0xd9, 0x11, 0xc1, 0x06, 0x01, 0x2e,\n"," 0x09, 0x19, 0x09, 0x0f, 0xbe, 0x00, 0xf7, 0x08, 0x10, 0x12, 0xff, 0x10,\n"," 0xf4, 0x05, 0xdf, 0x16, 0xe7, 0xe6, 0xef, 0xf4, 0xdd, 0x18, 0x18, 0x16,\n"," 0xeb, 0x1a, 0xd7, 0xdb, 0xee, 0x15, 0xf1, 0x1e, 0xfc, 0x02, 0xfe, 0x0a,\n"," 0xed, 0x17, 0x1c, 0x39, 0x01, 0xde, 0x06, 0xf3, 0xdb, 0x27, 0xfc, 0x1e,\n"," 0xe4, 0x01, 0x03, 0x1d, 0xc5, 0x0d, 0xea, 0x0b, 0xfe, 0x05, 0xfc, 0x10,\n"," 0xc2, 0x06, 0x0a, 0x51, 0xf4, 0xd8, 0xe8, 0x03, 0xcd, 0x1a, 0xe7, 0x13,\n"," 0xfb, 0xfd, 0xe2, 0x2a, 0xf7, 0x0d, 0xea, 0x29, 0xfc, 0xea, 0x1c, 0x08,\n"," 0x0a, 0x13, 0xfc, 0xf8, 0x15, 0xf3, 0x06, 0xe9, 0x1d, 0x0c, 0x1c, 0x14,\n"," 0xdc, 0x17, 0x16, 0xff, 0x00, 0x06, 0x0c, 0xfe, 0x0c, 0x0a, 0xe6, 0x18,\n"," 0xef, 0xd6, 0x1d, 0xee, 0xd2, 0x1c, 0xfe, 0x0d, 0xec, 0xfc, 0xe8, 0x02,\n"," 0xf8, 0x13, 0xf9, 0x17, 0x08, 0xf8, 0xf9, 0x06, 0x04, 0x07, 0xcf, 0x07,\n"," 0xfb, 0xde, 0xf2, 0x0c, 0xe4, 0xf2, 0x1d, 0xdd, 0xd7, 0xfd, 0xec, 0xfd,\n"," 0xd8, 0xd9, 0x0a, 0xf5, 0xf4, 0x02, 0x1f, 0x0e, 0xf8, 0x1a, 0xe0, 0x06,\n"," 0x0a, 0x23, 0xf6, 0x1f, 0xea, 0x07, 0xde, 0x00, 0xf5, 0x10, 0xe7, 0x06,\n"," 0xf3, 0xe1, 0x0a, 0x2a, 0xf0, 0x00, 0x18, 0x09, 0xe8, 0xd6, 0xec, 0x00,\n"," 0xef, 0x1c, 0xf2, 0x07, 0xf1, 0xf5, 0x16, 0x13, 0xdf, 0x0f, 0xdd, 0x1b,\n"," 0x10, 0xdb, 0xfb, 0x07, 0xda, 0x17, 0xdf, 0x28, 0xf5, 0xe9, 0x07, 0x0b,\n"," 0x02, 0xf4, 0xf0, 0x0e, 0xda, 0x1e, 0x1d, 0xff, 0xde, 0x0e, 0x1e, 0x24,\n"," 0xf5, 0xfc, 0x08, 0x1f, 0xff, 0x12, 0x09, 0x18, 0x20, 0xd8, 0x08, 0xf0,\n"," 0xef, 0x07, 0x02, 0x19, 0xe8, 0xf3, 0x02, 0x03, 0xdf, 0x22, 0x0e, 0x04,\n"," 0x0d, 0xf9, 0xea, 0x1c, 0xf1, 0x17, 0x08, 0x02, 0x0b, 0x02, 0x00, 0x22,\n"," 0xf0, 0x0e, 0xdf, 0x07, 0xea, 0x01, 0xf3, 0xef, 0xfb, 0xff, 0x07, 0xfd,\n"," 0xf7, 0xf2, 0x14, 0x1e, 0x17, 0xe7, 0x12, 0xf8, 0xee, 0xfc, 0x09, 0xe0,\n"," 0x08, 0xd5, 0x07, 0xff, 0x11, 0xf7, 0xee, 0x14, 0xfd, 0xe0, 0xda, 0x03,\n"," 0xd5, 0xcd, 0x04, 0xe5, 0xea, 0xde, 0xf7, 0x02, 0x0b, 0xfb, 0x03, 0x10,\n"," 0xf7, 0xcf, 0x0c, 0xfb, 0xee, 0x06, 0x0a, 0x12, 0x0e, 0xd7, 0xfb, 0x06,\n"," 0xf6, 0xe0, 0xfb, 0xf1, 0xec, 0xf6, 0x13, 0xf6, 0x0a, 0xea, 0x24, 0x0a,\n"," 0xfd, 0xe6, 0xf8, 0x19, 0x06, 0xe2, 0x05, 0x20, 0x08, 0xe3, 0xd8, 0x05,\n"," 0x00, 0xcd, 0xeb, 0x0f, 0xfd, 0xec, 0xf6, 0xfc, 0xe1, 0xf8, 0xf4, 0xfe,\n"," 0xdf, 0x10, 0xf8, 0x0d, 0xf3, 0xf9, 0x06, 0x06, 0xd5, 0xfb, 0x16, 0x18,\n"," 0x00, 0xfe, 0xf9, 0x17, 0x12, 0xe2, 0xfb, 0xf8, 0xe5, 0x06, 0x29, 0xdf,\n"," 0xfb, 0xfd, 0x08, 0x11, 0xf8, 0x10, 0x13, 0x03, 0xe1, 0xf9, 0xf8, 0xfd,\n"," 0x06, 0xf2, 0x11, 0xff, 0xf8, 0xfe, 0x12, 0xf5, 0xf2, 0xe1, 0x26, 0x0b,\n"," 0xe9, 0xfe, 0x04, 0xf1, 0xeb, 0xfd, 0x0c, 0x26, 0xfd, 0xfb, 0x12, 0xf8,\n"," 0xfd, 0x01, 0x03, 0x05, 0x09, 0x27, 0x28, 0xff, 0x0f, 0x0a, 0xe9, 0xff,\n"," 0x00, 0xec, 0xf7, 0xf4, 0x04, 0x03, 0x08, 0x10, 0xfe, 0xf3, 0x1f, 0xf5,\n"," 0xf0, 0xff, 0x0a, 0x20, 0x0c, 0xd4, 0xef, 0xdb, 0xf5, 0xf4, 0x1a, 0x02,\n"," 0xfe, 0xda, 0x04, 0xe4, 0x0b, 0xd9, 0x1a, 0xee, 0xfd, 0xc6, 0xf8, 0x0d,\n"," 0xec, 0xfe, 0x19, 0xe1, 0x1f, 0xc5, 0x1d, 0x02, 0xf6, 0xd6, 0x04, 0xe6,\n"," 0x06, 0xe4, 0x0c, 0xf0, 0x31, 0xe8, 0xe2, 0xec, 0x1d, 0xe8, 0x0f, 0x02,\n"," 0x2d, 0xe8, 0xf1, 0xf7, 0x0f, 0xf9, 0x13, 0xfd, 0x1f, 0xd8, 0x24, 0x17,\n"," 0xfb, 0xf8, 0x01, 0xe3, 0x14, 0xaf, 0x14, 0x01, 0x1c, 0xe5, 0x10, 0xf2,\n"," 0x16, 0xd3, 0xed, 0xe3, 0x15, 0x02, 0x27, 0xeb, 0x1e, 0x12, 0x19, 0xff,\n"," 0x16, 0xeb, 0x13, 0x11, 0xfa, 0x14, 0xf4, 0x02, 0x11, 0x08, 0xfc, 0xf9,\n"," 0x07, 0xdc, 0x1c, 0xeb, 0x16, 0xf0, 0x1c, 0x06, 0x08, 0xfa, 0xf9, 0x11,\n"," 0xee, 0x07, 0xf3, 0x06, 0xfd, 0xfd, 0x19, 0xf9, 0xf1, 0xe2, 0x1f, 0xf2,\n"," 0x0f, 0xe9, 0x0c, 0xfb, 0x1d, 0x03, 0x02, 0xe2, 0x1c, 0x11, 0xfb, 0xf7,\n"," 0x04, 0x04, 0x18, 0xe7, 0x27, 0xe2, 0xfc, 0xf5, 0x06, 0x00, 0x08, 0xfd,\n"," 0x15, 0xdb, 0x16, 0xfe, 0x04, 0x08, 0xf8, 0xff, 0xfb, 0xeb, 0xeb, 0xfe,\n"," 0xed, 0xf4, 0xf0, 0xe4, 0xfe, 0x22, 0x09, 0x02, 0x21, 0xc8, 0x0b, 0xe4,\n"," 0xf4, 0xf2, 0x04, 0x02, 0xef, 0xce, 0x13, 0x07, 0xfa, 0xe0, 0xff, 0xf1,\n"," 0xfe, 0xd5, 0xfc, 0xdc, 0x0f, 0xf2, 0x05, 0x10, 0x00, 0xd4, 0x24, 0xea,\n"," 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0xf3, 0x1c, 0x00, 0xd4, 0x15, 0x3e, 0x12, 0x31, 0xf4, 0x06, 0xf9, 0xdd,\n"," 0x11, 0x1c, 0x23, 0x11, 0xf8, 0xfb, 0x11, 0xfb, 0x19, 0x10, 0xd8, 0x24,\n"," 0x10, 0x18, 0x0d, 0x27, 0x04, 0x0f, 0xdf, 0xf5, 0x08, 0x07, 0x12, 0xdb,\n"," 0x08, 0x01, 0x07, 0xfe, 0xf3, 0x00, 0x09, 0xf9, 0x01, 0xd3, 0x00, 0xf9,\n"," 0x05, 0x1d, 0xf9, 0xf2, 0xf4, 0xf9, 0x1a, 0xfd, 0xf2, 0x38, 0x01, 0x12,\n"," 0xef, 0xf6, 0x06, 0xfb, 0x0a, 0x1c, 0xf6, 0x10, 0x06, 0x05, 0xf2, 0x03,\n"," 0xf9, 0x07, 0x07, 0xf8, 0x0f, 0xff, 0xf3, 0xff, 0x17, 0x18, 0x08, 0x0d,\n"," 0xf2, 0xff, 0xf1, 0x03, 0x2e, 0xfb, 0xff, 0xd5, 0xf0, 0x05, 0x01, 0x0d,\n"," 0xf5, 0xf0, 0xeb, 0x05, 0x0c, 0x0d, 0xff, 0x13, 0x0c, 0x13, 0x24, 0xf1,\n"," 0xf9, 0xf1, 0x07, 0x06, 0xe9, 0x45, 0x2c, 0x0e, 0xdc, 0xe5, 0x1c, 0xea,\n"," 0x0e, 0x4e, 0x32, 0x05, 0xed, 0xfb, 0xfa, 0xf6, 0x0d, 0x15, 0xfb, 0xfb,\n"," 0xe2, 0xf7, 0xea, 0xfb, 0xf1, 0x14, 0xef, 0x07, 0xf8, 0x08, 0x1d, 0x24,\n"," 0xed, 0x06, 0xe3, 0xed, 0xf1, 0x09, 0x1f, 0x0e, 0xef, 0x1b, 0xec, 0xfb,\n"," 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0xf3, 0x11, 0xe5, 0x12, 0xea, 0x1f, 0xee, 0x18, 0x0c, 0x39, 0x02, 0x1c,\n"," 0x03, 0x13, 0xf6, 0x1f, 0x0b, 0x39, 0xfb, 0x1d, 0x04, 0x03, 0xfb, 0xe9,\n"," 0x12, 0x29, 0xfd, 0xfc, 0x18, 0x13, 0xff, 0x13, 0x18, 0x30, 0x0b, 0x1f,\n"," 0xf9, 0x04, 0x02, 0xf8, 0x17, 0xfb, 0x26, 0xfe, 0x13, 0x02, 0x12, 0x1e,\n"," 0x03, 0xfa, 0xf2, 0x06, 0x04, 0xe9, 0xed, 0x22, 0xfa, 0xfa, 0xf9, 0x00,\n"," 0xfa, 0x18, 0x1b, 0xf9, 0x17, 0xf9, 0xed, 0x1c, 0xff, 0x22, 0x08, 0xfc,\n"," 0xfd, 0x0a, 0xfe, 0x0e, 0x00, 0x17, 0xf9, 0x0b, 0xfa, 0x18, 0x0f, 0xff,\n"," 0x01, 0x14, 0x27, 0xda, 0x10, 0x0a, 0xf0, 0xde, 0x10, 0x16, 0xfd, 0xef,\n"," 0xfb, 0x04, 0x04, 0xf9, 0x2d, 0xfb, 0x00, 0xfe, 0xf5, 0xff, 0xfe, 0xdf,\n"," 0x0a, 0x17, 0xfa, 0x04, 0xf6, 0x17, 0xf7, 0x11, 0xf4, 0x2a, 0xfa, 0x26,\n"," 0x09, 0xfa, 0xdf, 0x16, 0xea, 0x29, 0x03, 0xf4, 0xdc, 0xdc, 0xf2, 0xd7,\n"," 0x0a, 0x3e, 0x01, 0xfe, 0xf6, 0x04, 0x0a, 0x00, 0x0a, 0x38, 0xfb, 0xf7,\n"," 0xdc, 0x02, 0x0b, 0xff, 0xeb, 0x0e, 0xee, 0x00, 0xe8, 0x0c, 0x0c, 0x23,\n"," 0xf1, 0x00, 0xf0, 0x11, 0xec, 0x25, 0xf0, 0x0a, 0xfa, 0x23, 0xf7, 0xf2,\n"," 0x10, 0x1b, 0x09, 0x08, 0x04, 0x10, 0xed, 0x03, 0x19, 0x33, 0x16, 0x1c,\n"," 0xfb, 0x19, 0x08, 0x07, 0x07, 0x26, 0xfc, 0x11, 0x19, 0x05, 0xfb, 0xf6,\n"," 0x38, 0x0e, 0xed, 0x2a, 0x0a, 0x14, 0x13, 0xe5, 0x15, 0x01, 0x07, 0x08,\n"," 0xfc, 0x05, 0x1d, 0xf2, 0x08, 0x01, 0xde, 0xf3, 0x0d, 0xe8, 0x1b, 0xff,\n"," 0xf3, 0xf5, 0xfa, 0xea, 0x07, 0x16, 0x25, 0x01, 0x07, 0xfc, 0x09, 0x12,\n"," 0xf5, 0x12, 0xfc, 0x04, 0xf6, 0x0c, 0xef, 0xfd, 0x05, 0x2c, 0x04, 0x13,\n"," 0xf8, 0xfc, 0xec, 0x15, 0x04, 0xfb, 0x05, 0x14, 0x03, 0xea, 0x02, 0xfe,\n"," 0x0c, 0x14, 0x0d, 0x15, 0xfb, 0x07, 0xfd, 0xeb, 0x24, 0x06, 0xff, 0xeb,\n"," 0xf4, 0x07, 0xfb, 0x22, 0x07, 0xe8, 0xee, 0x0e, 0xfb, 0xfe, 0xde, 0x19,\n"," 0xf1, 0x38, 0xf6, 0x00, 0x0c, 0xf0, 0x00, 0x11, 0xfe, 0x36, 0xef, 0xd6,\n"," 0xe6, 0xed, 0x0f, 0xe7, 0xfe, 0x38, 0xf2, 0x21, 0xe0, 0x02, 0xe4, 0x06,\n"," 0x03, 0x1f, 0x08, 0xd9, 0xfd, 0xf6, 0x13, 0xfc, 0xe1, 0x0b, 0xfd, 0xfc,\n"," 0xf2, 0xff, 0x29, 0x1a, 0xef, 0x04, 0xfb, 0xf0, 0xe2, 0x1d, 0x0a, 0x16,\n"," 0xe3, 0x26, 0xdd, 0x0c, 0xf6, 0x23, 0xf0, 0x13, 0xfc, 0x0b, 0x10, 0x0e,\n"," 0x0f, 0x35, 0xfb, 0x16, 0x14, 0x20, 0x04, 0x01, 0x0a, 0x0e, 0xf1, 0x0f,\n"," 0x08, 0xf8, 0xf9, 0xf8, 0x1c, 0x32, 0x1a, 0x14, 0x05, 0x0c, 0x10, 0xda,\n"," 0x24, 0x25, 0x13, 0x1f, 0x14, 0xfb, 0x06, 0xdf, 0x01, 0x0c, 0xfa, 0x03,\n"," 0x00, 0xe5, 0x15, 0xf4, 0xf3, 0xdf, 0x0d, 0xee, 0xfe, 0x0e, 0x0e, 0x27,\n"," 0x11, 0xe9, 0x0c, 0x11, 0xed, 0x2b, 0x03, 0x16, 0x09, 0xec, 0x06, 0xe7,\n"," 0xf2, 0x33, 0x04, 0x09, 0xf8, 0x0f, 0x0e, 0xf2, 0xfd, 0xfa, 0x04, 0xf4,\n"," 0x10, 0x0a, 0x0b, 0xfc, 0x02, 0xfc, 0xfc, 0xf8, 0x1e, 0x04, 0xe8, 0xdb,\n"," 0x10, 0xf8, 0x0a, 0x0f, 0xfb, 0xf8, 0x1f, 0xee, 0x0e, 0xde, 0xed, 0xd8,\n"," 0x09, 0x0a, 0x1c, 0x2c, 0x06, 0x35, 0x01, 0x0a, 0x0f, 0xf5, 0xf7, 0x0f,\n"," 0xf7, 0x30, 0x15, 0x08, 0xcf, 0xf9, 0x20, 0xd9, 0x05, 0x35, 0xe3, 0x04,\n"," 0xe1, 0x12, 0xf0, 0x04, 0xfa, 0x1d, 0xfd, 0xff, 0x04, 0xfb, 0x28, 0xfd,\n"," 0xed, 0x2f, 0xf5, 0x04, 0xe6, 0x04, 0xe6, 0x16, 0xe5, 0xe8, 0xf2, 0xeb,\n"," 0xf1, 0x02, 0x07, 0x08, 0xe9, 0x22, 0xed, 0xf6, 0x01, 0x3c, 0xf4, 0x17,\n"," 0xe5, 0x0e, 0x07, 0x06, 0x00, 0x34, 0xfc, 0x1a, 0x1a, 0x17, 0x0c, 0xfe,\n"," 0xf7, 0x1d, 0xe9, 0x30, 0x11, 0xf8, 0x19, 0x05, 0x1d, 0x1b, 0xda, 0xfe,\n"," 0x07, 0xf1, 0x08, 0xf2, 0x2b, 0xff, 0xef, 0x01, 0xf9, 0x04, 0x05, 0xfb,\n"," 0xf8, 0x06, 0x0d, 0x04, 0x14, 0xfb, 0x14, 0x06, 0xf2, 0xe3, 0xfe, 0x07,\n"," 0xf4, 0x0c, 0xfd, 0x1d, 0x18, 0xeb, 0x05, 0xee, 0x12, 0x24, 0x00, 0x0b,\n"," 0xff, 0xf9, 0x01, 0xec, 0xfa, 0x1e, 0x1b, 0xfe, 0x01, 0x07, 0x26, 0x06,\n"," 0x02, 0x0c, 0xf7, 0x03, 0x1c, 0xf2, 0x14, 0xdc, 0x09, 0x1f, 0xf4, 0x14,\n"," 0x0e, 0x0c, 0xf8, 0xec, 0x1c, 0x0f, 0xf8, 0xf8, 0x0a, 0xf7, 0x1b, 0xfb,\n"," 0xfe, 0x1b, 0xfa, 0xee, 0x05, 0x06, 0xef, 0x20, 0xe5, 0x4e, 0xef, 0xea,\n"," 0xf5, 0xe7, 0x06, 0x17, 0xd8, 0x1e, 0x12, 0xfa, 0xed, 0xf5, 0x01, 0xf2,\n"," 0xfe, 0x2a, 0x07, 0xfd, 0xdd, 0x01, 0xfa, 0x02, 0x12, 0x2f, 0xf5, 0x0e,\n"," 0xf2, 0xff, 0x03, 0xfc, 0xe7, 0x23, 0xd8, 0x08, 0xef, 0x00, 0xef, 0x0c,\n"," 0xe4, 0xe7, 0xf6, 0xfc, 0xcb, 0x18, 0x0d, 0x0d, 0xe9, 0x12, 0x0c, 0x00,\n"," 0xf8, 0x23, 0xea, 0x28, 0xeb, 0x26, 0xfa, 0xe5, 0x1a, 0x32, 0x1a, 0x1b,\n"," 0x15, 0x16, 0xf1, 0x07, 0xf5, 0x2b, 0x01, 0x11, 0x12, 0x0f, 0x09, 0x00,\n"," 0x23, 0x23, 0xf4, 0xfb, 0x08, 0x0b, 0x10, 0x1f, 0x21, 0x0e, 0x0a, 0x08,\n"," 0x0a, 0xff, 0x01, 0x17, 0xf2, 0xe3, 0xdc, 0x12, 0x0f, 0x05, 0x16, 0xec,\n"," 0xf3, 0xef, 0xeb, 0xeb, 0xfb, 0x12, 0x11, 0xf8, 0x17, 0xe7, 0x0c, 0xf6,\n"," 0x08, 0x0e, 0x15, 0xe4, 0x0a, 0x00, 0xd8, 0xf8, 0xf6, 0x00, 0x08, 0x22,\n"," 0xfd, 0xfa, 0x0c, 0xfe, 0x08, 0x14, 0xfc, 0x04, 0x06, 0xfa, 0x15, 0xf5,\n"," 0x0f, 0xf6, 0xf0, 0x03, 0x03, 0xf2, 0x0e, 0xf1, 0x27, 0xf0, 0xf0, 0xf4,\n"," 0xf9, 0x07, 0xf0, 0x07, 0x02, 0x1b, 0xfc, 0x00, 0xf2, 0xfc, 0x13, 0x06,\n"," 0xef, 0x2a, 0xf2, 0xeb, 0xf9, 0xe5, 0xfa, 0x0c, 0xe6, 0x20, 0xf4, 0x03,\n"," 0xe2, 0x12, 0xfb, 0x03, 0x0b, 0x39, 0xed, 0x0f, 0xf4, 0x10, 0x04, 0xf8,\n"," 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0xd5, 0xfd, 0xfd, 0xf9, 0xd2, 0x14, 0xf3, 0x0c, 0xd5, 0x08, 0x15, 0xff,\n"," 0xe1, 0xfa, 0xe0, 0xf9, 0xfe, 0x10, 0x00, 0x15, 0xd5, 0xf0, 0x05, 0x1d,\n"," 0xf1, 0x28, 0x04, 0xf7, 0xea, 0x20, 0xf8, 0x0e, 0x08, 0x29, 0x10, 0x0a,\n"," 0xf1, 0x21, 0x0d, 0x16, 0xfc, 0x24, 0xf0, 0x1e, 0x14, 0x09, 0xec, 0x07,\n"," 0x1a, 0x1f, 0x09, 0xf0, 0x19, 0xe5, 0x19, 0xf4, 0x04, 0x0d, 0x01, 0x00,\n"," 0xf4, 0xf8, 0x07, 0xfd, 0x18, 0x10, 0x1d, 0x01, 0x0a, 0xfc, 0x18, 0x1b,\n"," 0xf5, 0x15, 0xfa, 0xf9, 0x09, 0xe7, 0x0d, 0x0d, 0xff, 0xfe, 0xf0, 0xf2,\n"," 0xf9, 0x10, 0x0f, 0x09, 0xfa, 0xdb, 0xf2, 0xe4, 0xfa, 0x14, 0x08, 0x0b,\n"," 0x04, 0xfb, 0x12, 0xe8, 0xf7, 0x02, 0x05, 0x0d, 0xfe, 0x0d, 0xe4, 0xf9,\n"," 0xef, 0x20, 0x0d, 0xe6, 0xff, 0x00, 0xea, 0xf0, 0x09, 0x07, 0x02, 0x0a,\n"," 0x14, 0xec, 0x1e, 0xe4, 0x20, 0xf8, 0xf5, 0x05, 0x02, 0x09, 0x0a, 0x10,\n"," 0xf8, 0xff, 0x01, 0xf3, 0x16, 0x10, 0x00, 0x02, 0xda, 0x24, 0xd2, 0x00,\n"," 0x0c, 0xff, 0xdd, 0x13, 0xdc, 0x2b, 0xd6, 0xf5, 0xfd, 0x1d, 0xf7, 0x0d,\n"," 0xd9, 0x18, 0xee, 0x0e, 0xef, 0x0f, 0xf2, 0xf8, 0xd5, 0x11, 0xdd, 0x0f,\n"," 0xf2, 0xfb, 0xfc, 0x07, 0xda, 0x01, 0xe1, 0xf2, 0xf4, 0xf8, 0xf6, 0xfa,\n"," 0xd4, 0xfa, 0xee, 0xdd, 0xce, 0x06, 0xf7, 0x0c, 0xf5, 0x1a, 0xe8, 0x0a,\n"," 0xf5, 0x1e, 0xf4, 0x12, 0xf1, 0x23, 0x02, 0x09, 0xfa, 0x00, 0xea, 0x21,\n"," 0xed, 0x04, 0xf7, 0x05, 0xf9, 0x1a, 0xf7, 0x09, 0x0c, 0xf8, 0x08, 0x20,\n"," 0x12, 0x21, 0xdd, 0x08, 0x04, 0xfd, 0x17, 0x08, 0x06, 0x17, 0xec, 0x12,\n"," 0x05, 0xfb, 0x07, 0x14, 0x01, 0x1c, 0x13, 0xf4, 0x1e, 0xea, 0x09, 0xf0,\n"," 0x1a, 0x04, 0xfb, 0xfe, 0xf2, 0x1e, 0x1a, 0xfb, 0x20, 0xef, 0x10, 0xff,\n"," 0x04, 0x19, 0x09, 0x07, 0x15, 0xee, 0xda, 0xc8, 0x01, 0x22, 0xf5, 0xe3,\n"," 0x05, 0xfb, 0x18, 0xf2, 0xf1, 0x07, 0xfb, 0x05, 0xf8, 0xef, 0xf9, 0xf4,\n"," 0xfa, 0xfa, 0xf0, 0xfa, 0x00, 0xe5, 0xf1, 0x0a, 0xfc, 0xf5, 0xe9, 0x25,\n"," 0xff, 0xed, 0xf8, 0xfd, 0xec, 0xf0, 0xfc, 0x00, 0xf3, 0x0b, 0x0a, 0x1c,\n"," 0xdb, 0x03, 0x0b, 0x0b, 0xfa, 0xfc, 0xda, 0xfc, 0xef, 0x2d, 0xff, 0xf5,\n"," 0x0b, 0x04, 0xfa, 0xe2, 0xd8, 0x03, 0x0f, 0x1c, 0xf8, 0x0c, 0x1c, 0x1e,\n"," 0xe3, 0x12, 0x18, 0xeb, 0xe7, 0x18, 0xfb, 0xdd, 0xcc, 0xf2, 0xf2, 0xe3,\n"," 0xfe, 0x11, 0xed, 0x15, 0xf6, 0xff, 0xdf, 0xf9, 0xfb, 0x04, 0x03, 0x23,\n"," 0xc6, 0x1b, 0x2e, 0xfa, 0x0a, 0x2d, 0x02, 0x08, 0xf2, 0x14, 0xeb, 0xe5,\n"," 0xfb, 0xf7, 0x03, 0x15, 0x12, 0x06, 0x1d, 0x05, 0x07, 0x10, 0x0d, 0x0c,\n"," 0x13, 0x0c, 0xf5, 0xf6, 0x14, 0x05, 0xee, 0xfa, 0xf6, 0x06, 0x0c, 0xe3,\n"," 0x06, 0xf9, 0xea, 0xf6, 0x23, 0xea, 0x0e, 0xfb, 0xf6, 0x10, 0x17, 0x11,\n"," 0x08, 0xfb, 0x25, 0xef, 0x07, 0x1e, 0xf4, 0xeb, 0xed, 0x27, 0xef, 0xf7,\n"," 0xfa, 0xe5, 0xee, 0xe9, 0x06, 0x18, 0xed, 0xea, 0x09, 0xec, 0x0e, 0x01,\n"," 0xfc, 0xe9, 0xff, 0xec, 0xee, 0xe0, 0x1f, 0xe7, 0xfb, 0x12, 0x20, 0x07,\n"," 0x16, 0xea, 0x08, 0xd3, 0x1d, 0xe8, 0xea, 0xff, 0xf1, 0xf2, 0x0f, 0xd1,\n"," 0x24, 0xfb, 0xe3, 0x1b, 0xff, 0xe4, 0xef, 0xf3, 0xfd, 0xf8, 0xfd, 0xe0,\n"," 0xf1, 0x01, 0x11, 0x0d, 0x0f, 0xf5, 0x05, 0xe3, 0xf8, 0xe3, 0xe5, 0xfd,\n"," 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0x01, 0x00, 0xf5, 0xff, 0x29, 0xe8, 0x11, 0xf4, 0x20, 0xf9, 0x16, 0xec,\n"," 0x0c, 0xd9, 0x23, 0xf0, 0x0f, 0x27, 0xdd, 0xe9, 0x05, 0xd9, 0x0d, 0x20,\n"," 0x0e, 0x34, 0xfe, 0xda, 0x27, 0xf9, 0x1a, 0x26, 0x17, 0x0b, 0xd8, 0xd7,\n"," 0xfe, 0x0a, 0x0c, 0xe3, 0xf8, 0x0c, 0xdd, 0xf9, 0x12, 0xef, 0xff, 0x1b,\n"," 0x01, 0xf7, 0xe9, 0xf6, 0x05, 0xf1, 0x1d, 0xdf, 0xf3, 0x05, 0xf2, 0xf2,\n"," 0x00, 0x05, 0x00, 0xf8, 0x0f, 0xdf, 0x00, 0x03, 0x00, 0x13, 0x0b, 0xf0,\n"," 0x0e, 0xec, 0x13, 0x11, 0x17, 0xf1, 0x07, 0xe7, 0x1d, 0xe1, 0xe7, 0xe9,\n"," 0x07, 0x00, 0x1e, 0x21, 0x0b, 0xe8, 0xeb, 0xf5, 0x14, 0xf0, 0x10, 0xe9,\n"," 0xf5, 0xf1, 0xf2, 0xcd, 0xf3, 0x0e, 0x10, 0xff, 0x11, 0xf0, 0x03, 0xf8,\n"," 0x1c, 0x0f, 0x13, 0xeb, 0xf1, 0xe3, 0x0e, 0xfc, 0x02, 0x0b, 0xf3, 0xf2,\n"," 0xfb, 0x01, 0x01, 0xfc, 0xee, 0xfb, 0xeb, 0xf9, 0xf4, 0x0d, 0x03, 0xfe,\n"," 0xda, 0x13, 0x15, 0xfa, 0x14, 0xf1, 0xd9, 0x09, 0xf5, 0x07, 0x04, 0x03,\n"," 0xfe, 0x15, 0xfe, 0x0b, 0x0e, 0xf9, 0x20, 0xeb, 0x11, 0xef, 0xf8, 0xf7,\n"," 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0x00, 0x00, 0x08, 0x00, 0x0a, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x04,\n"," 0x03, 0x00, 0x00, 0x00\n","};\n","unsigned int g_model_len = 18952;\n"],"name":"stdout"}]}]}
\ No newline at end of file