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Added Tutorial Hvass-Labs#7 
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‎.gitignore‎

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# Data for TensorFlow
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data/
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inception/
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checkpoints/
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checkpoints*
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logs/

‎07_Inception_Model.ipynb‎

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‎README.md‎

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# TensorFlow-Tutorials
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[Original repository on GitHub](https://github.com/Hvass-Labs/TensorFlow-Tutorials)
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## Contents
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1. Simple Linear Model ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/01_Simple_Linear_Model.ipynb))
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6. CIFAR-10 ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/06_CIFAR-10.ipynb))
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7. Inception Model ([Notebook](https://github.com/Hvass-Labs/TensorFlow-Tutorials/blob/master/07_Inception_Model.ipynb))
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## Videos
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These tutorials are also available as [YouTube Videos](https://www.youtube.com/playlist?list=PL9Hr9sNUjfsmEu1ZniY0XpHSzl5uihcXZ).

‎cifar10.py‎

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########################################################################
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#
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# This file is part of the TensorFlow Tutorials available at:
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#
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# https://github.com/Hvass-Labs/TensorFlow-Tutorials
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#
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# Published under the MIT License. See the file LICENSE for details.
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import numpy as np
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import pickle
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import urllib.request
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import tarfile
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import sys
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import os
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import download
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########################################################################
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########################################################################
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# Private functions for downloading, unpacking and loading data-files.
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def _print_download_progress(count, block_size, total_size):
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"""
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Used for printing the download progress.
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Used as a call-back function in maybe_download_and_extract().
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"""
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# Percentage completion.
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pct_complete = float(count * block_size) / total_size
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# Status-message. Note the \r which means the line should overwrite itself.
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msg = "\r- Download progress: {0:.1%}".format(pct_complete)
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# Print it.
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sys.stdout.write(msg)
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sys.stdout.flush()
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def _get_file_path(filename=""):
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"""
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in data_path (set this variable first to the desired path).
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"""
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# Check if the path for unpacked data-files already exists.
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# If it exists then we assume the tar-ball has already been
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# downloaded and extracted, otherwise we need to do that now.
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if not os.path.exists(_get_file_path()):
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# Check if the destination path exists, otherwise create it.
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if not os.path.exists(data_path):
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os.makedirs(data_path)
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# Filename for saving the file downloaded from the internet.
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# Use the original file-name and add it to the data_path.
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filename = data_url.split('/')[-1]
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file_path = os.path.join(data_path, filename)
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# Download the file from the internet.
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file_path, _ = urllib.request.urlretrieve(url=data_url,
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filename=file_path,
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reporthook=_print_download_progress)
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print()
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print("Download finished. Extracting files.")
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# Unpack the tar-ball.
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tarfile.open(name=file_path, mode="r:gz").extractall(data_path)
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print("Done.")
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else:
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print("CIFAR-10 data has apparently already been downloaded and unpacked.")
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download.maybe_download_and_extract(url=data_url, download_dir=data_path)
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def load_class_names():

‎download.py‎

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########################################################################
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#
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# Functions for downloading and extracting data-files from the internet.
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#
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# Implemented in Python 3.5
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#
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########################################################################
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#
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# This file is part of the TensorFlow Tutorials available at:
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#
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# https://github.com/Hvass-Labs/TensorFlow-Tutorials
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#
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# Published under the MIT License. See the file LICENSE for details.
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#
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# Copyright 2016 by Magnus Erik Hvass Pedersen
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#
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########################################################################
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import sys
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import os
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import urllib.request
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import tarfile
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########################################################################
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def _print_download_progress(count, block_size, total_size):
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"""
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Function used for printing the download progress.
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Used as a call-back function in maybe_download_and_extract().
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"""
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# Percentage completion.
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pct_complete = float(count * block_size) / total_size
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# Status-message. Note the \r which means the line should overwrite itself.
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msg = "\r- Download progress: {0:.1%}".format(pct_complete)
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# Print it.
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sys.stdout.write(msg)
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sys.stdout.flush()
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########################################################################
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def maybe_download_and_extract(url, download_dir):
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"""
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Download and extract the data if it doesn't already exist.
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Assumes the url is a tar-ball file.
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:param url:
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Internet URL for the tar-file to download.
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Example: "https://www.cs.toronto.edu/~kriz/cifar-10-python.tar.gz"
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:param download_dir:
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Directory where the downloaded file is saved.
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Example: "data/CIFAR-10/"
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:return:
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Nothing.
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"""
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# Filename for saving the file downloaded from the internet.
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# Use the filename from the URL and add it to the download_dir.
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filename = url.split('/')[-1]
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file_path = os.path.join(download_dir, filename)
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# Check if the file already exists.
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# If it exists then we assume it has also been extracted,
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# otherwise we need to download and extract it now.
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if not os.path.exists(file_path):
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# Check if the download directory exists, otherwise create it.
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if not os.path.exists(download_dir):
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os.makedirs(download_dir)
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# Download the file from the internet.
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file_path, _ = urllib.request.urlretrieve(url=url,
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filename=file_path,
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reporthook=_print_download_progress)
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print()
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print("Download finished. Extracting files.")
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# Unpack the tar-ball.
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tarfile.open(name=file_path, mode="r:gz").extractall(download_dir)
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print("Done.")
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else:
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print("Data has apparently already been downloaded and unpacked.")
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########################################################################

‎images/07_inception_flowchart.png‎

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‎images/elon_musk.jpg‎

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‎images/elon_musk_100x100.jpg‎

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‎images/parrot.jpg‎

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‎images/parrot_cropped1.jpg‎

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