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Quick tensorflow tutorial
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# Copyright 2018 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. | |
"""tf.data.Dataset interface to the MNIST dataset.""" | |
from __future__ import absolute_import | |
from __future__ import division | |
from __future__ import print_function | |
import gzip | |
import os | |
import shutil | |
import tempfile | |
import numpy as np | |
from six.moves import urllib | |
import tensorflow as tf | |
def read32(bytestream): | |
"""Read 4 bytes from bytestream as an unsigned 32-bit integer.""" | |
dt = np.dtype(np.uint32).newbyteorder('>') | |
return np.frombuffer(bytestream.read(4), dtype=dt)[0] | |
def check_image_file_header(filename): | |
"""Validate that filename corresponds to images for the MNIST dataset.""" | |
with tf.gfile.Open(filename, 'rb') as f: | |
magic = read32(f) | |
read32(f) # num_images, unused | |
rows = read32(f) | |
cols = read32(f) | |
if magic != 2051: | |
raise ValueError('Invalid magic number %d in MNIST file %s' % (magic, | |
f.name)) | |
if rows != 28 or cols != 28: | |
raise ValueError( | |
'Invalid MNIST file %s: Expected 28x28 images, found %dx%d' % | |
(f.name, rows, cols)) | |
def check_labels_file_header(filename): | |
"""Validate that filename corresponds to labels for the MNIST dataset.""" | |
with tf.gfile.Open(filename, 'rb') as f: | |
magic = read32(f) | |
read32(f) # num_items, unused | |
if magic != 2049: | |
raise ValueError('Invalid magic number %d in MNIST file %s' % (magic, | |
f.name)) | |
def download(directory, filename): | |
"""Download (and unzip) a file from the MNIST dataset if not already done.""" | |
filepath = os.path.join(directory, filename) | |
if tf.gfile.Exists(filepath): | |
return filepath | |
if not tf.gfile.Exists(directory): | |
tf.gfile.MakeDirs(directory) | |
# CVDF mirror of http://yann.lecun.com/exdb/mnist/ | |
url = 'https://storage.googleapis.com/cvdf-datasets/mnist/' + filename + '.gz' | |
_, zipped_filepath = tempfile.mkstemp(suffix='.gz') | |
print('Downloading %s to %s' % (url, zipped_filepath)) | |
urllib.request.urlretrieve(url, zipped_filepath) | |
with gzip.open(zipped_filepath, 'rb') as f_in, \ | |
tf.gfile.Open(filepath, 'wb') as f_out: | |
shutil.copyfileobj(f_in, f_out) | |
os.remove(zipped_filepath) | |
return filepath | |
def dataset(directory, images_file, labels_file): | |
"""Download and parse MNIST dataset.""" | |
images_file = download(directory, images_file) | |
labels_file = download(directory, labels_file) | |
check_image_file_header(images_file) | |
check_labels_file_header(labels_file) | |
def decode_image(image): | |
# Normalize from [0, 255] to [0.0, 1.0] | |
image = tf.decode_raw(image, tf.uint8) | |
image = tf.cast(image, tf.float32) | |
image = tf.reshape(image, [784]) | |
return image / 255.0 | |
def decode_label(label): | |
label = tf.decode_raw(label, tf.uint8) # tf.string -> [tf.uint8] | |
label = tf.reshape(label, []) # label is a scalar | |
return tf.to_int32(label) | |
images = tf.data.FixedLengthRecordDataset( | |
images_file, 28 * 28, header_bytes=16).map(decode_image) | |
labels = tf.data.FixedLengthRecordDataset( | |
labels_file, 1, header_bytes=8).map(decode_label) | |
return tf.data.Dataset.zip((images, labels)) | |
def train(directory): | |
"""tf.data.Dataset object for MNIST training data.""" | |
return dataset(directory, 'train-images-idx3-ubyte', | |
'train-labels-idx1-ubyte') | |
def test(directory): | |
"""tf.data.Dataset object for MNIST test data.""" | |
return dataset(directory, 't10k-images-idx3-ubyte', 't10k-labels-idx1-ubyte') |
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