#?Copyright?2015?Google?Inc.?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.
#?==============================================================================

“““Builds?the?CIFAR-10?network.

Summary?of?available?functions:

?#?Compute?input?images?and?labels?for?training.?If?you?would?like?to?run
?#?evaluations?use?input（）?instead.
?inputs?labels?=?distorted_inputs（）

?#?Compute?inference?on?the?model?inputs?to?make?a?prediction.
?predictions?=?inference（inputs）

?#?Compute?the?total?loss?of?the?prediction?with?respect?to?the?labels.
?loss?=?loss（predictions?labels）

?#?Create?a?graph?to?run?one?step?of?training?with?respect?to?the?loss.
?train_op?=?train（loss?global_step）
“““
#?pylint:?disable=missing-docstring
from?__future__?import?absolute_import
from?__future__?import?division
from?__future__?import?print_function

import?gzip
import?os
import?re
import?sys
import?tarfile

import?tensorflow.python.platform
from?six.moves?import?urllib
import?tensorflow?as?tf

from?tensorflow.models.image.cifar10?import?cifar10_input

FLAGS?=?tf.app.flags.FLAGS

#?Basic?model?parameters.
tf.app.flags.DEFINE_integer（‘batch_size‘?128
????????????????????????????“““Number?of?images?to?process?in?a?batch.“““）
tf.app.flags.DEFINE_string（‘data_dir‘?‘/tmp/cifar10_data‘
???????????????????????????“““Path?to?the?CIFAR-10?data?directory.“““）

#?Global?constants?describing?the?CIFAR-10?data?set.
IMAGE_SIZE?=?cifar10_input.IMAGE_SIZE
NUM_CLASSES?=?cifar10_input.NUM_CLASSES
NUM_EXAMPLES_PER_EPOCH_FOR_TRAIN?=?cifar10_input.NUM_EXAMPLES_PER_EPOCH_FOR_TRAIN
NUM_EXAMPLES_PER_EPOCH_FOR_EVAL?=?cifar10_input.NUM_EXAMPLES_PER_EPOCH_FOR_EVAL


#?Constants?describing?the?training?process.
MOVING_AVERAGE_DECAY?=?0.9999?????#?The?decay?to?use?for?the?moving?average.
NUM_EPOCHS_PER_DECAY?=?350.0??????#?Epochs?after?which?learning?rate?decays.
LEARNING_RATE_DECAY_FACTOR?=?0.1??#?Learning?rate?decay?factor.
INITIAL_LEARNING_RATE?=?0.1???????#?Initial?learning?rate.

#?If?a?model?is?trained?with?multiple?GPU‘s?prefix?all?Op?names?with?tower_name
#?to?differentiate?the?operations.?Note?that?this?prefix?is?removed?from?the
#?names?of?the?summaries?when?visualizing?a?model.
TOWER_NAME?=?‘tower‘

DATA_URL?=?‘http://www.cs.toronto.edu/~kriz/cifar-10-binary.tar.gz‘


def?_activation_summary（x）:
??“““Helper?to?create?summaries?for?activations.

??Creates?a?summary?that?provides?a?histogram?of?activations.
??Creates?a?summary?that?measure?the?sparsity?of?activations.

??Args:
?

?屬性????????????大小?????日期????時間???名稱
-----------?---------??----------?-----??----
?????文件????????1663??2017-10-17?22:51??BUILD
?????文件???????14063??2017-10-17?22:50??cifar10.py
?????文件????????5667??2017-10-17?22:50??cifar10_eval.py
?????文件????????9289??2017-10-17?22:50??cifar10_input.py
?????文件????????2334??2017-10-17?22:50??cifar10_input_test.py
?????文件???????10891??2017-10-17?22:50??cifar10_multi_gpu_train.py
?????文件????????4695??2017-10-17?22:50??cifar10_train.py
?????文件?????????419??2017-10-17?22:51??README.md
?????文件?????????961??2017-10-17?22:50??__init__.py