#?Copyright?2016?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.
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#
#?????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.
#?==============================================================================

“““Functions?for?downloading?and?reading?MNIST?data.“““
#-*-coding:utf-8-*-
from?__future__?import?absolute_import
from?__future__?import?division
from?__future__?import?print_function

import?gzip

import?numpy
from?six.moves?import?xrange??#?pylint:?disable=redefined-builtin

from?tensorflow.contrib.learn.python.learn.datasets?import?base
from?tensorflow.python.framework?import?dtypes

SOURCE_URL?=?‘http://yann.lecun.com/exdb/mnist/‘


def?_read32（bytestream）:
??dt?=?numpy.dtype（numpy.uint32）.newbyteorder（‘>‘）
??return?numpy.frombuffer（bytestream.read（4）?dtype=dt）[0]


def?extract_images（f）:
??“““Extract?the?images?into?a?4D?uint8?numpy?array?[index?y?x?depth].

??Args:
????f:?A?file?object?that?can?be?passed?into?a?gzip?reader.

??Returns:
????data:?A?4D?uint8?numpy?array?[index?y?x?depth].

??Raises:
????ValueError:?If?the?bytestream?does?not?start?with?2051.

??“““
??print（‘Extracting‘?f.name）
??with?gzip.GzipFile（fileobj=f）?as?bytestream:
????magic?=?_read32（bytestream）
????if?magic?!=?2051:
??????raise?ValueError（‘Invalid?magic?number?%d?in?MNIST?image?file:?%s‘?%
???????????????????????（magic?f.name））
????num_images?=?_read32（bytestream）
????rows?=?_read32（bytestream）
????cols?=?_read32（bytestream）
????buf?=?bytestream.read（rows?*?cols?*?num_images）
????data?=?numpy.frombuffer（buf?dtype=numpy.uint8）
????data?=?data.reshape（num_images?rows?cols?1）
????return?data


def?dense_to_one_hot（labels_dense?num_classes）:
??“““Convert?class?labels?from?scalars?to?one-hot?vectors.“““
??num_labels?=?labels_dense.shape[0]
??index_offset?=?numpy.arange（num_labels）?*?num_classes
??labels_one_hot?=?numpy.zeros（（num_labels?num_classes））
??labels_one_hot.flat[index_offset?+?labels_dense.ravel（）]?=?1
??return?labels_one_hot


def?extract_labels（f?one_hot=False?num_classes=2）:??????????????#這里打num_classes手動設置為自己的類別數
??“““Extract?the?labels?into?a?1D?uint8?numpy?array?[index].

??Args:
????f:?A?file?object?that?can?be?passed?into?a?gzip?reader.
????one_hot:?Does?one?hot?encoding?for?the?result.
????num_classes:?Number?of?classes?for?the?one?hot?encoding.

??Returns:
????labels:?a?1D?uint8?numpy?array.

??Raises:
????ValueError:?If?the?bystream?doesn‘t?start?with?2049.
??“““
??print（‘Extracting‘?f.name）
??with?gzip.GzipFile（fileobj=f）?as?bytestream:
????magic?=?_read