170615 创建tensorflow自己的nextbacth

stackover问题描述
nextbatch中文方法

代码来源：https://stackoverflow.com/questions/40994583/how-to-implement-tensorflows-next-batch-for-own-data
代码整理：

# -*- coding: utf-8 -*-
"""
Created on Thu Jun 15 14:49:43 2017

@author: Bruce Lau
"""

import numpy as np 
np.set_printoptions(threshold=200) 

class Dataset:
    def __init__(self,data):    
        self._index_in_epoch = 0
        self._epochs_completed = 0
        self._data = data
        self._num_examples = data.shape[0]
        pass
    @property
    def data(self):
        return self._data

    def next_batch(self,batch_size,shuffle = True):
        start = self._index_in_epoch
        if start == 0 and self._epochs_completed == 0:
            idx = np.arange(0, self._num_examples)  # get all possible indexes
            np.random.shuffle(idx)  # shuffle indexe
            self._data = self.data[idx]  # get list of `num` random samples

        # go to the next batch
        if start + batch_size > self._num_examples:
            self._epochs_completed += 1
            rest_num_examples = self._num_examples - start
            data_rest_part = self.data[start:self._num_examples]
            idx0 = np.arange(0, self._num_examples)  # get all possible indexes
            np.random.shuffle(idx0)  # shuffle indexes
            self._data = self.data[idx0]  # get list of `num` random samples

            start = 0
            self._index_in_epoch = batch_size - rest_num_examples #avoid the case where the #sample != integar times of batch_size
            end =  self._index_in_epoch  
            data_new_part =  self._data[start:end]  
            return np.concatenate((data_rest_part, data_new_part), axis=0)
        else:
            self._index_in_epoch += batch_size
            end = self._index_in_epoch
            return self._data[start:end]

#%% Test 
Ytr = Dataset(np.arange(0, 10))
Xtr = np.arange(0, 100).reshape(10, 10)
print('The training data is: \n')
for i in range(2):
    label = Ytr.next_batch(5)
    train = Xtr[label]
    print('The batch label number is:')
    print(label,'\n')
    print('The batch train data is:')
    print(train,'\n')