我按照本教程创建了以下数据生成器。但是，训练时间太长了。知道我已经创建了对象读取的所有数据文件，如何让它运行得更快reader？
ps：该方法__data_generation每次迭代执行 2 个磁盘访问。
import numpy as np
import keras
class DataGenerator(keras.utils.Sequence):
"""
Generates data for Keras
:return: data generator object
"""
def __init__(self, reader, list_IDs, labels, relations_list, batch_size=32, shuffle=True):
# Initialization
self.reader = reader
self.batch_size = batch_size
self.labels = labels
self.list_IDs = list_IDs
self.shuffle = shuffle
self.on_epoch_end()
self.relations = relations_list
self.data_num = 0
def __len__(self):
"""
Denotes the number of batches per epoch
:return: int
"""
return int(np.floor(len(self.list_IDs) / self.batch_size))
def __getitem__(self, index):
"""
Generate one batch of data
:param index: index of the current training item
:return: tuple
"""
# Generate indexes of the batch
indexes = self.indexes[index*self.batch_size:(index+1)*self.batch_size]
# Find list of IDs
list_IDs_temp = [self.list_IDs[k] for k in indexes]
# Generate data
X, y = self.__data_generation(list_IDs_temp)
return X, y
def on_epoch_end(self):
"""
Updates indexes after each epoch
:return:
"""
self.indexes = np.arange(len(self.list_IDs))
if self.shuffle:
np.random.shuffle(self.indexes)
def __data_generation(self, list_IDs_temp):
"""
Generates data containing batch_size samples'
:param list_IDs_temp: the list of IDs of the target batch
:return: tuple
"""
# Initialization
y = []
v_q_words = []
v_d_words = []
# Generate data
for i, ID in enumerate(list_IDs_temp):
# Store sample
q_words = self.reader.get_query(self.relations[ID][0]) # corresponds to 1 file read from disc
v_q_words.append(q_words)
d_words = self.reader.get_document(self.relations[ID][1]) # corresponds to another file read from disc
v_d_words.append(d_words)
# Store class
y.append(self.labels[ID])
X = [np.array(v_q_words), np.array(v_d_words)]
return X, np.array(y)
提前感谢您的回答。