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1 decode_csv读取数据
import tensorflow as tf
#创建文件队列
filenames ['./s0000025_1.csv','./s0000025_2.csv']
filename_queue = tf.train.string_input_producer(filenames,shuffle=True)
#shuffle=True 文件队列随机读取，默认TFReader = tf.TextLineReader(skip_header_lines=1) # 跳过首行
key,value = TFReader.read(filename_queue) #读取内容record_default = [0.0, 0.0,0.0,0.0]
col1,col2,col3,col4= tf.decode_csv(value, record_defaults=record_default,field_delim=",") #field_delim 分隔符默认是","features = tf.concat([[col1], [col2], [col3]], 0)with tf.Session() as sess:coord = tf.train.Coordinator()threads = tf.train.start_queue_runners(sess=sess,coord=coord)for i in range(10):example, lable = sess.run([features,col4])print(example, lable)coord.request_stop()coord.join(threads)2 TextLineDataset 读取数据
def decode_line(line):# Decode the line to tensorrecord_defaults = [[0.0] for col in range(4)]items = tf.decode_csv(line, record_defaults)features = items[0:3]label = items[3]# features = tf.cast(features, tf.float32)# features = tf.reshape(features,[28,28,1])# label = tf.cast(label, tf.int64)return features,labeldef create_dataset(filename, batch_size=32, is_shuffle=False, n_repeats=0):dataset = tf.data.TextLineDataset(filename).skip(1)if n_repeats > 0:dataset = dataset.repeat(n_repeats) # for traindataset = dataset.map(decode_line)if is_shuffle:dataset = dataset.shuffle(10000) # shuffledataset = dataset.batch(batch_size)return datasetfilename = './s0000025_2.csv'training_dataset = create_dataset(filename, batch_size=5, is_shuffle=True)
iterator = tf.data.Iterator.from_structure(training_dataset.output_types,training_dataset.output_shapes)
features, labels = iterator.get_next()
training_init_op = iterator.make_initializer(training_dataset)
sess = tf.Session()
sess.run(training_init_op)
print("TRAIN\n",sess.run([features,labels]))
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