tensorflow读取csv文件及搭建神经网络训练

最新推荐文章于 2024-01-21 13:54:38 发布

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最新推荐文章于 2024-01-21 13:54:38 发布 · 6.3k 阅读

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1.读取csv文件

import tensorflow as tf  
# 生成一个先入先出队列和一个QueueRunner,生成文件名队列 
def read_batch(filenames,batchsize):
    
    #filenames = ['mer_test/test_set.csv']  
    filename_queue = tf.train.string_input_producer(filenames, shuffle=False)  
    # 定义Reader  
    reader = tf.TextLineReader()  
    key, value = reader.read(filename_queue)  
    # 定义Decoder  
    record_defaults = [[0.0] for _ in range(65)] 
    data= tf.decode_csv(value,record_defaults=record_defaults)  
    
    features=data[1:65]
    #features=(features-tf.reduce_min(features))/(tf.reduce_max(features)-tf.reduce_min(features))
    label=data[0]
    label=tf.cast(label,dtype=tf.uint8)
    label=tf.one_hot(label,2)
    features_batch, label_batch = tf.train.batch([features,label], batch_size=batchsize, capacity=3*batchsize,)  
    return features_batch, label_batch
#测试是否正确读取
if __name__=='__main__':
    filenames = ['test_set.csv'] 
    example_batch, label_batch=read_batch(filenames,2)    
    # 运行Graph