如何使用tf.decode_csv在tensorflow中解码长行的csv文件? [英] How to decode a csv file with long lines in tensorflow with tf.decode_csv?

问题描述

如何使用tf.TextLineReader()和tf.decode_csv对行较长的 csv 文件进行解码(例如，每行包含很多项，以至于不现实地将它们逐一列出以进行输出)?

How to decode a csv file with long lines(e.g., with many items per line so as not realistic to list them one by one for output) with tf.TextLineReader() and tf.decode_csv?

典型用法是:

reader = tf.TextLineReader()    
key, value = reader.read(filename_queue)    
record_defaults = [1,1,1,1,1]    
a,b,c,d,e =  tf.decode_csv(records=value,record_defaults=record_defaults, field_delim=" ")

当一行中有成千上万个项目时，不可能像上面的(a，b，c，d，e)一样逐一分配它们，是否可以将所有项目解码为列表或类似内容?

When we have thousands of items in a line, it's impossible to assign them one by one as (a,b,c,d,e) above, can all the items be decoded to a list or something like that?

推荐答案

假设您有1800列数据.您可以将其用作记录默认值:

Lets say you have 1800 columns of data. You can use this as record default:

record_defaults=[[1]]*1800

然后使用

all_columns = tf.decode_csv(value, record_defaults=record_defaults)

阅读它们.

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