TensorFlow - 读取CSV格式文件
TensorFlow - 读取CSV格式文件
flyfish
以TensorFlow提供的例子说明
filename_queue = tf.train.string_input_producer(["file0.csv", "file1.csv"])
reader = tf.TextLineReader()
key, value = reader.read(filename_queue)
# Default values, in case of empty columns. Also specifies the type of the
# decoded result.
record_defaults = [[1], [1], [1], [1], [1]]
col1, col2, col3, col4, col5 = tf.decode_csv(
value, record_defaults=record_defaults)
features = tf.stack([col1, col2, col3, col4])
with tf.Session() as sess:
# Start populating the filename queue.
coord = tf.train.Coordinator()
threads = tf.train.start_queue_runners(coord=coord)
for i in range(1200):
# Retrieve a single instance:
example, label = sess.run([features, col5])
coord.request_stop()
coord.join(threads)API说明concat
代码示例
import tensorflow as tf
t1 = [[1, 2, 3],[4, 5, 6]]
t2 = [[7, 8, 9],[10, 11, 12]]
result =(tf.concat( [t1,t2],0))
sess = tf.Session()
print(sess.run(result)) tf.concat( [t1,t2],0)的结果是
[[ 1 2 3]
[ 4 5 6]
[ 7 8 9]
[10 11 12]]
tf.concat( [t1,t2],1)的结果是
[[ 1 2 3 7 8 9]
[ 4 5 6 10 11 12]]
API说明stack
代码示例
import tensorflow as tf
x =[1, 2]
y= [3, 4]
z= [5, 6]
result =tf.stack([x, y, z],0)
sess = tf.Session()
print(sess.run(result)) tf.stack([x, y, z],0)的结果是
[[1 2]
[3 4]
[5 6]]
tf.stack([x, y, z],1)的结果是
[[1 3 5]
[2 4 6]]
To read text files in comma-separated value (CSV) format, use a
tf.TextLineReader with the tf.decode_csv operation.
读取CSV格式的文本文件， 需要使用TextLineReader和decode_csv 操作
Each execution of read reads a single line from the file. The
decode_csv op then parses the result into a list of tensors. The
record_defaults argument determines the type of the resulting >tensors and sets thedefault value to use if a value is missing in the >input string.
每次执行read都会从文件中读取一行内容， decode_csv 操作会将内容解析到张量列表。record_default参数决定了结果的张量的类型，并设置了如果在输入字符串中缺失值时的默认值。
You must call tf.train.start_queue_runners to populate the queue
before you call run or eval to execute the read. Otherwise read will
block while it waits for filenames from the queue.
你必须在调用run或者eval去执行read之前， 调用tf.train.start_queue_runners来填充队列。否则read操作会阻塞。