import timeit
#檢視執行開始到結束所用的時間
import tensorflow
as tf
import os
defgenerate_tfrecords
(input_filename, output_filename):
print(
"\nstart to convert {} to {}\n".format(input_filename, output_filename))
start_time = timeit.default_timer()
writer = tf.python_io.tfrecordwriter(output_filename)
for line
in open(input_filename,
"r"):
data = line.split(
",")
label = float(data[
9])features = [float(i)
for i
in data[:
9]]
#特徵不要最後一列資料
#將資料轉化為原生 bytes
example = tf.train.example(features=tf.train.features(feature=))
writer.write(example.serializetostring())
#序列化為字串
writer.close()
print(
"successfully convert {} to {}".format(input_filename,
output_filename))
end_time = timeit.default_timer()
print(
"\nthe pretraining process ran for minutes\n".format((end_time - start_time) /
60))
defmain
():
current_path =
"g:/spyder/csv_tfrecords/"
for filename
in os.listdir(current_path):
if filename ==
"siteb.udp_train_unsupervised.csv":
#當前路徑下，需要轉換的csv檔案
generate_tfrecords(current_path+filename, current_path+filename +
".tfrecords")
return current_path+filename +
".tfrecords"
if __name__ ==
"__main__":
import timeit
#檢視執行開始到結束所用的時間
import tensorflow
as tf
import os
defgenerate_tfrecords
(input_filename, output_filename):
print(
"\nstart to convert {} to {}\n".format(input_filename, output_filename))
start_time = timeit.default_timer()
writer = tf.python_io.tfrecordwriter(output_filename)
for line
in open(input_filename,
"r"):
data = line.split(
",")
label = float(data[
9])features = [float(i)
for i
in data[:
9]]
#特徵不要最後一列資料
#將資料轉化為原生 bytes
example = tf.train.example(features=tf.train.features(feature=))
writer.write(example.serializetostring())
#序列化為字串
writer.close()
print(
"successfully convert {} to {}".format(input_filename,
output_filename))
end_time = timeit.default_timer()
print(
"\nthe pretraining process ran for minutes\n".format((end_time - start_time) /
60))
defmain
():
current_path =
"g:/spyder/csv_tfrecords/"
for filename
in os.listdir(current_path):
if filename ==
"siteb.udp_train_unsupervised.csv":
#當前路徑下，需要轉換的csv檔案
generate_tfrecords(current_path+filename, current_path+filename +
".tfrecords")
return current_path+filename +
".tfrecords"
if __name__ ==
"__main__":
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