使用带有大量压缩文本文件(1000多个文件,大小在100MB和1.5GB之间)的TextIO.Read转换,我们有时会收到以下错误:
java.util.zip.ZipException: too many length or distance symbols at
java.util.zip.InflaterInputStream.read(InflaterInputStream.java:164) at
java.util.zip.GZIPInputStream.read(GZIPInputStream.java:117) at
java.io.BufferedInputStream.fill(BufferedInputStream.java:246) at
java.io.BufferedInputStream.read1(BufferedInputStream.java:286) at
java.io.BufferedInputStream.read(BufferedInputStream.java:345) at
java.io.FilterInputStream.read(FilterInputStream.java:133) at
java.io.PushbackInputStream.read(PushbackInputStream.java:186) at
com.google.cloud.dataflow.sdk.runners.worker.TextReader$ScanState.readBytes(TextReader.java:261) at
com.google.cloud.dataflow.sdk.runners.worker.TextReader$TextFileIterator.readElement(TextReader.java:189) at
com.google.cloud.dataflow.sdk.runners.worker.FileBasedReader$FileBasedIterator.computeNextElement(FileBasedReader.java:265) at
com.google.cloud.dataflow.sdk.runners.worker.FileBasedReader$FileBasedIterator.hasNext(FileBasedReader.java:165) at
com.google.cloud.dataflow.sdk.util.common.worker.ReadOperation.runReadLoop(ReadOperation.java:169) at
com.google.cloud.dataflow.sdk.util.common.worker.ReadOperation.start(ReadOperation.java:118) at
com.google.cloud.dataflow.sdk.util.common.worker.MapTaskExecutor.execute(MapTaskExecutor.java:66) at
com.google.cloud.dataflow.sdk.runners.worker.DataflowWorker.executeWork(DataflowWorker.java:204) at
com.google.cloud.dataflow.sdk.runners.worker.DataflowWorker.doWork(DataflowWorker.java:151) at
com.google.cloud.dataflow.sdk.runners.worker.DataflowWorker.getAndPerformWork(DataflowWorker.java:118) at
com.google.cloud.dataflow.sdk.runners.worker.DataflowWorkerHarness$WorkerThread.call(DataflowWorkerHarness.java:139) at
com.google.cloud.dataflow.sdk.runners.worker.DataflowWorkerHarness$WorkerThread.call(DataflowWorkerHarness.java:124) at
java.util.concurrent.FutureTask.run(FutureTask.java:266) at
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142) at
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617) at
java.lang.Thread.run(Thread.java:745)
在线搜索相同的ZipException,只会导致此回复:
当热部署程序在将应用程序完全复制到deploy目录之前尝试部署应用程序时,通常会发生Zip文件错误.如果复制文件需要几秒钟,这是相当常见的.解决方案是将文件复制到与应用程序服务器相同的磁盘分区上的临时目录,然后将该文件移动到deploy目录.
有没有其他人遇到类似的例外？或者无论如何我们可以解决这个问题？
我正在按照"Deep MNIST for Experts"教程,https: //www.tensorflow.org/versions/r0.11/tutorials/mnist/pros/index.html#deep-mnist-for-experts
使用卷积神经网络,我得到93.49%的准确率.这实际上很低,我正在努力改进它,但我有一个疑问.根据教程,
for i in range(20000):
batch = mnist.train.next_batch(50)
if i%100 == 0:
train_accuracy = accuracy.eval(feed_dict={x:batch[0], y_: batch[1], keep_prob: 1.0})
print("step %d, training accuracy %g"%(i, train_accuracy))
train_step.run(feed_dict={x: batch[0], y_: batch[1], keep_prob: 0.5})
在每100次迭代之后记录列车精度并且看到准确性,它保持振荡,如增加然后减少.
step 100, training accuracy 0.1
step 200, training accuracy 0.13
step 300, training accuracy 0.12
step 400, training accuracy 0.08
step 500, training accuracy 0.12
step 600, training accuracy 0.05
step 700, training accuracy 0.09
step 800, training accuracy 0.1
step 900, …