I am learning tesnorflow from this blog:
http://www.wildml.com/2015/12/implementing-a-cnn-for-text-classification-in-tensorflow/
The code i am running is :
https://github.com/dennybritz/cnn-text-classification-tf/blob/master/train.py
I have installed tensorflow from sourcse in a virtual enviroment,in CPU only enviroment using followinbg bazel build command: bazel build --config=mkl ...
here is the exact error:
"2018-01-16 03:15:27.783040: F tensorflow/core/kernels/mkl_maxpooling_op.cc:157] Check failed: dnnPoolingCreateForward_F32( &prim_pooling_fwd, primAttr, algorithm, lt_user_input, params.kernel_size, params.kernel_stride, params.in_offset, dnnBorderZerosAsymm) == E_SUCCESS (-127 vs. 0)
Aborted
"
I have debugged error to the line where sess.run is written, i have beleived it has something to do it mkl_maxpooling, as i had installed tensorflow with mkl optimization of INTEL cpu's
Given below are the steps that I followed:
Build tensorflow 1.4 from source with mkl as mentioned in the question
Cloned the git repo "https://github.com/dennybritz/cnn-text-classification-tf.git"
Ran "python train.py" from "cnn-text-classification-tf" directory(created from git clone)
Code ran without any errors. So it seems like the tensorflow was not properly built from the source. Please confirm that there were no errors while building tensorflow from source.
Related
I'm trying to build the tensorflow lite for 'arm64-v8a' with linux on an amd64 with linux.I follow the guide to build the library libtensorflow-lite.a.but i found there remains a long tail of TensorFlow ops that are not yet natively supported by TensorFlow Lite,so i want Select TensorFlow operators to use in TensorFlow Lite. from the guide i should Recompile the library, I use the command bazel build -c opt //tensorflow/lite:libtensorflowlite.so --cpu=arm64-v8a, I got the following error:
/home/wang/.cache/bazel/_bazel_wang/c72f4772665ac4cb0690414b07635968/external/local_config_cc/BUILD:45:1: in cc_toolchain_suite rule #local_config_cc//:toolchain: cc_toolchain_suite '#local_config_cc//:toolchain' does not contain a toolchain for cpu 'arm64-v8a'
I'm new to bazel and cannot find a detailed walkthrough.what should i do?
The objective of my experiment is to build tensorflow on Jetson TK1 arm based embedded board. Since pre-builts of tensorflow for arm architecture are not given by the official releases, I was forced to the option of building it from source.
To build tensorflow, we need Bazel which should be also build from source. Now I got stuck here, not able to build bazel at all.
I have referred various blogs and github projects and tried to follow the instructions everyone said it worked for them.
1) Tensorflow on Raspberry-pi
2) Jetson Hacks building Tensorflow from source
3) Official Documentation
Steps Followed:
$ sudo apt-get install build-essential openjdk-8-jdk python zip
$ wget https://github.com/bazelbuild/bazel/releases/download/0.4.5/bazel-0.4.5-dist.zip
$ unzip -d bazel bazel-0.4.5-dist.zip
$ cd bazel
$ sudo ./compile.sh
Error Log:
ERROR: /build/bazel/src/main/protobuf/BUILD:25:2: Java compilation in rule '//src/main/protobuf:extra_actions_base_java_proto' failed: Worker process sent response with exit code: 1.
java.lang.InternalError: Cannot find requested resource bundle for locale en_US
at com.sun.tools.javac.util.JavacMessages.getBundles(JavacMessages.java:128)
at com.sun.tools.javac.util.JavacMessages.getLocalizedString(JavacMessages.java:147)
at com.sun.tools.javac.util.JavacMessages.getLocalizedString(JavacMessages.java:140)
at com.sun.tools.javac.util.Log.localize(Log.java:673)
at com.sun.tools.javac.util.Log.printLines(Log.java:485)
at com.sun.tools.javac.api.JavacTaskImpl.handleExceptions(JavacTaskImpl.java:156)
at com.sun.tools.javac.api.JavacTaskImpl.doCall(JavacTaskImpl.java:93)
at com.sun.tools.javac.api.JavacTaskImpl.call(JavacTaskImpl.java:87)
at com.google.devtools.build.buildjar.javac.BlazeJavacMain.compile(BlazeJavacMain.java:104)
at com.google.devtools.build.buildjar.SimpleJavaLibraryBuilder$1.invokeJavac(SimpleJavaLibraryBuilder.java:163)
at com.google.devtools.build.buildjar.ReducedClasspathJavaLibraryBuilder.compileSources(ReducedClasspathJavaLibraryBuilder.java:52)
at com.google.devtools.build.buildjar.SimpleJavaLibraryBuilder.compileJavaLibrary(SimpleJavaLibraryBuilder.java:166)
at com.google.devtools.build.buildjar.SimpleJavaLibraryBuilder.run(SimpleJavaLibraryBuilder.java:178)
at com.google.devtools.build.buildjar.BazelJavaBuilder.processRequest(BazelJavaBuilder.java:90)
at com.google.devtools.build.buildjar.BazelJavaBuilder.runPersistentWorker(BazelJavaBuilder.java:67)
at com.google.devtools.build.buildjar.BazelJavaBuilder.main(BazelJavaBuilder.java:44)
Caused by: java.util.MissingResourceException: Can't find bundle for base name com.google.errorprone.errors, locale en_US
at java.util.ResourceBundle.throwMissingResourceException(ResourceBundle.java:1573)
at java.util.ResourceBundle.getBundleImpl(ResourceBundle.java:1396)
at java.util.ResourceBundle.getBundle(ResourceBundle.java:854)
at com.sun.tools.javac.util.JavacMessages.lambda$add$0(JavacMessages.java:106)
at com.sun.tools.javac.util.JavacMessages.getBundles(JavacMessages.java:125)
... 15 more
Target //src:bazel failed to build
INFO: Elapsed time: 291.995s, Critical Path: 258.92s
ERROR: Could not build Bazel
To make sure the error is independent of the architecture, I have tried to build Bazel in x86_64 PC. Even there I am getting the same error. I have seen people created the similar issue in bazel github group, none solved.
Version 0.4.5 is very old. We just released 0.12.0, could you try that one?
I'm new to Tensorflow.
I am using a 64 bit version of Windows 10 and I would like to install Tensorflow for the CPU.
I don't remember the exact steps that I followed to install it, however when I checked for the installation using:
import tensorflow as tf
hello = tf.constant('Hello, TensorFlow!')
sess = tf.Session()
print(sess.run(hello))
I have the following output:
2017-10-18 09:56:21.656601: W C:\tf_jenkins\home\workspace\rel-win\M\windows\PY\36\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX instructions, but these are available on your machine and could speed up CPU computations.
2017-10-18 09:56:21.656984: W C:\tf_jenkins\home\workspace\rel-win\M\windows\PY\36\tensorflow\core\platform\cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX2 instructions, but these are available on your machine and could speed up CPU computations.
b'Hello, TensorFlow!'
I am running python in Sublime Text 3 using the package SublimeREPL.
I tried to search these errors and found out that it means that the tensorflow is built without these instructions which could improve performances for the CPU. I also found the code to hide these warnings, but I actually I want to use these instructions.
The code that I found that enables this is:
bazel build -c opt --copt=-mavx --copt=-mavx2 --copt=-msse4.2 --copt=-msse4.1 --copt=-msse3 --copt=-mfma -k //tensorflow/tools/pip_package:build_pip_package
but I got this output:
ERROR: Skipping '//tensorflow/tools/pip_package:build_pip_package': no such package 'tensorflow/tools/pip_package': BUILD file not found on package path.
WARNING: Target pattern parsing failed. Continuing anyway.
INFO: Found 0 targets...
ERROR: command succeeded, but there were errors parsing the target pattern.
INFO: Elapsed time: 8,147s, Critical Path: 0,02s
How can I solve this problem?
Lastly, I don't understand what pip, wheel and bazel are so I need a step by step instructions.
Thank you a lot!
if you want to download TensorFlow source, compile+install, use this link. If you want to download binaries, then use this link.
Whenever I run any script using Tensor Flow, I get the following warnings:
The TensorFlow library wasn't compiled to use SSE instructions, but
these are available on your machine and could speed up CPU
computations
I tried to follow the method posted on this stack overflow post and entered the following command on the command line:
bazel build -c opt --copt=-mavx --copt=-mavx2 --copt=-mfma --copt=-mfpmath=both --copt=-msse4.2 --config=cuda -k //tensorflow/tools/pip_package:build_pip_package
However I get the following error
The 'build' command is only supported from within a workspace.
How do I solve this error and then make the tensor flow compile using SSE instructions
The Installing Tensorflow from Sources page explains the procedure pretty well, make sure you have all the requirements met before running the build step.
If you wish to automate the ./configure (tensorflow-cpu) step you can run the following command from TF's root directory:
# CPU default configuration
tensorflow/tools/ci_build/builds/configured CPU
and then run the build command with native optimization:
# build with native optimization
bazel build -c opt --copt=-march=native tensorflow/tools/pip_package:build_pip_package
I am trying to run to get R + deepwater + tensorflow to work on a MBP.
The following have been installed.
Python 3.6.1
TensorFlow 1.1
The Hello, TensorFlow example on the TensorFlow website is working fine.
R version 3.4.0
curl -O http://h2o-release.s3.amazonaws.com/h2o/master/3904/R/src/contrib/h2o_3.11.0.3904.tar.gz
R CMD INSTALL h2o_3.11.0.3904.tar.gz
curl -O http://s3.amazonaws.com/h2o-deepwater/public/nightly/latest/h2o_3.11.0.tar.gz
R CMD INSTALL h2o_3.11.0.tar.gz
I am trying run the following example provided on the h2o website.
require(h2o)
h2o.init()
train <- h2o.importFile("https://h2o-public-test-data.s3.amazonaws.com/bigdata/laptop/mnist/train.csv.gz")
target <- "C785"
features <- setdiff(names(train), target)
train[target] <- as.factor(train[target])
model <- h2o.deepwater(x=features, y=target, training_frame=train, epochs=100, activation="Rectifier",
hidden=c(200,200), ignore_const_cols=FALSE, mini_batch_size=256, input_dropout_ratio=0.1,
hidden_dropout_ratios=c(0.5,0.5), stopping_rounds=3, stopping_tolerance=0.05,
stopping_metric="misclassification", score_interval=2, score_duty_cycle=0.5, score_training_samples=1000,
score_validation_samples=1000, nfolds=5, gpu=FALSE, seed=1234, backend="tensorflow")
The error I get is Error: java.lang.RuntimeException: Unable to initialize backend: Cannot find TensorFlow native library for OS: darwin, architecture: x86_64. Based on what I read on SO and the git page, I was under the impression that one does not need to build for the Mac platform.
One other thing that I tried was to use the info from https://github.com/rstudio/tensorflow. When I run install_tensorflow() I get Error: Prerequisites for installing TensorFlow not available. Please help!
We don't provide H2O+deepwater builds for MacOS. The one you downloaded is built for Linux machines (tested on Ubuntu), it's mentioned on the download page.
If you want to run it on MacOS you'd have to build both DeepWater and then H2O yourself.