lakshayg / tensorflow-build-archived Goto Github PK

I'd be grateful for MacOS builds. Thanks!

When i want to use tensorflow on my raspberry pi 1, I have the following problem:
/usr/lib/python3.5/importlib/_bootstrap.py:222: RuntimeWarning: compiletime version 3.4 of module 'tensorflow.python.framework.fast_tensor_util' does not match runtime version 3.5
return f(*args, **kwds)
/usr/lib/python3.5/importlib/_bootstrap.py:222: RuntimeWarning: builtins.type size changed, may indicate binary incompatibility. Expected 432, got 412
return f(*args, **kwds)

I have Python 3.5.3 and i install tensorflow (1.11) with the following command:
sudo python3 -m pip install --no-cache-dir tensorflow

I cant use your builds, because i have raspbian not ubuntu:( and when i try to use the linux version, i got this:
tensorflow-1.11.0-cp35-cp35m-linux_x86_64.whl is not a supported wheel on this platform.

Thx for the help!

since py36 has more and more adoption, would you please also provide a release?

When I running demo of model/research/slim,

scripts/finetune_inception_resnet_v2_on_flowers.sh: line 73: 90776 Illegal instruction: 4 python train_image_classifier.py --train_dir=${TRAIN_DIR} --dataset_name=flowers --dataset_split_name=train --dataset_dir=${DATASET_DIR} --model_name=${MODEL_NAME} --checkpoint_path=${PRETRAINED_CHECKPOINT_DIR}/${MODEL_NAME}.ckpt --checkpoint_exclude_scopes=InceptionResnetV2/Logits,InceptionResnetV2/AuxLogits --trainable_scopes=InceptionResnetV2/Logits,InceptionResnetV2/AuxLogits --max_number_of_steps=1000 --batch_size=32 --learning_rate=0.01 --learning_rate_decay_type=fixed --save_interval_secs=60 --save_summaries_secs=60 --log_every_n_steps=10 --optimizer=rmsprop --weight_decay=0.00004

Just letting you know that the windows link supports up to 1.8 and works very well on my machine.

is it possible to install the Ubuntu build on my Arch system or do I need to compile it myself?

I use tf 1.8 osx 10.13.4 High Sierra

Python 3.6.5 (default, Mar 30 2018, 06:41:53) 
[GCC 4.2.1 Compatible Apple LLVM 9.0.0 (clang-900.0.39.2)] on darwin

First I got
Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
then I install https://github.com/lakshayg/tensorflow-build/raw/master/tensorflow-1.8.0-cp36-cp36m-macosx_10_7_x86_64.whl which fit my env.

The whl fix AVX2 FMA but when I run another code in pycharm ,sth strange happen I only get Process finished with exit code 132 (interrupted by signal 4: SIGILL) without any traceback

Finally because I use virtualenv , I remove it and install the requirements again. Run my code and get great result.So it's not the code error. After install the whl ,the code crash after open tf.session. But I don't know why.

code:

import numpy as np
import tensorflow as tf
from sklearn.datasets import fetch_california_housing
from sklearn.preprocessing import StandardScaler

housing = fetch_california_housing()
m, n = housing.data.shape
housing_data_plus_bias = np.c_[np.ones((m, 1)), housing.data]


scaler = StandardScaler()
scaled_housing_data = scaler.fit_transform(housing.data)
scaled_housing_data_plus_bias = np.c_[np.ones((m, 1)), scaled_housing_data]

n_epochs = 1000
learning_rate = 0.01

X = tf.constant(scaled_housing_data_plus_bias, dtype=tf.float32, name="X")
y = tf.constant(housing.target.reshape(-1, 1), dtype=tf.float32, name="y")
theta = tf.Variable(tf.random_uniform([n + 1, 1], -1.0, 1.0, seed=42), name="theta")
y_pred = tf.matmul(X, theta, name="predictions")
error = y_pred - y
mse = tf.reduce_mean(tf.square(error), name="mse")
gradients = 2 / m * tf.matmul(tf.transpose(X), error)
training_op = tf.assign(theta, theta - learning_rate * gradients)

init_var = tf.global_variables_initializer()

with tf.Session() as sess:
    # sess.run(init_var)
    init_var.run()
    for epoch in range(n_epochs):
        if epoch % 100 == 0:
            print("Epoch", epoch, "MSE =", mse.eval())
        sess.run(training_op)

    best_theta = theta.eval()

print(best_theta)

result:

2018-05-17 17:07:28.075427: I tensorflow/core/platform/cpu_feature_guard.cc:140] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
Epoch 0 MSE = 2.7544262
Epoch 100 MSE = 0.632222
Epoch 200 MSE = 0.5727805
Epoch 300 MSE = 0.5585007
Epoch 400 MSE = 0.54907
Epoch 500 MSE = 0.542288
Epoch 600 MSE = 0.53737885
Epoch 700 MSE = 0.533822
Epoch 800 MSE = 0.5312425
Epoch 900 MSE = 0.5293705
[[ 2.06855226e+00]
 [ 7.74078071e-01]
 [ 1.31192386e-01]
 [-1.17845066e-01]
 [ 1.64778143e-01]
 [ 7.44081801e-04]
 [-3.91945131e-02]
 [-8.61356556e-01]
 [-8.23479712e-01]]

Process finished with exit code 0

This worked great! Thanks
(python 3.6.6
tf 1.9.0
ubuntu 16.04)

I am still seeing one message:
Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX512F
Do you think you could incorporate one as well?
(PS using AWS instances, so this might be useful for a few more people).

Thank you for sharing your builds.

When I try the whl created for issue #53 my system complains about wanting 1.13. I noticed the actual file name is tensorflow-1.12.0-..... , so might that be an issue ? I already have a working 1.13 install on ubun5u 16.04, and can run GPT-2 on both CPU and GPU but I do want the FMA AVX support since model is too big to train on my existing GPU but does train on the CPU (slowly).

tensorflow-gpu 1.13.1 has requirement tensorboard<1.14.0,>=1.13.0, but you'll have tensorboard 1.12.2 which is incompatible.

I was using :

python3 -m pip install --ignore-installed --upgrade "https://github.com/lakshayg/tensorflow-build/releases/download/tf1.13.0-ubuntu16.04-py3-avx512f/tensorflow-1.12.0-cp35-cp35m-linux_x86_64.whl"

Hello,

I'm getting an Illegal instruction: 4 error message when running tensorflow from the two (python 2.7.13 and 3.6.1) wheels on macOS Sierra (10.12.5).

Any ideas on what the problem might be? According to this SO answer this is due to running on an older system than used to compile, but I'm using the latest (non-beta) OS.

Could it be that my system does not support AVX2?

Thanks!

I am use TF in docker, the wheel should be installed in host or docker environment?
Please help me, thanks!

I get this error message

BadZipfile: File is not a zip file

when trying to install following wheel:
tensorflow-1.2.0rc1-cp27-cp27mu-linux_x86_64.whl

Hi. i miserably failed at installing from binary. Would be great if you could commit a wheel. This is for MacBook pro 2017 running macOS High Sierra (10.13.1) and Python 3.6.3.
Thanks
Steffen

Look forward an update!

Thank you so much.

This is fantastic! I spent two days trying to compile TensorFlow on my one to no avail - these precompiled files were a lifesaver!

I wanted to ask about a couple things (for Mac):

Any plans to add AVX512F?
Can MKL support be added too (for all builds)?

Thanks,

• Lee

Hi I am new to tensorflow, and wonder if there is a pre-build tensorflow (CPU) 1.9.0 for Ubuntu 18.04, Python 3.6.5

Thanks

After installing your library for ubuntu 16.04, python 2.7, I got this error

On compiling cnn_face.py -

Traceback (most recent call last):
File "cnn_face.py", line 12, in
import tensorflow as tf
File "/usr/local/lib/python2.7/dist-packages/tensorflow/init.py", line 24, in
from tensorflow.python import *
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/init.py", line 63, in
from tensorflow.python.framework.framework_lib import *
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/framework_lib.py", line 102, in
from tensorflow.python.framework.importer import import_graph_def
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/importer.py", line 30, in
from tensorflow.python.framework import function
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/function.py", line 32, in
from tensorflow.python.ops import array_ops
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/array_ops.py", line 97, in
from tensorflow.python.ops import gen_array_ops
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/gen_array_ops.py", line 8, in
from tensorflow.python.eager import execute as _execute
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/eager/execute.py", line 29, in
from tensorflow.python.eager import tape
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/eager/tape.py", line 23, in
from autograd import container_types
ImportError: cannot import name container_types

Can you please add binaries for the specified version? Thanks.

Can you please build for Mojave? Thanks!
https://github.com/tensorflow/tensorflow/releases

Could you compile this for Ubuntu 16.04?

1.12.0 | CPU | Ubuntu 18.04 | 7.3 | 3.6.5 | FMA, AVX2, AVX512F | Download

It requires Glibc 2.27, but I'm only able to compile glibc 2.23 on this old Redhat 6.1 system.

Currently I'm able to use

1.10.0 | CPU | Ubuntu 16.04 | 5.4 | 3.6.6 | FMA, AVX, AVX2, SSE4.1, SSE4.2, AVX512F | Downlod

I suppose if it could be run on Ubuntu 16.04, I can get it working on my system.

Other options don't include AVX512F which the CPUs support. And I want to use Python 3.

BTW, I'm able to use conda build of Tensorflow 1.12. But they don't enable all the CPU features.

I use MacOS High sierra with Python 3.6 and have G4560 without AVX support.
I would like to use one of the latest versions of Tensorflow.

Supports FMA, AVX, AVX2, SSE4.1, SSE4.2 Means CPU
must support all these: FMA, AVX, AVX2, SSE4.1, SSE4.2 can run the tensorflow-1.12.0-cp36-cp36m-linux_x86_64.whl.
if the cpu only support SSE4.1, SSE4.2 ,can not run the tensorflow-1.12.0-cp36-cp36m-linux_x86_64.whl?

hi， first thanks for your sharing.
are these tensorflows gpu version?
i test the tensorflow-1.4.0, and it is cpu version. do you have gpu version?

Hello,

I'm using your 1.2.1 MacOS build but now I'm running into random version problems with tensorboard. I'd like to try 1.4.1 but the mac-mini does not support AVX2 . Can you build a 1.4.1 to that spec? Or, send me a link on how to build one myself?

Many thanks!

I am receeving this following error while installing tensorflow-build.
I am using Ubuntu 18.04 with tensorflow -1.9.0

pip install --ignore-installed --upgrade /home/ifm-veeresh/Downloads/tensorflow-1.9.0-cp36-cp36m-linux_x86_64.whl --user tensorflow-1.9.0-cp36-cp36m-linux_x86_64.whl is not a supported wheel on this platform.

I tried to compile tensorflow 1.2.1 with avx and sse options for macOS but it produces the whl file for 2.7 version of python. And I need 3.6 version. Is it possible to so?

Hello,

Very cool project, I use it a lot.

Unfortunately, It seems that the link in this row is broken:

Package name: tensorflow-1.12.0-cp35-cp35m-linux_x86_64.whl

The table says it's for python 3.6 but the package name says cp35, i.e. CPython 3.5. Also, the version in the package name doesn't match the version in "TF" column. It's 1.12.0 but should be 1.13.0.

I hope it is easy to fix and I look forward to a corrected link 'cause it would be really nice to use it in our projects!

Cheers,
Denis

The packages can be installed via e.g.

pip install https://raw.githubusercontent.com/lakshayg/tensorflow-build/master/tensorflow-1.4.0rc1-cp36-cp36m-linux_x86_64.whl

perhaps this should be the recommended method for the readme, or at least an option?

Hi

I have installed tensorflow-1.4.1-cp27-cp27m-macosx_10_12_intel.whl in a macOS sierra successfully, however it seems that it makes everything slow down, when I run a handwritten digit recognition script it seems that it gets held... never finish, previously it was working and I was just getting the warning about "Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA"

I did the same for a PC wth ubuntu 16.04 installing tensorflow-1.6.0-cp27-cp27mu-linux_x86_64.whl and have the same issue it seems that it gets held... never finish

How can I uninstall this application?

thanks
Aaron

Hello is there any binary file for mac os 10.14 with python3.6? The one with 2.7 doesn't work and 3.7 file seems to be for 10.13 instead of 10.14 and under a wrong file name.

Could you add this one with FMA, AVX2, AVX512F, it's already on Mojave.

Thanks in advance

I am getting this error while installing tensorflow on a system with anaconda (python 2.7) + p6000 GPUs + Cuda 8 + Cudnn 7.5 .

https://github.com/tensorflow/tensorflow/releases/tag/v1.9.0

Hi,

Is it possible to add a custom build for Raspbian Stretch?
I work a lot with Raspberry pi and it would be nice to have a way of installing TensorFlow considering the specs of these microcomputers.

Thanks

Gave a lot of problems
mainly libstdc++.so.6: version GLIBCXX_3.4.22' not found also libstdc++.so.6: version GLIBCXX_3.4.21' not found

GLIBCXX_3.4.21 got resolved when when I tried
LD_PRELOAD="/usr/lib/x86_64-linux-gnu/libstdc++.so.6" python jncpy/dee2keras.py

then GLIBCXX_3.4.22 appeared
I took a risk and installed based on
https://askubuntu.com/questions/746369/how-can-i-install-and-use-gcc-6-on-xenial
sudo add-apt-repository ppa:ubuntu-toolchain-r/test
sudo apt-get update
sudo apt-get install gcc-6 g++-6

Lakshay Garg great job
Only please mention the GCC requirements as even on 16.04 gcc 5.4 is default

If possible plaese do another build on a clean install ubuntu 16.04 with all standard defaults
then more people will be benefited

Also installation command may be mentioned
pip install --ignore-installed --upgrade ~/Downloads/tensorflow-1.1.0-cp36-cp36m-linux_x86_64.whl

My cpu support avx and avx2, but not avx512f. I build tensorflow myself. And tensorflow works well, but tensorboard still report the following error:

2019-02-04 07:39:40.286677: F tensorflow/core/platform/cpu_feature_guard.cc:37] The TensorFlow library was compiled to use AVX512F instructions, but these aren't available on your machine.

I have two questions.

1. How can I set cpu feature support when building tensorflow? I think it is configured automatically when building on my platform.
2. How can I control tensorboard version? tensorboard is collected when installing tensorflow whl file. Is it possible that tensorflow is suitable for my cpu(avx and avx2 but not avx512f) but tensorboard is not suitable for my cpu?

Not an issue but an observation.
First, many thanks for providing these custom builds!
I have MacOS Mojave, & the specified versions of clang & python. pip3 install as specified failed, but sudo sorted it. I don't know if that was right but it certainly works fine now.

Anyone know if there is any risk if I run the special version of tensorflow supporting AVX2 on a mac while the mac's cpu not supporting AVX2?

Ubuntu 14.04 , conda only has below glibc

    glibc: 2.12.2-3 nlesc                           

Trying this on macOS High Sierra but getting this error:

tensorflow-1.4.1-cp36-cp36m-macosx_10_13_x86_64.whl is not a supported wheel on this platform.

Could you please upload Tensorflow 1.12 for MacOS Hight Sierra & Ubuntu 18?

I wish to create a custom build of tensorflow.js but to I need SSE4.1 and SSE4.2 bindings. Will these port to tensorflow.js. If not, can you suggest a method?

And Mojave is actually macOS version 10.14.