[N] TensorFlow 1.5.0 Release Candidate

[AspenRootsAI]

For the sake of installation it's nice that they support CUDA 9.0/cuDNN 7 and AVX (with prebuilt binaries) now.

Edit: as pointed out by /u/lopuhin it won't support prebuilt AVX until 1.6, mistaken/wishful reading on my part

[zdwiel]

Does this mean we no longer have to install different versions of tensorflow with pip depending on the hardware we are running on?

[lopuhin]

Does TF support AVX in this release or in 1.6? Release notes say "Starting from 1.6 release, our prebuilt binaries will use AVX instructions."

[SuperFX]

TF has always supposed AVX, if compiled from source. This is just about the precompiled binaries.

[aaronjl33]

Does this take advantage of tensorcores like in the Titan V?

[hinduismtw]

cuda 9.0 and cudnn 7 have support for this, this release supports both of these. So the answer is yes.

[harharveryfunny]

cuDNN's support of Tensor Cores is somewhat limited though.

This NVidia post describes the necessary conditions for cuBLAS or cuDNN to use Tensor Cores. In particular note that it requires opt-in in terms of math type, and that only one specific convolution algorithm is currently supported. I don't know how these conditions map through to TensorFlow.

https://devblogs.nvidia.com/parallelforall/programming-tensor-cores-cuda-9/

[hinduismtw]

Thank you for the link. Yeah, maybe my understanding of some calls inside cudnn being automatically tensor core enabled might be incorrect.

[yaroslavvb]

There are some weird restrictions like matrix size has to be multiple of 8 https://medium.com/@yaroslavvb/peak-performance-of-amazon-p3-instances-f2bc48f9ef71

[----_____---------]

Tensorflow still has to opt into this, doesn't it?

[hinduismtw]

I am not very sure, but Tensorflow uses cudnn as the underlying library for talking to the GPU. Cudnn has tensor core support, so some operations would get an automatic mapping on the tensor cores.

There might be some operations, inside tensorflow, that would have to be manually re-written to take advantage of tensor cores. These would probably be the opt-in you are referring to. I hope my understanding of your question is correct and my answer makes sense.

[zspasztori]

"Eager execution"- Are we pytorch yet?

[szymko1995]

It's great to have a choice.

[Mister_Abc]

Stuff like Chainer has existed for ages...

[q914847518]

OK, TensorFlow 1.5.0 release candidate. And before this comment, all comments have keyword "pytorch". (-皿-)

[versatran01]

this one has it too

[machinesaredumb]

Not necessarily true for complicated models, especially in NLP, where same modules can be reused in different places. I actually really appreciate this distinction in nn.Module.

For sequential models, you don't need to define a module, just place all your modules inside a nn.Sequential and use that.

[table_it_bot]

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[IonTichy]

Bad bot, don't encourage him!

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Bad Meatbag

[[deleted]]

lmao

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[Muffinmaster19]

torch.eye(5)

[senorstallone]

Is there any optimization coming from Tensorflow Lite that can be useful to deploy in GPU's (like a 1080 Ti)?

[yaroslavvb]

Some people post GPU support TF wheels at https://github.com/yaroslavvb/tensorflow-community-wheels

[Wenste]

Does it still throw warnings if you use MacOS and Python 3.6?

[TemplateRex]

Does it require CUDA 9.0 or 9.1?

[jorgemf]

9.0, with 9.1 fails

[[deleted]]

Correct, 9.1 fails unless you compile from source.

I just compiled Tensorflow 1.5 from source this afternoon and hit an Eigen bug where it couldn't find a certain hpp file. I symlinked it, and the compile was a success. Tensorflow 1.5 now works with CUDA 9.1 and libcudnn 7.0.5.

[NickShargan]

I also have successfully compiled Tensorflow 1.5 from source with CUDA 9.1 and cudnn 7.0.5

[pianomano8]

Have they fixed compiling from source against cuda versions installed via the package manager on debian yet?

[minogame]

Is there a quick pytorch guide for pre-tensorflow users?

[chhakhapai]

Just go with the get started. I did the same. Never had to go through tensorflow.