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A few more for your selection, - Bloated build system that is near impossible to get working - who even uses maven ?! Pytorch/Caffe are super-simple to build i

A few more for your selection, - Bloated build system that is near impossible to get working - who even uses maven ?! Pytorch/Caffe are super-simple to build in comparison; with Chainer, it's even simple: all you need is pip install (even on exotic ARM devices). - The benefits of all that static analysis simply aren't there. In addition, PyTorch has a jit-compiler which one can argue lets one have their cake and eat it too. - Loops are extremely limited. Okay, we know RNN/LSTMs aren't really TF's thing, but if you venture out to do something out of the ordinary even making it batch-size invariant is difficult. There isn't even a map-reduce op that works without knowing the dimension at compile time. You can hack something together by fooling one of those low level while_loop ops, but that just tells you how silly the whole thing is.

gormanc 9y ago
I love that PyTorch kind of went all-in with anaconda. Building it is so much easier than TF! I'm a recent convert but it's dang good.
- orf 9y ago
  Why not pip?
  - gormanc 9y ago
    For installing it, yeah pip is great too, but for building conda includes third party tools and libraries and stuff. e.g. in order to use the MPI backend for PyTorch's distributed processing you need to build it yourself and conda just makes it a bit easier. That and I had a real bad experience with trying to build Tensorflow (and Bazel) to run on an HPC cluster.
- haeffin 9y ago
  That's a serious point of frustration for me. Having an option to use anaconda, fine. Forcing it on your users, meh. I already have a working system using virtualenv and pip, why force another on me?
0xbear 9y ago
TF doesn’t use Maven. Also, its build system lets you build it for a lot of different platforms in a uniform fashion, and speeds up the development cycle due to fast incremental builds and built in incremental, parallel, multi-language test support.
- throw65554 9y ago
  Very well, Bazel then. I'm sure it's all the rage in the cube-farms, but that doesn't necessarily make one's life easier.

gormanc 9y ago

I love that PyTorch kind of went all-in with anaconda. Building it is so much easier than TF! I'm a recent convert but it's dang good.

orf 9y ago
Why not pip?
- gormanc 9y ago
  For installing it, yeah pip is great too, but for building conda includes third party tools and libraries and stuff. e.g. in order to use the MPI backend for PyTorch's distributed processing you need to build it yourself and conda just makes it a bit easier. That and I had a real bad experience with trying to build Tensorflow (and Bazel) to run on an HPC cluster.
haeffin 9y ago
That's a serious point of frustration for me. Having an option to use anaconda, fine. Forcing it on your users, meh. I already have a working system using virtualenv and pip, why force another on me?

0xbear 9y ago

TF doesn’t use Maven. Also, its build system lets you build it for a lot of different platforms in a uniform fashion, and speeds up the development cycle due to fast incremental builds and built in incremental, parallel, multi-language test support.

throw65554 9y ago
Very well, Bazel then. I'm sure it's all the rage in the cube-farms, but that doesn't necessarily make one's life easier.