Hello everyone, I am building my firsts deep-learning based projects and i just noticed that pytorch 2.0 is officially available. I started to learn tensorflow a while ago, but i have heard that pytorch is one of the most popular DL frameworks out there besides tf. Which one you guys prefer and why?

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SpareAnywhere8364 t1_jchalqa wrote on March 16, 2023 at 8:41 PM

#2,247,556

MATLAB ftw.

perrohunter t1_jchduna wrote on March 16, 2023 at 9:03 PM

#2,247,730

I’ve been a fervent user of TensorFlow since 2016 but we deduced to ditch TensorFlow at my company in favor of PyTorch because the community support and commitment from the PyTorch team is just way better

Finster201 t1_jci0kia wrote on March 16, 2023 at 11:37 PM

#2,248,957

Replying to SpareAnywhere8364 (#2,247,556)

You want to watch the world burn?

SpareAnywhere8364 t1_jcidjit wrote on March 17, 2023 at 1:12 AM

#2,249,663

Replying to Finster201 (#2,248,957)

I am an "the first index is obviously 1" type of man.

codeinassembly t1_jcj1cjd wrote on March 17, 2023 at 4:33 AM

#2,250,913

I wanted to modify model training to test a hypothesis. I chose TensorFlow. It may present a minor improvement in training speed (atleast before 2.0) but holy fuck was it not worth it with all the gotcha's.

It works well if you're okay with using their default pipeline. Attempt to setup anything custom and you'll be in for a lot of suffering unless you disable symbolic execution - at which point it's slower than PyTorch.

I tried to implement the same idea on PyTorch and was done in an hour. Use PyTorch; it's just better.

tenbilliondollarsman t1_jcj8sc1 wrote on March 17, 2023 at 5:57 AM

#2,251,236

Same, i just started to learn tf 2.0 a couple weeks ago, i think from rn i should learn pytorch too gif

JacksOngoingPresence t1_jcjfaac wrote on March 17, 2023 at 7:25 AM

#2,251,466

Replying to codeinassembly (#2,250,913)

+1
Default keras pipeline is fast, beginner friendly and great. As soon as something custom needs to be done - it's just painful if even possible.

Also the last time I checked (~a year ago) some features were heavily bugged ever since the introduction (literally for years). Like model.predict or tf.function cause memory leaks even with the "examples" code. That was the switching point for me.