
PyTorch vs. TensorFlow: 1 month summary - dmonn
https://www.codementor.io/dmonn/pytorch-vs-tensorflow-1-month-summary-d8o0kas25
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J0-nas
> A forward() function gets called when the Graph is run.

Isn't that almost exactly the same in tensorflow? You'd run your model to
generate an output, or/and run your optimization operation t optimize the
model.

> Based on some reviews, PyTorch also shows a better performance on a lot of
> models compared to TensorFlow.

Citation needed. How good are the examples optimized? What does performance
mean? Precision or learning iterations per second?

If it's the later, in which environment? CPU/GPU/distributed computing?

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dmonn
> A forward() function gets called when the Graph is run.

Yes, the idea behind it is the same. The difference: PyTorch has a forward()
function in their module class which you have to override, while in TensorFlow
you can specify that yourself.

> Based on some reviews, PyTorch also shows a better performance on a lot of
> models compared to TensorFlow.

E.g.

[http://deeplearningathome.com/2017/06/PyTorch-vs-
Tensorflow-...](http://deeplearningathome.com/2017/06/PyTorch-vs-Tensorflow-
lstm-language-model.html)

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Svenstaro
While I think that this is a somewhat useful rough overview, it should have
had some more details about the actual differences and in particular how to
accomplish the same thing with some code examples in each library.

On a side note: I know that I can also link tensorflow directly to a C++
application instead of using it with python. Can the same be done with
pytorch?

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dmonn
AFAIK there are unofficial C++ Torch Interfaces, but nothing official.

