kwertzzz

9 ms·

31.
by kwertzzz 5y ago
Would it be useful to add a Julia section?
32.
by kwertzzz 5y ago
The list comprehension in your example is now type-stable without additional type-annotation so you can just write [x^2 for x in xs] and the compiler known that the results is a list of integers (for your example). There have been many impr
33.
by kwertzzz 5y ago
I stand corrected. Thanks!
34.
by kwertzzz 5y ago
It also includes "Der Spiegel", a German newspaper (one of the most influential one in Germany). https://github.com/jonathandata1/2022_beijing/blob/main/ille...
35.
by kwertzzz 5y ago
Here is an interesting discussion from the julia language where string concatenation is indeed the * operator: https://github.com/JuliaLang/julia/issues/1771 In particular: https://github.com/
36.
by kwertzzz 5y ago
Nice article! One can you also use reduce(hcat,n) instead of hcat(n...). The function reduce(hcat,n) should be faster as there is optimized implementation of it: https://github.com/JuliaLang/julia/blob/89a51f
37.
by kwertzzz 5y ago
The code_warntype macro is helpful, but to prevent a future inadvertently introduced type stability, a failing test would be much better. Test.@inferred is not quite what is needed: function foo(x) s = 0 # better use a ze
38.
by kwertzzz 5y ago
One could check if the phone is vulnerable to any published issues in the CVE database. (I applaud this effort in reducing e-waste).
39.
by kwertzzz 5y ago
Installing CUDA (with kernel driver, CuDNN, Tensorflow/PyTorch) has not been easy for me either. Usually you want to have the latest version of all of them. But sometimes the very latest version of these packages is not yet supported b
40.
by kwertzzz 5y ago
This is really the main problem. As far as I know, ROCm requires a quite expensive GPU for data centers (if you want to have a current GPU) which makes it quite difficult to build a community around ROCm.
41.
by kwertzzz 5y ago
For Pytorch, I had no issues with conda. But with Tensorflow from conda, the training process just hangs (consuming 100% of CPU but no GPU resources, despite my GPUs are recognized). I got more luck with installing Tensorflow with pip. Give
42.
by kwertzzz 5y ago
Yes, you would still need to the NVIDIA kernel driver (preferably the most current one). Desktop users typically have it already installed. But the main difficulty in my opinion is to install CUDA (with CuDNN,...). Even the TensorFlow docum
43.
by kwertzzz 5y ago
The compactness of APL is indeed quite intriguing. One could also write your example in Julia by: sum(j -> j*2.0^(-j),1:n) sum(function,array) applies function to all elements of array before the summation (without need to allocate an in
44.
by kwertzzz 5y ago
I would be genuinely interested of the advantages of APL over languages like Julia or Python with numpy who have also quite flexible array types. For instance in Julia, I could write: data = [1,2,3] # . means element-wise operation sum(exp.
45.
by kwertzzz 5y ago
I don't know why you got downvoted, but I agree that matrix manipulation in numpy look quite foreign to to somebody new to python/numpy. I had heard this "complain" from several colleagues (mostly former matlab-users). S
46.
by kwertzzz 6y ago
> "Russia's or China's state-sponsored propaganda" I do not think that this is a crazy idea at all [1] [1] https://en.wikipedia.org/wiki/Internet_Research_Agency
47.
by kwertzzz 6y ago
The julia binding look really great. In zygote, arrays are immutable. Is enzyme able to handle such cases?
48.
by kwertzzz 6y ago
Indeed, the use of BinayBuilder was an important step forward. Before we had the problem that different package would require different versions of e.g. zlib ( https://github.com/JuliaGraphics/Gtk.jl/pull/387 )
49.
by kwertzzz 6y ago
I tried also recently the beta version of Julia 1.6 and the speed improvement of installing/loading package are quite impressive. Essentially, packages get precompiled after installation using multiple threads. Beside this, if you only
50.
by kwertzzz 6y ago
I full agree. With version number you can have a good sense whether a package update breaks your code or not (as long the package authors following semantic versioning). I think in julia this problem is solved quite nicely with the Project.
51.
by kwertzzz 6y ago
In my country you need to show that your kid is vaccinated against e.g. Polio before you can let him/her go to daycare. To me, it makes perfect sense, that somebody who wants to go to e.g. a music festival in 2022 without a face mask,
52.
by kwertzzz 6y ago
I have translated quite a bit of Matlab code to Julia. Just the simple fact that indices are handled the same way in Matlab and Julia makes this transition easier than going from Matlab to Python in my opinion. What I would suggest, is that
53.
by kwertzzz 6y ago
Note that this article is about a Fortran dialect called "High Performance Fortran" (a competitor to OpenMP). It is not about Fortran for High-Performance Computing in general. I used Fortran quite a lot in my PhD and I actually d
54.
by kwertzzz 6y ago
I also like that package environments are integrated in Julia and thus there is only one way handle environments.
55.
by kwertzzz 6y ago
Yes, and the interface is pretty fast and without any noticeable overhead: julia> data = rand(ComplexF64, 1024^2); # python fft from julia: julia> res = @btime np.fft.fft(data); 78.613 ms (39 allocations: 16.00 MiB) # python ff
56.
by kwertzzz 6y ago
I tried Julia as well to test the database feature. Unfortunately, when I `import HTTP`, I get "repl process died unexpectedly: signal killed". (julia 1.3.1 and HTTP v0.8.17)
57.
by kwertzzz 6y ago
I would argue that Julia can be similarly flexible than Python, but you have to be more explicit that you need this flexibility. For instance, in python you happily add a string to the list [1,2,3], but not in Julia because the list has bee
58.
by kwertzzz 7y ago
Why are you sending the data (including medical conditions) to Facebook? https://www.facebook.com/v6.0/plugins/like.php?action=like&a...
59.
by kwertzzz 7y ago
This is exactly what I like too about Delpi (and Pascal if I remember correctly) compared to C++ and Java. Julia, which I use now, has a similar feature but properties are less extensively used there (except for interoperability with Python
60.
by kwertzzz 7y ago
Did you know that Java for instance, was originally designed to run on interactive TVs? But then, Java run on many type of devices and in broad range of use-cases (maybe with the exception of TVs :-)). The original niche for which a program

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