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If you are wondering where the data of this site comes from, please visit https://api.github.com/users/clouds56/events. GitMemory does not store any data, but only uses NGINX to cache data for a period of time. The idea behind GitMemory is simply to give users a better reading experience.
Clouds clouds56 Swiss Happens to be a student of mathematics

clouds56/crnlib 1

rust port of https://github.com/BinomialLLC/crunch

clouds56/ardour 0

Mirror of Ardour Source Code

clouds56/assimp-sys 0

Forked from Eljay, but that user seems to have deleted all their projects

clouds56/atasks 0

rust async tasks package

clouds56/atom-ide-reason 0

ReasonML/OCaml language support for Atom-IDE, using ocaml-language-server under the hood.

clouds56/aur-rtl8812au 0

forked from https://aur.archlinux.org/rtl8812au-rpi-dkms-git.git

clouds56/beakerx 0

Beaker Extensions for Jupyter Notebook

clouds56/blockscout 0

Blockchain explorer for Ethereum based network and a tool for inspecting and analyzing EVM based blockchains.

Pull request review commentmicrosoft/vscode-arduino

Split by lines when parsing stdout of build

 export class ArduinoApp {             }
             return ret;
         }
-        let stdoutbuf = ""
+        let stdoutbuf = "";
         const stdoutcb = (line: string) => {
             if (cocopa.callback) {
-                stdoutbuf += line
-                let lines = [stdoutbuf];
-                lines = stdoutbuf.split('\n');
+                stdoutbuf += line;
+                let lines = stdoutbuf.split('\n');
                 stdoutbuf = lines.pop()!;

The stdoutbuf is upvalue variable of the closure, the last update is taking the remain characters that in last line.

clouds56

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pull request commentpandas-dev/pandas

BUG: read-only values in cython funcs

to_datetime not works when unit set,

import pandas as pd
import numpy as np

a = np.array([1,2,3])
a.setflags(write=False)
pd.to_datetime(a, utc=True, unit='s')

This would call tslib.array_with_unit_to_datetime eventually.

jbrockmendel

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add test.py

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issue closedJuliaPackaging/BinaryBuilderBase.jl

Add ASM compiler support?

Some environment like mingw would like asm compiler such as uasm. https://github.com/msys2/MINGW-packages/blob/8ff2f8d0c3589b43d538cb6c738a0d9eed7e9d7e/mingw-w64-clang/PKGBUILD#L297-L298

      export ASM_COMPILER="${MINGW_PREFIX}/bin/uasm.exe"
      platform_config+=(-DCMAKE_ASM_MASM_COMPILER="${ASM_COMPILER}"

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clouds56

issue commentJuliaPackaging/BinaryBuilderBase.jl

Add ASM compiler support?

Thanks for the information, I successfully install uasm via

apk add uasm --repository=http://dl-cdn.alpinelinux.org/alpine/edge/testing
clouds56

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fix build on windows

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Create 0901-cast-to-make-gcc-happy.patch

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Update build_tarballs.jl

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Update build_tarballs.jl

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Rename O/openmp/build_tarballs.jl to L/LLVMOpenMP/build_tarballs.jl

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Create build_tarballs.jl

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create barnchclouds56/Yggdrasil

branch : clouds56-patch-1

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issue closedJunoLab/Weave.jl

display plot is slow

@time using Plots # tag-import
import Markdown
@time for (d, feat) in collect(zip(data, feats))[1:3] # tag-all: takes >300s
  @time display(Markdown.parse("## `$feat`")) # tag-md
  colnames = propertynames(d)
  @time plots = [Feat.plot_feat(d[!, colname]; name=colname) for colname in colnames] # tag-plot: takes average ~2s
  @time display(@time plot(plots..., layout=(length(plots), 1), size=(800, 300*length(plots)))) # tag-inner: inner average <1s, tag-outer: outer takes [30, 120, 150] seconds
end

I think this is not related to first plot time and actually there's something wrong inside display, the time seems increasing (the output plot is almost the same)

output like this

tag-import:  0.000372 seconds (137 allocations: 9.891 KiB)
tag-md    :   0.000228 seconds (134 allocations: 8.344 KiB)
tag-plot  :   2.727499 seconds (409.84 k allocations: 960.588 MiB, 8.04% gc time, 29.44% compilation time)
tag-inner :   0.231747 seconds (8.08 k allocations: 175.876 MiB, 41.44% gc time)
tag-outer :  30.318927 seconds (24.10 M allocations: 1.392 GiB, 1.99% gc time)
tag-md    :   0.000184 seconds (133 allocations: 8.438 KiB)
tag-plot  :   1.634230 seconds (69.91 k allocations: 940.056 MiB, 8.27% gc time)
tag-inner :   0.088039 seconds (8.07 k allocations: 175.872 MiB)
tag-outer : 126.838568 seconds (23.95 M allocations: 1.387 GiB, 0.52% gc time)
tag-md    :   0.000234 seconds (133 allocations: 8.500 KiB)
tag-plot  :   1.874118 seconds (69.91 k allocations: 940.056 MiB, 7.38% gc time)
tag-inner :   0.238603 seconds (8.07 k allocations: 175.868 MiB, 48.30% gc time)
tag-outer : 154.335929 seconds (23.94 M allocations: 1.387 GiB, 0.46% gc time)
tag-all   : 317.732765 seconds (72.54 M allocations: 6.940 GiB, 0.77% gc time, 0.25% compilation time)

closed time in 19 days

clouds56

issue commentJunoLab/Weave.jl

display plot is slow

I find out that the actual render would be done in display.

clouds56

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commit sha ad3dc06babcc41e2803ed4817aa822dfd8c52575

fix attribute would change content

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PR opened opus111/BaseOnnx.jl

fix `Ref{Any}(p::TensorProto)`
+2 -2

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commit sha 635df698bd95b97ec9a40f6c8fdb459905d97b61

fix `Ref{Any}(p::TensorProto)`

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pull request commentopenvinotoolkit/openvino

[MO] pip packaging

@dkurt thanks for the information! That's exactly what I need. (Maybe we should add a link to openvino-dev in package openvino)

dkurt

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issue commentopenvinotoolkit/openvino

Publish model optimizer to PyPI

@jgespino If I recall correctly, the openvino package only contains inference-engine but not model-optimizer, shall we add model-optimizer as well?

wangzhenyu32

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pull request commentopenvinotoolkit/openvino

[MO] pip packaging

Cloning full openvino repo is quite long process. Will there be a pip distribution of release on pypi.org similar to https://pypi.org/project/openvino/ package

setup.py still required for both. You may install in two ways: as git repo or as a wheel. See the tests workflow with wheel example.

Shall we release a wheel (maybe named openvino-mo) on pypi.org?

dkurt

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issue commentonnx/onnx

Cannot import after build from source (AGX Xavier)

I'm using windows pip install onnx and same error occurs

AttributeError: 'module' object has no attribute '_internal_create_key'
aaravpandya

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Update build_tarballs.jl

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commit sha 282d36295d62d75aeae4983c07d2faeda248426a

Apply suggestions from code review Co-authored-by: Mosè Giordano <giordano@users.noreply.github.com>

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issue commentJuliaPackaging/BinaryBuilderBase.jl

Add ASM compiler support?

Sorry missed that comment, do you mean I could use pacman in Mingw and install any package in the script?

clouds56

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Pull request review commentJuliaPackaging/Yggdrasil

[openmp] Add initial recipe.

+# Note that this script can accept some limited command-line arguments, run+# `julia build_tarballs.jl --help` to see a usage message.+using BinaryBuilder++name = "openmp"+version = v"12.0.0"++# Collection of sources required to build mpg123+sources = [+    ArchiveSource(+        "https://github.com/llvm/llvm-project/releases/download/llvmorg-$version/openmp-$version.src.tar.xz",+        "eb1b7022a247332114985ed155a8fb632c28ce7c35a476e2c0caf865150f167d"+    ),+]++# Bash recipe for building across all platforms+script = raw"""+cd $WORKSPACE/srcdir/openmp-*/++if [[ "${target}" == *-freebsd* ]]; then+    CMAKE_SHARED_LINKER_FLAGS="-Wl,--version-script=$(pwd)/runtime/src/exports_so.txt"+fi+cmake . -DCMAKE_INSTALL_PREFIX=${prefix} -DCMAKE_TOOLCHAIN_FILE="${CMAKE_TARGET_TOOLCHAIN}" -DCMAKE_SHARED_LINKER_FLAGS="${CMAKE_SHARED_LINKER_FLAGS}" -DLIBOMP_INSTALL_ALIASES=OFF+make -j${nproc}+make install+"""++# These are the platforms we will build for by default, unless further+# platforms are passed in on the command line+# disable for mingw for now, blocking on uasm+platforms = expand_cxxstring_abis(supported_platforms(exclude=Sys.iswindows))

As mentioned above, there's no suitable ASM compiler (mingw uses uasm)

I struggled to make it work on freebsd, but it's hard to compile with mingw, you could see in official code, it relies on uasm, which I'd like to have it in BinaryBuilderBase, I fired a issue here (but nobody replies).

clouds56

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Pull request review commentJuliaPackaging/Yggdrasil

[openmp] Add initial recipe.

+# Note that this script can accept some limited command-line arguments, run+# `julia build_tarballs.jl --help` to see a usage message.+using BinaryBuilder++name = "openmp"+version = v"12.0.0"++# Collection of sources required to build mpg123+sources = [+    ArchiveSource(+        "https://github.com/llvm/llvm-project/releases/download/llvmorg-$version/openmp-$version.src.tar.xz",+        "eb1b7022a247332114985ed155a8fb632c28ce7c35a476e2c0caf865150f167d"+    ),+]++# Bash recipe for building across all platforms+script = raw"""+cd $WORKSPACE/srcdir/openmp-*/++if [[ "${target}" == *-freebsd* ]]; then+    CMAKE_SHARED_LINKER_FLAGS="-Wl,--version-script=$(pwd)/runtime/src/exports_so.txt"+fi+cmake . -DCMAKE_INSTALL_PREFIX=${prefix} -DCMAKE_TOOLCHAIN_FILE="${CMAKE_TARGET_TOOLCHAIN}" -DCMAKE_SHARED_LINKER_FLAGS="${CMAKE_SHARED_LINKER_FLAGS}" -DLIBOMP_INSTALL_ALIASES=OFF+make -j${nproc}+make install+"""++# These are the platforms we will build for by default, unless further+# platforms are passed in on the command line+# disable for mingw for now, blocking on uasm+platforms = expand_cxxstring_abis(supported_platforms(exclude=Sys.iswindows))++# The products that we will ensure are always built+products = [+    LibraryProduct("libomp", :libomp),+]++# Dependencies that must be installed before this package can be built+dependencies = [+]++# Build the tarballs, and possibly a `build.jl` as well.+build_tarballs(ARGS, name, version, sources, script, platforms, products, dependencies; preferred_gcc_version=v"8", perferred_llvm_version=v"12")

It do compiles with other versions of LLVM, but since it fetches from the LLVM 12, I think it would prefer v"12"?

clouds56

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