tudorjnu

{
  "$schema": "https://raw.githubusercontent.com/jsonresume/resume-schema/v1.0.0/schema.json",

  "basics": {
    "name": "Jordan Smith",
    "label": "Full Stack Developer",
    "image": "https://randomuser.me/api/portraits/men/75.jpg",
    "email": "[email protected]",
    "phone": "+1-415-555-2673",
    "url": "https://jordansmith.dev",

tudorjnu

# Compositor
sudo pacman -S picom

# Display Manager
sudo pacman -S ly

# Window Manager and Dependencies
sudo pacman -S qtile python-psutil

# Notification Server

tudorjnu

#### MATPLOTLIBRC FORMAT

## NOTE FOR END USERS: DO NOT EDIT THIS FILE!
##
## This is a sample Matplotlib configuration file - you can find a copy
## of it on your system in site-packages/matplotlib/mpl-data/matplotlibrc
## (relative to your Python installation location).
## DO NOT EDIT IT!
##
## If you wish to change your default style, copy this file to one of the

tudorjnu

set -xe

# remove any copies
rm -f testVHACD
# grab the VHACD (convex segmenter) binary
wget https://github.com/mikedh/v-hacd-1/raw/master/bin/linux/testVHACD
# check the hash of the downloaded file
echo "e1e79b2c1b274a39950ffc48807ecb0c81a2192e7d0993c686da90bd33985130  testVHACD" | sha256sum --check
# make it executable
chmod +x testVHACD

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def parse_tensorboard_log(path: Path):
    from tensorboard.backend.event_processing.event_accumulator import EventAccumulator
    import pandas as pd

    tag = 'rollout/ep_len_mean'
    acc = EventAccumulator(path)
    acc.Reload()
    # check if the tag exists

    if tag not in acc.Tags()['scalars']:

tudorjnu

import trimesh
from lxml import etree
import sys
import os
import shutil
import argparse
from trimesh.decomposition import convex_decomposition


_VHACD_EXECUTABLE = shutil.which('testVHACD')