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Qt/PySide6 Installation Fixes for Ubuntu

This document contains fixes for Qt/PySide6 import errors and missing system libraries when running pyqtgraph applications on Ubuntu.

Quick Start

If you're encountering Qt/PySide6 import errors, follow these steps:

1. Install system libraries (run as root/admin):

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# Inside the container, edit /root/.bashrc and add this at the very bottom:

# --- Fix DISPLAY for IDE-attached shells ---
# Prefer the newest X socket (usually the active desktop)
for d in /tmp/.X11-unix/X*; do
  n="${d##*/X}"
  export DISPLAY=":$n"
done

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import numpy as np
import torch
from torch import nn
import tqdm

def convNd(in_channels=1, out_channels=1, kernel_size=2, stride=1, padding=1, weight=None, bias=None):
    # These are filters or kernels
    if weight is None:
        weight = np.ones((out_channels, in_channels, *kernel_size))
    # O,C,*kernel_size

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# env [MDP environment]

# nS [state_dim]
# nA [action_dim]

# env.TransitProb [state_dim x action_dim x state_dim]

# env.TransitReward [state_dim x action_dim], Note: It maybe in shape [state_dim x action_dim x state_dim]. In such
# case no need to expand dim. It can also be in the same [state_dim], then it is required to expand dim twice accordingly

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# Value iteration compact

# env [MDP environment]

# nS [state_dim]

# env.TransitProb [state_dim x action_dim x state_dim]

# env.TransitReward [state_dim x action_dim], Note: It maybe in shape [state_dim x action_dim x state_dim]. In such

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import copy
from typing import Optional, Any, Union, Callable

import torch
from torch import Tensor
from .. import functional as F
from .module import Module
from .activation import MultiheadAttention
from .container import ModuleList
from ..init import xavier_uniform_

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1. I set this on my local machine and flip
`alias port_map='f(){ ssh -N -L "$2":localhost:"$2" panditb@"$1".engr.oregonstate.edu;  unset -f f; }; f'`

2. Enter into flip3 (use same node to re-establish connection to HPC if lost, eg '3' here)
`ssh panditb@flip3.engr.oregonstate.edu`

3. Enter HPC and whatever node thereafter (For example if you connect to cn-gpu5, hostname will be gpu5). 
`ssh panditb@compute-{hostname}.hpc.engr.oregonstate.edu`

4. I start the jupyter on node

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name: ml
channels:
  - apple
  - defaults
  - conda-forge
dependencies:
  - anyio=3.5.0
  - aom=3.3.0
  - appdirs=1.4.4
  - appnope=0.1.2

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Setting up miniforge for TensorFlow support

1. Download [Miniforge3-MacOSX-arm64.sh][1]
2. Run the file using the following command:-
   • ./Miniforge3-MacOSX-arm64.sh
3. It will download miniforge in the current directory. Now you have to activate it. Use the following command to do so.
   • source miniforge3/bin/activate
4. You should see (conda) is prepended in your command line. To make sure it is activated during terminal start-up. Use the following command.
   • conda init
   • or if you are using zsh, conda init zsh

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conosle.log('Hello World');