raytroop

import torch
from torch import nn

# 1.
# register_forward_pre_hook(hook)
# The hook will be called every time before forward() is invoked. It should have the following signature:
# `hook(module, input) -> None`

# The hook should not modify the input

raytroop

#include <stdio.h>
#include <stdlib.h>
#include <cuda_runtime.h>


//http://www.techdarting.com/2014/03/matrix-multiplication-in-cuda-using.html


// This code assumes that your device support block size of 1024
#define MAX_RANGE 9999

raytroop

# gtk3 in Rocky Linux 8.5
./configure --with-features=huge --enable-gui=gtk3 --enable-python3interp --prefix=/usr
make -j`nproc`
sudo make install

raytroop

import tensorflow as tf

#aplly exponential decay on learning rate
global_step = tf.Variable(0, trainable=False)
stater_learning_rate = lr #for start
learning_rate = tf.train.exponential_decay(starter_learning_rate, global_step, 
                                           decay_steps, decay_rate, staircase=True)

optimizer = tf.train.AdamOptimizer(learning_rate)

raytroop

sudo yum install openssl compat-openssl10 qca-qt5-ossl.x86_64 openssl-devel

raytroop

1) gparted extend
2) 
  lvextend -l +100%FREE /dev/rl/root
3) 
  xfs_growfs /dev/mapper/rl-root

usefull command:
  df -h
  lvdisplay
  fdisk -l

raytroop

A = zeros(10,21);
n = [1:10];

% post cursor
for m = 1:3
    A(m, 11+n(m)) = 0.5;
    A(m, 11-n(m)) = 0.5;
end

% one

raytroop

a: -> variable scope
s: -> current script’s namespace
b: -> local to the current buffer

raytroop

g:coc_snippet_next                                      g:coc_snippet_next

        Trigger key for going to the next snippet position, applied in insert
        and select mode.

        Only works when snippet session is activated.

        Default: <C-j>

g:coc_snippet_prev                                      g:coc_snippet_prev

raytroop

git clone https://github.com/raytroop/svlangserver.git
cd svlangserver/
npm pack
npm install -g imc-trading-svlangserver-0.3.4.tgz