chsasank

# Eternal bash history.
# ---------------------
# Undocumented feature which sets the size to "unlimited".
# http://stackoverflow.com/questions/9457233/unlimited-bash-history
export HISTFILESIZE=
export HISTSIZE=
export HISTTIMEFORMAT="[%F %T] "
# Change the file location because certain bash sessions truncate .bash_history file upon close.
# http://superuser.com/questions/575479/bash-history-truncated-to-500-lines-on-each-login
export HISTFILE=~/.bash_eternal_history

chsasank

//==============================================================
// Copyright © 2022 Intel Corporation
//
// SPDX-License-Identifier: MIT
// =============================================================

#include <iostream>
#include <sycl/sycl.hpp>
#include <chrono>

chsasank

set -g mouse on

unbind C-b
set-option -g prefix C-a
bind-key C-a send-prefix

chsasank

import torch
import time
import numpy as np
from torch import mps, cuda

num_trails = 10

def flops_benchmark(device):
    test_range = 2 ** np.arange(8, 13, 0.25)

chsasank

M1 Macbook Air

MacBook Air (M1, 2020)

Native (brew)

$ /opt/homebrew/bin/python3 -c 'import platform; print(platform.platform())'
macOS-11.4-arm64-arm-64bit

chsasank

1. Install rosetta2
2. Install NVM using instructions here curl -o- https://raw.githubusercontent.com/nvm-sh/nvm/v0.38.0/install.sh | bash
3. Add the stuff from the above command to zshrc to initialize nvm
4. Go to x86 shell by arch -x86_64 zsh
5. Install lts node using nvm in the intel shell: nvm install --lts
6. Enjoy node in all shells (x86 or arm)

chsasank

"""Convert jupyter notebook to sphinx gallery notebook styled examples.

Usage: python ipynb_to_gallery.py <notebook.ipynb>

Dependencies:
pypandoc: install using `pip install pypandoc`
"""
import pypandoc as pdoc
import json

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import numpy as np
from scipy.ndimage.interpolation import map_coordinates
from scipy.ndimage.filters import gaussian_filter

def elastic_transform(image, alpha, sigma, random_state=None):
    """Elastic deformation of images as described in [Simard2003]_.


    .. [Simard2003] Simard, Steinkraus and Platt, "Best Practices for
       Convolutional Neural Networks applied to Visual Document Analysis", in

chsasank

require 'image'

function ElasticTransform(img, alpha, sigma)
	--[[
	Parameters
	----------
	img: Tensor of size KxHxW
		Image on which elastic transformation have to be applied
	alpha: number
		Intensity of the transformation

chsasank

import numpy as np
from skimage import io
from skimage import transform
import matplotlib.pyplot as plt
import math
import time

I = io.imread('random_img.jpg')

# Homography