ityonemo

import torch
import torch.nn as nn

class ResNetBlock(nn.Module):
    def __init__(self, input_channel_count, internal_channel_count, downsampler = None, stride=1, layers = 'all'):
        # input_channel_count:  An image tensor is a h*w*k tensor where k is represents
        #    how many channels, naively, groups of features discovered by the ml model.
        #    the shape of the input tensor is h*w*input_channel.
        # internal_channel_count:  like above, but the shape of the output tensor is
        #    h*w*internal_channel_count.  In a typical convnet strategy, you will want the

ityonemo

A half-hour to learn Zig

This is inspired by https://fasterthanli.me/blog/2020/a-half-hour-to-learn-rust/

Basics

the command zig run my_code.zig will compile and immediately run your Zig program. Each of these cells contains a zig program that you can try to run (some of them contain compile-time errors that you can comment out to play with)

ityonemo

const std = @import("std");

pub fn Algebra(comptime fields: []const type) type {
    return struct{
        pub fn @"<+>"(a: anytype, b: anytype) FieldFor(@TypeOf(a), @TypeOf(b)).Type {
            const F: type = FieldFor(@TypeOf(a), @TypeOf(b));
            return F.@"<+>"(a, b);
        }

        pub fn FieldFor(comptime AType: type, comptime BType: type) type {

ityonemo

const std = @import("std");
const print = std.debug.print;

var yielded = false;

fn yield() void {
  yielded = true;
  suspend;
}

ityonemo

defmodule Lisp do

  @type ast :: [String.t | number | ast]
  @type token :: :lp | :rp | number | String.t

  @letters Enum.concat(?a..?z, ?A..?Z)
  @numbers ?0..?9
  @operators [?+]

  @doc """

ityonemo

Gromacs on Lambda V100 nodes

Installation

1. Install singularity

sudo apt-get update && sudo apt-get install -y build-essential libssl-dev uuid-dev \
  libgpgme11-dev squashfs-tools libseccomp-dev wget pkg-config git cryptsetup

ityonemo

using JSON

#make sure we have what we're looking for.
(length(ARGS) == 0) && throw(ErrorException("needs a file name"))
###################################
#rows iterator
type rows; tgt::Matrix; end
Base.start(r::rows) = 1
Base.next(r::rows, idx) = (r.tgt[idx, :], idx + 1)
Base.done(r::rows, idx) = idx > size(r.tgt, 1)

ityonemo

//! The Computer Language Benchmarks Game
//! https://salsa.debian.org/benchmarksgame-team/benchmarksgame/
//!
//! This implementation is written in simple and idiomatic Zig.
//! The only optimization is using SIMD vector intrinsics.

const std = @import("std");

/////////////////////////////////////////////////////////////////////////
// important constants.  ALLCAPS constants are not idiomatic Zig, but it's

ityonemo

{
	"Inspect": {
		"prefix": "ins",
		"body": "|> IO.inspect(label: \"$0$TM_LINE_NUMBER\")",
		"description": "Adds a pipeline with a labelled `IO.inspect`",
 	}
}

ityonemo

#!/bin/sh

IMAGE=<your image id>
CMD=<your cmd>

podman run --net host -v $HOME:$HOME -e HOME="$HOME" -w$(PWD) -it $IMAGE "$CMD $@"