I hereby claim:
- I am stites on github.
- I am stites (https://keybase.io/stites) on keybase.
- I have a public key whose fingerprint is 2C16 B515 DB66 C385 D569 E0B8 2418 B81B A203 9C3F
To claim this, I am signing this object:
(************************************) | |
(* Exceptions and Testing Functions *) | |
(************************************) | |
exception Not_implemented ;; | |
exception Runtime ;; | |
(* Asserts that a function call throws a Runtime exception. *) | |
let assert_runtime (f: unit -> 'a): unit = |
zpool create \ | |
-o compatibility=grub2 \ | |
-o ashift=12 \ | |
-o autotrim=on \ | |
-O acltype=posixacl \ | |
-O canmount=off \ | |
-O compression=lz4 \ | |
-O devices=off \ | |
-O normalization=formD \ | |
-O relatime=on \ |
{ pkgs, ... }: | |
{ | |
home.packages = [ pkgs.stack ]; | |
home.file = { | |
".stack/config.yaml".source = ./local.yaml; | |
".stack/global-project/stack.yaml".source = ./global.yaml; | |
}; | |
} |
import torch | |
import torch.nn.functional as F | |
from torch import Tensor | |
from typing import Tuple | |
from torch.distributions.categorical import Categorical | |
from torch.distributions.uniform import Uniform | |
from combinators.tensor.utils import kw_autodevice | |
from probtorch.stochastic import Trace, RandomVariable, ImproperRandomVariable | |
def run_gibbs(nsweeps=1): | |
xs = get_dataset() | |
xs, ys = xs[:1,:], xs[2,:] | |
# xs is Shape([1000,2]) | |
# ys is Shape([1000,1]) of cluster labels | |
prior = [Normal(-1, 0.5), Normal(1, 0.5)] | |
for sweep in range(0, nsweeps): | |
postieror = gibbs(prior, xs) | |
prior = posterior # do something with that posterior? |
I hereby claim:
To claim this, I am signing this object:
This is primarily a stub for any nix-shells that I want to add to to my config.nix |
constraints: any.Cabal ==2.2.0.1, | |
any.HTTP ==4000.3.12, | |
HTTP -conduit10 -mtl1 +network-uri -warn-as-error +warp-tests, | |
any.HUnit ==1.6.0.0, | |
any.JuicyPixels ==3.3, | |
JuicyPixels -mmap, | |
any.QuickCheck ==2.11.3, | |
QuickCheck +templatehaskell, | |
any.alex ==3.2.4, | |
alex +small_base, |
module Torch.Models.LeNet where | |
data LeNet ch step = LeNet | |
{ _conv1 :: !(Conv2d ch 6 '(step,step)) | |
, _conv2 :: !(Conv2d 6 16 '(step,step)) | |
, _fc1 :: !(Linear (16*step*step) 120) | |
, _fc2 :: !(Linear 120 84) | |
, _fc3 :: !(Linear 84 10) | |
} |
{-# LANGUAGE TypeOperators #-} | |
{-# LANGUAGE TypeApplications #-} | |
{-# LANGUAGE AllowAmbiguousTypes #-} | |
{-# LANGUAGE TypeFamilies #-} | |
{-# LANGUAGE FlexibleContexts #-} | |
{-# OPTIONS_GHC -fplugin GHC.TypeLits.Normalise #-} | |
module LeNet where | |
import Data.Function ((&)) | |
import GHC.Natural |