currymj

import jax.numpy as jnp
from jax import grad, hessian, jit
from jax.scipy.linalg import solve
import numpy as np
import matplotlib.pyplot as plt

# The goal here is to solve a Stackelberg game in a particularly grotesque way.

# To compute the follower best response, we take a few Newton steps using autograd to compute the Hessian and gradients. 
# This is implemented in function `follower_bestresponse`.

currymj

#!/bin/bash
#SBATCH --ntasks 2
#SBATCH -N 2
#SBATCH --job-name=distributed-pbg
#SBATCH -o log-gloo-test-%j.out

source /etc/profile

export HDF5_USE_FILE_LOCKING='FALSE'
export PARENT=`/bin/hostname -s`

currymj

In file included from ../caffe2/operators/batch_matmul_op.h:11:0,
                 from ../caffe2/operators/batch_matmul_op_test.cc:6:
../caffe2/core/operator.h: In member function 'std::vector<_RealType> caffe2::OperatorBase::GetVectorFromIValueList(const c10::IValue&) const':
../caffe2/core/operator.h:129:47: error: parse error in template argument list
     return c10::impl::toVector(value.template to<List<T>>());
                                               ^
../caffe2/core/operator.h: In instantiation of 'std::vector<_RealType> caffe2::OperatorBase::GetVectorFromIValueList(const c10::IValue&) const [with T = long int]':
../caffe2/core/operator.h:818:52:   required from here
../caffe2/core/operator.h:129:31: error: no matching function for call to 'c10::IValue::to() const'
     return c10::impl::toVector(value.template to<List<T>>());

currymj

function genlist()
    arr = zeros(32768)
    for i=1:length(arr)
        arr[i] = rand(Int) % 256
    end
    arr
end

function processlist(arr)
    sum = 0

currymj

using DifferentialEquations
using DiffEqBayes
using Distributions

const p0 = 0.2; const q0 = 0.3; const v0 = 1; const d0 = 5
const p1 = 0.2; const q1 = 0.3; const v1 = 1; const d1 = 1
const d2 = 1; const beta0 = 1; const beta1 = 1; #const tau = 1
function bc_model(du,u,h,p,t)
  du[1] = (v0/(1+beta0*(h(p, t-p[1])[3]^2))) * (p0 - q0)*u[1] - d0*u[1]
  du[2] = (v0/(1+beta0*(h(p, t-p[1])[3]^2))) * (1 - p0 + q0)*u[1] +

currymj

using Distributions
using Plots
using StatsFuns

# function from Kandasamy et al

# each Fd is trimodal
struct Fd <: Function
        d::Int64
        v1::Vector{Float64}

currymj

with import <nixpkgs> {};

let ps = pkgs.python3Packages;
in
(python3.buildEnv.override {
 extraLibs = [
 ps.numpy
 ps.toolz
 ps.notebook
 ps.matplotlib

currymj

(bayesopt) Michaels-MacBook-Pro-2:release_pre_alpha curry$ python run_stybtang_transform.py 
[array([2, 4, 9]), array([8]), array([6, 7, 5]), array([1, 3, 0])]
Running Multi MCMC model selection BO on rotated Stybtang
12.3249773332
141.004751431
 /Users/curry/src/GPy/GPy/kern/src/rbf.py:43: RuntimeWarning:overflow encountered in square
 /Users/curry/src/GPy/GPy/kern/src/stationary.py:167: RuntimeWarning:overflow encountered in divide
 /Users/curry/src/GPy/GPy/kern/src/rbf.py:46: RuntimeWarning:invalid value encountered in multiply
 /Users/curry/anaconda3/envs/bayesopt/lib/python2.7/site-packages/paramz/transformations.py:108: RuntimeWarning:invalid value encountered in greater
 /Users/curry/anaconda3/envs/bayesopt/lib/python2.7/site-packages/paramz/transformations.py:113: RuntimeWarning:invalid value encountered in greater

currymj

Keybase proof

I hereby claim:

• I am currymj on github.
• I am curry (https://keybase.io/curry) on keybase.
• I have a public key ASAYThi4MBMaHHY_sPaY-F7foTp5G-eJVMhn38np7nAtYgo

To claim this, I am signing this object:

currymj

import tensorflow as tf
import numpy as np

def backward_tf(transition, emission, initial_state, seq):
    beta = tf.ones_like(transition[:,-1])
    jrange = tf.reverse(tf.range(1,seq.get_shape()[0]),[0])
    def scan_op(curr_beta, j):
        return tf.reduce_sum( emission[:,seq[j]] * transition * curr_beta,1)
    betas = tf.scan(scan_op, jrange, initializer=beta)
    final_beta = initial_state * betas[-1,:] * emission[:,seq[0]]