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#[no_mangle]
pub unsafe extern fn mr_MatrixIsZero(
    mut m : *const f64, n1 : i32, n2 : i32
) -> i32 {
    let mut _currentBlock;
    let mut i : i32;
    let mut n : i32 = n1 * n2;
    i = 0i32;
    'loop1: loop {
        if !(i < n) {

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struct _mjModel
{
    // ------------------------------- sizes

    // sizes needed at mjModel construction
    int nq;                         // number of generalized coordinates = dim(qpos)
    int nv;                         // number of degrees of freedom = dim(qvel)
    int nu;                         // number of actuators/controls = dim(ctrl)
    int na;                         // number of activation states = dim(act)
    int nbody;                      // number of bodies

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let gaussian 

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# examples/mountain_car.jl

# Import the RL algorithms
using Reinforce

# Import the Mountain car environment
using Reinforce.MountainCarEnv: MountainCar

# Import the Plots plotting library and use GR as the backend 
# https://github.com/jheinen/GR.jl

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# examples/mountain_car.jl

# Import the RL algorithms
using Reinforce

# Import the Mountain car environment
using Reinforce.MountainCarEnv: MountainCar

# Import the Plots plotting library and use GR as the backend 
# https://github.com/jheinen/GR.jl

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cd github.com

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git clone https://github.com/JuliaML/Reinforce.jl
cd Reinforce.jl

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# Full example here https://github.com/JuliaOpt/JuMP.jl/blob/master/examples/cannery.jl

@variable(cannery, ship[1:num_plants, 1:num_markets] >= 0)

    # Ship no more than plant capacity
    @constraint(cannery, capacity_con[i in 1:num_plants],
        sum(ship[i,j] for j in 1:num_markets) <= capacity[i]
    )

    # Ship at least market demand

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struct Point{T}
  x::T
  y::T
end

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# https://github.com/JuliaML/Reinforce.jl/blob/master/examples/mountain_car.jl
using Reinforce
using Reinforce.MountainCarEnv: MountainCar

using Plots
gr()

# Deterministic policy that is solving the problem
mutable struct BasicCarPolicy <: Reinforce.AbstractPolicy end