BoundsError: attempt to access 2-element Vector in DDPG algorithm

Specific Domains Machine Learning
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1

Hi,

I was implementing DDPG algorithm for 1-D vector action space but, during run it shows error as:

BoundsError: attempt to access 2-element Vector{Float64} at index []

Now, when looked into DDPG policy on Github

# TODO: handle Training/Testing mode
function (p::DDPGPolicy)(env)
    p.step += 1

    if p.step <= p.start_steps
        p.start_policy(env)
    else
        D = device(p.behavior_actor)
        s = state(env)
        s = Flux.unsqueeze(s, ndims(s) + 1)
        action = p.behavior_actor(send_to_device(D, s)) |> vec |> send_to_host
        clamp(action[] + randn(p.rng) * p.act_noise, -p.act_limit, p.act_limit)
    end
end

It has action[], so is it expecting action to be scalar. As we have action_space of form [1..3,2..3].
I am using start policy in DDPG agent as -

start_policy = RandomPolicy(action_space(env);rng)

Any help or suggestion on how this is usually done is appreciated! :smiley:

2

Ah, it’s still not fixed yet after a year…