RepeatObservationEnvironment.cs

namespace Gradient.Samples {
    using System;
    using System.Collections.Generic;
    using System.Diagnostics;
    using Gradient;
    using mlagents_envs.base_env;
    using numpy;
    /// <summary>
    /// A simple environment, where agents simply have to repeat observations.
    /// <para>(Do what Archimonde does anyone?)</para>
    /// </summary>
    class RepeatObservationEnvironment : IEnvironment {
        float previousObservation;
        float observation;
        float[] action;
        readonly Random random = new Random();
        public RepeatObservationEnvironment(int agents) {
            this.action = new float[agents];
        }
        public int AgentCount => this.action.Length;
        public BatchedStepResult GetStepResult(string? agentGroupName) {
            if (agentGroupName != null) throw new KeyNotFoundException();
            return new BatchedStepResult(
                obs: new[] { np.ones(new int[] { this.AgentCount, 1 }, dtype: PythonClassContainer<float32>.Instance).__mul__(this.observation) },
                reward: (ndarray)ndarray.FromList(this.action).__sub__(this.previousObservation).__abs__().__rsub__(2),
                done: np.zeros(this.AgentCount),
                max_step: null,
                agent_id: np.zeros(this.AgentCount),
                action_mask: null);
        }
        public void Reset() {
            this.observation = this.previousObservation = 0;
            Array.Fill(this.action, 0);
        }
        public void SetActions(string? agentGroupName, ndarray actions) {
            if (agentGroupName != null) throw new KeyNotFoundException();
            for (int agentN = 0; agentN < this.action.Length; agentN++)
                this.action[agentN] = (float32)actions[agentN, 0];
        }
        public void Step() {
            this.previousObservation = this.observation;
            this.observation = (float)this.random.NextDouble() * 2 - 1;
        }

        public static void SanityCheck() {
            // sanity check
            var env = new RepeatObservationEnvironment(agents: 3);
            env.Reset();
            env.Step();
            for(int episode = 0; episode < 100; episode++) {
                var observation = (ndarray)env.GetStepResult(null).obs[0];
                env.SetActions(null, observation);
                env.Step();
                var step = env.GetStepResult(null);
                ndarray success = step.reward.__ge___dyn(1.99f);
                bool allPass = success.all_dyn(keepdims: new ImplicitContainer<object>(null));
                Trace.Assert(allPass);
            }
        }
    }
}