From ffb55b41429b78d48ca93164cbee898481f74d23 Mon Sep 17 00:00:00 2001 From: anabwan <46447582+anabwan@users.noreply.github.com> Date: Tue, 7 May 2019 10:04:05 +0300 Subject: [PATCH] tests: update traces (#302) * Traces folder removed from repo and moved to S3 * Traces jobs and update will use directly the S3 files --- .circleci/config.yml | 110 +- rl_coach/tests/trace_tests.py | 70 +- .../traces/Atari_A3C_LSTM_breakout/trace.csv | 201 --- rl_coach/traces/Atari_A3C_LSTM_pong/trace.csv | 6 - .../Atari_A3C_LSTM_space_invaders/trace.csv | 31 - rl_coach/traces/Atari_A3C_breakout/trace.csv | 201 --- rl_coach/traces/Atari_A3C_pong/trace.csv | 6 - .../traces/Atari_A3C_space_invaders/trace.csv | 31 - .../Atari_Bootstrapped_DQN_breakout/trace.csv | 201 --- .../Atari_Bootstrapped_DQN_pong/trace.csv | 6 - .../trace.csv | 26 - rl_coach/traces/Atari_C51_breakout/trace.csv | 176 -- rl_coach/traces/Atari_C51_pong/trace.csv | 6 - .../traces/Atari_C51_space_invaders/trace.csv | 26 - rl_coach/traces/Atari_DDQN_breakout/trace.csv | 176 -- rl_coach/traces/Atari_DDQN_pong/trace.csv | 6 - .../Atari_DDQN_space_invaders/trace.csv | 21 - .../Atari_DDQN_with_PER_breakout/trace.csv | 206 --- .../traces/Atari_DDQN_with_PER_pong/trace.csv | 6 - .../trace.csv | 26 - rl_coach/traces/Atari_DQN_breakout/trace.csv | 181 -- rl_coach/traces/Atari_DQN_pong/trace.csv | 6 - .../traces/Atari_DQN_space_invaders/trace.csv | 21 - .../Atari_DQN_with_PER_breakout/trace.csv | 201 --- .../traces/Atari_DQN_with_PER_pong/trace.csv | 6 - .../trace.csv | 26 - .../Atari_Dueling_DDQN_breakout/trace.csv | 176 -- .../traces/Atari_Dueling_DDQN_pong/trace.csv | 6 - .../trace.csv | 26 - .../trace.csv | 196 --- .../trace.csv | 6 - .../trace.csv | 26 - .../traces/Atari_NStepQ_breakout/trace.csv | 171 -- rl_coach/traces/Atari_NStepQ_pong/trace.csv | 6 - .../Atari_NStepQ_space_invaders/trace.csv | 21 - .../traces/Atari_QR_DQN_breakout/trace.csv | 176 -- rl_coach/traces/Atari_QR_DQN_pong/trace.csv | 6 - .../Atari_QR_DQN_space_invaders/trace.csv | 26 - .../trace.csv | 206 --- .../Atari_UCB_with_Q_Ensembles_pong/trace.csv | 6 - .../trace.csv | 26 - rl_coach/traces/BitFlip_DQN/trace.csv | 761 -------- rl_coach/traces/BitFlip_DQN_HER/trace.csv | 301 ---- rl_coach/traces/CartPole_A3C/trace.csv | 211 --- rl_coach/traces/CartPole_DFP/trace.csv | 96 -- rl_coach/traces/CartPole_DQN/trace.csv | 166 -- .../traces/CartPole_Dueling_DDQN/trace.csv | 196 --- rl_coach/traces/CartPole_NStepQ/trace.csv | 171 -- rl_coach/traces/CartPole_PAL/trace.csv | 161 -- rl_coach/traces/CartPole_PG/trace.csv | 236 --- .../trace.csv | 6 - .../ControlSuite_DDPG_hopper_hop/trace.csv | 6 - rl_coach/traces/Doom_Basic_A3C/trace.csv | 136 -- rl_coach/traces/Doom_Basic_DFP/trace.csv | 66 - rl_coach/traces/Doom_Basic_DQN/trace.csv | 136 -- .../traces/Doom_Basic_Dueling_DDQN/trace.csv | 151 -- rl_coach/traces/Doom_Battle_DFP/trace.csv | 56 - .../trace.csv | 221 --- .../ExplorationChain_Dueling_DDQN/trace.csv | 221 --- .../trace.csv | 221 --- .../trace.csv | 121 -- .../Fetch_DDPG_HER_baselines_push/trace.csv | 121 -- .../Fetch_DDPG_HER_baselines_reach/trace.csv | 121 -- .../Fetch_DDPG_HER_baselines_slide/trace.csv | 121 -- rl_coach/traces/InvertedPendulum_PG/trace.csv | 301 ---- .../traces/Mujoco_A3C_LSTM_hopper/trace.csv | 226 --- .../trace.csv | 616 ------- rl_coach/traces/Mujoco_A3C_hopper/trace.csv | 166 -- .../Mujoco_A3C_inverted_pendulum/trace.csv | 601 ------- .../traces/Mujoco_ClippedPPO_hopper/trace.csv | 216 --- .../trace.csv | 641 ------- rl_coach/traces/Mujoco_DDPG_hopper/trace.csv | 116 -- .../Mujoco_DDPG_inverted_pendulum/trace.csv | 741 -------- rl_coach/traces/Mujoco_NAF_hopper/trace.csv | 266 --- .../Mujoco_NAF_inverted_pendulum/trace.csv | 1531 ----------------- rl_coach/traces/Mujoco_PPO_hopper/trace.csv | 276 --- .../Mujoco_PPO_inverted_pendulum/trace.csv | 766 --------- rl_coach/traces/Pendulum_HAC/trace.csv | 6 - .../Starcraft_CollectMinerals_A3C/trace.csv | 11 - .../trace.csv | 11 - 80 files changed, 174 insertions(+), 13379 deletions(-) delete mode 100644 rl_coach/traces/Atari_A3C_LSTM_breakout/trace.csv delete mode 100644 rl_coach/traces/Atari_A3C_LSTM_pong/trace.csv delete mode 100644 rl_coach/traces/Atari_A3C_LSTM_space_invaders/trace.csv delete mode 100644 rl_coach/traces/Atari_A3C_breakout/trace.csv delete mode 100644 rl_coach/traces/Atari_A3C_pong/trace.csv delete mode 100644 rl_coach/traces/Atari_A3C_space_invaders/trace.csv delete mode 100644 rl_coach/traces/Atari_Bootstrapped_DQN_breakout/trace.csv delete mode 100644 rl_coach/traces/Atari_Bootstrapped_DQN_pong/trace.csv delete mode 100644 rl_coach/traces/Atari_Bootstrapped_DQN_space_invaders/trace.csv delete mode 100644 rl_coach/traces/Atari_C51_breakout/trace.csv delete mode 100644 rl_coach/traces/Atari_C51_pong/trace.csv delete mode 100644 rl_coach/traces/Atari_C51_space_invaders/trace.csv delete mode 100644 rl_coach/traces/Atari_DDQN_breakout/trace.csv delete mode 100644 rl_coach/traces/Atari_DDQN_pong/trace.csv delete mode 100644 rl_coach/traces/Atari_DDQN_space_invaders/trace.csv delete mode 100644 rl_coach/traces/Atari_DDQN_with_PER_breakout/trace.csv delete mode 100644 rl_coach/traces/Atari_DDQN_with_PER_pong/trace.csv delete mode 100644 rl_coach/traces/Atari_DDQN_with_PER_space_invaders/trace.csv delete mode 100644 rl_coach/traces/Atari_DQN_breakout/trace.csv delete mode 100644 rl_coach/traces/Atari_DQN_pong/trace.csv delete mode 100644 rl_coach/traces/Atari_DQN_space_invaders/trace.csv delete mode 100644 rl_coach/traces/Atari_DQN_with_PER_breakout/trace.csv delete mode 100644 rl_coach/traces/Atari_DQN_with_PER_pong/trace.csv delete mode 100644 rl_coach/traces/Atari_DQN_with_PER_space_invaders/trace.csv delete mode 100644 rl_coach/traces/Atari_Dueling_DDQN_breakout/trace.csv delete mode 100644 rl_coach/traces/Atari_Dueling_DDQN_pong/trace.csv delete mode 100644 rl_coach/traces/Atari_Dueling_DDQN_space_invaders/trace.csv delete mode 100644 rl_coach/traces/Atari_Dueling_DDQN_with_PER_OpenAI_breakout/trace.csv delete mode 100644 rl_coach/traces/Atari_Dueling_DDQN_with_PER_OpenAI_pong/trace.csv delete mode 100644 rl_coach/traces/Atari_Dueling_DDQN_with_PER_OpenAI_space_invaders/trace.csv delete mode 100644 rl_coach/traces/Atari_NStepQ_breakout/trace.csv delete mode 100644 rl_coach/traces/Atari_NStepQ_pong/trace.csv delete mode 100644 rl_coach/traces/Atari_NStepQ_space_invaders/trace.csv delete mode 100644 rl_coach/traces/Atari_QR_DQN_breakout/trace.csv delete mode 100644 rl_coach/traces/Atari_QR_DQN_pong/trace.csv delete mode 100644 rl_coach/traces/Atari_QR_DQN_space_invaders/trace.csv delete mode 100644 rl_coach/traces/Atari_UCB_with_Q_Ensembles_breakout/trace.csv delete mode 100644 rl_coach/traces/Atari_UCB_with_Q_Ensembles_pong/trace.csv delete mode 100644 rl_coach/traces/Atari_UCB_with_Q_Ensembles_space_invaders/trace.csv delete mode 100644 rl_coach/traces/BitFlip_DQN/trace.csv delete mode 100644 rl_coach/traces/BitFlip_DQN_HER/trace.csv delete mode 100644 rl_coach/traces/CartPole_A3C/trace.csv delete mode 100644 rl_coach/traces/CartPole_DFP/trace.csv delete mode 100644 rl_coach/traces/CartPole_DQN/trace.csv delete mode 100644 rl_coach/traces/CartPole_Dueling_DDQN/trace.csv delete mode 100644 rl_coach/traces/CartPole_NStepQ/trace.csv delete mode 100644 rl_coach/traces/CartPole_PAL/trace.csv delete mode 100644 rl_coach/traces/CartPole_PG/trace.csv delete mode 100644 rl_coach/traces/ControlSuite_DDPG_cartpole_swingup/trace.csv delete mode 100644 rl_coach/traces/ControlSuite_DDPG_hopper_hop/trace.csv delete mode 100644 rl_coach/traces/Doom_Basic_A3C/trace.csv delete mode 100644 rl_coach/traces/Doom_Basic_DFP/trace.csv delete mode 100644 rl_coach/traces/Doom_Basic_DQN/trace.csv delete mode 100644 rl_coach/traces/Doom_Basic_Dueling_DDQN/trace.csv delete mode 100644 rl_coach/traces/Doom_Battle_DFP/trace.csv delete mode 100644 rl_coach/traces/ExplorationChain_Bootstrapped_DQN/trace.csv delete mode 100644 rl_coach/traces/ExplorationChain_Dueling_DDQN/trace.csv delete mode 100644 rl_coach/traces/ExplorationChain_UCB_Q_ensembles/trace.csv delete mode 100644 rl_coach/traces/Fetch_DDPG_HER_baselines_pick_and_place/trace.csv delete mode 100644 rl_coach/traces/Fetch_DDPG_HER_baselines_push/trace.csv delete mode 100644 rl_coach/traces/Fetch_DDPG_HER_baselines_reach/trace.csv delete mode 100644 rl_coach/traces/Fetch_DDPG_HER_baselines_slide/trace.csv delete mode 100644 rl_coach/traces/InvertedPendulum_PG/trace.csv delete mode 100644 rl_coach/traces/Mujoco_A3C_LSTM_hopper/trace.csv delete mode 100644 rl_coach/traces/Mujoco_A3C_LSTM_inverted_pendulum/trace.csv delete mode 100644 rl_coach/traces/Mujoco_A3C_hopper/trace.csv delete mode 100644 rl_coach/traces/Mujoco_A3C_inverted_pendulum/trace.csv delete mode 100644 rl_coach/traces/Mujoco_ClippedPPO_hopper/trace.csv delete mode 100644 rl_coach/traces/Mujoco_ClippedPPO_inverted_pendulum/trace.csv delete mode 100644 rl_coach/traces/Mujoco_DDPG_hopper/trace.csv delete mode 100644 rl_coach/traces/Mujoco_DDPG_inverted_pendulum/trace.csv delete mode 100644 rl_coach/traces/Mujoco_NAF_hopper/trace.csv delete mode 100644 rl_coach/traces/Mujoco_NAF_inverted_pendulum/trace.csv delete mode 100644 rl_coach/traces/Mujoco_PPO_hopper/trace.csv delete mode 100644 rl_coach/traces/Mujoco_PPO_inverted_pendulum/trace.csv delete mode 100644 rl_coach/traces/Pendulum_HAC/trace.csv delete mode 100644 rl_coach/traces/Starcraft_CollectMinerals_A3C/trace.csv delete mode 100644 rl_coach/traces/Starcraft_CollectMinerals_Dueling_DDQN/trace.csv diff --git a/.circleci/config.yml b/.circleci/config.yml index baab360..b4a7b18 100644 --- a/.circleci/config.yml +++ b/.circleci/config.yml @@ -345,6 +345,7 @@ jobs: - run: name: run gym related trace tests command: | + aws s3 cp s3://coach-traces-aws rl_coach/traces --recursive \ export TRACE_PRESETS='CartPole_A3C,CartPole_Dueling_DDQN,CartPole_NStepQ,CartPole_DQN,CartPole_DFP,CartPole_PG,CartPole_NEC,CartPole_ClippedPPO,CartPole_PAL' python3 rl_coach/tests/test_eks.py -c coach-test -bn ${CIRCLE_BUILD_NUM} -tn trace-test-gym -tc "export TRACE_PRESETS=${TRACE_PRESETS} && make trace_tests_without_docker" -i 316971102342.dkr.ecr.us-west-2.amazonaws.com/coach-gym_environment:$(git describe --tags --always --dirty) -cpu 2048 -mem 4096 no_output_timeout: 30m @@ -365,6 +366,7 @@ jobs: - run: name: run doom related trace tests command: | + aws s3 cp s3://coach-traces-aws rl_coach/traces --recursive \ export TRACE_PRESETS='Doom_Basic_DQN,Doom_Basic_A3C,Doom_Health_DFP' python3 rl_coach/tests/test_eks.py -c coach-test -bn ${CIRCLE_BUILD_NUM} -tn trace-test-doom -tc "export TRACE_PRESETS=${TRACE_PRESETS} && make trace_tests_without_docker" -i 316971102342.dkr.ecr.us-west-2.amazonaws.com/coach-doom_environment:$(git describe --tags --always --dirty) -cpu 2048 -mem 4096 no_output_timeout: 30m @@ -385,6 +387,7 @@ jobs: - run: name: run mujoco related trace tests command: | + aws s3 cp s3://coach-traces-aws rl_coach/traces --recursive \ export TRACE_PRESETS='BitFlip_DQN_HER,BitFlip_DQN,Mujoco_A3C,Mujoco_A3C_LSTM,Mujoco_PPO,Mujoco_ClippedPPO,Mujoco_DDPG' python3 rl_coach/tests/test_eks.py -c coach-test -bn ${CIRCLE_BUILD_NUM} -tn trace-test-mujoco -tc "export TRACE_PRESETS=${TRACE_PRESETS} && make trace_tests_without_docker" -i 316971102342.dkr.ecr.us-west-2.amazonaws.com/coach-mujoco_environment:$(git describe --tags --always --dirty) -cpu 2048 -mem 4096 no_output_timeout: 45m @@ -395,7 +398,100 @@ jobs: kubectl delete ns trace-test-mujoco-${CIRCLE_BUILD_NUM} || true when: always -# Starcraft is running too long for evaluation on nightly runs. Consider running in weekly test. + update_gym_traces_test: + <<: *executor_prep + steps: + - checkout + - *remote_docker + - *restore_cache + - *aws_prep + - run: + name: Update GYM traces + command: | + kubectl create ns trace-test-gym-test-${CIRCLE_BUILD_NUM} + docker run -e CIRCLE_BUILD_NUM=$CIRCLE_BUILD_NUM -e TAG=$(git describe --tags --always --dirty) -e AWS_SECRET_ACCESS_KEY=$AWS_SECRET_ACCESS_KEY -e AWS_ACCESS_KEY_ID=$AWS_ACCESS_KEY_ID -e AWS_DEFAULT_REGION=$AWS_DEFAULT_REGION 316971102342.dkr.ecr.us-west-2.amazonaws.com/coach-gym_environment:$(git describe --tags --always --dirty) \ + /bin/bash -c 'pip install awscli; curl -o /usr/local/bin/aws-iam-authenticator https://amazon-eks.s3-us-west-2.amazonaws.com/1.10.3/2018-07-26/bin/linux/amd64/aws-iam-authenticator \ + && chmod a+x /usr/local/bin/aws-iam-authenticator \ + && aws eks update-kubeconfig --name coach-aws-cicd \ + && curl -o /usr/local/bin/kubectl https://storage.googleapis.com/kubernetes-release/release/$(curl -s https://storage.googleapis.com/kubernetes-release/release/stable.txt)/bin/linux/amd64/kubectl \ + && chmod a+x /usr/local/bin/kubectl \ + && kubectl config set-context $(kubectl config current-context) --namespace=trace-test-gym-test-${CIRCLE_BUILD_NUM} \ + && aws s3 cp s3://coach-traces-aws rl_coach/traces --recursive \ + && TRACE_PRESETS="CartPole_A3C,CartPole_Dueling_DDQN,CartPole_NStepQ,CartPole_DQN,CartPole_DFP,CartPole_PG,CartPole_NEC,CartPole_ClippedPPO,CartPole_PAL" \ + && python3 rl_coach/tests/trace_tests.py -p ${TRACE_PRESETS} -prl -ow -ut -i 316971102342.dkr.ecr.us-west-2.amazonaws.com/coach-gym_environment:${TAG} -b coach-trace-gym-aws-test-${CIRCLE_BUILD_NUM}' + docker ps -a -q | head -n 1 | xargs -I% docker cp %:/root/src/rl_coach/traces . || true + aws s3 sync ~/repo/traces s3://coach-traces-aws || true + no_output_timeout: 30m + - run: + name: cleanup + command: | + kubectl delete --all pods --namespace=trace-test-gym-test-${CIRCLE_BUILD_NUM} || true + kubectl delete ns trace-test-gym-test-${CIRCLE_BUILD_NUM} || true + when: always + + update_doom_traces_test: + <<: *executor_prep + steps: + - checkout + - *remote_docker + - *restore_cache + - *aws_prep + - run: + name: Update DOOM traces + command: | + kubectl create ns trace-test-doom-test-${CIRCLE_BUILD_NUM} + docker run -e CIRCLE_BUILD_NUM=$CIRCLE_BUILD_NUM -e TAG=$(git describe --tags --always --dirty) -e AWS_SECRET_ACCESS_KEY=$AWS_SECRET_ACCESS_KEY -e AWS_ACCESS_KEY_ID=$AWS_ACCESS_KEY_ID -e AWS_DEFAULT_REGION=$AWS_DEFAULT_REGION 316971102342.dkr.ecr.us-west-2.amazonaws.com/coach-doom_environment:$(git describe --tags --always --dirty) \ + /bin/bash -c 'pip install awscli; curl -o /usr/local/bin/aws-iam-authenticator https://amazon-eks.s3-us-west-2.amazonaws.com/1.10.3/2018-07-26/bin/linux/amd64/aws-iam-authenticator \ + && chmod a+x /usr/local/bin/aws-iam-authenticator \ + && aws eks update-kubeconfig --name coach-aws-cicd \ + && curl -o /usr/local/bin/kubectl https://storage.googleapis.com/kubernetes-release/release/$(curl -s https://storage.googleapis.com/kubernetes-release/release/stable.txt)/bin/linux/amd64/kubectl \ + && chmod a+x /usr/local/bin/kubectl \ + && kubectl config set-context $(kubectl config current-context) --namespace=trace-test-doom-test-${CIRCLE_BUILD_NUM} \ + && aws s3 cp s3://coach-traces-aws rl_coach/traces --recursive \ + && TRACE_PRESETS="Doom_Basic_DQN,Doom_Basic_A3C,Doom_Health_DFP" \ + && python3 rl_coach/tests/trace_tests.py -p ${TRACE_PRESETS} -prl -ow -ut -i 316971102342.dkr.ecr.us-west-2.amazonaws.com/coach-doom_environment:${TAG} -b coach-trace-doom-aws-test-${CIRCLE_BUILD_NUM}' + docker ps -a -q | head -n 1 | xargs -I% docker cp %:/root/src/rl_coach/traces . || true + aws s3 sync ~/repo/traces s3://coach-traces-aws || true + no_output_timeout: 30m + - run: + name: cleanup + command: | + kubectl delete --all pods --namespace=trace-test-doom-test-${CIRCLE_BUILD_NUM} || true + kubectl delete ns trace-test-doom-test-${CIRCLE_BUILD_NUM} || true + when: always + + update_mujoco_traces_test: + <<: *executor_prep + steps: + - checkout + - *remote_docker + - *restore_cache + - *aws_prep + - run: + name: Update MUJOCO traces + command: | + kubectl create ns trace-test-mujoco-test-${CIRCLE_BUILD_NUM} + docker run -e CIRCLE_BUILD_NUM=$CIRCLE_BUILD_NUM -e TAG=$(git describe --tags --always --dirty) -e AWS_SECRET_ACCESS_KEY=$AWS_SECRET_ACCESS_KEY -e AWS_ACCESS_KEY_ID=$AWS_ACCESS_KEY_ID -e AWS_DEFAULT_REGION=$AWS_DEFAULT_REGION 316971102342.dkr.ecr.us-west-2.amazonaws.com/coach-mujoco_environment:$(git describe --tags --always --dirty) \ + /bin/bash -c 'pip install awscli; curl -o /usr/local/bin/aws-iam-authenticator https://amazon-eks.s3-us-west-2.amazonaws.com/1.10.3/2018-07-26/bin/linux/amd64/aws-iam-authenticator \ + && chmod a+x /usr/local/bin/aws-iam-authenticator \ + && aws eks update-kubeconfig --name coach-aws-cicd \ + && curl -o /usr/local/bin/kubectl https://storage.googleapis.com/kubernetes-release/release/$(curl -s https://storage.googleapis.com/kubernetes-release/release/stable.txt)/bin/linux/amd64/kubectl \ + && chmod a+x /usr/local/bin/kubectl \ + && kubectl config set-context $(kubectl config current-context) --namespace=trace-test-mujoco-test-${CIRCLE_BUILD_NUM} \ + && aws s3 cp s3://coach-traces-aws rl_coach/traces --recursive \ + && TRACE_PRESETS="BitFlip_DQN_HER,BitFlip_DQN,Mujoco_A3C,Mujoco_A3C_LSTM,Mujoco_PPO,Mujoco_ClippedPPO,Mujoco_DDPG" \ + && python3 rl_coach/tests/trace_tests.py -p ${TRACE_PRESETS} -prl -ow -ut -i 316971102342.dkr.ecr.us-west-2.amazonaws.com/coach-mujoco_environment:${TAG} -b coach-trace-mujoco-aws-test-${CIRCLE_BUILD_NUM}' + docker ps -a -q | head -n 1 | xargs -I% docker cp %:/root/src/rl_coach/traces . || true + aws s3 sync ~/repo/traces s3://coach-traces-aws || true + no_output_timeout: 30m + - run: + name: cleanup + command: | + kubectl delete --all pods --namespace=trace-test-mujoco-test-${CIRCLE_BUILD_NUM} || true + kubectl delete ns trace-test-mujoco-test-${CIRCLE_BUILD_NUM} || true + when: always + +# Starcraft is running too long for evaluation on nightly runs. Consider running in weekly test # trace_test_starcraft: # <<: *executor_prep # steps: @@ -542,6 +638,18 @@ workflows: # - golden_test_starcraft: # requires: # - build_starcraft_env + - update_gym_traces_test: + requires: + - trace_test_gym + type: approval + - update_doom_traces_test: + requires: + - trace_test_doom + type: approval + - update_mujoco_traces_test: + requires: + - trace_test_mujoco + type: approval - trace_test_gym: requires: - gym_approval diff --git a/rl_coach/tests/trace_tests.py b/rl_coach/tests/trace_tests.py index 39095f7..f235eb8 100644 --- a/rl_coach/tests/trace_tests.py +++ b/rl_coach/tests/trace_tests.py @@ -22,15 +22,15 @@ import subprocess import multiprocessing import sys import signal +import pandas as pd +import time +from configparser import ConfigParser from importlib import import_module from os import path sys.path.append('.') -import pandas as pd -import time - -# -*- coding: utf-8 -*- from rl_coach.logger import screen + processes = [] @@ -45,6 +45,7 @@ def sigint_handler(signum, frame): os.remove(f) exit() + signal.signal(signal.SIGINT, sigint_handler) @@ -76,12 +77,15 @@ def run_trace_based_test(preset_name, num_env_steps, level=None): screen.log_title("Running test {}{}".format(preset_name, ' - ' + level if level else '')) log_file_name = 'trace_test_log_{preset_name}.txt'.format(preset_name=test_name[13:]) + config_file = './tmp.cred' + cmd = ( 'python3 rl_coach/coach.py ' '-p {preset_name} ' '-e {test_name} ' '--seed 42 ' '-c ' + '-dcp {template}' '--no_summary ' '-cp {custom_param} ' '{level} ' @@ -89,6 +93,7 @@ def run_trace_based_test(preset_name, num_env_steps, level=None): ).format( preset_name=preset_name, test_name=test_name, + template=config_file, log_file_name=log_file_name, level='-lvl ' + level if level else '', custom_param='\"improve_steps=EnvironmentSteps({n});' @@ -166,6 +171,31 @@ def wait_and_check(args, processes, force=False): return test_passed +def generate_config(image, memory_backend, s3_end_point, s3_bucket_name, s3_creds_file, config_file): + """ + Generate the s3 config file to be used and also the dist-coach-config.template to be used for the test + It reads the `AWS_ACCESS_KEY_ID` and `AWS_SECRET_ACCESS_KEY` env vars and fails if they are not provided. + """ + # Write s3 creds + aws_config = ConfigParser({ + 'aws_access_key_id': os.environ.get('AWS_ACCESS_KEY_ID'), + 'aws_secret_access_key': os.environ.get('AWS_SECRET_ACCESS_KEY') + }, default_section='default') + with open(s3_creds_file, 'w') as f: + aws_config.write(f) + + coach_config = ConfigParser({ + 'image': image, + 'memory_backend': memory_backend, + 'data_store': 's3', + 's3_end_point': s3_end_point, + 's3_bucket_name': s3_bucket_name, + 's3_creds_file': s3_creds_file + }, default_section="coach") + with open(config_file, 'w') as f: + coach_config.write(f) + + def main(): parser = argparse.ArgumentParser() parser.add_argument('-p', '--preset', '--presets', @@ -188,12 +218,42 @@ def main(): parser.add_argument('-prl', '--parallel', help="(flag) run tests in parallel", action='store_true') + parser.add_argument('-ut', '--update_traces', + help="(flag) update traces on repository", + action='store_true') parser.add_argument('-mt', '--max_threads', help="(int) maximum number of threads to run in parallel", default=multiprocessing.cpu_count()-2, type=int) + parser.add_argument( + '-i', '--image', help="(string) Name of the testing image", type=str, default=None + ) + parser.add_argument( + '-mb', '--memory_backend', help="(string) Name of the memory backend", type=str, default="redispubsub" + ) + parser.add_argument( + '-e', '--endpoint', help="(string) Name of the s3 endpoint", type=str, default='s3.amazonaws.com' + ) + parser.add_argument( + '-cr', '--creds_file', help="(string) Path of the s3 creds file", type=str, default='.aws_creds' + ) + parser.add_argument( + '-b', '--bucket', help="(string) Name of the bucket for s3", type=str, default=None + ) args = parser.parse_args() + + if args.update_traces: + if not args.bucket: + print("bucket_name required for s3") + exit(1) + if not os.environ.get('AWS_ACCESS_KEY_ID') or not os.environ.get('AWS_SECRET_ACCESS_KEY'): + print("AWS_ACCESS_KEY_ID and AWS_SECRET_ACCESS_KEY env vars need to be set") + exit(1) + + config_file = './tmp.cred' + generate_config(args.image, args.memory_backend, args.endpoint, args.bucket, args.creds_file, config_file) + if not args.parallel: args.max_threads = 1 @@ -251,7 +311,7 @@ def main(): if fail_count == 0: screen.success(" Summary: " + str(test_count) + "/" + str(test_count) + " tests passed successfully") else: - screen.error(" Summary: " + str(test_count - fail_count) + "/" + str(test_count) + " tests passed successfully") + screen.error(" Summary: " + str(test_count - fail_count) + "/" + str(test_count) + " tests passed successfully", crash=False) if __name__ == '__main__': diff --git a/rl_coach/traces/Atari_A3C_LSTM_breakout/trace.csv b/rl_coach/traces/Atari_A3C_LSTM_breakout/trace.csv deleted file mode 100644 index 72ea6a4..0000000 --- a/rl_coach/traces/Atari_A3C_LSTM_breakout/trace.csv +++ /dev/null @@ -1,201 +0,0 @@ -Episode #,Training Iter,In Heatup,ER #Transitions,ER #Episodes,Episode Length,Total steps,Epsilon,Shaped Training Reward,Training Reward,Update Target Network,Evaluation Reward,Shaped Evaluation Reward,Success Rate,Loss/Mean,Loss/Stdev,Loss/Max,Loss/Min,Learning Rate/Mean,Learning Rate/Stdev,Learning Rate/Max,Learning Rate/Min,Grads (unclipped)/Mean,Grads (unclipped)/Stdev,Grads (unclipped)/Max,Grads (unclipped)/Min,Discounted Return/Mean,Discounted Return/Stdev,Discounted Return/Max,Discounted Return/Min,Entropy/Mean,Entropy/Stdev,Entropy/Max,Entropy/Min,Advantages/Mean,Advantages/Stdev,Advantages/Max,Advantages/Min,Values/Mean,Values/Stdev,Values/Max,Values/Min,Value Loss/Mean,Value Loss/Stdev,Value Loss/Max,Value Loss/Min,Policy Loss/Mean,Policy Loss/Stdev,Policy Loss/Max,Policy Loss/Min 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index 7c23961..0000000 --- a/rl_coach/traces/Atari_A3C_breakout/trace.csv +++ /dev/null @@ -1,201 +0,0 @@ -Episode #,Training Iter,In Heatup,ER #Transitions,ER #Episodes,Episode Length,Total steps,Epsilon,Shaped Training Reward,Training Reward,Update Target Network,Evaluation Reward,Shaped Evaluation Reward,Success Rate,Loss/Mean,Loss/Stdev,Loss/Max,Loss/Min,Learning Rate/Mean,Learning Rate/Stdev,Learning Rate/Max,Learning Rate/Min,Grads (unclipped)/Mean,Grads (unclipped)/Stdev,Grads (unclipped)/Max,Grads (unclipped)/Min,Discounted Return/Mean,Discounted Return/Stdev,Discounted Return/Max,Discounted Return/Min,Entropy/Mean,Entropy/Stdev,Entropy/Max,Entropy/Min,Advantages/Mean,Advantages/Stdev,Advantages/Max,Advantages/Min,Values/Mean,Values/Stdev,Values/Max,Values/Min,Value Loss/Mean,Value Loss/Stdev,Value Loss/Max,Value Loss/Min,Policy Loss/Mean,Policy Loss/Stdev,Policy Loss/Max,Policy Loss/Min -1,0.0,1.0,24.0,1.0,24.0,24.0,0.0,,,0.0,,,,,,,,,,,,,,,,0.0,0.0,0.0,0.0,,,,,,,,,,,,,,,,,,,, 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--- a/rl_coach/traces/Atari_A3C_pong/trace.csv +++ /dev/null @@ -1,6 +0,0 @@ -Episode #,Training Iter,In Heatup,ER #Transitions,ER #Episodes,Episode Length,Total steps,Epsilon,Shaped Training Reward,Training Reward,Update Target Network,Evaluation Reward,Shaped Evaluation Reward,Success Rate,Loss/Mean,Loss/Stdev,Loss/Max,Loss/Min,Learning Rate/Mean,Learning Rate/Stdev,Learning Rate/Max,Learning Rate/Min,Grads (unclipped)/Mean,Grads (unclipped)/Stdev,Grads (unclipped)/Max,Grads (unclipped)/Min,Discounted Return/Mean,Discounted Return/Stdev,Discounted Return/Max,Discounted Return/Min,Entropy/Mean,Entropy/Stdev,Entropy/Max,Entropy/Min,Advantages/Mean,Advantages/Stdev,Advantages/Max,Advantages/Min,Values/Mean,Values/Stdev,Values/Max,Values/Min,Value Loss/Mean,Value Loss/Stdev,Value Loss/Max,Value Loss/Min,Policy Loss/Mean,Policy Loss/Stdev,Policy Loss/Max,Policy Loss/Min 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a/rl_coach/traces/Atari_A3C_space_invaders/trace.csv b/rl_coach/traces/Atari_A3C_space_invaders/trace.csv deleted file mode 100644 index b19a756..0000000 --- a/rl_coach/traces/Atari_A3C_space_invaders/trace.csv +++ /dev/null @@ -1,31 +0,0 @@ -Episode #,Training Iter,In Heatup,ER #Transitions,ER #Episodes,Episode Length,Total steps,Epsilon,Shaped Training Reward,Training Reward,Update Target Network,Evaluation Reward,Shaped Evaluation Reward,Success Rate,Loss/Mean,Loss/Stdev,Loss/Max,Loss/Min,Learning Rate/Mean,Learning Rate/Stdev,Learning Rate/Max,Learning Rate/Min,Grads (unclipped)/Mean,Grads (unclipped)/Stdev,Grads (unclipped)/Max,Grads (unclipped)/Min,Discounted Return/Mean,Discounted Return/Stdev,Discounted Return/Max,Discounted Return/Min,Entropy/Mean,Entropy/Stdev,Entropy/Max,Entropy/Min,Advantages/Mean,Advantages/Stdev,Advantages/Max,Advantages/Min,Values/Mean,Values/Stdev,Values/Max,Values/Min,Value Loss/Mean,Value Loss/Stdev,Value Loss/Max,Value Loss/Min,Policy 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Return/Min,Q/Mean,Q/Stdev,Q/Max,Q/Min -1,0.0,1.0,1117.0,1117.0,1117.0,1117.0,1.0,,,0.0,,,,,,,,,,,,,,,,-1.5180229894995567,0.6998808293377133,-0.08930329112720292,-3.148474706421977,,,, -2,205.0,0.0,1937.0,1937.0,820.0,1937.0,0.9991882000000176,-21.0,-21.0,0.0,,,,3.9304792799600734,0.0010089336974329131,3.931626558303833,3.92692494392395,0.0002500000000000001,1.0842021724855042e-19,0.00025,0.00025,0.0020478016,0.0020630334,0.012544215,0.00089145615,-2.3361342922088504,0.784322378590693,-0.38878391807422696,-3.369599601005491,,,, -3,413.0,0.0,2768.0,2768.0,831.0,2768.0,0.9983655100000356,-21.0,-21.0,0.0,,,,3.929040307035813,0.0010817403254347628,3.9303982257843018,3.922320127487183,0.0002500000000000001,1.0842021724855042e-19,0.00025,0.00025,0.0013938454,0.0020394863,0.01589611,0.0005865627,-2.320394201181889,0.6047235028955231,-0.7105532272722921,-3.350537576335216,0.06064815086623099,0.017702449170361085,0.09529060125351008,0.03914397135377001 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index ad0620f..0000000 --- a/rl_coach/traces/Atari_C51_space_invaders/trace.csv +++ /dev/null @@ -1,26 +0,0 @@ -Episode #,Training Iter,In Heatup,ER #Transitions,ER #Episodes,Episode Length,Total steps,Epsilon,Shaped Training Reward,Training Reward,Update Target Network,Evaluation Reward,Shaped Evaluation Reward,Success Rate,Loss/Mean,Loss/Stdev,Loss/Max,Loss/Min,Learning Rate/Mean,Learning Rate/Stdev,Learning Rate/Max,Learning Rate/Min,Grads (unclipped)/Mean,Grads (unclipped)/Stdev,Grads (unclipped)/Max,Grads (unclipped)/Min,Discounted Return/Mean,Discounted Return/Stdev,Discounted Return/Max,Discounted Return/Min,Q/Mean,Q/Stdev,Q/Max,Q/Min -1,0.0,1.0,486.0,486.0,486.0,486.0,1.0,,,0.0,,,,,,,,,,,,,,,,1.027285241237078,0.8961037725396955,3.502959469093688,0.0,,,, -2,0.0,1.0,573.0,573.0,87.0,573.0,1.0,,,0.0,,,,,,,,,,,,,,,,0.2991949731169189,0.4147830569909918,1.0,0.0,,,, 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a/rl_coach/traces/Atari_DDQN_space_invaders/trace.csv +++ /dev/null @@ -1,21 +0,0 @@ -Episode #,Training Iter,In Heatup,ER #Transitions,ER #Episodes,Episode Length,Total steps,Epsilon,Shaped Training Reward,Training Reward,Update Target Network,Evaluation Reward,Shaped Evaluation Reward,Success Rate,Loss/Mean,Loss/Stdev,Loss/Max,Loss/Min,Learning Rate/Mean,Learning Rate/Stdev,Learning Rate/Max,Learning Rate/Min,Grads (unclipped)/Mean,Grads (unclipped)/Stdev,Grads (unclipped)/Max,Grads (unclipped)/Min,Discounted Return/Mean,Discounted Return/Stdev,Discounted Return/Max,Discounted Return/Min,Q/Mean,Q/Stdev,Q/Max,Q/Min -1,0.0,1.0,486.0,486.0,486.0,486.0,1.0,,,0.0,,,,,,,,,,,,,,,,1.027285241237078,0.8961037725396955,3.502959469093688,0.0,,,, -2,0.0,1.0,573.0,573.0,87.0,573.0,1.0,,,0.0,,,,,,,,,,,,,,,,0.2991949731169189,0.4147830569909918,1.0,0.0,,,, -3,0.0,1.0,722.0,722.0,149.0,722.0,1.0,,,0.0,,,,,,,,,,,,,,,,1.089942054123867,0.6773639260883686,1.9560606270183023,0.0,,,, 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Reward,Shaped Evaluation Reward,Success Rate,Loss/Mean,Loss/Stdev,Loss/Max,Loss/Min,Learning Rate/Mean,Learning Rate/Stdev,Learning Rate/Max,Learning Rate/Min,Grads (unclipped)/Mean,Grads (unclipped)/Stdev,Grads (unclipped)/Max,Grads (unclipped)/Min,Discounted Return/Mean,Discounted Return/Stdev,Discounted Return/Max,Discounted Return/Min,Q/Mean,Q/Stdev,Q/Max,Q/Min -1,0.0,1.0,1117.0,1117.0,1117.0,1117.0,1.0,,,0.0,,,,,,,,,,,,,,,,-1.5180229894995567,0.6998808293377133,-0.08930329112720292,-3.148474706421977,,,, -2,205.0,0.0,1937.0,1937.0,820.0,1937.0,0.9992620000000244,-21.0,-21.0,0.0,,,,0.011032734143000421,0.013050631943252157,0.06188610941171646,5.788924681837671e-05,0.00010000000000000002,1.3552527156068802e-20,0.0001,0.0001,0.09481886,0.06547235,0.4128104,0.014912024,-2.3361342922088504,0.784322378590693,-0.38878391807422696,-3.369599601005491,,,, 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#Episodes,Episode Length,Total steps,Epsilon,Shaped Training Reward,Training Reward,Update Target Network,Evaluation Reward,Shaped Evaluation Reward,Success Rate,Loss/Mean,Loss/Stdev,Loss/Max,Loss/Min,Learning Rate/Mean,Learning Rate/Stdev,Learning Rate/Max,Learning Rate/Min,Grads (unclipped)/Mean,Grads (unclipped)/Stdev,Grads (unclipped)/Max,Grads (unclipped)/Min,Discounted Return/Mean,Discounted Return/Stdev,Discounted Return/Max,Discounted Return/Min,Q/Mean,Q/Stdev,Q/Max,Q/Min -1,0.0,1.0,24.0,24.0,24.0,24.0,1.0,,,0.0,,,,,,,,,,,,,,,,0.0,0.0,0.0,0.0,,,, -2,0.0,1.0,43.0,43.0,19.0,43.0,1.0,,,0.0,,,,,,,,,,,,,,,,0.0,0.0,0.0,0.0,,,, -3,0.0,1.0,67.0,67.0,24.0,67.0,1.0,,,0.0,,,,,,,,,,,,,,,,0.0,0.0,0.0,0.0,,,, -4,0.0,1.0,119.0,119.0,52.0,119.0,1.0,,,0.0,,,,,,,,,,,,,,,,0.5148012122030814,0.42792094166684,1.0,0.0,,,, -5,0.0,1.0,143.0,143.0,24.0,143.0,1.0,,,0.0,,,,,,,,,,,,,,,,0.0,0.0,0.0,0.0,,,, -6,0.0,1.0,167.0,167.0,24.0,167.0,1.0,,,0.0,,,,,,,,,,,,,,,,0.0,0.0,0.0,0.0,,,, 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-169,1023.0,0.0,24.0,1.0,24.0,5990.0,0.4513723999999789,0.0,0.0,0.0,,,,,,,,,,,,,,,,0.0,0.0,0.0,0.0,,,,,,,,,0.08227284,0.007494508,0.097882286,0.0686567,4.114283e-05,3.4968238e-05,9.736268e-05,1.8153918000000001e-06 -170,1028.0,0.0,24.0,1.0,24.0,6014.0,0.4511371999999788,0.0,0.0,0.0,,,,,,,,,,,,,,,,0.0,0.0,0.0,0.0,,,,,,,,,0.07731951,0.0059566037,0.08605237,0.06250259999999999,0.00014898041000000002,0.00016109177,0.00042544805999999996,3.1070897e-05 diff --git a/rl_coach/traces/Atari_NStepQ_pong/trace.csv b/rl_coach/traces/Atari_NStepQ_pong/trace.csv deleted file mode 100644 index 321b1d7..0000000 --- a/rl_coach/traces/Atari_NStepQ_pong/trace.csv +++ /dev/null @@ -1,6 +0,0 @@ -Episode #,Training Iter,In Heatup,ER #Transitions,ER #Episodes,Episode Length,Total steps,Epsilon,Shaped Training Reward,Training Reward,Update Target Network,Evaluation Reward,Shaped Evaluation Reward,Success Rate,Loss/Mean,Loss/Stdev,Loss/Max,Loss/Min,Learning Rate/Mean,Learning Rate/Stdev,Learning Rate/Max,Learning Rate/Min,Grads (unclipped)/Mean,Grads (unclipped)/Stdev,Grads (unclipped)/Max,Grads (unclipped)/Min,Discounted Return/Mean,Discounted Return/Stdev,Discounted Return/Max,Discounted Return/Min,Entropy/Mean,Entropy/Stdev,Entropy/Max,Entropy/Min,Q/Mean,Q/Stdev,Q/Max,Q/Min,Q Values/Mean,Q Values/Stdev,Q Values/Max,Q Values/Min,Value Loss/Mean,Value Loss/Stdev,Value Loss/Max,Value Loss/Min -1,0.0,1.0,1117.0,1.0,1117.0,1117.0,0.5,,,0.0,,,,,,,,,,,,,,,,-1.5180229894995567,0.6998808293377133,-0.08930329112720292,-3.148474706421977,,,,,,,,,,,,,,,, -2,151.0,0.0,760.0,1.0,760.0,1877.0,0.4925519999999968,-21.0,-21.0,0.0,,,,,,,,,,,,,,,,-2.5205372468300253,0.5838419974113738,-0.7105532272722921,-3.3699982440767453,,,,,,,,,0.07112427,0.07581978,0.32078072,-0.06063268,0.11560041,0.23668602,0.97285825,0.00011849090000000001 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a/rl_coach/traces/Atari_NStepQ_space_invaders/trace.csv +++ /dev/null @@ -1,21 +0,0 @@ -Episode #,Training Iter,In Heatup,ER #Transitions,ER #Episodes,Episode Length,Total steps,Epsilon,Shaped Training Reward,Training Reward,Update Target Network,Evaluation Reward,Shaped Evaluation Reward,Success Rate,Loss/Mean,Loss/Stdev,Loss/Max,Loss/Min,Learning Rate/Mean,Learning Rate/Stdev,Learning Rate/Max,Learning Rate/Min,Grads (unclipped)/Mean,Grads (unclipped)/Stdev,Grads (unclipped)/Max,Grads (unclipped)/Min,Discounted Return/Mean,Discounted Return/Stdev,Discounted Return/Max,Discounted Return/Min,Entropy/Mean,Entropy/Stdev,Entropy/Max,Entropy/Min,Q/Mean,Q/Stdev,Q/Max,Q/Min,Q Values/Mean,Q Values/Stdev,Q Values/Max,Q Values/Min,Value Loss/Mean,Value Loss/Stdev,Value Loss/Max,Value Loss/Min -1,0.0,1.0,486.0,1.0,486.0,486.0,0.5,,,0.0,,,,,,,,,,,,,,,,1.027285241237078,0.8961037725396955,3.502959469093688,0.0,,,,,,,,,,,,,,,, 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Heatup,ER #Transitions,ER #Episodes,Episode Length,Total steps,Epsilon,Shaped Training Reward,Training Reward,Update Target Network,Evaluation Reward,Shaped Evaluation Reward,Success Rate,Loss/Mean,Loss/Stdev,Loss/Max,Loss/Min,Learning Rate/Mean,Learning Rate/Stdev,Learning Rate/Max,Learning Rate/Min,Grads (unclipped)/Mean,Grads (unclipped)/Stdev,Grads (unclipped)/Max,Grads (unclipped)/Min,Discounted Return/Mean,Discounted Return/Stdev,Discounted Return/Max,Discounted Return/Min,Entropy/Mean,Entropy/Stdev,Entropy/Max,Entropy/Min,Advantages/Mean,Advantages/Stdev,Advantages/Max,Advantages/Min,Values/Mean,Values/Stdev,Values/Max,Values/Min,Value Loss/Mean,Value Loss/Stdev,Value Loss/Max,Value Loss/Min,Policy Loss/Mean,Policy Loss/Stdev,Policy Loss/Max,Policy Loss/Min -1,0.0,1.0,13.0,1.0,13.0,13.0,0.0,,,0.0,,,,,,,,,,,,,,,,0.033637741419147334,0.017534929825633462,0.06123948850051601,0.005,,,,,,,,,,,,,,,,,,,, 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-9,0.0,1.0,36.0,1.0,36.0,248.0,0.0,,,0.0,,,,,,,,,,,,,,,,0.08256817481816388,0.04353468290208385,0.1517933909752131,0.005,,,,,,,,,,,,,,,,,,,, -10,0.0,1.0,28.0,1.0,28.0,276.0,0.0,,,0.0,,,,,,,,,,,,,,,,0.06637873987785067,0.035179766690898784,0.12264035639818364,0.005,,,,,,,,,,,,,,,,,,,, -11,0.0,1.0,12.0,1.0,12.0,288.0,0.0,,,0.0,,,,,,,,,,,,,,,,0.03133759582903328,0.016257855673222694,0.056807564141935364,0.005,,,,,,,,,,,,,,,,,,,, -12,0.0,1.0,17.0,1.0,17.0,305.0,0.0,,,0.0,,,,,,,,,,,,,,,,0.042687533676728284,0.02251082658499651,0.07852840330803658,0.005,,,,,,,,,,,,,,,,,,,, -13,0.0,1.0,12.0,1.0,12.0,317.0,0.0,,,0.0,,,,,,,,,,,,,,,,0.03133759582903328,0.016257855673222694,0.056807564141935364,0.005,,,,,,,,,,,,,,,,,,,, -14,0.0,1.0,57.0,1.0,57.0,374.0,0.0,,,0.0,,,,,,,,,,,,,,,,0.12128608644549467,0.0624489738253126,0.21804740477380607,0.005,,,,,,,,,,,,,,,,,,,, -15,0.0,1.0,22.0,1.0,22.0,396.0,0.0,,,0.0,,,,,,,,,,,,,,,,0.05366882646285343,0.02844734535364565,0.09918470523047698,0.005,,,,,,,,,,,,,,,,,,,, -16,0.0,1.0,17.0,1.0,17.0,413.0,0.0,,,0.0,,,,,,,,,,,,,,,,0.042687533676728284,0.02251082658499651,0.07852840330803658,0.005,,,,,,,,,,,,,,,,,,,, -17,0.0,1.0,31.0,1.0,31.0,444.0,0.0,,,0.0,,,,,,,,,,,,,,,,0.07254892896428006,0.03839361485936839,0.13384831517280116,0.005,,,,,,,,,,,,,,,,,,,, -18,0.0,1.0,13.0,1.0,13.0,457.0,0.0,,,0.0,,,,,,,,,,,,,,,,0.033637741419147334,0.017534929825633462,0.06123948850051601,0.005,,,,,,,,,,,,,,,,,,,, -19,0.0,1.0,27.0,1.0,27.0,484.0,0.0,,,0.0,,,,,,,,,,,,,,,,0.06429497630302354,0.0340862968900576,0.11882864282644813,0.005,,,,,,,,,,,,,,,,,,,, -20,0.0,1.0,11.0,1.0,11.0,495.0,0.0,,,0.0,,,,,,,,,,,,,,,,0.029022144164224006,0.014966996075313928,0.052330872870641774,0.005,,,,,,,,,,,,,,,,,,,, -21,0.0,1.0,38.0,1.0,38.0,533.0,0.0,,,0.0,,,,,,,,,,,,,,,,0.08648559086879386,0.045518179563016486,0.15872270249480636,0.005,,,,,,,,,,,,,,,,,,,, -22,0.0,1.0,31.0,1.0,31.0,564.0,0.0,,,0.0,,,,,,,,,,,,,,,,0.07254892896428006,0.03839361485936839,0.13384831517280116,0.005,,,,,,,,,,,,,,,,,,,, -23,0.0,1.0,18.0,1.0,18.0,582.0,0.0,,,0.0,,,,,,,,,,,,,,,,0.04491284398774094,0.023722760004486008,0.0827431192749562,0.005,,,,,,,,,,,,,,,,,,,, -24,0.0,1.0,44.0,1.0,44.0,626.0,0.0,,,0.0,,,,,,,,,,,,,,,,0.09793805234530817,0.051228969118242235,0.17869419895764074,0.005,,,,,,,,,,,,,,,,,,,, -25,0.0,1.0,28.0,1.0,28.0,654.0,0.0,,,0.0,,,,,,,,,,,,,,,,0.06637873987785067,0.035179766690898784,0.12264035639818364,0.005,,,,,,,,,,,,,,,,,,,, -26,0.0,1.0,22.0,1.0,22.0,676.0,0.0,,,0.0,,,,,,,,,,,,,,,,0.05366882646285343,0.02844734535364565,0.09918470523047698,0.005,,,,,,,,,,,,,,,,,,,, -27,0.0,1.0,28.0,1.0,28.0,704.0,0.0,,,0.0,,,,,,,,,,,,,,,,0.06637873987785067,0.035179766690898784,0.12264035639818364,0.005,,,,,,,,,,,,,,,,,,,, -28,0.0,1.0,35.0,1.0,35.0,739.0,0.0,,,0.0,,,,,,,,,,,,,,,,0.08059031149939104,0.04252751095672352,0.14827615250021525,0.005,,,,,,,,,,,,,,,,,,,, -29,0.0,1.0,15.0,1.0,15.0,754.0,0.0,,,0.0,,,,,,,,,,,,,,,,0.03819257031625213,0.02004889587224851,0.06997082267935574,0.005,,,,,,,,,,,,,,,,,,,, -30,0.0,1.0,26.0,1.0,26.0,780.0,0.0,,,0.0,,,,,,,,,,,,,,,,0.062197527590584126,0.032981544845425315,0.11497842709742236,0.005,,,,,,,,,,,,,,,,,,,, -31,0.0,1.0,20.0,1.0,20.0,800.0,0.0,,,0.0,,,,,,,,,,,,,,,,0.049319670553146414,0.02610938697149644,0.09104653120138456,0.005,,,,,,,,,,,,,,,,,,,, -32,0.0,1.0,44.0,1.0,44.0,844.0,0.0,,,0.0,,,,,,,,,,,,,,,,0.09793805234530817,0.051228969118242235,0.17869419895764074,0.005,,,,,,,,,,,,,,,,,,,, -33,0.0,1.0,15.0,1.0,15.0,859.0,0.0,,,0.0,,,,,,,,,,,,,,,,0.03819257031625213,0.02004889587224851,0.06997082267935574,0.005,,,,,,,,,,,,,,,,,,,, -34,0.0,1.0,23.0,1.0,23.0,882.0,0.0,,,0.0,,,,,,,,,,,,,,,,0.055822045233084684,0.02959841778336178,0.10319285817817224,0.005,,,,,,,,,,,,,,,,,,,, -35,0.0,1.0,13.0,1.0,13.0,895.0,0.0,,,0.0,,,,,,,,,,,,,,,,0.033637741419147334,0.017534929825633462,0.06123948850051601,0.005,,,,,,,,,,,,,,,,,,,, -36,0.0,1.0,15.0,1.0,15.0,910.0,0.0,,,0.0,,,,,,,,,,,,,,,,0.03819257031625213,0.02004889587224851,0.06997082267935574,0.005,,,,,,,,,,,,,,,,,,,, -37,0.0,1.0,18.0,1.0,18.0,928.0,0.0,,,0.0,,,,,,,,,,,,,,,,0.04491284398774094,0.023722760004486008,0.0827431192749562,0.005,,,,,,,,,,,,,,,,,,,, -38,0.0,1.0,15.0,1.0,15.0,943.0,0.0,,,0.0,,,,,,,,,,,,,,,,0.03819257031625213,0.02004889587224851,0.06997082267935574,0.005,,,,,,,,,,,,,,,,,,,, -39,0.0,1.0,14.0,1.0,14.0,957.0,0.0,,,0.0,,,,,,,,,,,,,,,,0.035922695147459015,0.01879852463102244,0.06562709361551085,0.005,,,,,,,,,,,,,,,,,,,, -40,0.0,1.0,18.0,1.0,18.0,975.0,0.0,,,0.0,,,,,,,,,,,,,,,,0.04491284398774094,0.023722760004486008,0.0827431192749562,0.005,,,,,,,,,,,,,,,,,,,, -41,0.0,1.0,45.0,1.0,45.0,1020.0,0.0,,,0.0,,,,,,,,,,,,,,,,0.09980403467025832,0.052146814637499095,0.1819072569680644,0.005,,,,,,,,,,,,,,,,,,,, -42,0.0,1.0,13.0,1.0,13.0,1033.0,0.0,,,0.0,,,,,,,,,,,,,,,,0.033637741419147334,0.017534929825633462,0.06123948850051601,0.005,,,,,,,,,,,,,,,,,,,, -43,14.0,0.0,74.0,1.0,74.0,1107.0,0.0,0.3700000000000002,74.0,0.0,,,,,,,,,,,,0.019597721999999998,0.017400822,0.05765006,0.004498246599999999,0.1490450280984123,0.07499742440099848,0.26232997899714633,0.005,0.69309086,9.558595e-05,0.69314694,0.69261944,0.011688435329899922,0.032624422614845015,0.12187724791380634,-0.07934371183920755,0.017200878,0.033334654,0.107463345,-0.023952308999999998,0.0006004862000000001,0.0008063634,0.0030937865000000004,3.9719875000000004e-05,0.008115358,0.019123038000000002,0.048891958,-0.035559405 -44,17.0,0.0,13.0,1.0,13.0,1120.0,0.0,0.06499999999999999,13.0,0.0,,,,,,,,,,,,0.04156263,0.004143089,0.04570572,0.037419543,0.033637741419147334,0.017534929825633462,0.06123948850051601,0.005,0.6921232,0.0009996742,0.69314516,0.6902285,0.04340068389789983,0.029410440341049417,0.07611234454582529,-0.013809616565704341,0.056007117,0.04513419,0.13232644,0.0009479597,0.0013742966,0.00044299644999999996,0.0018172931,0.0009313002,0.029239732999999997,0.009705960999999999,0.038945693999999996,0.019533771999999998 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#Episodes,Episode Length,Total steps,Epsilon,Shaped Training Reward,Training Reward,Update Target Network,Evaluation Reward,Shaped Evaluation Reward,Success Rate,Loss/Mean,Loss/Stdev,Loss/Max,Loss/Min,Learning Rate/Mean,Learning Rate/Stdev,Learning Rate/Max,Learning Rate/Min,Grads (unclipped)/Mean,Grads (unclipped)/Stdev,Grads (unclipped)/Max,Grads (unclipped)/Min,Discounted Return/Mean,Discounted Return/Stdev,Discounted Return/Max,Discounted Return/Min,Entropy/Mean,Entropy/Stdev,Entropy/Max,Entropy/Min,Returns Mean/Mean,Returns Mean/Stdev,Returns Mean/Max,Returns Mean/Min,Returns Variance/Mean,Returns Variance/Stdev,Returns Variance/Max,Returns Variance/Min -1,0.0,1.0,15.0,1.0,15.0,15.0,0.0,,,0.0,,,,,,,,,,,,,,,,0.03819257031625213,0.02004889587224851,0.06997082267935574,0.005,,,,,,,,,,,, -2,0.0,1.0,16.0,1.0,16.0,31.0,0.0,,,0.0,,,,,,,,,,,,,,,,0.04044747932477151,0.02128626449475752,0.07427111445256218,0.005,,,,,,,,,,,, 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-234,185.0,0.0,39.0,1.0,39.0,5951.0,0.0,0.1950000000000001,39.0,0.0,,,,,,,,,,,,,,,,0.08842533149959039,0.04649470368874317,0.1621354754698583,0.005,0.6789911999999999,0.01352521,0.69314694,0.6466755999999999,,,,,,,, -235,186.0,0.0,47.0,1.0,47.0,5998.0,0.0,0.2350000000000001,47.0,0.0,,,,,,,,,,,,,,,,0.10350014993860444,0.05395423827762871,0.18823730255439988,0.005,0.6754326999999999,0.022059182000000004,0.6927123000000001,0.59076184,,,,,,,, diff --git a/rl_coach/traces/ControlSuite_DDPG_cartpole_swingup/trace.csv b/rl_coach/traces/ControlSuite_DDPG_cartpole_swingup/trace.csv deleted file mode 100644 index 96365cf..0000000 --- a/rl_coach/traces/ControlSuite_DDPG_cartpole_swingup/trace.csv +++ /dev/null @@ -1,6 +0,0 @@ -Episode #,Training Iter,In Heatup,ER #Transitions,ER #Episodes,Episode Length,Total steps,Epsilon,Shaped Training Reward,Training Reward,Update Target Network,Evaluation Reward,Shaped Evaluation Reward,Success Rate,Loss/Mean,Loss/Stdev,Loss/Max,Loss/Min,Learning Rate/Mean,Learning Rate/Stdev,Learning Rate/Max,Learning Rate/Min,Grads (unclipped)/Mean,Grads (unclipped)/Stdev,Grads (unclipped)/Max,Grads (unclipped)/Min,Discounted Return/Mean,Discounted Return/Stdev,Discounted Return/Max,Discounted Return/Min,Entropy/Mean,Entropy/Stdev,Entropy/Max,Entropy/Min,Advantages/Mean,Advantages/Stdev,Advantages/Max,Advantages/Min,Values/Mean,Values/Stdev,Values/Max,Values/Min,Value Loss/Mean,Value Loss/Stdev,Value Loss/Max,Value Loss/Min,Policy Loss/Mean,Policy Loss/Stdev,Policy Loss/Max,Policy Loss/Min,Q/Mean,Q/Stdev,Q/Max,Q/Min,TD targets/Mean,TD targets/Stdev,TD targets/Max,TD targets/Min,actions/Mean,actions/Stdev,actions/Max,actions/Min -1,0.0,1.0,1001.0,1.0,1001.0,1001.0,0.0,,,0.0,,,,,,,,,,,,,,,,0.1810549437584988,0.08342612458204374,0.3657155727590055,0.012114535848885052,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, 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-5,3002.0,0.0,5005.0,5.0,1001.0,5005.0,-0.02134772535498328,13.93309848305012,139.33098483050114,0.0,,,,4.3079992066850536e-05,6.204749497676766e-05,0.0006331046461127697,2.68419535132125e-06,0.00010000000000000003,2.7105054312137605e-20,0.0001,0.0001,0.012529638000000001,0.010803898999999999,0.07596945,0.0010158704,1.2820087653786647,0.3980341965211882,2.1725203141180294,6.57125185393007e-05,,,,,,,,,,,,,,,,,,,,,0.42543635,0.20454627,0.8917187,0.05104744,0.08902145835758844,0.04616376194044128,0.2426698236415496,-0.00472626581328319,-0.5524111559396501,0.6382799035600116,1.0798330140144352,-1.2145754834427926 diff --git a/rl_coach/traces/ControlSuite_DDPG_hopper_hop/trace.csv b/rl_coach/traces/ControlSuite_DDPG_hopper_hop/trace.csv deleted file mode 100644 index d897deb..0000000 --- a/rl_coach/traces/ControlSuite_DDPG_hopper_hop/trace.csv +++ /dev/null @@ -1,6 +0,0 @@ -Episode #,Training Iter,In Heatup,ER #Transitions,ER #Episodes,Episode Length,Total steps,Epsilon,Shaped Training Reward,Training Reward,Update Target Network,Evaluation Reward,Shaped Evaluation Reward,Success Rate,Loss/Mean,Loss/Stdev,Loss/Max,Loss/Min,Learning Rate/Mean,Learning Rate/Stdev,Learning Rate/Max,Learning Rate/Min,Grads (unclipped)/Mean,Grads (unclipped)/Stdev,Grads (unclipped)/Max,Grads (unclipped)/Min,Discounted Return/Mean,Discounted Return/Stdev,Discounted Return/Max,Discounted Return/Min,Entropy/Mean,Entropy/Stdev,Entropy/Max,Entropy/Min,Advantages/Mean,Advantages/Stdev,Advantages/Max,Advantages/Min,Values/Mean,Values/Stdev,Values/Max,Values/Min,Value Loss/Mean,Value Loss/Stdev,Value Loss/Max,Value Loss/Min,Policy Loss/Mean,Policy Loss/Stdev,Policy Loss/Max,Policy Loss/Min,Q/Mean,Q/Stdev,Q/Max,Q/Min,TD targets/Mean,TD targets/Stdev,TD targets/Max,TD targets/Min,actions/Mean,actions/Stdev,actions/Max,actions/Min -1,0.0,1.0,1000.0,1.0,1000.0,1000.0,0.0,,,0.0,,,,,,,,,,,,,,,,0.0,0.0,0.0,0.0,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, 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-120,3960.0,0.0,29520.0,120.0,50.0,6000.0,0.1,-50.0,-50.0,0.0,,,,,,,,,,,,,,,,-18.84431432426873,9.007305717332294,-1.0,-31.79151599564413,,,,,,,,,,,,,,,,,,,,,-4.3970723,0.07216070599999999,-4.2654076,-4.531833,,,,,-0.07895948514556546,0.6321871798767333,1.163310969887592,-1.3586834040626514 diff --git a/rl_coach/traces/InvertedPendulum_PG/trace.csv b/rl_coach/traces/InvertedPendulum_PG/trace.csv deleted file mode 100644 index 19a6519..0000000 --- a/rl_coach/traces/InvertedPendulum_PG/trace.csv +++ /dev/null @@ -1,301 +0,0 @@ -Episode #,Training Iter,In Heatup,ER #Transitions,ER #Episodes,Episode Length,Total steps,Epsilon,Shaped Training Reward,Training Reward,Update Target Network,Evaluation Reward,Shaped Evaluation Reward,Success Rate,Loss/Mean,Loss/Stdev,Loss/Max,Loss/Min,Learning Rate/Mean,Learning Rate/Stdev,Learning Rate/Max,Learning Rate/Min,Grads (unclipped)/Mean,Grads (unclipped)/Stdev,Grads (unclipped)/Max,Grads (unclipped)/Min,Discounted Return/Mean,Discounted Return/Stdev,Discounted Return/Max,Discounted Return/Min,Entropy/Mean,Entropy/Stdev,Entropy/Max,Entropy/Min,Returns Mean/Mean,Returns Mean/Stdev,Returns Mean/Max,Returns Mean/Min,Returns Variance/Mean,Returns Variance/Stdev,Returns Variance/Max,Returns Variance/Min -1,0.0,1.0,4.0,1.0,4.0,4.0,0.1,,,0.0,,,,,,,,,,,,,,,,0.1237562375,0.054791469323191344,0.19701995,0.05,,,,,,,,,,,, -2,0.0,1.0,3.0,1.0,3.0,7.0,0.1,,,0.0,,,,,,,,,,,,,,,,0.099335,0.040214667100449804,0.148505,0.05,,,,,,,,,,,, -3,0.0,1.0,3.0,1.0,3.0,10.0,0.1,,,0.0,,,,,,,,,,,,,,,,0.099335,0.040214667100449804,0.148505,0.05,,,,,,,,,,,, -4,0.0,1.0,7.0,1.0,7.0,17.0,0.1,,,0.0,,,,,,,,,,,,,,,,0.19604960199429286,0.09655815980645327,0.33967326046505,0.05,,,,,,,,,,,, -5,0.0,1.0,6.0,1.0,6.0,23.0,0.1,,,0.0,,,,,,,,,,,,,,,,0.17211232558249998,0.08286397799189531,0.292599252995,0.05,,,,,,,,,,,, -6,0.0,1.0,8.0,1.0,8.0,31.0,0.1,,,0.0,,,,,,,,,,,,,,,,0.2198279677275562,0.11007233160822624,0.38627652786039945,0.05,,,,,,,,,,,, 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file mode 100644 index 65d5a63..0000000 --- a/rl_coach/traces/Mujoco_A3C_LSTM_inverted_pendulum/trace.csv +++ /dev/null @@ -1,616 +0,0 @@ -Episode #,Training Iter,In Heatup,ER #Transitions,ER #Episodes,Episode Length,Total steps,Epsilon,Shaped Training Reward,Training Reward,Update Target Network,Evaluation Reward,Shaped Evaluation Reward,Success Rate,Loss/Mean,Loss/Stdev,Loss/Max,Loss/Min,Learning Rate/Mean,Learning Rate/Stdev,Learning Rate/Max,Learning Rate/Min,Grads (unclipped)/Mean,Grads (unclipped)/Stdev,Grads (unclipped)/Max,Grads (unclipped)/Min,Discounted Return/Mean,Discounted Return/Stdev,Discounted Return/Max,Discounted Return/Min,Entropy/Mean,Entropy/Stdev,Entropy/Max,Entropy/Min,Advantages/Mean,Advantages/Stdev,Advantages/Max,Advantages/Min,Values/Mean,Values/Stdev,Values/Max,Values/Min,Value Loss/Mean,Value Loss/Stdev,Value Loss/Max,Value Loss/Min,Policy Loss/Mean,Policy Loss/Stdev,Policy Loss/Max,Policy Loss/Min 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ebd0de7..0000000 --- a/rl_coach/traces/Mujoco_A3C_inverted_pendulum/trace.csv +++ /dev/null @@ -1,601 +0,0 @@ -Episode #,Training Iter,In Heatup,ER #Transitions,ER #Episodes,Episode Length,Total steps,Epsilon,Shaped Training Reward,Training Reward,Update Target Network,Evaluation Reward,Shaped Evaluation Reward,Success Rate,Loss/Mean,Loss/Stdev,Loss/Max,Loss/Min,Learning Rate/Mean,Learning Rate/Stdev,Learning Rate/Max,Learning Rate/Min,Grads (unclipped)/Mean,Grads (unclipped)/Stdev,Grads (unclipped)/Max,Grads (unclipped)/Min,Discounted Return/Mean,Discounted Return/Stdev,Discounted Return/Max,Discounted Return/Min,Entropy/Mean,Entropy/Stdev,Entropy/Max,Entropy/Min,Advantages/Mean,Advantages/Stdev,Advantages/Max,Advantages/Min,Values/Mean,Values/Stdev,Values/Max,Values/Min,Value Loss/Mean,Value Loss/Stdev,Value Loss/Max,Value Loss/Min,Policy Loss/Mean,Policy Loss/Stdev,Policy Loss/Max,Policy Loss/Min 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b/rl_coach/traces/Mujoco_ClippedPPO_hopper/trace.csv deleted file mode 100644 index 5493d7a..0000000 --- a/rl_coach/traces/Mujoco_ClippedPPO_hopper/trace.csv +++ /dev/null @@ -1,216 +0,0 @@ -Episode #,Training Iter,In Heatup,ER #Transitions,ER #Episodes,Episode Length,Total steps,Epsilon,Shaped Training Reward,Training Reward,Update Target Network,Evaluation Reward,Shaped Evaluation Reward,Success Rate,Loss/Mean,Loss/Stdev,Loss/Max,Loss/Min,Learning Rate/Mean,Learning Rate/Stdev,Learning Rate/Max,Learning Rate/Min,Grads (unclipped)/Mean,Grads (unclipped)/Stdev,Grads (unclipped)/Max,Grads (unclipped)/Min,Discounted Return/Mean,Discounted Return/Stdev,Discounted Return/Max,Discounted Return/Min,Entropy/Mean,Entropy/Stdev,Entropy/Max,Entropy/Min,Advantages/Mean,Advantages/Stdev,Advantages/Max,Advantages/Min,Values/Mean,Values/Stdev,Values/Max,Values/Min,Value Loss/Mean,Value Loss/Stdev,Value Loss/Max,Value Loss/Min,Policy Loss/Mean,Policy Loss/Stdev,Policy Loss/Max,Policy Loss/Min,Value Targets/Mean,Value Targets/Stdev,Value Targets/Max,Value Targets/Min,KL Divergence/Mean,KL Divergence/Stdev,KL Divergence/Max,KL Divergence/Min,Likelihood Ratio/Mean,Likelihood Ratio/Stdev,Likelihood Ratio/Max,Likelihood Ratio/Min,Clipped Likelihood Ratio/Mean,Clipped Likelihood Ratio/Stdev,Clipped Likelihood Ratio/Max,Clipped Likelihood Ratio/Min -1,0.0,1.0,17.0,1.0,17.0,17.0,0.10000000000000002,,,0.0,,,,,,,,,,,,,,,,6.162379521079859,3.609954821692951,12.578831844357849,0.7107869962784428,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, -2,0.0,1.0,40.0,2.0,23.0,40.0,0.10000000000000002,,,0.0,,,,,,,,,,,,,,,,6.444564121549556,4.523807302228816,14.892816778727136,0.4339427590058468,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, -3,0.0,1.0,55.0,3.0,15.0,55.0,0.10000000000000002,,,0.0,,,,,,,,,,,,,,,,5.372082027351956,3.290894637318891,11.137801685828423,0.6193940407704618,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, 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-209,2.0,0.0,1383.0,26.0,51.0,5491.0,0.10000000000000002,70.30180771681185,70.30180771681185,0.0,,,,,,,,,,,,,,,,31.97326634197281,16.77759647191585,54.54085038626839,1.30447245921723,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, -210,2.0,0.0,1462.0,27.0,79.0,5570.0,0.10000000000000002,150.23454114405442,150.23454114405442,0.0,,,,,,,,,,,,,,,,68.70878477660612,29.736578840980787,98.77020431409781,2.4430485012861705,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, -211,2.0,0.0,1479.0,28.0,17.0,5587.0,0.10000000000000002,16.754454169862143,16.754454169862143,0.0,,,,,,,,,,,,,,,,9.119194422214154,4.037872958758843,15.357768806147204,1.4336949712428038,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, -212,2.0,0.0,1559.0,29.0,80.0,5667.0,0.10000000000000002,117.79710024366554,117.79710024366554,0.0,,,,,,,,,,,,,,,,52.44651043392246,20.95871827384402,76.60595141063388,2.256832244963402,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, -213,2.0,0.0,1604.0,30.0,45.0,5712.0,0.10000000000000002,63.215691539541815,63.215691539541815,0.0,,,,,,,,,,,,,,,,30.763959098292162,14.346310171845696,49.870616106374094,1.9018439352727017,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, -214,2.0,0.0,1735.0,31.0,131.0,5843.0,0.10000000000000002,236.12632804156067,236.12632804156067,0.0,,,,,,,,,,,,,,,,95.88918307240696,31.541679518215822,120.93281508383664,3.4384573958150884,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, -215,2.0,0.0,1841.0,32.0,106.0,5949.0,0.10000000000000002,159.6244169455343,159.6244169455343,0.0,,,,,,,,,,,,,,,,67.39505333344762,24.75038278863234,90.01141923046606,2.5183556450980946,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, diff --git a/rl_coach/traces/Mujoco_ClippedPPO_inverted_pendulum/trace.csv b/rl_coach/traces/Mujoco_ClippedPPO_inverted_pendulum/trace.csv deleted file mode 100644 index 8274a6d..0000000 --- a/rl_coach/traces/Mujoco_ClippedPPO_inverted_pendulum/trace.csv +++ /dev/null @@ -1,641 +0,0 @@ -Episode #,Training Iter,In Heatup,ER #Transitions,ER #Episodes,Episode Length,Total steps,Epsilon,Shaped Training Reward,Training Reward,Update Target Network,Evaluation Reward,Shaped Evaluation Reward,Success Rate,Loss/Mean,Loss/Stdev,Loss/Max,Loss/Min,Learning Rate/Mean,Learning Rate/Stdev,Learning Rate/Max,Learning Rate/Min,Grads (unclipped)/Mean,Grads (unclipped)/Stdev,Grads (unclipped)/Max,Grads (unclipped)/Min,Discounted Return/Mean,Discounted Return/Stdev,Discounted Return/Max,Discounted Return/Min,Entropy/Mean,Entropy/Stdev,Entropy/Max,Entropy/Min,Advantages/Mean,Advantages/Stdev,Advantages/Max,Advantages/Min,Values/Mean,Values/Stdev,Values/Max,Values/Min,Value Loss/Mean,Value Loss/Stdev,Value Loss/Max,Value Loss/Min,Policy Loss/Mean,Policy Loss/Stdev,Policy Loss/Max,Policy Loss/Min,Value Targets/Mean,Value Targets/Stdev,Value Targets/Max,Value Targets/Min,KL Divergence/Mean,KL Divergence/Stdev,KL Divergence/Max,KL Divergence/Min,Likelihood Ratio/Mean,Likelihood Ratio/Stdev,Likelihood Ratio/Max,Likelihood Ratio/Min,Clipped Likelihood Ratio/Mean,Clipped Likelihood Ratio/Stdev,Clipped Likelihood Ratio/Max,Clipped Likelihood Ratio/Min -1,0.0,1.0,5.0,1.0,5.0,5.0,0.1,,,0.0,,,,,,,,,,,,,,,,2.960298802,1.3792204603784504,4.90099501,1.0,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, -2,0.0,1.0,11.0,2.0,6.0,11.0,0.1,,,0.0,,,,,,,,,,,,,,,,3.44224651165,1.657279559837906,5.8519850599000005,1.0,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, -3,0.0,1.0,15.0,3.0,4.0,15.0,0.1,,,0.0,,,,,,,,,,,,,,,,2.47512475,1.0958293864638269,3.940399,1.0,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, -4,0.0,1.0,27.0,4.0,12.0,27.0,0.1,,,0.0,,,,,,,,,,,,,,,,6.267519165806655,3.251571134644539,11.36151282838707,1.0,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, -5,0.0,1.0,31.0,5.0,4.0,31.0,0.1,,,0.0,,,,,,,,,,,,,,,,2.47512475,1.0958293864638269,3.940399,1.0,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, -6,0.0,1.0,36.0,6.0,5.0,36.0,0.1,,,0.0,,,,,,,,,,,,,,,,2.960298802,1.3792204603784504,4.90099501,1.0,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, 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-14,0.0,1.0,81.0,14.0,4.0,81.0,0.1,,,0.0,,,,,,,,,,,,,,,,2.47512475,1.0958293864638269,3.940399,1.0,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, -15,0.0,1.0,84.0,15.0,3.0,84.0,0.1,,,0.0,,,,,,,,,,,,,,,,1.9867,0.8042933420089962,2.9701,1.0,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, -16,0.0,1.0,94.0,16.0,10.0,94.0,0.1,,,0.0,,,,,,,,,,,,,,,,5.338254258716446,2.7323939462696547,9.561792499119552,1.0,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, -17,0.0,1.0,97.0,17.0,3.0,97.0,0.1,,,0.0,,,,,,,,,,,,,,,,1.9867,0.8042933420089962,2.9701,1.0,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, -18,0.0,1.0,105.0,18.0,8.0,105.0,0.1,,,0.0,,,,,,,,,,,,,,,,4.396559354551124,2.2014466321645245,7.725530557207988,1.0,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, -19,0.0,1.0,118.0,19.0,13.0,118.0,0.1,,,0.0,,,,,,,,,,,,,,,,6.727548283829467,3.506985965126692,12.2478977001032,1.0,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, -20,0.0,1.0,122.0,20.0,4.0,122.0,0.1,,,0.0,,,,,,,,,,,,,,,,2.47512475,1.0958293864638269,3.940399,1.0,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, 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-640,2.0,0.0,1874.0,129.0,22.0,5988.0,0.1,22.0,22.0,0.0,,,,,,,,,,,,,,,,10.733765292570688,5.689469070729128,19.836941046095394,1.0,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, diff --git a/rl_coach/traces/Mujoco_DDPG_hopper/trace.csv b/rl_coach/traces/Mujoco_DDPG_hopper/trace.csv deleted file mode 100644 index b04beae..0000000 --- a/rl_coach/traces/Mujoco_DDPG_hopper/trace.csv +++ /dev/null @@ -1,116 +0,0 @@ -Episode #,Training Iter,In Heatup,ER #Transitions,ER #Episodes,Episode Length,Total steps,Epsilon,Shaped Training Reward,Training Reward,Update Target Network,Evaluation Reward,Shaped Evaluation Reward,Success Rate,Loss/Mean,Loss/Stdev,Loss/Max,Loss/Min,Learning Rate/Mean,Learning Rate/Stdev,Learning Rate/Max,Learning Rate/Min,Grads (unclipped)/Mean,Grads (unclipped)/Stdev,Grads (unclipped)/Max,Grads (unclipped)/Min,Discounted Return/Mean,Discounted Return/Stdev,Discounted Return/Max,Discounted 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Reward,Success Rate,Loss/Mean,Loss/Stdev,Loss/Max,Loss/Min,Learning Rate/Mean,Learning Rate/Stdev,Learning Rate/Max,Learning Rate/Min,Grads (unclipped)/Mean,Grads (unclipped)/Stdev,Grads (unclipped)/Max,Grads (unclipped)/Min,Discounted Return/Mean,Discounted Return/Stdev,Discounted Return/Max,Discounted Return/Min,Entropy/Mean,Entropy/Stdev,Entropy/Max,Entropy/Min,Advantages/Mean,Advantages/Stdev,Advantages/Max,Advantages/Min,Values/Mean,Values/Stdev,Values/Max,Values/Min,Value Loss/Mean,Value Loss/Stdev,Value Loss/Max,Value Loss/Min,Policy Loss/Mean,Policy Loss/Stdev,Policy Loss/Max,Policy Loss/Min,KL Divergence/Mean,KL Divergence/Stdev,KL Divergence/Max,KL Divergence/Min -1,0.0,1.0,17.0,1.0,17.0,17.0,0.10000000000000002,,,0.0,,,,,,,,,,,,,,,,6.162379521079859,3.609954821692951,12.578831844357849,0.7107869962784428,,,,,,,,,,,,,,,,,,,,,,,, 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-275,1.0,0.0,967.0,26.0,17.0,5992.0,0.10000000000000002,13.71169901392541,13.71169901392541,0.0,,,,,,,,,,,,,,,,6.324659559590202,3.733783446827686,12.764148372520275,0.6381799672563699,,,,,,,,,,,,,,,,,,,,,,,, diff --git a/rl_coach/traces/Mujoco_PPO_inverted_pendulum/trace.csv b/rl_coach/traces/Mujoco_PPO_inverted_pendulum/trace.csv deleted file mode 100644 index 2f0e1c9..0000000 --- a/rl_coach/traces/Mujoco_PPO_inverted_pendulum/trace.csv +++ /dev/null @@ -1,766 +0,0 @@ -Episode #,Training Iter,In Heatup,ER #Transitions,ER #Episodes,Episode Length,Total steps,Epsilon,Shaped Training Reward,Training Reward,Update Target Network,Evaluation Reward,Shaped Evaluation Reward,Success Rate,Loss/Mean,Loss/Stdev,Loss/Max,Loss/Min,Learning Rate/Mean,Learning Rate/Stdev,Learning Rate/Max,Learning Rate/Min,Grads (unclipped)/Mean,Grads (unclipped)/Stdev,Grads (unclipped)/Max,Grads (unclipped)/Min,Discounted Return/Mean,Discounted Return/Stdev,Discounted Return/Max,Discounted 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Reward,Shaped Evaluation Reward,Success Rate,Loss/Mean,Loss/Stdev,Loss/Max,Loss/Min,Learning Rate/Mean,Learning Rate/Stdev,Learning Rate/Max,Learning Rate/Min,Grads (unclipped)/Mean,Grads (unclipped)/Stdev,Grads (unclipped)/Max,Grads (unclipped)/Min,Discounted Return/Mean,Discounted Return/Stdev,Discounted Return/Max,Discounted Return/Min,Entropy/Mean,Entropy/Stdev,Entropy/Max,Entropy/Min,Advantages/Mean,Advantages/Stdev,Advantages/Max,Advantages/Min,Values/Mean,Values/Stdev,Values/Max,Values/Min,Value Loss/Mean,Value Loss/Stdev,Value Loss/Max,Value Loss/Min,Policy Loss/Mean,Policy Loss/Stdev,Policy Loss/Max,Policy Loss/Min,Q/Mean,Q/Stdev,Q/Max,Q/Min,TD targets/Mean,TD targets/Stdev,TD targets/Max,TD targets/Min,actions/Mean,actions/Stdev,actions/Max,actions/Min -1,0.0,1.0,97.0,1.0,25.0,25.0,0.0,,,0.0,,,,,,,,,,,,,,,,-480.6903328824848,254.92315277284558,-40.0,-888.7145624034126,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, 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-5,0.0,0.0,485.0,5.0,25.0,125.0,0.0,-1000.0,-1000.0,0.0,,,,,,,,,,,,,,,,-480.6903328824848,254.92315277284558,-40.0,-888.7145624034126,,,,,,,,,,,,,,,,,,,,,-0.050059527,0.0325627,0.057268333,-0.10848339,,,,,-0.10842234288811206,0.1848078590593072,0.10341470901523106,-0.6624982986866047 diff --git a/rl_coach/traces/Starcraft_CollectMinerals_A3C/trace.csv b/rl_coach/traces/Starcraft_CollectMinerals_A3C/trace.csv deleted file mode 100644 index 68c726f..0000000 --- a/rl_coach/traces/Starcraft_CollectMinerals_A3C/trace.csv +++ /dev/null @@ -1,11 +0,0 @@ -Episode #,Training Iter,In Heatup,ER #Transitions,ER #Episodes,Episode Length,Total steps,Epsilon,Shaped Training Reward,Training Reward,Update Target Network,Evaluation Reward,Shaped Evaluation Reward,Success Rate,Loss/Mean,Loss/Stdev,Loss/Max,Loss/Min,Learning Rate/Mean,Learning Rate/Stdev,Learning Rate/Max,Learning Rate/Min,Grads (unclipped)/Mean,Grads (unclipped)/Stdev,Grads (unclipped)/Max,Grads (unclipped)/Min,Discounted Return/Mean,Discounted Return/Stdev,Discounted Return/Max,Discounted Return/Min,Entropy/Mean,Entropy/Stdev,Entropy/Max,Entropy/Min,Advantages/Mean,Advantages/Stdev,Advantages/Max,Advantages/Min,Values/Mean,Values/Stdev,Values/Max,Values/Min,Value Loss/Mean,Value Loss/Stdev,Value Loss/Max,Value Loss/Min,Policy Loss/Mean,Policy Loss/Stdev,Policy Loss/Max,Policy Loss/Min -1,0.0,1.0,478.0,1.0,478.0,478.0,0.05,,,0.0,,,,,,,,,,,,,,,,0.6772166738139332,1.3606583998522768,7.111435392915562,0.0,,,,,,,,,,,,,,,,,,,, -2,0.0,1.0,478.0,1.0,478.0,956.0,0.05,,,0.0,,,,,,,,,,,,,,,,0.3461585865957836,0.7129541964353258,3.4825898934060247,0.0,,,,,,,,,,,,,,,,,,,, -3,0.0,1.0,478.0,1.0,478.0,1434.0,0.05,,,0.0,,,,,,,,,,,,,,,,0.8221885517216162,1.0710747025505476,7.5093869236316815,0.0,,,,,,,,,,,,,,,,,,,, -4,23.0,0.0,478.0,1.0,478.0,1912.0,0.05,3.0,3.0,0.0,,,,,,,,,,,,6.035387999999999,19.725208,82.50349,0.039248765,0.12383280129798925,0.5223793934675833,2.79990211919977,0.0,,,,,0.0452739237450773,0.2183428467460978,1.8627784317196168,-0.0030643000370221317,-0.004365872,0.0017351342000000002,-0.0009706963,-0.013218256000000001,0.03401077,0.11164869,0.451847,4.2722320000000005e-07,1.0746696000000002,3.4710016,13.569623000000002,-0.042516552 -5,47.0,0.0,478.0,1.0,478.0,2390.0,0.05,4.0,4.0,0.0,,,,,,,,,,,,4.0586433,13.706188000000001,61.88896,0.01625376,0.1100642112599555,0.4374646870965546,3.5802294655332134,0.0,,,,,0.06605603117614679,0.2828204733180097,2.495711163345754,-0.003739734889965058,-0.014320336000000001,0.001017332,-0.011700756999999999,-0.019422526000000002,0.06243892400000001,0.22280176,1.0344708,5.7007526e-07,1.0248749,3.348449,14.245454999999998,0.0033072747999999996 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-10,167.0,0.0,478.0,1.0,478.0,4780.0,0.05,0.0,0.0,0.0,,,,,,,,,,,,0.07378042,0.035627235,0.1401871,0.011221955,0.0,0.0,0.0,0.0,,,,,0.0006671480381455103,0.0011843871302212494,0.0037133864868810437,-0.003517640307545661,-0.008119860999999999,0.0009026574000000001,-0.005373695,-0.010452669,1.3184773000000002e-06,1.1577918e-06,4.8367815e-06,3.1812826e-07,0.012648877,0.012855935,0.034687527,-0.009518709 diff --git a/rl_coach/traces/Starcraft_CollectMinerals_Dueling_DDQN/trace.csv b/rl_coach/traces/Starcraft_CollectMinerals_Dueling_DDQN/trace.csv deleted file mode 100644 index 10d264d..0000000 --- a/rl_coach/traces/Starcraft_CollectMinerals_Dueling_DDQN/trace.csv +++ /dev/null @@ -1,11 +0,0 @@ -Episode #,Training Iter,In Heatup,ER #Transitions,ER #Episodes,Episode Length,Total steps,Epsilon,Shaped Training Reward,Training Reward,Update Target Network,Evaluation Reward,Shaped Evaluation Reward,Success Rate,Loss/Mean,Loss/Stdev,Loss/Max,Loss/Min,Learning Rate/Mean,Learning Rate/Stdev,Learning 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