mirror of
https://github.com/wassname/Run-Skeleton-Run.git
synced 2026-06-27 18:21:58 +08:00
wassname
363 lines
8.9 KiB
Plaintext
363 lines
8.9 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 6,
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"metadata": {
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"ExecuteTime": {
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"end_time": "2018-01-19T02:39:09.387985Z",
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"start_time": "2018-01-19T02:39:09.291235Z"
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},
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"import os\n",
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"os.environ['CUDA_VISIBLE_DEVICES']=\"\"\n",
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"os.environ[\"PYTHONPATH\"]='.'"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"metadata": {
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"ExecuteTime": {
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"end_time": "2018-01-19T02:39:09.542108Z",
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"start_time": "2018-01-19T02:39:09.390592Z"
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}
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Populating the interactive namespace from numpy and matplotlib\n"
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]
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}
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],
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"source": [
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"%pylab --no-import-all inline\n",
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"%reload_ext autoreload\n",
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"%autoreload 2"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 8,
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"metadata": {
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"ExecuteTime": {
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"end_time": "2018-01-19T02:39:09.722311Z",
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"start_time": "2018-01-19T02:39:09.552596Z"
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},
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"scrolled": true
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"['ddpg/train.py',\n",
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" '--logdir',\n",
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" './outputs/logs_ddpg',\n",
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" '--num-threads',\n",
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" '1',\n",
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" '--reward-scale',\n",
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" '1',\n",
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" '--actor-layers',\n",
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" '64-64-64',\n",
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" '--actor-layer-norm',\n",
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" '--actor-parameters-noise',\n",
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" '--actor-lr',\n",
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" '0.001',\n",
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" '--actor-lr-end',\n",
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" '0.000001',\n",
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" '--dynamics-lr',\n",
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" '0.0001',\n",
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" '--dynamics-lr-end',\n",
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" '0.0000001',\n",
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" '--critic-layers',\n",
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" '64-32',\n",
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" '--critic-layer-norm',\n",
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" '--critic-lr',\n",
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" '0.002',\n",
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" '--critic-lr-end',\n",
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" '0.000001',\n",
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" '--initial-epsilon',\n",
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" '0.5',\n",
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" '--final-epsilon',\n",
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" '0.001',\n",
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" '--tau',\n",
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" '0.0001']"
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]
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},
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"execution_count": 8,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"os.sys.argv=\"ddpg/train.py --logdir ./outputs/logs_ddpg \\\n",
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"--num-threads 1 \\\n",
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"--reward-scale 1 \\\n",
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"--actor-layers 64-64-64 --actor-layer-norm --actor-parameters-noise --actor-lr 0.001 --actor-lr-end 0.000001 \\\n",
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"--dynamics-lr 0.0001 --dynamics-lr-end 0.0000001 \\\n",
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"--critic-layers 64-32 --critic-layer-norm --critic-lr 0.002 --critic-lr-end 0.000001 \\\n",
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"--initial-epsilon 0.5 --final-epsilon 0.001 --tau 0.0001\".split(\" \")\n",
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"os.sys.argv"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 9,
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"metadata": {
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"ExecuteTime": {
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"end_time": "2018-01-19T02:39:09.829347Z",
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"start_time": "2018-01-19T02:39:09.724292Z"
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},
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"from ddpg.train import *"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 10,
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"metadata": {
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"ExecuteTime": {
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"end_time": "2018-01-19T02:39:18.905244Z",
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"start_time": "2018-01-19T02:39:09.834586Z"
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},
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"scrolled": true
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},
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"[2018-01-19 10:39:09,999] Making new env: Pendulum-v0\n"
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]
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},
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Base (\n",
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" (feature_net): LinearNet (\n",
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" (net): Sequential (\n",
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" (linear_0): NoisyLinear (3 -> 64)\n",
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" (layer_norm_0): LayerNorm (\n",
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" )\n",
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" (act_0): ReLU ()\n",
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" (linear_1): NoisyLinear (64 -> 64)\n",
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" (layer_norm_1): LayerNorm (\n",
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" )\n",
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" (act_1): ReLU ()\n",
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" (linear_2): NoisyLinear (64 -> 64)\n",
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" (layer_norm_2): LayerNorm (\n",
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" )\n",
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" (act_2): ReLU ()\n",
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" )\n",
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" )\n",
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")\n",
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"ActorHead (\n",
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" (base): Base (\n",
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" (feature_net): LinearNet (\n",
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" (net): Sequential (\n",
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" (linear_0): NoisyLinear (3 -> 64)\n",
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" (layer_norm_0): LayerNorm (\n",
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" )\n",
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" (act_0): ReLU ()\n",
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" (linear_1): NoisyLinear (64 -> 64)\n",
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" (layer_norm_1): LayerNorm (\n",
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" )\n",
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" (act_1): ReLU ()\n",
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" (linear_2): NoisyLinear (64 -> 64)\n",
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" (layer_norm_2): LayerNorm (\n",
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" )\n",
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" (act_2): ReLU ()\n",
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" )\n",
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" )\n",
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" )\n",
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" (policy_net): LinearNet (\n",
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" (net): Sequential (\n",
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" (linear_0): Linear (64 -> 1)\n",
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" (act_0): ELU (alpha=1.0)\n",
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" )\n",
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" )\n",
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")\n",
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"CriticHead (\n",
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" (base): Base (\n",
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" (feature_net): LinearNet (\n",
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" (net): Sequential (\n",
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" (linear_0): NoisyLinear (3 -> 64)\n",
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" (layer_norm_0): LayerNorm (\n",
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" )\n",
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" (act_0): ReLU ()\n",
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" (linear_1): NoisyLinear (64 -> 64)\n",
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" (layer_norm_1): LayerNorm (\n",
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" )\n",
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" (act_1): ReLU ()\n",
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" (linear_2): NoisyLinear (64 -> 64)\n",
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" (layer_norm_2): LayerNorm (\n",
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" )\n",
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" (act_2): ReLU ()\n",
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" )\n",
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" )\n",
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" )\n",
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" (value_net): Linear (64 -> 1)\n",
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")\n",
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"DynamicsHead (\n",
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" (base): Base (\n",
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" (feature_net): LinearNet (\n",
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" (net): Sequential (\n",
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" (linear_0): NoisyLinear (3 -> 64)\n",
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" (layer_norm_0): LayerNorm (\n",
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" )\n",
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" (act_0): ReLU ()\n",
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" (linear_1): NoisyLinear (64 -> 64)\n",
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" (layer_norm_1): LayerNorm (\n",
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" )\n",
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" (act_1): ReLU ()\n",
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" (linear_2): NoisyLinear (64 -> 64)\n",
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" (layer_norm_2): LayerNorm (\n",
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" )\n",
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" (act_2): ReLU ()\n",
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" )\n",
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" )\n",
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" )\n",
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" (value_net): LinearNet (\n",
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" (net): Sequential (\n",
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" (linear_0): Linear (65 -> 64)\n",
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" (layer_norm_0): LayerNorm (\n",
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" )\n",
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" (act_0): ReLU ()\n",
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" )\n",
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" )\n",
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" (value_net2): Linear (64 -> 3)\n",
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")\n"
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]
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}
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],
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"source": [
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"os.environ['OMP_NUM_THREADS'] = '1'\n",
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"torch.set_num_threads(1)\n",
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"args = parse_args()\n",
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"train(args,\n",
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" create_model,\n",
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" create_act_update_fns,\n",
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" train_multi_thread,\n",
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" train_single_thread,\n",
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" play_single_thread)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"ExecuteTime": {
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"start_time": "2018-01-18T08:39:00.927Z"
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},
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"collapsed": true
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},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"ExecuteTime": {
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"start_time": "2018-01-18T08:39:00.929Z"
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},
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"collapsed": true
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},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "jupyter3",
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"language": "python",
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"name": "jupyter3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.6.0"
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},
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"toc": {
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"colors": {
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"hover_highlight": "#DAA520",
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"navigate_num": "#000000",
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"navigate_text": "#333333",
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"running_highlight": "#FF0000",
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"selected_highlight": "#FFD700",
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"sidebar_border": "#EEEEEE",
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"wrapper_background": "#FFFFFF"
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},
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"moveMenuLeft": true,
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"nav_menu": {
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"height": "12px",
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"width": "252px"
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},
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"navigate_menu": true,
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"number_sections": true,
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"sideBar": true,
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"threshold": 4,
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"toc_cell": false,
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"toc_section_display": "block",
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"toc_window_display": false,
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"widenNotebook": false
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},
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"varInspector": {
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"cols": {
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"lenName": 16,
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"lenType": 16,
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"lenVar": 40
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},
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"kernels_config": {
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"python": {
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"delete_cmd_postfix": "",
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"delete_cmd_prefix": "del ",
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"library": "var_list.py",
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"varRefreshCmd": "print(var_dic_list())"
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},
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"r": {
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"delete_cmd_postfix": ") ",
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"delete_cmd_prefix": "rm(",
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"library": "var_list.r",
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"varRefreshCmd": "cat(var_dic_list()) "
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}
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},
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"types_to_exclude": [
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"module",
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"function",
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"builtin_function_or_method",
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"instance",
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"_Feature"
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],
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"window_display": false
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}
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