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run12
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wassname committed
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3 files changed
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-80
@@ -5,8 +5,8 @@
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"execution_count": 1,
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"metadata": {
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"ExecuteTime": {
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"end_time": "2018-12-07T06:05:16.248384Z",
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"start_time": "2018-12-08T14:01:12.023472Z"
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}
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},
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"outputs": [
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@@ -30,8 +30,8 @@
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"execution_count": 2,
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"metadata": {
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"ExecuteTime": {
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}
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},
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"outputs": [],
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@@ -45,15 +45,15 @@
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"execution_count": 3,
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"metadata": {
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"ExecuteTime": {
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"start_time": "2018-12-08T14:01:13.059743Z"
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}
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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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"'../outputs/train_2018-12-07_07-38-26.log'"
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"'../outputs/train_2018-12-08_08-34-55.log'"
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]
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},
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"execution_count": 3,
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@@ -83,8 +83,8 @@
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"execution_count": 4,
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"metadata": {
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"ExecuteTime": {
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"end_time": "2018-12-07T06:05:16.553578Z",
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"start_time": "2018-12-07T06:05:16.546753Z"
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"start_time": "2018-12-08T14:01:13.074309Z"
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}
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},
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"outputs": [],
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@@ -112,8 +112,8 @@
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"execution_count": 5,
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"metadata": {
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"ExecuteTime": {
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"end_time": "2018-12-07T06:05:16.594825Z",
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"start_time": "2018-12-07T06:05:16.555877Z"
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"end_time": "2018-12-08T14:01:13.141441Z",
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"start_time": "2018-12-08T14:01:13.086973Z"
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}
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},
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"outputs": [],
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@@ -126,8 +126,8 @@
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"execution_count": 6,
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"metadata": {
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"ExecuteTime": {
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"end_time": "2018-12-07T06:05:16.883358Z",
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"start_time": "2018-12-07T06:05:16.598460Z"
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"end_time": "2018-12-08T14:01:13.424728Z",
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"start_time": "2018-12-08T14:01:13.144119Z"
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},
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"scrolled": true
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},
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@@ -135,7 +135,7 @@
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{
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"data": {
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"text/plain": [
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"<matplotlib.axes._subplots.AxesSubplot at 0x7ff884559b00>"
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"<matplotlib.axes._subplots.AxesSubplot at 0x7f516f97a518>"
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]
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},
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"execution_count": 6,
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@@ -144,9 +144,9 @@
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},
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{
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"data": {
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"image/png": 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truncated
|
||||
"text/plain": [
|
||||
"<matplotlib.figure.Figure at 0x7ff853919780>"
|
||||
"<matplotlib.figure.Figure at 0x7f516fc25c18>"
|
||||
]
|
||||
},
|
||||
"metadata": {},
|
||||
@@ -159,29 +159,29 @@
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 15,
|
||||
"execution_count": 7,
|
||||
"metadata": {
|
||||
"ExecuteTime": {
|
||||
"end_time": "2018-12-07T06:06:36.743828Z",
|
||||
"start_time": "2018-12-07T06:06:36.463093Z"
|
||||
"end_time": "2018-12-08T14:01:13.705024Z",
|
||||
"start_time": "2018-12-08T14:01:13.428611Z"
|
||||
}
|
||||
},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"<matplotlib.axes._subplots.AxesSubplot at 0x7ff884f0cda0>"
|
||||
"<matplotlib.axes._subplots.AxesSubplot at 0x7f516fa66198>"
|
||||
]
|
||||
},
|
||||
"execution_count": 15,
|
||||
"execution_count": 7,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"image/png": 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truncated
|
||||
"image/png": 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truncated
|
||||
"text/plain": [
|
||||
"<matplotlib.figure.Figure at 0x7ff84da32860>"
|
||||
"<matplotlib.figure.Figure at 0x7f516fc53eb8>"
|
||||
]
|
||||
},
|
||||
"metadata": {},
|
||||
@@ -197,15 +197,15 @@
|
||||
"execution_count": 8,
|
||||
"metadata": {
|
||||
"ExecuteTime": {
|
||||
"end_time": "2018-12-07T06:05:17.396367Z",
|
||||
"start_time": "2018-12-07T06:05:17.160066Z"
|
||||
"end_time": "2018-12-08T14:01:13.938521Z",
|
||||
"start_time": "2018-12-08T14:01:13.707513Z"
|
||||
}
|
||||
},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"<matplotlib.axes._subplots.AxesSubplot at 0x7ff88c02f9e8>"
|
||||
"<matplotlib.axes._subplots.AxesSubplot at 0x7f516f972390>"
|
||||
]
|
||||
},
|
||||
"execution_count": 8,
|
||||
@@ -214,9 +214,9 @@
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"image/png": 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truncated
|
||||
"image/png": 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truncated
|
||||
"text/plain": [
|
||||
"<matplotlib.figure.Figure at 0x7ff88c1a3668>"
|
||||
"<matplotlib.figure.Figure at 0x7f516fbec048>"
|
||||
]
|
||||
},
|
||||
"metadata": {},
|
||||
@@ -232,15 +232,15 @@
|
||||
"execution_count": 9,
|
||||
"metadata": {
|
||||
"ExecuteTime": {
|
||||
"end_time": "2018-12-07T06:05:17.728365Z",
|
||||
"start_time": "2018-12-07T06:05:17.398913Z"
|
||||
"end_time": "2018-12-08T14:01:14.271133Z",
|
||||
"start_time": "2018-12-08T14:01:13.941096Z"
|
||||
}
|
||||
},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"<matplotlib.legend.Legend at 0x7ff884d896d8>"
|
||||
"<matplotlib.legend.Legend at 0x7f516fb6deb8>"
|
||||
]
|
||||
},
|
||||
"execution_count": 9,
|
||||
@@ -249,9 +249,9 @@
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"image/png": 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truncated
|
||||
"image/png": 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truncated
|
||||
"text/plain": [
|
||||
"<matplotlib.figure.Figure at 0x7ff884e0ce80>"
|
||||
"<matplotlib.figure.Figure at 0x7f516fb6d588>"
|
||||
]
|
||||
},
|
||||
"metadata": {},
|
||||
@@ -269,15 +269,15 @@
|
||||
"execution_count": 10,
|
||||
"metadata": {
|
||||
"ExecuteTime": {
|
||||
"end_time": "2018-12-07T06:05:18.057535Z",
|
||||
"start_time": "2018-12-07T06:05:17.730931Z"
|
||||
"end_time": "2018-12-08T14:01:14.482924Z",
|
||||
"start_time": "2018-12-08T14:01:14.273830Z"
|
||||
}
|
||||
},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"<matplotlib.axes._subplots.AxesSubplot at 0x7ff884f95ef0>"
|
||||
"<matplotlib.axes._subplots.AxesSubplot at 0x7f516fb1b160>"
|
||||
]
|
||||
},
|
||||
"execution_count": 10,
|
||||
@@ -286,9 +286,9 @@
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"image/png": 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truncated
|
||||
"image/png": 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truncated
|
||||
"text/plain": [
|
||||
"<matplotlib.figure.Figure at 0x7ff8534dfd68>"
|
||||
"<matplotlib.figure.Figure at 0x7f516faa7ac8>"
|
||||
]
|
||||
},
|
||||
"metadata": {},
|
||||
@@ -304,17 +304,17 @@
|
||||
"execution_count": 11,
|
||||
"metadata": {
|
||||
"ExecuteTime": {
|
||||
"end_time": "2018-12-07T06:05:21.713481Z",
|
||||
"start_time": "2018-12-07T06:05:18.059926Z"
|
||||
"end_time": "2018-12-08T14:01:18.120808Z",
|
||||
"start_time": "2018-12-08T14:01:14.485530Z"
|
||||
},
|
||||
"scrolled": false
|
||||
},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"image/png": 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truncated
|
||||
"image/png": 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truncated
|
||||
"text/plain": [
|
||||
"<matplotlib.figure.Figure at 0x7ff884e0cb70>"
|
||||
"<matplotlib.figure.Figure at 0x7f516fabdb00>"
|
||||
]
|
||||
},
|
||||
"metadata": {},
|
||||
@@ -322,9 +322,9 @@
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"image/png": 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truncated
|
||||
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truncated
|
||||
"text/plain": [
|
||||
"<matplotlib.figure.Figure at 0x7ff884e27438>"
|
||||
"<matplotlib.figure.Figure at 0x7f516a0dfc18>"
|
||||
]
|
||||
},
|
||||
"metadata": {},
|
||||
@@ -332,9 +332,9 @@
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
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truncated
|
||||
"image/png": 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truncated
|
||||
"text/plain": [
|
||||
"<matplotlib.figure.Figure at 0x7ff884f059e8>"
|
||||
"<matplotlib.figure.Figure at 0x7f516a0fb4a8>"
|
||||
]
|
||||
},
|
||||
"metadata": {},
|
||||
@@ -342,9 +342,9 @@
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"image/png": 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truncated
|
||||
"image/png": 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truncated
|
||||
"text/plain": [
|
||||
"<matplotlib.figure.Figure at 0x7ff88c03f0f0>"
|
||||
"<matplotlib.figure.Figure at 0x7f516a090160>"
|
||||
]
|
||||
},
|
||||
"metadata": {},
|
||||
@@ -352,9 +352,9 @@
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"image/png": 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truncated
|
||||
"image/png": 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truncated
|
||||
"text/plain": [
|
||||
"<matplotlib.figure.Figure at 0x7ff88c1d5eb8>"
|
||||
"<matplotlib.figure.Figure at 0x7f5169ffd748>"
|
||||
]
|
||||
},
|
||||
"metadata": {},
|
||||
@@ -362,9 +362,9 @@
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"image/png": 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truncated
|
||||
"image/png": 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truncated
|
||||
"text/plain": [
|
||||
"<matplotlib.figure.Figure at 0x7ff88c162c18>"
|
||||
"<matplotlib.figure.Figure at 0x7f5169fdb908>"
|
||||
]
|
||||
},
|
||||
"metadata": {},
|
||||
@@ -372,9 +372,9 @@
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"image/png": 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truncated
|
||||
"image/png": 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truncated
|
||||
"text/plain": [
|
||||
"<matplotlib.figure.Figure at 0x7ff84da8c470>"
|
||||
"<matplotlib.figure.Figure at 0x7f516fa43860>"
|
||||
]
|
||||
},
|
||||
"metadata": {},
|
||||
@@ -382,9 +382,9 @@
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"image/png": 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truncated
|
||||
"image/png": 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truncated
|
||||
"text/plain": [
|
||||
"<matplotlib.figure.Figure at 0x7ff88c0df3c8>"
|
||||
"<matplotlib.figure.Figure at 0x7f516a06af28>"
|
||||
]
|
||||
},
|
||||
"metadata": {},
|
||||
@@ -392,9 +392,9 @@
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"image/png": 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truncated
|
||||
"image/png": 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truncated
|
||||
"text/plain": [
|
||||
"<matplotlib.figure.Figure at 0x7ff88c12a6a0>"
|
||||
"<matplotlib.figure.Figure at 0x7f516a0ca630>"
|
||||
]
|
||||
},
|
||||
"metadata": {},
|
||||
@@ -402,9 +402,9 @@
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"image/png": 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truncated
|
||||
"image/png": 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truncated
|
||||
"text/plain": [
|
||||
"<matplotlib.figure.Figure at 0x7ff884ea4fd0>"
|
||||
"<matplotlib.figure.Figure at 0x7f516a070518>"
|
||||
]
|
||||
},
|
||||
"metadata": {},
|
||||
@@ -412,9 +412,9 @@
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"image/png": 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truncated
|
||||
"image/png": 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truncated
|
||||
"text/plain": [
|
||||
"<matplotlib.figure.Figure at 0x7ff84da665f8>"
|
||||
"<matplotlib.figure.Figure at 0x7f5169f2f630>"
|
||||
]
|
||||
},
|
||||
"metadata": {},
|
||||
@@ -422,9 +422,9 @@
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"image/png": 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truncated
|
||||
"image/png": 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truncated
|
||||
"text/plain": [
|
||||
"<matplotlib.figure.Figure at 0x7ff84d98b6a0>"
|
||||
"<matplotlib.figure.Figure at 0x7f5169f13748>"
|
||||
]
|
||||
},
|
||||
"metadata": {},
|
||||
@@ -432,9 +432,9 @@
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"image/png": 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truncated
|
||||
"image/png": 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truncated
|
||||
"text/plain": [
|
||||
"<matplotlib.figure.Figure at 0x7ff84d9a2a20>"
|
||||
"<matplotlib.figure.Figure at 0x7f5169e5e278>"
|
||||
]
|
||||
},
|
||||
"metadata": {},
|
||||
@@ -442,9 +442,9 @@
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"image/png": 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truncated
|
||||
"image/png": 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truncated
|
||||
"text/plain": [
|
||||
"<matplotlib.figure.Figure at 0x7ff84d936dd8>"
|
||||
"<matplotlib.figure.Figure at 0x7f5169e42c50>"
|
||||
]
|
||||
},
|
||||
"metadata": {},
|
||||
@@ -452,9 +452,9 @@
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"image/png": 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truncated
|
||||
"image/png": 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truncated
|
||||
"text/plain": [
|
||||
"<matplotlib.figure.Figure at 0x7ff84d90f898>"
|
||||
"<matplotlib.figure.Figure at 0x7f5169ded4a8>"
|
||||
]
|
||||
},
|
||||
"metadata": {},
|
||||
@@ -462,9 +462,9 @@
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"image/png": 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truncated
|
||||
"image/png": 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truncated
|
||||
"text/plain": [
|
||||
"<matplotlib.figure.Figure at 0x7ff884eef160>"
|
||||
"<matplotlib.figure.Figure at 0x7f5169d6b358>"
|
||||
]
|
||||
},
|
||||
"metadata": {},
|
||||
@@ -472,9 +472,9 @@
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"image/png": 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truncated
|
||||
"image/png": 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truncated
|
||||
"text/plain": [
|
||||
"<matplotlib.figure.Figure at 0x7ff88c1da748>"
|
||||
"<matplotlib.figure.Figure at 0x7f5169d589b0>"
|
||||
]
|
||||
},
|
||||
"metadata": {},
|
||||
@@ -482,9 +482,9 @@
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"image/png": 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truncated
|
||||
"image/png": 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truncated
|
||||
"text/plain": [
|
||||
"<matplotlib.figure.Figure at 0x7ff884f720f0>"
|
||||
"<matplotlib.figure.Figure at 0x7f5169cb9a20>"
|
||||
]
|
||||
},
|
||||
"metadata": {},
|
||||
@@ -492,9 +492,9 @@
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"image/png": 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truncated
|
||||
"image/png": 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truncated
|
||||
"text/plain": [
|
||||
"<matplotlib.figure.Figure at 0x7ff884e190b8>"
|
||||
"<matplotlib.figure.Figure at 0x7f5169c74d30>"
|
||||
]
|
||||
},
|
||||
"metadata": {},
|
||||
@@ -502,9 +502,9 @@
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"image/png": 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truncated
|
||||
"image/png": "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 truncated
|
||||
"text/plain": [
|
||||
"<matplotlib.figure.Figure at 0x7ff88c220d30>"
|
||||
"<matplotlib.figure.Figure at 0x7f5169c2f358>"
|
||||
]
|
||||
},
|
||||
"metadata": {},
|
||||
|
||||
+3
-3
@@ -72,9 +72,9 @@ class HeadlessGame {
|
||||
|
||||
desiredActionStddev: 0.2,
|
||||
minActionStddev: 0.001,
|
||||
initialStddev: 0.4,
|
||||
initialStddev: 0.6,
|
||||
adoptionCoefficient: 1.01,
|
||||
noiseDecay: 0.999,
|
||||
noiseDecay: 0.99,
|
||||
|
||||
actorFirstLayerSize: 128,
|
||||
actorSecondLayerSize: 64,
|
||||
@@ -82,7 +82,7 @@ class HeadlessGame {
|
||||
criticFirstLayerASize: 128,
|
||||
criticSecondLayerSize: 64,
|
||||
|
||||
nbEpochs: 700,
|
||||
nbEpochs: 500,
|
||||
nbEpochsCycle: 10,
|
||||
nbTrainSteps: 100,
|
||||
maxStep: 1800,
|
||||
|
||||
+7
-7
@@ -10,7 +10,7 @@ const {
|
||||
Renderer
|
||||
} = require('./renderer')
|
||||
|
||||
const STRENGTH = 2
|
||||
const STRENGTH = 1.7
|
||||
|
||||
class Walker {
|
||||
constructor(world, floor, config) {
|
||||
@@ -134,16 +134,16 @@ class Walker {
|
||||
var otherFixture = contact.m_fixtureA.m_body.m_userData == "floor" ? contact.m_fixtureB : contact.m_fixtureA
|
||||
if (otherFixture.m_body === self.right_leg.foot) {
|
||||
// TODO let the agent act to grip or not. Only if palm or foot down?
|
||||
self.right_leg.frictionJoint.maxForce = 1000 * self.grips[0]
|
||||
self.right_leg.frictionJoint.maxForce = 0 * self.grips[0]
|
||||
self.right_leg.frictionJoint.maxTorque = 1000 * self.grips[0]
|
||||
} else if (otherFixture.m_body === self.left_leg.foot) {
|
||||
self.left_leg.frictionJoint.maxForce = 1000 * self.grips[1]
|
||||
self.left_leg.frictionJoint.maxForce = 0 * self.grips[1]
|
||||
self.left_leg.frictionJoint.maxTorque = 1000 * self.grips[1]
|
||||
} else if (otherFixture.m_body == self.right_arm.hand) {
|
||||
self.right_arm.frictionJoint.maxForce = 1000 * self.grips[2]
|
||||
self.right_arm.frictionJoint.maxForce = 0 * self.grips[2]
|
||||
self.right_arm.frictionJoint.maxTorque = 1000 * self.grips[2]
|
||||
} else if (otherFixture.m_body === self.left_arm.hand) {
|
||||
self.left_arm.frictionJoint.maxForce = 1000 * self.grips[3]
|
||||
self.left_arm.frictionJoint.maxForce = 0 * self.grips[3]
|
||||
self.left_arm.frictionJoint.maxTorque = 1000 * self.grips[3]
|
||||
}
|
||||
}
|
||||
@@ -211,10 +211,10 @@ class Walker {
|
||||
position.y -= this.torso_def.upper_height / 2;
|
||||
position.x -= this.torso_def.lower_width / 3;
|
||||
jd.Initialize(upper_torso, lower_torso, position);
|
||||
jd.lowerAngle = deg2rad(-35 / 2);
|
||||
jd.lowerAngle = deg2rad(-10 / 2);
|
||||
jd.upperAngle = deg2rad(30 / 2);
|
||||
jd.enableLimit = true;
|
||||
jd.maxMotorTorque = 150 * STRENGTH;
|
||||
jd.maxMotorTorque = 10 * STRENGTH;
|
||||
jd.motorSpeed = 0;
|
||||
jd.enableMotor = true;
|
||||
var j = this.world.CreateJoint(jd)
|
||||
|
||||
Reference in new issue
Block a user