mirror of
https://github.com/clearml/clearml
synced 2025-01-31 09:07:00 +00:00
161 lines
48 KiB
Plaintext
161 lines
48 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {
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"pycharm": {
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"is_executing": false
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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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"TRAINS Task: created new task id=e8fc2b809a384c3f8ec3ded54a2aae44\n",
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"TRAINS results page: http://ec2-3-218-72-191.compute-1.amazonaws.com:8080/projects/ec4476fb59c64d89af880ff0445c836b/experiments/e8fc2b809a384c3f8ec3ded54a2aae44/output/log\n"
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]
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}
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],
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"source": [
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"from trains import Task\n",
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"task = Task.init(project_name='examples', task_name='Jupyter exmaple')"
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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": 2,
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"metadata": {},
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"outputs": [],
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"source": [
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"import numpy as np\n",
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"import matplotlib.pyplot as plt\n",
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"import matplotlib\n",
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"%matplotlib inline"
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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": 3,
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"metadata": {
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"pycharm": {
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"name": "#%%\n"
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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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"image/png": 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\n",
|
|
"text/plain": [
|
|
"<Figure size 432x288 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {
|
|
"needs_background": "light"
|
|
},
|
|
"output_type": "display_data"
|
|
},
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"[<matplotlib.lines.Line2D at 0x7fcd6491d898>]"
|
|
]
|
|
},
|
|
"execution_count": 3,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"data": {
|
|
"image/png": "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\n",
|
|
"text/plain": [
|
|
"<Figure size 432x288 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {
|
|
"needs_background": "light"
|
|
},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"N = 50\n",
|
|
"x = np.random.rand(N)\n",
|
|
"y = np.random.rand(N)\n",
|
|
"colors = np.random.rand(N)\n",
|
|
"area = (30 * np.random.rand(N))**2 # 0 to 15 point radii\n",
|
|
"plt.scatter(x, y, s=area, c=colors, alpha=0.5)\n",
|
|
"plt.show()\n",
|
|
"\n",
|
|
"x = np.linspace(0, 10, 30)\n",
|
|
"y = np.sin(x)\n",
|
|
"plt.plot(x, y, 'o', color='black')"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 4,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"<matplotlib.image.AxesImage at 0x7fcd646ff550>"
|
|
]
|
|
},
|
|
"execution_count": 4,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
},
|
|
{
|
|
"data": {
|
|
"image/png": "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\n",
|
|
"text/plain": [
|
|
"<Figure size 432x288 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {
|
|
"needs_background": "light"
|
|
},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"m = np.eye(8, 8, dtype=np.uint8)\n",
|
|
"plt.imshow(m)"
|
|
]
|
|
}
|
|
],
|
|
"metadata": {
|
|
"kernelspec": {
|
|
"display_name": "PyCharm (trains-internal)",
|
|
"language": "python",
|
|
"name": "pycharm-40126efe"
|
|
},
|
|
"language_info": {
|
|
"codemirror_mode": {
|
|
"name": "ipython",
|
|
"version": 3
|
|
},
|
|
"file_extension": ".py",
|
|
"mimetype": "text/x-python",
|
|
"name": "python",
|
|
"nbconvert_exporter": "python",
|
|
"pygments_lexer": "ipython3",
|
|
"version": "3.5.2"
|
|
},
|
|
"pycharm": {
|
|
"stem_cell": {
|
|
"cell_type": "raw",
|
|
"metadata": {
|
|
"collapsed": false
|
|
},
|
|
"source": []
|
|
}
|
|
}
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 1
|
|
}
|