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tsbertalan/Streaming Bokeh Plot.ipynb

Last active January 6, 2021 04:04
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Update a loss history plot live in a Jupyter notebook.
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Streaming Bokeh Plot.ipynb
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Simulate streaming data\n",
"This example shows how to dynamically update a Bokeh plot as new data comes in."
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
" <div class=\"bk-root\">\n",
" <a href=\"https://bokeh.pydata.org\" target=\"_blank\" class=\"bk-logo bk-logo-small bk-logo-notebook\"></a>\n",
" <span id=\"1001\">Loading BokehJS ...</span>\n",
" </div>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"application/javascript": [
"\n",
"(function(root) {\n",
" function now() {\n",
" return new Date();\n",
" }\n",
"\n",
" var force = true;\n",
"\n",
" if (typeof (root._bokeh_onload_callbacks) === \"undefined\" || force === true) {\n",
" root._bokeh_onload_callbacks = [];\n",
" root._bokeh_is_loading = undefined;\n",
" }\n",
"\n",
" var JS_MIME_TYPE = 'application/javascript';\n",
" var HTML_MIME_TYPE = 'text/html';\n",
" var EXEC_MIME_TYPE = 'application/vnd.bokehjs_exec.v0+json';\n",
" var CLASS_NAME = 'output_bokeh rendered_html';\n",
"\n",
" /**\n",
" * Render data to the DOM node\n",
" */\n",
" function render(props, node) {\n",
" var script = document.createElement(\"script\");\n",
" node.appendChild(script);\n",
" }\n",
"\n",
" /**\n",
" * Handle when an output is cleared or removed\n",
" */\n",
" function handleClearOutput(event, handle) {\n",
" var cell = handle.cell;\n",
"\n",
" var id = cell.output_area._bokeh_element_id;\n",
" var server_id = cell.output_area._bokeh_server_id;\n",
" // Clean up Bokeh references\n",
" if (id != null && id in Bokeh.index) {\n",
" Bokeh.index[id].model.document.clear();\n",
" delete Bokeh.index[id];\n",
" }\n",
"\n",
" if (server_id !== undefined) {\n",
" // Clean up Bokeh references\n",
" var cmd = \"from bokeh.io.state import curstate; print(curstate().uuid_to_server['\" + server_id + \"'].get_sessions()[0].document.roots[0]._id)\";\n",
" cell.notebook.kernel.execute(cmd, {\n",
" iopub: {\n",
" output: function(msg) {\n",
" var id = msg.content.text.trim();\n",
" if (id in Bokeh.index) {\n",
" Bokeh.index[id].model.document.clear();\n",
" delete Bokeh.index[id];\n",
" }\n",
" }\n",
" }\n",
" });\n",
" // Destroy server and session\n",
" var cmd = \"import bokeh.io.notebook as ion; ion.destroy_server('\" + server_id + \"')\";\n",
" cell.notebook.kernel.execute(cmd);\n",
" }\n",
" }\n",
"\n",
" /**\n",
" * Handle when a new output is added\n",
" */\n",
" function handleAddOutput(event, handle) {\n",
" var output_area = handle.output_area;\n",
" var output = handle.output;\n",
"\n",
" // limit handleAddOutput to display_data with EXEC_MIME_TYPE content only\n",
" if ((output.output_type != \"display_data\") || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n",
" return\n",
" }\n",
"\n",
" var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n",
"\n",
" if (output.metadata[EXEC_MIME_TYPE][\"id\"] !== undefined) {\n",
" toinsert[toinsert.length - 1].firstChild.textContent = output.data[JS_MIME_TYPE];\n",
" // store reference to embed id on output_area\n",
" output_area._bokeh_element_id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n",
" }\n",
" if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n",
" var bk_div = document.createElement(\"div\");\n",
" bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n",
" var script_attrs = bk_div.children[0].attributes;\n",
" for (var i = 0; i < script_attrs.length; i++) {\n",
" toinsert[toinsert.length - 1].firstChild.setAttribute(script_attrs[i].name, script_attrs[i].value);\n",
" }\n",
" // store reference to server id on output_area\n",
" output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n",
" }\n",
" }\n",
"\n",
" function register_renderer(events, OutputArea) {\n",
"\n",
" function append_mime(data, metadata, element) {\n",
" // create a DOM node to render to\n",
" var toinsert = this.create_output_subarea(\n",
" metadata,\n",
" CLASS_NAME,\n",
" EXEC_MIME_TYPE\n",
" );\n",
" this.keyboard_manager.register_events(toinsert);\n",
" // Render to node\n",
" var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n",
" render(props, toinsert[toinsert.length - 1]);\n",
" element.append(toinsert);\n",
" return toinsert\n",
" }\n",
"\n",
" /* Handle when an output is cleared or removed */\n",
" events.on('clear_output.CodeCell', handleClearOutput);\n",
" events.on('delete.Cell', handleClearOutput);\n",
"\n",
" /* Handle when a new output is added */\n",
" events.on('output_added.OutputArea', handleAddOutput);\n",
"\n",
" /**\n",
" * Register the mime type and append_mime function with output_area\n",
" */\n",
" OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n",
" /* Is output safe? */\n",
" safe: true,\n",
" /* Index of renderer in `output_area.display_order` */\n",
" index: 0\n",
" });\n",
" }\n",
"\n",
" // register the mime type if in Jupyter Notebook environment and previously unregistered\n",
" if (root.Jupyter !== undefined) {\n",
" var events = require('base/js/events');\n",
" var OutputArea = require('notebook/js/outputarea').OutputArea;\n",
"\n",
" if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n",
" register_renderer(events, OutputArea);\n",
" }\n",
" }\n",
"\n",
" \n",
" if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n",
" root._bokeh_timeout = Date.now() + 5000;\n",
" root._bokeh_failed_load = false;\n",
" }\n",
"\n",
" var NB_LOAD_WARNING = {'data': {'text/html':\n",
" \"<div style='background-color: #fdd'>\\n\"+\n",
" \"<p>\\n\"+\n",
" \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
" \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
" \"</p>\\n\"+\n",
" \"<ul>\\n\"+\n",
" \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
" \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
" \"</ul>\\n\"+\n",
" \"<code>\\n\"+\n",
" \"from bokeh.resources import INLINE\\n\"+\n",
" \"output_notebook(resources=INLINE)\\n\"+\n",
" \"</code>\\n\"+\n",
" \"</div>\"}};\n",
"\n",
" function display_loaded() {\n",
" var el = document.getElementById(\"1001\");\n",
" if (el != null) {\n",
" el.textContent = \"BokehJS is loading...\";\n",
" }\n",
" if (root.Bokeh !== undefined) {\n",
" if (el != null) {\n",
" el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n",
" }\n",
" } else if (Date.now() < root._bokeh_timeout) {\n",
" setTimeout(display_loaded, 100)\n",
" }\n",
" }\n",
"\n",
"\n",
" function run_callbacks() {\n",
" try {\n",
" root._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n",
" }\n",
" finally {\n",
" delete root._bokeh_onload_callbacks\n",
" }\n",
" console.info(\"Bokeh: all callbacks have finished\");\n",
" }\n",
"\n",
" function load_libs(js_urls, callback) {\n",
" root._bokeh_onload_callbacks.push(callback);\n",
" if (root._bokeh_is_loading > 0) {\n",
" console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
" return null;\n",
" }\n",
" if (js_urls == null || js_urls.length === 0) {\n",
" run_callbacks();\n",
" return null;\n",
" }\n",
" console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
" root._bokeh_is_loading = js_urls.length;\n",
" for (var i = 0; i < js_urls.length; i++) {\n",
" var url = js_urls[i];\n",
" var s = document.createElement('script');\n",
" s.src = url;\n",
" s.async = false;\n",
" s.onreadystatechange = s.onload = function() {\n",
" root._bokeh_is_loading--;\n",
" if (root._bokeh_is_loading === 0) {\n",
" console.log(\"Bokeh: all BokehJS libraries loaded\");\n",
" run_callbacks()\n",
" }\n",
" };\n",
" s.onerror = function() {\n",
" console.warn(\"failed to load library \" + url);\n",
" };\n",
" console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
" document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
" }\n",
" };var element = document.getElementById(\"1001\");\n",
" if (element == null) {\n",
" console.log(\"Bokeh: ERROR: autoload.js configured with elementid '1001' but no matching script tag was found. \")\n",
" return false;\n",
" }\n",
"\n",
" var js_urls = [\"https://cdn.pydata.org/bokeh/release/bokeh-1.0.1.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-widgets-1.0.1.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-tables-1.0.1.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-gl-1.0.1.min.js\"];\n",
"\n",
" var inline_js = [\n",
" function(Bokeh) {\n",
" Bokeh.set_log_level(\"info\");\n",
" },\n",
" \n",
" function(Bokeh) {\n",
" \n",
" },\n",
" function(Bokeh) {\n",
" console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-1.0.1.min.css\");\n",
" Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-1.0.1.min.css\");\n",
" console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-widgets-1.0.1.min.css\");\n",
" Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-widgets-1.0.1.min.css\");\n",
" console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-tables-1.0.1.min.css\");\n",
" Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-tables-1.0.1.min.css\");\n",
" }\n",
" ];\n",
"\n",
" function run_inline_js() {\n",
" \n",
" if ((root.Bokeh !== undefined) || (force === true)) {\n",
" for (var i = 0; i < inline_js.length; i++) {\n",
" inline_js[i].call(root, root.Bokeh);\n",
" }if (force === true) {\n",
" display_loaded();\n",
" }} else if (Date.now() < root._bokeh_timeout) {\n",
" setTimeout(run_inline_js, 100);\n",
" } else if (!root._bokeh_failed_load) {\n",
" console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
" root._bokeh_failed_load = true;\n",
" } else if (force !== true) {\n",
" var cell = $(document.getElementById(\"1001\")).parents('.cell').data().cell;\n",
" cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
" }\n",
"\n",
" }\n",
"\n",
" if (root._bokeh_is_loading === 0) {\n",
" console.log(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
" run_inline_js();\n",
" } else {\n",
" load_libs(js_urls, function() {\n",
" console.log(\"Bokeh: BokehJS plotting callback run at\", now());\n",
" run_inline_js();\n",
" });\n",
" }\n",
"}(window));"
],
"application/vnd.bokehjs_load.v0+json": "\n(function(root) {\n function now() {\n return new Date();\n }\n\n var force = true;\n\n if (typeof (root._bokeh_onload_callbacks) === \"undefined\" || force === true) {\n root._bokeh_onload_callbacks = [];\n root._bokeh_is_loading = undefined;\n }\n\n \n\n \n if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n root._bokeh_timeout = Date.now() + 5000;\n root._bokeh_failed_load = false;\n }\n\n var NB_LOAD_WARNING = {'data': {'text/html':\n \"<div style='background-color: #fdd'>\\n\"+\n \"<p>\\n\"+\n \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n \"</p>\\n\"+\n \"<ul>\\n\"+\n \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n \"<li>use INLINE resources instead, as so:</li>\\n\"+\n \"</ul>\\n\"+\n \"<code>\\n\"+\n \"from bokeh.resources import INLINE\\n\"+\n \"output_notebook(resources=INLINE)\\n\"+\n \"</code>\\n\"+\n \"</div>\"}};\n\n function display_loaded() {\n var el = document.getElementById(\"1001\");\n if (el != null) {\n el.textContent = \"BokehJS is loading...\";\n }\n if (root.Bokeh !== undefined) {\n if (el != null) {\n el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n }\n } else if (Date.now() < root._bokeh_timeout) {\n setTimeout(display_loaded, 100)\n }\n }\n\n\n function run_callbacks() {\n try {\n root._bokeh_onload_callbacks.forEach(function(callback) { callback() });\n }\n finally {\n delete root._bokeh_onload_callbacks\n }\n console.info(\"Bokeh: all callbacks have finished\");\n }\n\n function load_libs(js_urls, callback) {\n root._bokeh_onload_callbacks.push(callback);\n if (root._bokeh_is_loading > 0) {\n console.log(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n return null;\n }\n if (js_urls == null || js_urls.length === 0) {\n run_callbacks();\n return null;\n }\n console.log(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n root._bokeh_is_loading = js_urls.length;\n for (var i = 0; i < js_urls.length; i++) {\n var url = js_urls[i];\n var s = document.createElement('script');\n s.src = url;\n s.async = false;\n s.onreadystatechange = s.onload = function() {\n root._bokeh_is_loading--;\n if (root._bokeh_is_loading === 0) {\n console.log(\"Bokeh: all BokehJS libraries loaded\");\n run_callbacks()\n }\n };\n s.onerror = function() {\n console.warn(\"failed to load library \" + url);\n };\n console.log(\"Bokeh: injecting script tag for BokehJS library: \", url);\n document.getElementsByTagName(\"head\")[0].appendChild(s);\n }\n };var element = document.getElementById(\"1001\");\n if (element == null) {\n console.log(\"Bokeh: ERROR: autoload.js configured with elementid '1001' but no matching script tag was found. \")\n return false;\n }\n\n var js_urls = [\"https://cdn.pydata.org/bokeh/release/bokeh-1.0.1.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-widgets-1.0.1.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-tables-1.0.1.min.js\", \"https://cdn.pydata.org/bokeh/release/bokeh-gl-1.0.1.min.js\"];\n\n var inline_js = [\n function(Bokeh) {\n Bokeh.set_log_level(\"info\");\n },\n \n function(Bokeh) {\n \n },\n function(Bokeh) {\n console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-1.0.1.min.css\");\n Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-1.0.1.min.css\");\n console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-widgets-1.0.1.min.css\");\n Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-widgets-1.0.1.min.css\");\n console.log(\"Bokeh: injecting CSS: https://cdn.pydata.org/bokeh/release/bokeh-tables-1.0.1.min.css\");\n Bokeh.embed.inject_css(\"https://cdn.pydata.org/bokeh/release/bokeh-tables-1.0.1.min.css\");\n }\n ];\n\n function run_inline_js() {\n \n if ((root.Bokeh !== undefined) || (force === true)) {\n for (var i = 0; i < inline_js.length; i++) {\n inline_js[i].call(root, root.Bokeh);\n }if (force === true) {\n display_loaded();\n }} else if (Date.now() < root._bokeh_timeout) {\n setTimeout(run_inline_js, 100);\n } else if (!root._bokeh_failed_load) {\n console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n root._bokeh_failed_load = true;\n } else if (force !== true) {\n var cell = $(document.getElementById(\"1001\")).parents('.cell').data().cell;\n cell.output_area.append_execute_result(NB_LOAD_WARNING)\n }\n\n }\n\n if (root._bokeh_is_loading === 0) {\n console.log(\"Bokeh: BokehJS loaded, going straight to plotting\");\n run_inline_js();\n } else {\n load_libs(js_urls, function() {\n console.log(\"Bokeh: BokehJS plotting callback run at\", now());\n run_inline_js();\n });\n }\n}(window));"
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"from time import sleep\n",
"import numpy as np\n",
"from bokeh.io import push_notebook, show, output_notebook\n",
"from bokeh.plotting import figure\n",
"output_notebook()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Make some fake training data."
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n",
"\n",
"\n",
"\n",
"\n",
" <div class=\"bk-root\" id=\"006e39d0-e1b5-4f27-90dd-5333a8798e5e\"></div>\n"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"application/javascript": [
"(function(root) {\n",
" function embed_document(root) {\n",
" \n",
" var docs_json = 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DUP+5+kEU719Y/WIC5Ny6P1j8D9vYZikDXP+Vxy0Lc1dU/shGTmCa41T9z5gIMxVDUPyVw+FrQSdU/4H2Rdgf21T86rj8C0yLTP/YsX1P7ldI/jbmi6ivE1T9qiDvWmxzVP05U/t6GDdQ/YkmnBGs+0j9ofd6ZfNfSP30Sg+53mtQ/ESdH9jsI1j9y8k/GQrDRP078KNHmdNQ/Fw3BJs/c1D9gWSAu2tfSPy3VfzjqONY/STjiOOO11T/BHofKF1HSPzSGNynendI/bGR5zV2b1T8kdbvybYPRPw5Vitb+QNQ/aAA+nOSr1D+06ri0kw/SP82bBq884NU/CxshAWos0z9XvBjhRMjSP1fkw0PdvNI/ZLCIERnc0z8lCZHJhGfTPwzr4ndoOdQ/Ota9tdvU0z/rsrE0YOzSP1jEWh90fNI/AQ/1yjkE0j/cIiCgOMrSPzRhST/Zl9I/2tPmQxUI1D+UNMPTOdPSP/RPAOh/u9E/dYZ2rx900T9bPI4EqU7TP+10AQ0yPtI/q3M1ZTU/0z8e38lp1f/WP8jwXC6aeNI/zdxqUvKu0j8DtiTIQxDUP5izZTNBztI/oasYOMqR0z/lJLfOG87SPxHFvkn2v9E/jJODjX/B0j/TPMfEfxjTPwGN5gkO49M/RPmmqmLc0z+8ehXAUd7RPyAvVO1tVtA/yaizDRX/0j/A2xqqCyDRP7WGDmoWtNE/SaBd26Upzz8ac6xAm0/RPyaPAQ9cjdM/njOeDc3V0j/C//bZ4kfQP8mrsJelp9I/ATnikWsJ0j+n+ShlxsDQP8W5Ws2BVtE/23OaqYHW0j/+aueHIuXPP0pWTvIfBdI/jmpRTvsSzj8wb77PNgHQP0G6sVzK/tE/pMiBDYY/0z+9OlkM0kPMP1oofDKpFM4/d7EsC4pU0D+NpsGAGZ3OPzH3ovpX4tE/76RmwHLL0T8HUvQUW+LOP3jTslaThtA//GvrTzFSzj/4xTZx0ErOPzGLi27n8NE/psQzb0vh0D+qLezp2VvQP0GaOxzxq80/73JoY4RY0j87VNMSesbRP9T7hFakcc8/WcbGJyE1zz+AEd0IWfHQP7PzgjiqS8w/+oae0CGLzD8g1TAxr1LNP0gQRCo0ZM8/8Flv8JWXyz+YW+D5Aq7RP5iyw9m9zs0/07uEB0U4yz+nU1jdmxHPP1bNy4mx7s4/KTlotba2zT8EU3W2sNnIP7WuH4d+zc4/IyO1wuro0D99gf9pClrLP6Qe/V9QGM8/azfWBXWU0T9CpP0xtGLSP4EfVsHFKNE/j3ftvBt4zD8rMbZPd83OP1Q7PfLe/c4/IBlPM0NDzT9momepa0PMP7DmSeSz08c/+ZuCHXTgzj/YTKLdF07NP3b3T3vqR80/Ri3uU4d3yz/UhXTMS+zIP2d6g9CHhMo/l9bNPSiyyj8FxIf+eO/IP35ZiFEiSco/61nnrA3vzT9TKrvqoI/PPzNyuiD6Jcw/FqgEAGZDyz9LugQWbhfKP711ekA0UtA/FyFXeWciyz/KFq5xwOzIP0C2pu4vhNE/SMPdWpE3yD/gfJcUeAzNP/yCT4dsAsg/cPnhRPeizT+sg/qXp6rNP4W0gb2JdMw/daX3jVY4yz/EVP4rC5HNPxZBhdtvEss/UllzYSoEyT9EJFj+12rIP9EOKYV1/8k/FgeVyLwGzD9ELjMngBDKP7zIUUBy0sk/prWTkUP/xz+pQjXX+h/PP3ayl3bmt8k/e9P9rYdpzT8eAB2HEdDIPzabosL/IsU/ncfcyIS7yT+GTW6p6IHGP3EAhswRPMc/ed+hu5iLyT9q3KbsDADNP5hvMQhmvco/oDZaDQx+0D++TQx+J3fLP9y4BWmtYcs/plFisrLbyT97LjSHlFPKP8f2/12Hwss/fqMega/jyD8HQIi7X37IP8GB5cef3Ms/Syu1eaYJwz+9eaQU2oDHPye3u3xV+sk/tJA6crXdxj+qx0TC0SfGP/pig9BhpMg/bU6dBGE6zj8Y8xGL4M/FP8Gxfg4tfsU/uNzSpjI4yT+Yhgsi3+PBP/I5HTqp88Y/110WsZ2PyT/AEdJ+Md3DP/uePpcpVMU/0La9lPbLxT+RiSEFFZnIP6hkXF8sOc4/hUIFHwlDyT/eFqtfoY3EPwCPzZmCIMk/JCwxmEMgvz+BNALBg/rAP7X8qid2vMU/sfpLyexmyD+X2tFtS87BP7HCFaoHYcI/WbqSpyLexz9UEXdhh6zEPycBoJRHXsA/GuOmCQUhyD9Eg68XEQDDP7clOa5I/sc/ufRT8i0WzT+VnNGBl3DLP1uyXIioxcQ/3lLtfDyvxj9XA4KGh97FPynmClZ9ysk/p3Dxke4oxT8Ly11/353DP+M9y/YrtMU/o4Xgo7ifxD983MdMb1jEP1xATEc/zMM/mkCMeMtNvj8sNzbAidbHPycE/5hmmcc/rNv2eReayD+EkRVdntvBP6T/FXF9d8U/G2hNuUkLxT8kh3hU+F7GP1be7kUWnsc/0aIDJy/swD+A+/zPhVXCPy60EFDZZMk/RsspMkZvwz9mpYLz8FTIPxXzUjl2vsc/H6kJqpTtxD+Bi3zD5xnEP8reCWyl9MU/OyhmsI9Pxj/kXt4AMq6+P0tkKsFe28U/+IXJYspDxz8GqaXhkcLEPxCBd8KkFsk/jmfMafWjwD+lm9O/E2rGP1g4mPD3csg/D0getU/cxT/D8SADQMnCP6xmky02oMk/LB9RwTS0yD/BMS9vX93CP+49URmr/sE/9F8ah9ZSxj8ouXSk4QPAP0Oi/JzHncU/DS0H8Dyruz9gf32MeLPBP31AuKspf8M/sFRQ4xhLwT9HT7FkSYbHPyGUEM7I08A/nAE2ndXywz+aSRHE0zrKP1iUmiM9qL4/VaFCab25zD9derBRyf7EPwb0sXpYlLs/XBjrhY9OwT/qBeZ39kzIP4eIeLOQ8sQ/kqSv3FnNwz8xlq3JXxjBP0MbgaovJ8A/DWQ6popCwz9vnqjs7lnGP5CMlufEEbg/hv/8YbZrwj9HrPmNPSnDP+ioK3SyZ8Q/FHwKTZQGxj80Ys+eGNTBPw3R5YOMhb0/dinaMi1Zsz/e+/BdigDBP2HTRruNA8Q/xOaxLjyztj+MM/++XLe9Pxw9qAirK7o/T+lg5xXVwD+Eg8excivBP+oVoXLgwsY/3w9sBB7bvj/+HIZ61w7DP+TzHJXXn7c/DLkkgbfBwD+dxQOXqV+8P70jF/r3CcA/lXgAyO+Rtj/IVq6S4UDBP0raSkMTObo/pPwo0wlfvD8m+UR/9SHHP9eVD/suAcQ/EgivdPzdvT90X8bDIFvGP9VBSr2+p70/YsjujbtRxD9O3UqQpRTDP1Qy0TXrnr8/BOaMNbcWwz91eHMmVCm9PywGjUbFksE/Q7MRnpC0vT9vCCL1mFG4P/QbceTkMbk/AGwguPMKwD/4jAwaPPG+P8G3HFe697o/YWuze2TitT9se3Dmx8W/PyykCaXPhcA/Snj6oyi1wj8Ht3uyF5bDP3gpP+9BHLQ/77LvOjWouz/QJwLtBQnEP1WlH668ncA/TW7HmMWmvD9mwWUXORC1Pw+JymMOGLY/Q9YdjV6StT+E5AH806fBP1DZhpEO4cE/nEGoAvadxT9ovit+t1a+PxyMX1x7br8/rPH1z8FExD8hWeTWuVK7P41eK7wk6bc/UoXkbqbQxT9K54BH7qizP8yhYnt1sbg/vThx1fIUvj94lzuH96XAP+SVcQvihME/FMoxLlz0tT/k1jzrUfbFP1+WOzElwrs/EeDcHbZJuD/o+Im5nWXGPykks79eUb8/7Iu1TO3CsD+u8mA0W3W+P8wQDd1QdLs/WxC0/5NnwT9CdSdsKfmwP3aD0m7Jg8E/dlNqjsDawz8mJS++P+q9PwRZsRTSmsI/12qf1F55uT+o0oSBUrqxP5BI5Ku6v7w/t/v/0bwTvT/1aLwWmcq4P5Dyx0WcS7k/0NDS0D3BuT9JV5Wuef22P6Y9wW1/gMA/4WSsvIHNuz8ilyCcKmS+P/8IFJuUIbo/PTo2F7Tlsj+yxylEzI6wP/5TouTsZbk/Nc/FLF/fwD/se3h9pNu8P3xHVLJLnMA/vRSiWVaVwD+QsWISEuPBP0/xFCH5Vbo/RbzJ2Dggvj/qQL7CeCy9P+j0Re9hBag/1n2UjVx7qj+p7UC1jEG4P0IhqBZWhLQ/AAXGRpYbqT/3KF3TNo28Px9YdlTiULQ/Radn8RUDsz/GDKHcePe7PxQwWGxhB7o/ZHqF7S+Hwj+LiALBOUu6P+LWLMIkp7Y/99Hv0gpVuT+9NQ945KqrP0LSurVgWLc/WfSdJx28sj9clSsQpa61P++iNQEf36w/n2Bnw6gVqz9Cd7dIjrG4PxFQ1SQ087k/Oj/WYPoguj86g0c79tG7P4VEbjQT1rk/oPbZDBsivD952T3+22q5P79HKTu3x7c//18W1vDWtD8dUFANF5G3P6ctzvKmlLc/Dm6Giwe/uT9hLvoAaXOyPx+SnbZIV7c/jCq8KGl2uD9WHdMYBZ2yP5ibiy6pnrM/gN/fLFvNsz/LVdf1zFKrP7qVuavaS7w/Dd1gsG+JtD8AWvd/o+XEPyLciKxB6q4/EoNk5A0ovT91RMDlGkTCP1k3fzP38qs/qe1ljxXftT9f3u1y98m0PxAZxU+Idro/gPgqfEp/rz9kUovuHMisP54f5b2a6Lw/FbgIxNybtD+rwJFl/92sP2mJBMHjGrA/0XNJgAS8oD9xwedJEhi4Pxh9W8jukLs/a6i6MiH8rj/EjzhIwe28P8ae9vtHvLo/dRaIDPvbtj/xrcmvrfuhPx8ndgsk27U/PqjFwi6Huz9BukwuNTu7P3+3uqfJwK8/GEOE0/7ouD+qu0+94N6zP+osBVw6Vqo/NfhInULIsD+olLcfEvyyPyoGXpm/Yro/WfOt0ItasT8iOZj0Bo2zP15NNn1y6bc/2HF92Am9oD9nF9jTIUCyP71YZa8IGrY/HtK/Koo5tT8CRYJqbP6zP55/PX+VM7Y/0g5fThj0oj+4EnCNLYC+P8jRPXj727M/zXSLjGCxtz9G1gGT9V+4PyCaehQxI6o/Yr1AAT0jtD+QPH3xK0S5PwiKO9dkAaU/m0WO628bsT96tME3Kyu0PwzEYP+PFqw/wF00J/thfj/FtVjFnV20PyjnRhBPlbM/B3WvORV5sT/c3fAqYNS6Px5JvAryHLE/FBFF1IHbtD/ozawC0qy+P0+FolqsNLo/cWqwP68Bsz9dp13hW+myP5VKWVbWfLA/VlqA2U9Zvz8kbK0OgTqmPwBFmJMFtKY/GCgdYFWusz/IlemsDWK7PxSfupQiZqU/737FdBcytj8KhiP+odijP8wk1BwDhbo/Z4wd8YdVtD9c/4+QK2ObPwDroxoh+K0/6Mpa4Z2Zrj+EACWkPc22P+RLg9I6FLQ/bBz8+Hk2ij85PtCBX6ayP3fh79G+Z64/0ANKGnYqmz/hJZT48vCzP/o4H9USprk/qrE4LlN6oz+sVhyKvbC3Pz6LiI7e76Y/ti+7zU3vtz+R9fmflPmlP7Sf/lg5lqk/FdtLU4ifsz9gUCWQCr61P+XY7ZARlbI/+OaNFMf+rT8Nm1HbNQygP/aTRrVz3Ko//q/II5/1lT/wrExY0EemP7w0PQOFSac/xgFgktjkqj8NYYLwlcmtP/Xy681rO7A/RNac/8J5pT8Yi55DpK+lPxIsrekTfLU/J6OwEnKxqD/589MQRjS8PxW8m+SpoK0/bOjUdwEQpz+Yh8B6b6m3P3cZnQrPa6M/lVVZMWQ9pz8jgwNguzOfP1+l4CBrDLY/6WZBpO6Otz9I0YBlT3+mP5usdpDMIKc/gKXEG0OEpT8QUatFK5StPxtKr/HPibM/4zzTIaGQqz/kRSRPVnKhP+MJdB60pLU/wBY5VtJKuD9q/+Xz3qirP38toExHIrY/IEwKVSPFjz/Hnql6seerP+7boFZdN5A/cD0e9uMwqD9cYKPAcFW1PyHxR9OERrI/MXidc2AltD/kI0FKAUeOP8iQMRX6lLM/MXnqquKgqj8lDD/sIVG3P78zobXS464/AcaBBN9apD/TfsTMIDS4P4pVEYDx8KA/WbA9egD8tT9S8L2FyrW1P+WzIrGUZKo/ihxDbtk6sz/VNGWUq+CtP2ErSy8Hn5k/AoLywgj/mz8EXg3J1qewPwGmSwp8+Ks/dD6BDBOxpD/cuqEbzvadP9Err5dEGJ0/OEnl76gtsD9iywimHT6qP0ghPVT4YKQ/OqHX5JnwpD8mxUIBYPyUP6AM7N12fbs/sGgc0lsmsz88MhmMU0uwPxnqR8OoPas/DzUDvXwZqz+51I1jOwWcP0xS0QltnKY/Oa2OchfrtT/U3j8d4H6rPzRghQzjGp8/unFZkpYJsz+jCkQiVqqwP2k2oJRqp7Q/RJbmVrrhsz/SOnANd2S3P5tEGDcI0q4/rSj1fQEgsT8DzqnCTMamP9Tk1ee6obM/Ouj3UCPisz9Ib6MesgukP7BiQLy0RqE/z87mhCKRsT/B1rt81FOrP3xP+T7wXWQ/Zr4Epy6csj8AE9yxIsuwP+iMDy/zua0/aL4yg4PesD98T/k+8F1kP+aDYthb1LU/qKlDEEOMrT/oZEedwV+XP3xP+T7wXWQ/kJT4tnOrtj/gF5KTN42fP0L6Sr0WCqA/VUbvBSuCsD8nPB0WubaZP7H7dq6Ku5U/g1fk7wvarT/mMbDgTWyyP1ZWECQXJZk/UaPrqQVerz9oN+9hgZaTPysjFFKK56s/4OyTCThLrT/9aWB6kGawPxJ30F/tvJc/1lVgCyUVqj9rEByzYU2pPyqrYDq4Xa8/uD5cZpFDqj+FxatFxqSqP0Y4y0HotLQ/5ortWjkhkD+kv3D94AGpP+TPCsrPd4s/O74ABa6eoT/ouiV0tg+lP3wnArbNPaY/3rrSJ0ufpj9pccXEzFCeP2+/ATc/kZQ/Jr4p3AY0lj+a249wUy2lP3/+DcZTML0/LzWyvOGPoT9+QfaHFhKwPwMUNWd87JY/eXr7bMQ4sz/FYnp0Mg2VP4ely6YVRJk/s7dw+LGXoT8qgxC8YJW5P9WrhhTqa5o/njL1j88bqT8wqteShrWjP6gaDZmZ/qI/5Pas7sg7tT979Hh7qVScP6jaoNfZHoE/kdIFMEtTqT9zugOua0irP/90z9CyoJw/JZRKW/JnsT98T/k+8F1kP0YFNCgOhrM/qCybDvUEsT9XfmIwVpmnPw5u64xF3rQ/MnHeDUF3mT8w9OXCf5loP7OSll2pYKY/GVjvwPcqsz98T/k+8F1kPxHosqCeh6g/WV0HuMlZrz8nmQGhHyKVPy+H/0EGBao/z5/hElZCoz+1WxJcNLelP2uWSofega8/GQgSXJ2EpD+f23y6YJOyPw6mpCPP/LM/K4mFvHIMsz9kH965NHK6P4W9FxLrI6U/OyQZcz2cnD9X92EwdhSxP2qBKXMplKg/HVJtRm67qz/+6rk7wXWWP5RQNK907LE/4qnIwIOovj87XybyFdGrPwBmRmlJXLI/zRQUlLBYsT+kvh/VGVulP6kliDBtO60/F08RDYiNpT9wHfMjWJJ7P/A2BUBexJ8/aAjiOrUDqT9ynFsmzuCoP6GzcbjSCbM/LQIBUIHvsT+SyrPQnCKjP4TugLFGBbc//Ra0qDQ5oz8izOVY+IygP4fdE0rEK5o/11BGoOqimD9cwkTyUFumP0c8jdjnrKM/Um9dGyzDqD8CDUvI/JioPxofzatvu7A/GvtIvG04tD9ean4iTA6bP2duC1ZmF6Y/2CnLkYcToz8BkvQTK0GyPxDJthbGwHk/gx1OOMJ6oz9yq+5JyYWkPz7QYqqofpw/Llh7UIB5rD8oNfcvgrepP92KFHCslpE/fE/5PvBdZD8QXxj08CabP63KL0Oi+bI/IKRkMknhqj+We4N8DA6uPzgwoAJxdq0/VD0gGMQjoz/W3vqViTe1P0zouJBWEbA/bkZ9CvjEsz+c9RkOBJ6aP4qnOdKEkpI/am45kE02oT+i0W2wnsunP6g5P8qsWpY/lGEa85cNmj9ieYEb00e8P/0KaMU3D5I/ufl4m7HPrT8Yq2cro66pP/nTzzuMdKY/dxFhRQFisT92N+PULc6fPzMcMdQsO6s/nosQTSJesT+jUs9j72asP/E8nQtJVak/QKE/mFN8bz+41JYH5i1xP2yAPU4+foo/9is0+E8fuj+D8OnuwS2sP1Dorhydmn8/xU6r3kRhsD9JwW7++lKWPwLrSxHAO6w/DDJAFefaiD98T/k+8F1kPy0Tbl03Ea4/U/FmmHfVrz98T/k+8F1kP9OiaQIrv6o/laaZV360tD+wUJgQ+JmVP0ETk5tJp68/tvpB1wrNrj/P1IunO6ynP6FMPRI7srI/k2USZbTGpz9cc+8Lsc2IP72HWUxBkbA/E/hyhvBQrT8p4A59IgGtP9xeS8Z/Q6Y/z+T+h0BftD+AvXy38TqwP54D1HV9K6E/xDRTQtw7rT/+P+c7p0mgP0AKP/dOW4c/NnKZF+lJtD+/H9FIQd6sP6CZJ5Ae0qg/hDuLej+rqT+oabradUm/P2uuNg7ouqo/ZGRkr/4btj9UrA/hvKq1PwI9ySgICKA/kdF6BDgfqz98vTMgTlK3P8Qyg1N68qY/fE/5PvBdZD94J6h8g7CtP70Xe8fQ0pA/GQhzdNV0oT/sNse9lc+BPzJXB1cFN6g/fE/5PvBdZD/SX/c2Wi6pPxlJbC/SB7Q/m9L09DCNpD83k+U0aUmpP8zNIAZfo5E/QMysz8xhiT+jfkkNZrWpPxYbAxuN1Z8/q0M2X7aGsT9mVWje9YOyP0KUABz0lLE/bYf2CpX3rT8oh5gbhguoPwxnI/sEXZ0/BKDR8Y4Voj98T/k+8F1kPzpCu/qyXJI/CIPSWJwfkD/o+8K01kqzP88Ns0JjX6Y/HdD30BFoqT8yNwU5eJWSPzutUELiS5Y/vIleo6eGpz+Xcxo9yVaePxSpgsYOvLU/IqpkfSd/kD8hQ8O8/hSwP+hee4KuRaU/FBzn8I+wqT9+dRYKXpGRP3xP+T7wXWQ/3jKOyB5NsT8oXeQbNgmmPy2RvHEjEp0/ZNn0JnjsiT+I8Mv6iUK3P9TAO5LMHYc/1S8H2JvSkD+Mvy0YMg6hP7jJSYRuqqM/CTP0P3isrT9uVBO8Sw6sP7JCDcm5U6w/cMEAUDOLmz9Ft6ghHL+hP/6SxKGqBKQ/mnAQoktCqz/2giy8oOChP58D46ZDRZk/H3AJJVVJoz8lYqpt6F6zP+eaQp3LzqI/mpBoHuw1kj/ZEmo/fn+ZPyyiLTJ/KIg/WE8/hI55rT8jtacZzLmiP3JohaqMl6Q/sI8jxXjQoT8nTyyI4FOjPyzJ/3BFH6o/j8JBzlPToj8I4WxMHTOFP3JxQUehd6c/agaR9FyGpz9Qns3WSgCyP9AYp5znRK8/NdvW+GIyrj+sSskTjKilP88vRhw9bKw/hkmTXSj7qD9aFoNj4cCzPzqJzWXyAK0/HgsHo1qVsz9ibYhnuTirP1WayhmEHbI/GujjBKs/uD/w3nE/V1SMP29BAAbW9rQ/fE/5PvBdZD+gAn98CT+XP5NCHyBGCaI/1pWfh/lXuT+aOxzBUzqgP3Gk+SABaLc/DPuBPCKbtD9aV7c61rOwP+h7RBCB7Jo/7hf9dUsdsj80V5m1K2uhP1M/UU/7g6s/va8dRuu4qT/idO8vDF+xPz5NPTANyLc/iDZLHDJ2sT8L3Nz7ztyuP/JHl1x1jbU/74JglKrspT89Qg4RD9ecP5QpHeKew5c/GoeBzNjDqD8AoH/6G9yDPwXk7ftGHKw/SADLMdM8sj/4R78yzHeMP4DZes269ak/cYbo7Z33uD8kTiHeUBKQP4ZYsfWFrKc/u1Y13X8Tsj/Q47/ZRtWqP0MrOSkRobE/KEvFdmVPpT8C1k0HPHO2P1v7f90zV5g/TDes05aqlD8qTUTP63e2P/yC5qpFi60//uncJjpDpj+e1kYgMCK4PyIr3/LloK0/o0ohOLqcoz+SisFepWerP9tDQFfnnbE/Zl4xtGXUsD8kTnkgID2gP0TXN3IWz7g/D8uTFC5JlD8tCsuOh+mqP+tPu9G2VKs/avBkGHfIrT9stxxIaYucP2rPuo1kCaE/nJ2o+tDvpz90wDF7TfinP4/NV7Bx0Lc/E938zE1wnz/7zUtaFXOnP/UpQIxUNKc/CtZT4gYHtT8z/uKRwtmvP7DCRAXyY6U/jO3ePl64tj9W3hqhgdulP7N75wam3rY/X5R9tW1XqD9wrBNHyUKrP9+eYwbUU6w/e5beCHKRqD8IBONLYiisP3jSOQYUrqA/cLjKmFCbkT/iYN0o9fm3P3RHnRHFaaE/eokTuzYesz9l5uxO1QiwP6EyYNgAG5c/Jn2A6Xqyrz+S7LPi1vepP9LunhzoNqw/k3GDAdeHrT+o3jy9V4mSP8vhocu8OLI/9IErGKcMuz8cDcfU29G1P7TYpf5DJqc/7r0SjC7AoT8zoPJ+uAewPxx9bDaE5rU/PF1a1gUDrz8qL9NS2uu0P6jgMVLDGrQ/4nx2P+kZpT/GyJGIwv+xPwZROgHXGbU/cmdFi4wimj+8UxjLfmSwP95PngGBCbo/hSqjMf73oD+3UKqnpIelP4xhE53q6KY/vOx6KRsLoD98T/k+8F1kPzF6n5JbB7Q/sx3mi0yEoz99gN5zBVmlPxyb4Zk4N64/fv+t2LNdkD88nz2eAhqjPwDo9HA0X6k/lUXsnMI4vj/gSFmvlqCDP48vM2PgAK0/dEjm+erssT9qpyrCOxu1P3QRXJ29BaA/xFBat8bNpz9Bp/m2ErClP9kteXZRjp8/GZtiD1rXqT8tVXCvD9enP0t3HEWDmaU/CP3E5asMrT/ajNzMk1K0P94Jl5tog64/eX/1mqpEsT8DRjqBOI+fP+Axl5UhvIs/1NNkFr5hqz8D2ZFWxLurPyKEHQfHqac/+sVQlzrcqj/pI7+MwE+pP08HYvun36w/u6Q/J/P9pT+7atu49bKkP3xP+T7wXWQ/IMP7aC4voz/ftHyhkyGoP4iQYPbuEXw/C6rIKb3sqD/+CAGPPuScP/XZ8TSbUrA/IznjrwsFtD98T/k+8F1kPxDhRAUcvm8/fE/5PvBdZD/F3CjPN3WwP7iFpqyBd5E/D0dq+EegsD+S2RAe4jmvP7bqy8UCD6M/SqXB8ZqzuD9tH/qHdTKuPwqQ9amAyqM/2qUoSgRltj+ak+y9lDC4P2tNovH3HqU/4JN5EEjncD8J57iWE4GtP02Q58gi6rg/05Xkvo1knj9307aFId6mP8MF/11pbqg/iKdjIIOdqz98T/k+8F1kP5xAYX2zkLY/bOBhbv3Tij8Pt1jaLo23P6Cld7RToIw/oEh2j8HYoj90D0X0PWKwP3pzVHNd7bE/9qL6aCDDqz9LVxXFXLOtP3YEbGtOm7A/z7nrjAFSrD9nkFOsBRCcPygEuBRPZqM/zRota23/rj/5TSrrsjikP3/yeKK36qw/+3RsMjCmqz8lcuS9Y/GpP6EmwCDSNqI/cn8gnQgXqD9onnfh6md8P3bgyTiR6pI/49QFUueEqz/gtcnbd3WwP750Au+wb60/aem4q2LRsD+qNaiZNuWzP4yiBUETULA/RA8buGEXpT/u2GyRT7+4P+pWctEaTLA/VKpGBWovjT+Ev/F9Ohe0PwAqpTA6uKA//X93cpqepD98GKtMkJuKP4Cp8ReHenY/uzd19ZGksz/AbBiIQbe2P3xP+T7wXWQ/psnE8WBXsT8RU9onsTytP9I/foZIYLg/rE3D5bptsj9vR+gXDJasP3Kc/jiE4LU/GR1rflq4oz8YVNwuarV7Pw+ltb8XzrA/CQfzSta7oD+XwuqIjzSfP0X2x/raF6k/Ky3hRvupsj8mvDjjiTu3PxJy4yAl6bE/6uBHZs5ppT/e17SF5+CwPyqSexdKPbQ/OOI08yEJrT/V3kwl4r+wP3vU+6b28Zw/t/I5pGyqsT8KpzInznGZP3xP+T7wXWQ/QXVNmAR+pD9YXDBQDharP/RifLrJG6g/nNLG7v57tD94xhnQT121PzREjFtVd6s/Ney+2Os0rD9O3zF8TbObP+djoAqO+7M/UGkjB+TZtz/C6HKKpkuyP8HcUDm0f7Q/yt1Om4Rxrj+3nDsTZHKqP7DRF29V93w/E/+vprgenT+CKpl72+qoP4Or5iInpKw/eHdMVIF8kj/QQu1k8NixPwHNRi3cjLg/Ac4XxQxQqj8eS661ncKjP/5Jq0s40aM/aOywXwCSkj/2Alk9WU+lP0aygvgsF7I/Vg1vNo7dtj9GqttOO+awP7YtiyWzcrE/K24w2s7Jpz9EYnxF6zytPyAzbRvGGno/kEQmVHHfrj8UYNKKqN+jPwbCdnOXz6U/ewIkr4/brD9+XdnlKPesP8ECl1WdfbQ/Xrczp/Hwsj+KbeZh4ue2P75eMx7zj6Q/yiGfD948rj96MKHIha65PxZ87oi2q6w/fE/5PvBdZD86uM+VkXOxPxNu6jykqK0/8pmDT5rXtD9uQwtIXWGyP3WkLazGtqY/bgqQjearqj+cuVBodOymP2Sw6r4QMJA/UlZPcEvnpD/0aeqkQhaxP8ghzUWPsbc/Xfaj7oUGsD8lxnEJUK61P9dOb1F2z6Y/yH3oEEz/iz/N4haA1e2tP0xxwvx/Wqo/oYKdiGnwsD/w3yFPLJOSP0E0YH+5Z7M/fLbkqeyRsT/c8ehhb+iyP36546h7pqc/4PX0q1wPqD8Q/1vFhX+yP9EgQoI0zLE/GbAVJY7Elj9gw10tm3a4P+j1i7ROGqE/dpGwiNmYsj9E6jfY7zCvP78zXFHuUqE/nohX62EasT/WxBpM+WGmP+LvQo1ZC7c/36+ga+Bzsj9PwrPnWj2zP307VsbZPps/dw1uKCLZlD+He3NiuiqVP3bV0NgKEqI/AOoirQIysz9hfSLZz8WzP5TY6uNoSK4/cEXCTfyIqj8A8RmjZR+FP/IzX4+MlLE/fE/5PvBdZD9+9pLnxVOyP+laQQFTC6I/aFNGX+/DoT8Q0SCS4feRPyLmAEOgi6Q/iKati6P+kD9RAZXS4mCkP8DpHiso2LU/zghqtqfZrj8/UOiiyveqP1heoGWGF7A/qLnAMbvOqD+lOz2WXxyqP3nESa8uPqA/qYegF/Wdsz++pjWI5ZOtP/AcFcx3M4A/djSXtLqDpj8QnGGCpN+bP+KAZ18bs6I/tlDr8paksT9HZHaAwWWiP4UZW0TyMbA/oDZClrB3aj8j41rk5ty5PzMqLzhmu7I/me9+s6DbqT/oQo/rgWmyP2bewrAF6pg/NomnLgM3qz+unQ0h7qmxPwKVBppqybA/jrlUOiWJoz9cGdPDtAecP6cPG2Wqhp8//HRRlVq9tj/N46yml1S7P6b2iCoCCbU/YfUexTWirD8Plr8hPcGuP2OGyL22WaU/JG+7E1Apnj/SeY6JlMuuP64X9+onprY/CmF+Au/Wrz+KQ4NuHBq+P56DBElpv7M/ZO/Cnn3Tqz+L4kM1uwGwP5a2pkkSMLk/aj9YZFBLsj+1vo/dvKWsP0jJOETGgac/IiCY60vtsj8Ah2ZBGOWjP/BmHN7aJLI//qs0x3Nmqj90UAAn49SyP3M4NSOx0bI/VkvXkgHepD8+eMSDlKWhPy4OchvBbaA/n6aJSMCorz81J379RTSmP18PTS8lTqE/fE/5PvBdZD9qnMZ8CA6uP0CFGMKcW6I/WK4Za9IvfT9WtTjaA5u0P2fLeCh8qqk/livbbRNAoj/1fXg1fqKwPygofddprac/lyLvctkltD94ZnVo1KeeP3ufm3M2lKs/vkEGDQi9kD+KvXmY90ewP2qP3DcP8ZY/fE/5PvBdZD/QgDF3xTy1P+kfHereiKo/MVYoXUjeqT8tec+oPfirP88BmFEhBrY/49X8fQz3pz+Dm+6bRkSiP6EbwBPp16I/DyucGn0srT+0WMbLZsa1P2QTzGiMSow/9lEBtT3GtD/6UwOLV+60P51uHjMplac/4TkKVZVouT/HtKVGoQ2oP6It3PPDuas/fE/5PvBdZD/oGWu/BTKtP8JONZvi8LY/rwLdKkEsuD+gfy2zQO20P+qzD7ldj6U/NxgfrXehoz/gojQxEOWYP3LgFMMif5E/146m3LH7pD9/cQBROw+rPxD1O9j4N64/2BWZUbWmoT8k6omHmT+qPyhzXGuS260/JA63Vs0wrz+Edih0yoqvP08F5lpjzaM/RXmHBbdLtj8WL/DtG5ywPyOmltXyEKA/mBlo7TMvsj8EaROfUbKzP9kkrXFVi6I/4O+sxcR0tD8xURKIwyKyP1TJtblUbKA/tq/XqFNAvT8ZM6b5EoKbP3ir33ScZ6s/bgHsYPqhtz8iwmSq+UKrP/jDnYQCyYk/zouMy5RmvD8tbeHVjkuvP0tz/HEWXLw/iOYM7blrdD/c/Q8nBeahP3tm7EYkErA/ad2jbH5Woj9Tp2/8w16WP/h52mQq0KM/zIgJOiJAkD8EZhJuniO1P9X617aQbLI/3N6vBxmOoT9kl8Uyr8CxPxA+iqPTM7M/UE8CKJ8coj99rDehHbCwP3FBk5nCvK8/OLHRRPutuj+doOOr9hK1P/rAgIwVXLY/qD8GWPgArT8xrPkt6ECdP49tqLxUOrA/aCbkj7iNoD+z4vs7YCWhP6xjYObv3r8/RqGhtHrenj8CZPlua+W2PyLSfQvLe6g/LGhPYC2onT9f/1MPUJa0P8AHS62H0YA/Ki14CLPtpj/5OVlMKUu1P2gMy5yNZ6g/RBEPX0P/oz8RvnBBhcixPx0ZK5BFx7k/qgd74ZQtrz+gpbgJGB6yP0V3EOfuHqo/TuoAz8LZoD+iAlayV9eiP4AP8ghl0Z8/Ivnhxduyrz+pm2WB2UmjP3gwWu7j9ak/9u9nvIMIqT/t45eJ96WjP7NoHnGCGLU/8zpjVyaUlD/tdyr4VPauPyk3ZQYEp7A/UwLoDYJ3uD/ipVf6y9KQP/WaFuoeXa0/potcd10IqD9fgOdA4h2uP3aYpaNL3bM/iJN1SqUopz8dvDrCBeGpP5YJS9WYcbQ/9HfFP2eCqT+HHUeuotKyPykviCuKB6s/XMPdudBvoz+5IDWV+F+gPxIbs6Z+mbA/JlpM/sDxpT+xJ9QHvn2tP1vKHgYrWKY/JNx+PlJXrT9W/BTynsKWPy+2Co+Aq7Q/WoqJT9XSsj9LGRCjDtWmP71ovdlxqqA/fE/5PvBdZD8M05UG1KqVP/wz0e5Oyag/D+GIBY04qD+HlqcVWU+nP8FZ7b73bq8/q4cTZugOrz9W05tTsOi1P/5njJQjbbw/NLHQQO5VqT/+emCYucKzP4HKxF9Jfao/rgC+S+nYsD+scrpSb7WgP3R7JLuHQKA/6DnoRNFsij+UO+d1HNitPwGcrc0N954/vg0vnOTlvT8kXrwrdwK2P2V3K7++mqc/wLn5A+u/oj88WwX5uZeTP7CFnjxepXM/PeuX1stuqj+7/N4KocmvPwCAvh1CZbI/t/wcUh0nqz8wQfLWJgyvP3xP+T7wXWQ/If7yfmokqD9fvWD0nfCkP1yOjdJha48/RmrTlWEurj9ii0qLSgufP1pZjng7N5E/ld3/D4u+sz8XBWPISM2fP0zvlugVaYU/yd5NEu3lpj/qZpa6/WyoP3Z/fAjR0qk/H3R5JkraoD9qV+aeK/WvP+81GQqqhLc/JP+TxmOXqT/S0ZTINYCZPyKgk4E60p8/bR9vTdzEoT/+mW2OBBGuPwmovHex15o/pSjZS5GBtT+xBcbBWfGnP4B3jYflXrE/az5s97DGqz+QlHKRFGmCP5OLZ3PojZk/z5ILnUG4nD+rdWB6r2CvP8jp8qRbSoQ/4Sm2aSKPpT/Q+eyuGgpvPwPZ8TpMM6M/6ocndHbPqT/uT5XsliCvPxS/17iWDqA/RtkhP81GoT8Tfcc9Tia3P7mIonXHcK0/ZybzFgmWrT/esNR86Ju1P1R0nvGOSqc/GR9FEtNopT9b4UXx6gWaP0YyfiVuk5k/wXs+b2+/oT8RyKUe7UyvP8TOi92ZIKU/6M2GysFEdz/uC9MeQreiP8lrBvxO0Zg/d77d8FhZrT8A1DxAmBetP3xP+T7wXWQ/9mvPgX/Yqz9FxqnPugOXP3AAXP/wbbA/eGK/+RHptz9P45X2vdisP56cM6pGNag/B1kiCaqasD/tr/BnzxKpP/V223Oz4Kk/7w4YkyU2qT8sEP1pHmq2P0KWywkNe6s/lWn23yeRtD8qZV0DXq2yP9kjwIpQm6c/BGriPKruiT+lYa2ESQGgP0LHhCwxaLo/xB9oNisRpj98T/k+8F1kP//LHvABdLA/WmfsPK1Ttz+IE0Ai3Zq1P1Yl2JWEkKc/f/2JvJmSmj+WTOsbnvavP2G1LQ64o7A/hf4RXkmunD9Jq8OvxHStP0KZGVwjw5k/0XOLdrNJtD86ZlEZIMisP1xeHCxZWZg/vJzEMeqosD/yfbrV5Bi2P+l5bD6ezpk/JIQ1DB39hj98T/k+8F1kP/IRpV879rE/hEXPbVGZlz8eOuHYjpSrP561jYbMwaY/lH7zdwTHrj/sSXkGfR+RP6gqUKeFBKs/ur398g0boz98T/k+8F1kPwROUCupSaw/ElJSTNbqwT+3RX7V9zuiP8Q4KuTVe7A/D+DVQrLsrT8rgI3U2T+xP/isgSYRcbA/GwWHzVbXlD99OzMsBVG1P1bXm1fS2LQ/eELAOInpgz+qdDZcd7ygP6v+oHQ2iZ4/JVsQDyoTnj87uCUAD8ClPwCaHBp+BrM/mR/8vk34oz9U9B9JIf+wPww7nuWhWbA/7jFR20sJpz+eX09DPKG1Pzt+VrSzp6Q/RF15WfCagD/PpsjvdVWfP06r9KmvlqQ/3G3gZ2nctT9hSg9h/M2jPxRKYBIlRqI/fM07iovjpD+PHr9v4G2yP7ms1sRUeak/wOXkWNozsj+YYZZkPmyuP8IhPpCnda8/tPIAUYgDnj8Lk9xoI3qYP7zXQcqFbrg/qO+/MIaZsD+lbM1zDTueP7eq0US8RKw/L7J9Flw9tD98T/k+8F1kP0YfT9s4fq8/kya4xIyHsj8mF3N5ouWyP7VOtIs35as/Rq3R5JCNuD/BRm7nalSnP6eXJgiOgrc/Z4SzWR1VsD9e3YDKB3CkP8pPsYvvya0/YEpamzC+rD9Ry33DC2KhP3o0lp3Jo5w/blipAXSjqz+VtjExqNCkP/P7SGAijbA/cOIX8esNgD9ww89iohSKPx3ZtzexlbM/3Tmn0OuYsj/KjEsqldSyP9ag+g9HgaI/EelIKdIKlz8oyMAT6yWbP6udIi4XALU/KIJrqsN6tj8GRVIT7yWyP2Cy62ohm6U/D3XdO1gfpz+TvMTr4jGUPw==\",\"dtype\":\"float64\",\"shape\":[2000]}},\"selected\":{\"id\":\"1094\",\"type\":\"Selection\"},\"selection_policy\":{\"id\":\"1093\",\"type\":\"UnionRenderers\"}},\"id\":\"1065\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"line_alpha\":0.1,\"line_color\":\"#1f77b4\",\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"1052\",\"type\":\"Line\"},{\"attributes\":{},\"id\":\"1021\",\"type\":\"PanTool\"},{\"attributes\":{\"data_source\":{\"id\":\"1050\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"1051\",\"type\":\"Line\"},\"hover_glyph\":null,\"muted_glyph\":null,\"nonselection_glyph\":{\"id\":\"1052\",\"type\":\"Line\"},\"selection_glyph\":null,\"view\":{\"id\":\"1054\",\"type\":\"CDSView\"}},\"id\":\"1053\",\"type\":\"GlyphRenderer\"},{\"attributes\":{},\"id\":\"1022\",\"type\":\"WheelZoomTool\"},{\"attributes\":{\"line_alpha\":0.1,\"line_color\":\"#1f77b4\",\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"1038\",\"type\":\"Line\"},{\"attributes\":{\"overlay\":{\"id\":\"1029\",\"type\":\"BoxAnnotation\"}},\"id\":\"1023\",\"type\":\"BoxZoomTool\"}],\"root_ids\":[\"1002\"]},\"title\":\"Bokeh Application\",\"version\":\"1.0.1\"}};\n",
" var render_items = [{\"docid\":\"9a316480-8d03-4550-a54c-bb6016879631\",\"roots\":{\"1002\":\"006e39d0-e1b5-4f27-90dd-5333a8798e5e\"}}];\n",
" root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
"\n",
" }\n",
" if (root.Bokeh !== undefined) {\n",
" embed_document(root);\n",
" } else {\n",
" var attempts = 0;\n",
" var timer = setInterval(function(root) {\n",
" if (root.Bokeh !== undefined) {\n",
" embed_document(root);\n",
" clearInterval(timer);\n",
" }\n",
" attempts++;\n",
" if (attempts > 100) {\n",
" console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
" clearInterval(timer);\n",
" }\n",
" }, 10, root)\n",
" }\n",
"})(window);"
],
"application/vnd.bokehjs_exec.v0+json": ""
},
"metadata": {
"application/vnd.bokehjs_exec.v0+json": {
"id": "1002"
}
},
"output_type": "display_data"
}
],
"source": [
"x = np.arange(2000)\n",
"iswitch = 1000\n",
"# Switch between a progressing regime and a learned regime.\n",
"switch_rate = .005\n",
"switching = (np.tanh((x-x[iswitch])*switch_rate)+1)/2.\n",
"\n",
"# Progressing regime is exponential decay.\n",
"decay = np.exp(-x/2000.*6)\n",
"y = decay*(1-switching) + decay[iswitch] * switching\n",
"\n",
"# Add noise.\n",
"y += np.random.normal(size=x.shape) * decay[iswitch] * .5\n",
"\n",
"# Keep it positive.\n",
"y[y<decay[-1]] = decay[-1]\n",
"\n",
"f = figure(y_axis_type='log')\n",
"f.line(x, decay, legend='decay', color='darkslategrey')\n",
"f.line(x, switching, legend='switching', color='silver')\n",
"f.line(x, y, color='lime', legend='loss')\n",
"show(f)"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n",
"\n",
"\n",
"\n",
"\n",
" <div class=\"bk-root\" id=\"bbfc785f-0a86-4139-9f7b-5068e80aadad\"></div>\n"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"application/javascript": [
"(function(root) {\n",
" function embed_document(root) {\n",
" \n",
" var docs_json = {\"e6a89486-4288-4d25-add9-36e1f2c0fcfd\":{\"roots\":{\"references\":[{\"attributes\":{\"below\":[{\"id\":\"1184\",\"type\":\"LinearAxis\"}],\"left\":[{\"id\":\"1189\",\"type\":\"LogAxis\"}],\"plot_height\":300,\"renderers\":[{\"id\":\"1184\",\"type\":\"LinearAxis\"},{\"id\":\"1188\",\"type\":\"Grid\"},{\"id\":\"1189\",\"type\":\"LogAxis\"},{\"id\":\"1193\",\"type\":\"Grid\"},{\"id\":\"1202\",\"type\":\"BoxAnnotation\"},{\"id\":\"1212\",\"type\":\"GlyphRenderer\"}],\"title\":{\"id\":\"1173\",\"type\":\"Title\"},\"toolbar\":{\"id\":\"1200\",\"type\":\"Toolbar\"},\"x_range\":{\"id\":\"1176\",\"type\":\"Range1d\"},\"x_scale\":{\"id\":\"1180\",\"type\":\"LinearScale\"},\"y_range\":{\"id\":\"1178\",\"type\":\"Range1d\"},\"y_scale\":{\"id\":\"1182\",\"type\":\"LogScale\"}},\"id\":\"1174\",\"subtype\":\"Figure\",\"type\":\"Plot\"},{\"attributes\":{\"line_color\":\"#1f77b4\",\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"1210\",\"type\":\"Line\"},{\"attributes\":{\"active_drag\":\"auto\",\"active_inspect\":\"auto\",\"active_multi\":null,\"active_scroll\":\"auto\",\"active_tap\":\"auto\",\"tools\":[{\"id\":\"1194\",\"type\":\"PanTool\"},{\"id\":\"1195\",\"type\":\"WheelZoomTool\"},{\"id\":\"1196\",\"type\":\"BoxZoomTool\"},{\"id\":\"1197\",\"type\":\"SaveTool\"},{\"id\":\"1198\",\"type\":\"ResetTool\"},{\"id\":\"1199\",\"type\":\"HelpTool\"}]},\"id\":\"1200\",\"type\":\"Toolbar\"},{\"attributes\":{},\"id\":\"1194\",\"type\":\"PanTool\"},{\"attributes\":{},\"id\":\"1195\",\"type\":\"WheelZoomTool\"},{\"attributes\":{\"overlay\":{\"id\":\"1202\",\"type\":\"BoxAnnotation\"}},\"id\":\"1196\",\"type\":\"BoxZoomTool\"},{\"attributes\":{},\"id\":\"1197\",\"type\":\"SaveTool\"},{\"attributes\":{},\"id\":\"1198\",\"type\":\"ResetTool\"},{\"attributes\":{},\"id\":\"1199\",\"type\":\"HelpTool\"},{\"attributes\":{\"callback\":null,\"data\":{\"x\":[],\"y\":[]},\"selected\":{\"id\":\"1234\",\"type\":\"Selection\"},\"selection_policy\":{\"id\":\"1233\",\"type\":\"UnionRenderers\"}},\"id\":\"1209\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"plot\":null,\"text\":\"loss\"},\"id\":\"1173\",\"type\":\"Title\"},{\"attributes\":{\"line_alpha\":0.1,\"line_color\":\"#1f77b4\",\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"1211\",\"type\":\"Line\"},{\"attributes\":{\"bottom_units\":\"screen\",\"fill_alpha\":{\"value\":0.5},\"fill_color\":{\"value\":\"lightgrey\"},\"left_units\":\"screen\",\"level\":\"overlay\",\"line_alpha\":{\"value\":1.0},\"line_color\":{\"value\":\"black\"},\"line_dash\":[4,4],\"line_width\":{\"value\":2},\"plot\":null,\"render_mode\":\"css\",\"right_units\":\"screen\",\"top_units\":\"screen\"},\"id\":\"1202\",\"type\":\"BoxAnnotation\"},{\"attributes\":{\"callback\":null,\"end\":2000,\"start\":100},\"id\":\"1176\",\"type\":\"Range1d\"},{\"attributes\":{\"data_source\":{\"id\":\"1209\",\"type\":\"ColumnDataSource\"},\"glyph\":{\"id\":\"1210\",\"type\":\"Line\"},\"hover_glyph\":null,\"muted_glyph\":null,\"nonselection_glyph\":{\"id\":\"1211\",\"type\":\"Line\"},\"selection_glyph\":null,\"view\":{\"id\":\"1213\",\"type\":\"CDSView\"}},\"id\":\"1212\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"callback\":null,\"end\":1.0231807824474182,\"start\":0.0024861995987439083},\"id\":\"1178\",\"type\":\"Range1d\"},{\"attributes\":{\"source\":{\"id\":\"1209\",\"type\":\"ColumnDataSource\"}},\"id\":\"1213\",\"type\":\"CDSView\"},{\"attributes\":{},\"id\":\"1180\",\"type\":\"LinearScale\"},{\"attributes\":{},\"id\":\"1182\",\"type\":\"LogScale\"},{\"attributes\":{\"num_minor_ticks\":10},\"id\":\"1190\",\"type\":\"LogTicker\"},{\"attributes\":{},\"id\":\"1233\",\"type\":\"UnionRenderers\"},{\"attributes\":{\"axis_label\":\"batch\",\"formatter\":{\"id\":\"1229\",\"type\":\"BasicTickFormatter\"},\"plot\":{\"id\":\"1174\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"1185\",\"type\":\"BasicTicker\"}},\"id\":\"1184\",\"type\":\"LinearAxis\"},{\"attributes\":{},\"id\":\"1229\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{\"dimension\":1,\"plot\":{\"id\":\"1174\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"1190\",\"type\":\"LogTicker\"}},\"id\":\"1193\",\"type\":\"Grid\"},{\"attributes\":{},\"id\":\"1185\",\"type\":\"BasicTicker\"},{\"attributes\":{\"ticker\":null},\"id\":\"1231\",\"type\":\"LogTickFormatter\"},{\"attributes\":{},\"id\":\"1234\",\"type\":\"Selection\"},{\"attributes\":{\"formatter\":{\"id\":\"1231\",\"type\":\"LogTickFormatter\"},\"plot\":{\"id\":\"1174\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"1190\",\"type\":\"LogTicker\"}},\"id\":\"1189\",\"type\":\"LogAxis\"},{\"attributes\":{\"plot\":{\"id\":\"1174\",\"subtype\":\"Figure\",\"type\":\"Plot\"},\"ticker\":{\"id\":\"1185\",\"type\":\"BasicTicker\"}},\"id\":\"1188\",\"type\":\"Grid\"}],\"root_ids\":[\"1174\"]},\"title\":\"Bokeh Application\",\"version\":\"1.0.1\"}};\n",
" var render_items = [{\"docid\":\"e6a89486-4288-4d25-add9-36e1f2c0fcfd\",\"notebook_comms_target\":\"1235\",\"roots\":{\"1174\":\"bbfc785f-0a86-4139-9f7b-5068e80aadad\"}}];\n",
" root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
"\n",
" }\n",
" if (root.Bokeh !== undefined) {\n",
" embed_document(root);\n",
" } else {\n",
" var attempts = 0;\n",
" var timer = setInterval(function(root) {\n",
" if (root.Bokeh !== undefined) {\n",
" embed_document(root);\n",
" clearInterval(timer);\n",
" }\n",
" attempts++;\n",
" if (attempts > 100) {\n",
" console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
" clearInterval(timer);\n",
" }\n",
" }, 10, root)\n",
" }\n",
"})(window);"
],
"application/vnd.bokehjs_exec.v0+json": ""
},
"metadata": {
"application/vnd.bokehjs_exec.v0+json": {
"id": "1174"
}
},
"output_type": "display_data"
}
],
"source": [
"p = figure(title=\"loss\", x_axis_label='batch',y_axis_type='log',\n",
" plot_height=300, plot_width=600, \n",
" x_range=(100, len(x)), y_range=(y.min(), y.max()))\n",
"r = p.line([], [])\n",
"show(p, notebook_handle=True)\n",
"\n",
"def update(losses):\n",
" x = np.arange(len(losses))\n",
" r.data_source.data.update(x=x, y=losses)\n",
" if len(losses) > 0:\n",
" p.x_range.end = max(x)\n",
" p.y_range.start = min(losses)\n",
" push_notebook()"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"for i in range(0, len(x), 10):\n",
" # Pretend we do a step of our optimizer here.\n",
" sleep(.05)\n",
" new_losses = y[:i]\n",
" update(new_losses)"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.3"
}
},
"nbformat": 4,
"nbformat_minor": 1
}
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