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import pathlib | |
import sys | |
from icecream import ic | |
import requests | |
term = "weather" | |
words = set([]) |
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$ ./bin/spark-shell | |
14/04/18 15:23:49 INFO spark.HttpServer: Starting HTTP Server | |
14/04/18 15:23:49 INFO server.Server: jetty-7.x.y-SNAPSHOT | |
14/04/18 15:23:49 INFO server.AbstractConnector: Started SocketConnector@0.0.0.0:49861 | |
Welcome to | |
____ __ | |
/ __/__ ___ _____/ /__ | |
_\ \/ _ \/ _ `/ __/ '_/ | |
/___/ .__/\_,_/_/ /_/\_\ version 0.9.1 | |
/_/ |
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import spacy | |
import pytextrank | |
# example text | |
text = "Compatibility of systems of linear constraints over the set of natural numbers. Criteria of compatibility of a system of linear Diophantine equations, strict inequations, and nonstrict inequations are considered. Upper bounds for components of a minimal set of solutions and algorithms of construction of minimal generating sets of solutions for all types of systems are given. These criteria and the corresponding algorithms for constructing a minimal supporting set of solutions can be used in solving all the considered types systems and systems of mixed types." | |
# load a spaCy model, depending on language, scale, etc. | |
nlp = spacy.load("de_core_news_sm") | |
# add PyTextRank to the spaCy pipeline |
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import org.apache.spark.graphx._ | |
import org.apache.spark.rdd.RDD | |
case class Peep(name: String, age: Int) | |
val vertexArray = Array( | |
(1L, Peep("Kim", 23)), | |
(2L, Peep("Pat", 31)), | |
(3L, Peep("Chris", 52)), | |
(4L, Peep("Kelly", 39)), |
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wget https://www2.census.gov/geo/tiger/GENZ2018/shp/cb_2018_us_state_20m.zip | |
mkdir maps | |
cd maps | |
unzip ../cb_2018_us_state_20m.zip |
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1 reward 0.00/ 0.02/ 1.00 len 7.83 saved tmp/ppo/froz/checkpoint_1/checkpoint-1 | |
2 reward 0.00/ 0.02/ 1.00 len 7.40 saved tmp/ppo/froz/checkpoint_2/checkpoint-2 | |
3 reward 0.00/ 0.02/ 1.00 len 7.21 saved tmp/ppo/froz/checkpoint_3/checkpoint-3 | |
4 reward 0.00/ 0.03/ 1.00 len 7.36 saved tmp/ppo/froz/checkpoint_4/checkpoint-4 | |
5 reward 0.00/ 0.03/ 1.00 len 7.26 saved tmp/ppo/froz/checkpoint_5/checkpoint-5 | |
6 reward 0.00/ 0.05/ 1.00 len 7.57 saved tmp/ppo/froz/checkpoint_6/checkpoint-6 | |
7 reward 0.00/ 0.05/ 1.00 len 7.82 saved tmp/ppo/froz/checkpoint_7/checkpoint-7 | |
8 reward 0.00/ 0.07/ 1.00 len 7.42 saved tmp/ppo/froz/checkpoint_8/checkpoint-8 | |
9 reward 0.00/ 0.07/ 1.00 len 7.87 saved tmp/ppo/froz/checkpoint_9/checkpoint-9 | |
10 reward 0.00/ 0.09/ 1.00 len 8.84 saved tmp/ppo/froz/checkpoint_10/checkpoint-10 |
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1 reward -902.00/-751.75/-345.00 len 194.80 saved tmp/ppo/taxi/checkpoint_1/checkpoint-1 | |
2 reward -902.00/-751.85/-345.00 len 193.70 saved tmp/ppo/taxi/checkpoint_2/checkpoint-2 | |
3 reward -902.00/-725.72/-340.00 len 193.00 saved tmp/ppo/taxi/checkpoint_3/checkpoint-3 | |
4 reward -902.00/-705.04/-151.00 len 192.59 saved tmp/ppo/taxi/checkpoint_4/checkpoint-4 | |
5 reward -902.00/-682.85/-151.00 len 192.62 saved tmp/ppo/taxi/checkpoint_5/checkpoint-5 | |
6 reward -902.00/-643.69/-128.00 len 190.27 saved tmp/ppo/taxi/checkpoint_6/checkpoint-6 | |
7 reward -902.00/-585.58/-78.00 len 185.95 saved tmp/ppo/taxi/checkpoint_7/checkpoint-7 | |
8 reward -794.00/-524.43/-21.00 len 176.76 saved tmp/ppo/taxi/checkpoint_8/checkpoint-8 | |
9 reward -794.00/-482.32/-21.00 len 172.15 saved tmp/ppo/taxi/checkpoint_9/checkpoint-9 | |
10 reward -713.00/-443.42/-21.00 len 166.61 saved tmp/ppo/taxi/checkpoint_10/checkpoint-10 |
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1 reward -200.00/-200.00/-200.00 len 200.00 saved tmp/ppo/moun/checkpoint_1/checkpoint-1 | |
2 reward -200.00/-200.00/-200.00 len 200.00 saved tmp/ppo/moun/checkpoint_2/checkpoint-2 | |
3 reward -200.00/-200.00/-200.00 len 200.00 saved tmp/ppo/moun/checkpoint_3/checkpoint-3 | |
4 reward -200.00/-200.00/-200.00 len 200.00 saved tmp/ppo/moun/checkpoint_4/checkpoint-4 | |
5 reward -200.00/-200.00/-200.00 len 200.00 saved tmp/ppo/moun/checkpoint_5/checkpoint-5 | |
6 reward -200.00/-200.00/-200.00 len 200.00 saved tmp/ppo/moun/checkpoint_6/checkpoint-6 | |
7 reward -200.00/-200.00/-200.00 len 200.00 saved tmp/ppo/moun/checkpoint_7/checkpoint-7 | |
8 reward -200.00/-200.00/-200.00 len 200.00 saved tmp/ppo/moun/checkpoint_8/checkpoint-8 | |
9 reward -200.00/-200.00/-200.00 len 200.00 saved tmp/ppo/moun/checkpoint_9/checkpoint-9 |
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1 reward 9.00/ 22.65/ 63.00 len 22.65 saved tmp/ppo/cart/checkpoint_1/checkpoint-1 | |
2 reward 12.00/ 42.72/151.00 len 42.72 saved tmp/ppo/cart/checkpoint_2/checkpoint-2 | |
3 reward 12.00/ 68.17/322.00 len 68.17 saved tmp/ppo/cart/checkpoint_3/checkpoint-3 | |
4 reward 13.00/ 97.87/408.00 len 97.87 saved tmp/ppo/cart/checkpoint_4/checkpoint-4 | |
5 reward 13.00/131.53/500.00 len 131.53 saved tmp/ppo/cart/checkpoint_5/checkpoint-5 | |
6 reward 13.00/165.24/500.00 len 165.24 saved tmp/ppo/cart/checkpoint_6/checkpoint-6 | |
7 reward 13.00/202.48/500.00 len 202.48 saved tmp/ppo/cart/checkpoint_7/checkpoint-7 | |
8 reward 22.00/233.83/500.00 len 233.83 saved tmp/ppo/cart/checkpoint_8/checkpoint-8 | |
9 reward 22.00/271.82/500.00 len 271.82 saved tmp/ppo/cart/checkpoint_9/checkpoint-9 | |
10 reward 22.00/302.99/500.00 len 302.99 saved tmp/ppo/cart/checkpoint_10/checkpoint-10 |
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CHECKPOINT_ROOT = "tmp/ppo/froz" | |
shutil.rmtree(CHECKPOINT_ROOT, ignore_errors=True, onerror=None) | |
ray_results = os.getenv("HOME") + "/ray_results/" | |
shutil.rmtree(ray_results, ignore_errors=True, onerror=None) |
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