small change to SolveShorts, FASTsearch now using GPU for calculations, requirements.txt added, cuda has to be exact version 9.0, cudann exact version 7.0
This commit is contained in:
parent
ed40090463
commit
3b66a89dc2
19 changed files with 328 additions and 79 deletions
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@ -185,14 +185,18 @@
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"source": [
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"\n",
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"# importing the libraries\n",
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"#print('importing libraries')\n",
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"#from SolveShorts import *\n",
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"#import SentSeg\n",
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"#from SayYes import *\n",
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"#from Passiv2Aktiv import *\n",
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"#from GenitivSolve import *\n",
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"#from ConjunctSolve import *\n",
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"\n",
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"#from FremdWB import *\n",
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"#from Medio import *\n",
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"#from oi import *\n",
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"#print('done')\n",
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"\n",
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"\n",
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"# Initializing the libraries\n",
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"#print('initializing the libraries')\n",
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@ -210,10 +214,12 @@
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"#cs = ConjunctSolve(None,None)\n",
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"#print('7')\n",
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"#oi = oi()\n",
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"\n",
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"#from FremdWB import *\n",
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"#print('8')\n",
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"#fwb = FremdWB(None,None)\n",
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"#fwb.load_DB_into_FASTsearch()\n",
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"#print('9')\n",
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"#medi = Medio(None,None)\n",
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"#print('done')\n",
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"\n",
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"\n",
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"# loading the databases and models\n",
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"#print('loading SolveShorts Databases')\n",
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@ -226,6 +232,11 @@
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"#p2a.load_DB_into_FASTsearch()\n",
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"#print('loading conjunctivesolve Databases')\n",
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"#cs.load_DB_into_FASTsearch()\n",
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"#print('loading the fremdwb Databases')\n",
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"#fwb.load_DB_into_FASTsearch()\n",
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"#print('loading the mediodot Databases')\n",
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"#medi.load_DB_into_FASTsearch()\n",
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"\n",
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"#print('done')\n",
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"\n"
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]
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@ -241,15 +252,6 @@
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"loading SolveShorts Databases\n",
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"Creating the bag of words...\n",
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"\n",
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"dumping the data to hkl format..\n",
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"done\n",
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"Creating the bag of words...\n",
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"\n",
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"dumping the data to hkl format..\n",
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"done\n",
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"dumping the session\n",
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"done\n"
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]
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@ -257,7 +259,7 @@
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{
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"data": {
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"application/vnd.jupyter.widget-view+json": {
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"model_id": "82646fa586ba44aabc1608ec7a268b2c",
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"model_id": "74fc341e0a474605b1f95c3e4e35d0b2",
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"version_major": 2,
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"version_minor": 0
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},
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@ -474,7 +476,7 @@
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{
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"data": {
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"application/vnd.jupyter.widget-view+json": {
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"model_id": "9e547f27f67f484c9b455ead6f63afb2",
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"model_id": "082cb6fb58aa41cc82d918d2a056258d",
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"version_major": 2,
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"version_minor": 0
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},
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@ -674,7 +676,7 @@
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{
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"data": {
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"application/vnd.jupyter.widget-view+json": {
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"model_id": "dad4baed09a5407194ae2daf153e8f43",
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"version_major": 2,
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"version_minor": 0
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},
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@ -714,7 +716,7 @@
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{
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"data": {
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"application/vnd.jupyter.widget-view+json": {
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"model_id": "564058b35ab743fabff90d4c49c5aac3",
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"model_id": "4bff927b0a404ed0b909db2bd766ac65",
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"version_major": 2,
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"version_minor": 0
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},
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@ -836,7 +838,7 @@
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{
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"data": {
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"application/vnd.jupyter.widget-view+json": {
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"model_id": "2e67ffb1c4ec4ddeb2c18935f4d0fdc4",
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"model_id": "b6053b85bdcd4446b010b5fb872dc52c",
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"version_major": 2,
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"version_minor": 0
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},
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@ -862,7 +864,7 @@
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{
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"data": {
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"application/vnd.jupyter.widget-view+json": {
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"model_id": "f8e8a92efa8e41bbb3efe44c35c37ec1",
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"model_id": "4d3e6e3a2bcb499697a50a1a1e88a8a4",
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"version_major": 2,
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"version_minor": 0
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},
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@ -15,6 +15,7 @@ import scipy as sc
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import tensorflow as tf
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import _pickle as cPickle
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import hickle as hkl
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@ -132,7 +133,7 @@ class FASTsearch(object):
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uiOZ = uiOZ.transpose()
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sess = tf.Session()
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with tf.device('/gpu:0'):
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with sess.as_default():
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uiOZ_tensor = tf.constant(uiOZ)
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@ -206,7 +207,7 @@ class FASTsearch(object):
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uiOZ = uiOZ.transpose()
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sess = tf.Session()
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with tf.device('/gpu:0'):
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with sess.as_default():
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uiOZ_tensor = tf.constant(uiOZ)
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@ -257,7 +258,7 @@ class FASTsearch(object):
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uiOZ = uiOZ.transpose()
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sess = tf.Session()
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with tf.device('/gpu:0'):
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with sess.as_default():
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uiOZ_tensor = tf.constant(uiOZ)
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@ -185,14 +185,18 @@
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"source": [
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"\n",
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"# importing the libraries\n",
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"#print('importing libraries')\n",
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"#from SolveShorts import *\n",
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"#import SentSeg\n",
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"#from SayYes import *\n",
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"#from Passiv2Aktiv import *\n",
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"#from GenitivSolve import *\n",
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"#from ConjunctSolve import *\n",
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"\n",
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"#from FremdWB import *\n",
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"#from Medio import *\n",
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"#from oi import *\n",
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"#print('done')\n",
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"\n",
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"\n",
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"# Initializing the libraries\n",
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"#print('initializing the libraries')\n",
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@ -210,10 +214,12 @@
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"#cs = ConjunctSolve(None,None)\n",
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"#print('7')\n",
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"#oi = oi()\n",
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"\n",
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"#from FremdWB import *\n",
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"#print('8')\n",
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"#fwb = FremdWB(None,None)\n",
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"#fwb.load_DB_into_FASTsearch()\n",
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"#print('9')\n",
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"#medi = Medio(None,None)\n",
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"#print('done')\n",
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"\n",
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"\n",
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"# loading the databases and models\n",
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"#print('loading SolveShorts Databases')\n",
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@ -226,6 +232,11 @@
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"#p2a.load_DB_into_FASTsearch()\n",
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"#print('loading conjunctivesolve Databases')\n",
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"#cs.load_DB_into_FASTsearch()\n",
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"#print('loading the fremdwb Databases')\n",
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"#fwb.load_DB_into_FASTsearch()\n",
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"#print('loading the mediodot Databases')\n",
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"#medi.load_DB_into_FASTsearch()\n",
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"\n",
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"#print('done')\n",
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"\n"
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]
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@ -241,15 +252,6 @@
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"loading SolveShorts Databases\n",
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"Creating the bag of words...\n",
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"\n",
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"dumping the data to hkl format..\n",
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"done\n",
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"Creating the bag of words...\n",
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"\n",
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"dumping the data to hkl format..\n",
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"done\n",
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"dumping the session\n",
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"done\n"
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]
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@ -257,7 +259,7 @@
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{
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"data": {
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"application/vnd.jupyter.widget-view+json": {
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"model_id": "82646fa586ba44aabc1608ec7a268b2c",
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"model_id": "74fc341e0a474605b1f95c3e4e35d0b2",
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"version_major": 2,
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"version_minor": 0
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},
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@ -474,7 +476,7 @@
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{
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"data": {
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"application/vnd.jupyter.widget-view+json": {
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"model_id": "9e547f27f67f484c9b455ead6f63afb2",
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"model_id": "082cb6fb58aa41cc82d918d2a056258d",
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"version_major": 2,
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"version_minor": 0
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},
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@ -674,7 +676,7 @@
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{
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"data": {
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"application/vnd.jupyter.widget-view+json": {
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"model_id": "0d27a028dcb449e2a2a6a7dfd25acd49",
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"model_id": "dad4baed09a5407194ae2daf153e8f43",
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"version_major": 2,
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"version_minor": 0
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},
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@ -714,7 +716,7 @@
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{
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"data": {
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"application/vnd.jupyter.widget-view+json": {
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"model_id": "564058b35ab743fabff90d4c49c5aac3",
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"model_id": "4bff927b0a404ed0b909db2bd766ac65",
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"version_major": 2,
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"version_minor": 0
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},
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@ -836,7 +838,7 @@
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{
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"data": {
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"application/vnd.jupyter.widget-view+json": {
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"model_id": "2e67ffb1c4ec4ddeb2c18935f4d0fdc4",
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"model_id": "b6053b85bdcd4446b010b5fb872dc52c",
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"version_major": 2,
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"version_minor": 0
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},
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@ -862,7 +864,7 @@
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{
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"data": {
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"application/vnd.jupyter.widget-view+json": {
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"model_id": "f8e8a92efa8e41bbb3efe44c35c37ec1",
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"model_id": "4d3e6e3a2bcb499697a50a1a1e88a8a4",
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"version_major": 2,
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"version_minor": 0
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},
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@ -130,7 +130,7 @@ class SolveShorts(object):
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NhasToBeChecked = False
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# Liste von falsch erkannten, zb er sollte nicht erkannt werden :)
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if sentence[n] in ['Er', 'er', 'ab', 'Ab', 'so', 'da', 'an', 'mit']:
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if sentence[n] in ['Er', 'er', 'ab', 'Ab', 'so', 'da', 'an', 'mit', 'Am', 'am']:
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NhasToBeChecked = False
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if n != 0 and sentence[n][-1] != '.' and doc[n - 1].dep_[:2] != 'ART':
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7
Prototyp/Verbesserungen/Input144.txt
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7
Prototyp/Verbesserungen/Input144.txt
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@ -0,0 +1,7 @@
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die Rede ist vom NRW-Polizeiskandal .
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29 PolizistInnen wurden suspendiert, weil sie Teil rechtsextremer Whatsapp-Chatgruppen waren, die teils seit 2012 bestanden .
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die Betroffenen gehörten fast alle zum Polizeipräsidium Essen, eine Dienstgruppe in Mülheim wurde komplett freigestellt, inklusive Dienstgruppenführer .
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am Donnerstag sprach Reul von einer weiteren suspendierten Beamtin, auch sie aus der Mülheimer Gruppe .
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Bundesweit wird nun über Konsequenzen diskutiert .
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und die Affäre könnte sich noch ausweiten .
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denn bisher hatten die Ermittler nur das Telefon eines Beamten, welches die Ermittlungen ins Rollen brachten .
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16
Prototyp/Verbesserungen/Output144.txt
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16
Prototyp/Verbesserungen/Output144.txt
Normal file
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die Rede ist vom NRW-Polizeiskandal .
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29 PolizistInnen wurden suspendiert .
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Teil sie waren rechtsextremer Whatsapp-Chatgruppen weil .
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Teils bestanden diese seit 2012 .
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die Betroffenen gehoerten fast alle zum Polizeipraesidium Essen .
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eine Dienstgruppe in Muelheim wurde komplett freigestellt .
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Inklusive Dienstgruppenfuehrer .
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am (amos) Donnerstag sprach Reul von einer weiteren suspendierten Beamtin .
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auch sie aus der Muelheimer Gruppe .
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bundesweit diskutiert jemand nun ueber Konsequenzen .
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und die Affaere koennte sich noch ausweiten .
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eine Affaere ist ein Skandal .
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zum Beispiel :
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etwas was viele Menschen schlimm finden .
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die Ermittler eines Beamten hatten nur das Telefon denn bisher .
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dieses ins Rollen brachten die Ermittlungen .
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15
Prototyp/Verbesserungen/Verbesserungen144.txt
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15
Prototyp/Verbesserungen/Verbesserungen144.txt
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die Rede ist vom NRW-Polizeiskandal .
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29 PolizistInnen wurden suspendiert .
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weil sie Teil rechtsextremer Whatsapp-Chatgruppen waren .
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Teils bestanden diese seit 2012 .
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die Betroffenen gehoerten fast alle zum Polizeipraesidium Essen .
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eine Dienstgruppe in Muelheim wurde komplett freigestellt .
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Inklusive Dienstgruppenfuehrer .
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am Donnerstag sprach Reul von einer weiteren suspendierten Beamtin .
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auch sie aus der Muelheimer Gruppe .
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bundesweit diskutiert jemand nun ueber Konsequenzen .
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und die Affaere koennte sich noch ausweiten .
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eine Affaere ist ein Skandal .
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zum Beispiel: etwas was viele Menschen schlimm finden .
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denn bisher hatten die Ermittler nur das Telefon eines Beamten .
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dieses brachten die Ermittlungen ins Rollen .
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@ -1 +1 @@
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143
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144
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206
Prototyp/requirements.txt
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206
Prototyp/requirements.txt
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absl-py==0.6.1
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aiohttp==3.5.4
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aiohttp-socks==0.2.2
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anytree==2.4.3
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appdirs==1.4.3
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appmode==0.7.0
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argh==0.26.2
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asn1crypto==0.24.0
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astor==0.7.1
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astunparse==1.6.3
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async-generator==1.10
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async-timeout==3.0.1
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attrs==18.2.0
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Automat==0.7.0
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backcall==0.1.0
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beautifulsoup4==4.6.3
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bleach==1.5.0
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blis==0.4.1
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boto==2.49.0
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boto3==1.9.71
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botocore==1.12.71
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bqplot==0.12.6
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bz2file==0.98
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CacheControl==0.12.5
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cachetools==4.1.1
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catalogue==1.0.0
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certifi==2019.6.16
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cffi==1.11.5
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chardet==3.0.4
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Click==7.0
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colorama==0.4.1
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constantly==15.1.0
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cryptography==2.4.2
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cssselect==1.0.3
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cycler==0.10.0
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cymem==2.0.2
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Cython==0.29.2
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cytoolz==0.9.0.1
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de-core-news-sm==2.0.0
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decorator==4.3.0
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defusedxml==0.5.0
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dill==0.2.8.2
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distlib==0.2.8
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distro==1.3.0
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dnspython==1.16.0
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docutils==0.14
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ecdsa==0.13
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engineering-notation==0.6.0
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entrypoints==0.2.3
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gast==0.2.0
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gensim==3.6.0
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Glances==3.0.2
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grpcio==1.17.0
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gunicorn==19.9.0
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h5py==2.8.0
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hickle==3.3.2
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html5lib==0.9999999
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hyperlink==18.0.0
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idna==2.7
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idna-ssl==1.1.0
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importlib-metadata==1.4.0
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incremental==17.5.0
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ipykernel==4.9.0
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ipython==7.1.1
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ipython-genutils==0.1.0
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ipyvue==1.3.1
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ipyvuetify==1.2.2
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ipywidgets==7.5.1
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jedi==0.13.1
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Jinja2==2.10
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jmespath==0.9.3
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jsonrpclib-pelix==0.3.2
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jsonschema==2.6.0
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jupyter-client==6.1.2
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jupyter-console==6.0.0
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jupyter-contrib-core==0.3.3
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jupyter-contrib-nbextensions==0.5.1
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jupyter-core==4.6.0
|
||||
jupyter-highlight-selected-word==0.2.0
|
||||
jupyter-latex-envs==1.4.6
|
||||
jupyter-nbextensions-configurator==0.4.1
|
||||
jupyter-server==0.1.1
|
||||
jupyterlab-pygments==0.1.0
|
||||
jupyterthemes==0.20.0
|
||||
Keras-Applications==1.0.6
|
||||
Keras-Preprocessing==1.0.5
|
||||
kiwisolver==1.0.1
|
||||
lesscpy==0.14.0
|
||||
lockfile==0.12.2
|
||||
lxml==4.2.5
|
||||
Markdown==2.6.11
|
||||
MarkupSafe==1.1.0
|
||||
matplotlib==3.0.2
|
||||
mistune==0.8.4
|
||||
mock==3.0.5
|
||||
more-itertools==8.1.0
|
||||
msgpack==0.5.6
|
||||
msgpack-numpy==0.4.3.2
|
||||
multidict==4.5.2
|
||||
murmurhash==1.0.1
|
||||
nbconvert==5.6.1
|
||||
nbformat==4.4.0
|
||||
ngrok==0.0.1
|
||||
nltk==3.4.1
|
||||
notebook==5.7.2
|
||||
numpy==1.15.4
|
||||
oauthlib==3.1.0
|
||||
olefile==0.46
|
||||
opt-einsum==3.3.0
|
||||
packaging==18.0
|
||||
pandas==0.23.4
|
||||
pandocfilters==1.4.2
|
||||
parsel==1.5.1
|
||||
parso==0.3.1
|
||||
pathlib2==2.3.5
|
||||
pbkdf2==1.3
|
||||
pdfminer3k==1.3.1
|
||||
pep517==0.3
|
||||
pexpect==4.6.0
|
||||
pickleshare==0.7.5
|
||||
Pillow==5.3.0
|
||||
plac==0.9.6
|
||||
pluggy==0.13.1
|
||||
ply==3.11
|
||||
preshed==2.0.1
|
||||
progress==1.4
|
||||
prometheus-client==0.4.2
|
||||
prompt-toolkit==2.0.7
|
||||
protobuf==3.6.1
|
||||
psutil==5.4.8
|
||||
ptyprocess==0.6.0
|
||||
py==1.8.1
|
||||
pyaes==1.6.1
|
||||
pyasn1==0.4.4
|
||||
pyasn1-modules==0.2.2
|
||||
pycparser==2.19
|
||||
pycryptodomex==3.6.6
|
||||
PyDispatcher==2.0.5
|
||||
Pygments==2.6.1
|
||||
PyHamcrest==1.9.0
|
||||
pyOpenSSL==18.0.0
|
||||
pyparsing==2.3.0
|
||||
PyQt5==5.11.3
|
||||
PyQt5-sip==4.19.13
|
||||
PySocks==1.6.8
|
||||
PyStemmer==1.3.0
|
||||
pytest==5.3.2
|
||||
python-dateutil==2.7.5
|
||||
pytoml==0.1.20
|
||||
pytz==2018.7
|
||||
PyYAML==5.3
|
||||
pyzmq==17.1.0
|
||||
qrcode==6.0
|
||||
QtPy==1.5.1
|
||||
queuelib==1.5.0
|
||||
regex==2018.1.10
|
||||
requests==2.20.1
|
||||
requests-oauthlib==1.3.0
|
||||
retrying==1.3.3
|
||||
rsa==4.6
|
||||
s3transfer==0.1.13
|
||||
scikit-learn==0.20.0
|
||||
scipy==1.1.0
|
||||
Scrapy==1.5.1
|
||||
Send2Trash==1.5.0
|
||||
service-identity==18.1.0
|
||||
simplegeneric==0.8.1
|
||||
six==1.12.0
|
||||
smart-open==1.7.1
|
||||
spacy==2.0.18
|
||||
srsly==1.0.1
|
||||
tensorboard==1.12.0
|
||||
tensorboard-plugin-wit==1.7.0
|
||||
tensorflow==1.12.0
|
||||
tensorflow-gpu==1.12.0
|
||||
tensorflow-serving-api==1.12.0
|
||||
tensorflow-tensorboard==1.5.1
|
||||
termcolor==1.1.0
|
||||
terminado==0.8.1
|
||||
testpath==0.4.2
|
||||
thinc==6.12.1
|
||||
tk-tools==0.12.0
|
||||
toolz==0.9.0
|
||||
tornado==5.1.1
|
||||
tqdm==4.28.1
|
||||
traitlets==4.3.2
|
||||
traittypes==0.2.1
|
||||
Twisted==18.9.0
|
||||
typing-extensions==3.7.4.1
|
||||
ujson==1.35
|
||||
urllib3==1.24.1
|
||||
virtualenv==16.1.0
|
||||
voila==0.1.21
|
||||
voila-gridstack==0.0.8
|
||||
voila-vuetify==0.2.2
|
||||
w3lib==1.19.0
|
||||
wasabi==0.6.0
|
||||
wcwidth==0.1.7
|
||||
webencodings==0.5.1
|
||||
websocket-client==0.54.0
|
||||
Werkzeug==0.14.1
|
||||
widgetsnbextension==3.5.1
|
||||
wrapt==1.10.11
|
||||
yarl==1.3.0
|
||||
zipp==0.6.0
|
||||
zope.interface==4.6.0
|
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Reference in a new issue