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| //OpensCAD | |
| car_diam = 63; | |
| car_height = 90; | |
| cup_diam = 74; | |
| cup_height = 70; | |
| wall = 2; | |
| cup_floor = 3; | |
| view = 0; |
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| bill_height = 69.85; | |
| bill_width = 152.4; | |
| space = 3; | |
| cutout = 25; | |
| walls = 5; | |
| view = 1; | |
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| import json | |
| from botocore.vendored import requests | |
| url = 'https://voyagesarabais.com/recherche-sud/getpricedetails?search%5Bgateway%5D=YUL&search%5BdateDep%5D=2019-12-15&search%5Bduration%5D=7day%2C8day&search%5BdestDep%5D=o&search%5BnoHotel%5D=p7&search%5Broom1%5D=a%3A4%3A%7Bi%3A0%3Bs%3A2%3A%2240%22%3Bi%3A1%3Bs%3A2%3A%2240%22%3Bi%3A2%3Bs%3A1%3A%223%22%3Bi%3A3%3Bs%3A1%3A%221%22%3B%7D&search%5Broom2%5D=&search%5Broom3%5D=&search%5Broom4%5D=&search%5Broom5%5D=&search%5Broom6%5D=&search%5Bflex%5D=N&search%5Bflexhigh%5D=3&search%5Bflexlow%5D=3&search%5Broomcallgroup%5D=%5B%7B%22_priority%22%3A9%2C%22nb_rooms%22%3A1%2C%22nb_adults%22%3A2%2C%22non_adults%22%3A%5B%223%22%2C%221%22%5D%7D%5D&search%5Bpricemax%5D=9000&search%5Bpricemin%5D=1&search%5Ballinclusive%5D=Y&search%5Bbeach%5D=&search%5Bcasino%5D=&search%5Bfamily%5D=&search%5Bgolf%5D=&search%5Bkitchenette%5D=&search%5Boceanview%5D=&search%5Bminiclub%5D=&search%5Bspa%5D=&search%5Bwedding%5D=&search%5Badultonly%5D=&search%5Bnoextrasingle%5D=&search%5Bvilla%5D=&s |
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| from utils.scala_functions import find_matching_patterns | |
| from pyspark.sql import functions as F | |
| regexes = regex.agg(F.collect_list(F.col("pattern"))).collect()[0][0] | |
| regexes = sc.broadcast(regexes) | |
| articles = articles \ | |
| .withColumn("patterns", find_matching_patterns(F.col("text"), regexes.value) | |
| .withColumn("patterns", F.when(F.col("patterns").isNull(), F.array(F.lit(None))).otherwise(F.col("patterns"))) \ | |
| .withColumn("pattern", F.explode(F.col("patterns"))) |
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| def findMatchingPatterns(regexes: ArrayList[String]): UserDefinedFunction = { | |
| udf((value: String) => { | |
| for { | |
| text <- Option(value) | |
| matches = regexes.asScala.filter(r => Pattern.matches(r, text)) | |
| if matches.nonEmpty | |
| } yield matches | |
| }, ArrayType(StringType)) | |
| } |
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| wiki.join(regex, expr("text rlike pattern") how='left_outer') |
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| def lossless_triplet_loss(y_true, y_pred, N = 3, beta=N, epsilon=1e-8): | |
| """ | |
| Implementation of the triplet loss function | |
| Arguments: | |
| y_true -- true labels, required when you define a loss in Keras, you don't need it in this function. | |
| y_pred -- python list containing three objects: | |
| anchor -- the encodings for the anchor data | |
| positive -- the encodings for the positive data (similar to anchor) | |
| negative -- the encodings for the negative data (different from anchor) |
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| def triplet_loss(y_true, y_pred, alpha = 0.4): | |
| """ | |
| Implementation of the triplet loss function | |
| Arguments: | |
| y_true -- true labels, required when you define a loss in Keras, you don't need it in this function. | |
| y_pred -- python list containing three objects: | |
| anchor -- the encodings for the anchor data | |
| positive -- the encodings for the positive data (similar to anchor) | |
| negative -- the encodings for the negative data (different from anchor) |
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| import json | |
| import decimal | |
| import urllib.request | |
| import boto3 | |
| dynamodb = boto3.resource('dynamodb') | |
| table = dynamodb.Table('AltCoinHistory') | |
| def lambda_handler(event, context): |
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| # change the prefix from 'C-b' to 'C-a' | |
| # (remap capslock to CTRL for easy access) | |
| unbind C-b | |
| set-option -g prefix C-a | |
| bind-key C-a send-prefix | |
| # start with window 1 (instead of 0) | |
| set -g base-index 1 | |
| # start with pane 1 |
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