Bage (Hyewoong Park) bage79

## top_k_viterbi.py
import torch

# Credits to AllenNLP for the base implementation and base tests:
# https://github.com/allenai/allennlp/blob/master/allennlp/nn/util.py#L174

# Modified AllenNLP `viterbi_decode` to support `top_k` sequences efficiently.
def viterbi_decode(tag_sequence: torch.Tensor, transition_matrix: torch.Tensor, top_k: int=5):
    """
    Perform Viterbi decoding in log space over a sequence given a transition matrix
    specifying pairwise (transition) potentials between tags and a matrix of shape

## 한글과유니코드.md

      
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                Pusnow
                / 한글과유니코드.md
            
            
              Last active
              March 17, 2024 08:27
            
              
                한글과 유니코드
              
          
    한글과 유니코드

유니코드에서 한글을 어떻게 다루는지를 정리하였다.
유니코드


유니코드(Unicode)는 전 세계의 모든 문자를 컴퓨터에서 일관되게 표현하고 다룰 수 있도록 설계된 산업 표준 (위키 백과)
단순히 문자마다 번호를 붙임
계속 업데이트되며 현재는 Unicode Version 9.0.0 이 최신이다.

UTF


유니코드를 실제 파일 등에 어떻게 기록할 것인지를 표준화한 것이다.


## euclid.prototxt
name: 'EuclideanExample'
layer {
  type: 'DummyData'
  name: 'x'
  top: 'x'
  dummy_data_param {
    shape: { dim: 10 dim: 3 dim: 2 }
    data_filler: { type: 'gaussian' }
  }
}

## gist:7360908

      
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                rxaviers
                / gist:7360908
            
            
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              May 7, 2024 22:35
            
              
                Complete list of github markdown emoji markup
              
          
    People


 :bowtie:
😄 :smile:
😆 :laughing:


😊 :blush:
😃 :smiley:
☺️ :relaxed:


😏 :smirk:
😍 :heart_eyes:
😘 :kissing_heart:


😚 :kissing_closed_eyes:
😳 :flushed:
😌 :relieved:


😆 :satisfied:
😁 :grin:
😉 :wink:


😜 :stuck_out_tongue_winking_eye:
😝 :stuck_out_tongue_closed_eyes:
😀 :grinning:


😗 :kissing:
😙 :kissing_smiling_eyes:
😛 :stuck_out_tongue:


## stresstest.py
import multiprocessing
import requests

URLS = (
    'http://50.56.81.42:8080/V0.2/favroutes-list/?userid=18',
    'http://50.56.81.42:8080/V0.2/favroutes-list/?userid=4',
    'http://50.56.81.42:8080/getfavadd/18',
    'http://50.56.81.42:8080/getfavadd/1'
)
	import torch

	# Credits to AllenNLP for the base implementation and base tests:
	# https://github.com/allenai/allennlp/blob/master/allennlp/nn/util.py#L174

	# Modified AllenNLP `viterbi_decode` to support `top_k` sequences efficiently.
	def viterbi_decode(tag_sequence: torch.Tensor, transition_matrix: torch.Tensor, top_k: int=5):
	"""
	Perform Viterbi decoding in log space over a sequence given a transition matrix
	specifying pairwise (transition) potentials between tags and a matrix of shape
	name: 'EuclideanExample'
	layer {
	type: 'DummyData'
	name: 'x'
	top: 'x'
	dummy_data_param {
	shape: { dim: 10 dim: 3 dim: 2 }
	data_filler: { type: 'gaussian' }
	}
	}
`:bowtie:`	😄 `:smile:`	😆 `:laughing:`
😊 `:blush:`	😃 `:smiley:`	☺️ `:relaxed:`
😏 `:smirk:`	😍 `:heart_eyes:`	😘 `:kissing_heart:`
😚 `:kissing_closed_eyes:`	😳 `:flushed:`	😌 `:relieved:`
😆 `:satisfied:`	😁 `:grin:`	😉 `:wink:`
😜 `:stuck_out_tongue_winking_eye:`	😝 `:stuck_out_tongue_closed_eyes:`	😀 `:grinning:`
😗 `:kissing:`	😙 `:kissing_smiling_eyes:`	😛 `:stuck_out_tongue:`
	import multiprocessing
	import requests

	URLS = (
	'http://50.56.81.42:8080/V0.2/favroutes-list/?userid=18',
	'http://50.56.81.42:8080/V0.2/favroutes-list/?userid=4',
	'http://50.56.81.42:8080/getfavadd/18',
	'http://50.56.81.42:8080/getfavadd/1'
	)