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: |
| <!DOCTYPE html> | |
| <head> | |
| <!--Little CSS fade in --> | |
| <style> | |
| .fade-in{ | |
| -webkit-animation: fade-in 2s ease; | |
| -moz-animation: fade-in ease-in-out 2s both; | |
| -ms-animation: fade-in ease-in-out 2s both; | |
| -o-animation: fade-in ease-in-out 2s both; |
| require 'nn' | |
| require 'dpnn' | |
| require 'rnn' | |
| require 'nngraph' | |
| local opt = { | |
| n_seq = 3, | |
| d_hid = 4, | |
| d_mem = 20, | |
| n_batch = 2, |
The repository for the assignment is public and Github does not allow the creation of private forks for public repositories.
The correct way of creating a private frok by duplicating the repo is documented here.
For this assignment the commands are:
git clone --bare [email protected]:usi-systems/easytrace.git
| def _sequence_mask(sequence_length, max_len=None): | |
| if max_len is None: | |
| max_len = sequence_length.data.max() | |
| batch_size = sequence_length.size(0) | |
| seq_range = torch.range(0, max_len - 1).long() | |
| seq_range_expand = seq_range.unsqueeze(0).expand(batch_size, max_len) | |
| seq_range_expand = Variable(seq_range_expand) | |
| if sequence_length.is_cuda: | |
| seq_range_expand = seq_range_expand.cuda() | |
| seq_length_expand = (sequence_length.unsqueeze(1) |
| import torch | |
| import torch.nn as nn | |
| from torch.nn.utils.rnn import pack_padded_sequence, pad_packed_sequence | |
| seqs = ['gigantic_string','tiny_str','medium_str'] | |
| # make <pad> idx 0 | |
| vocab = ['<pad>'] + sorted(set(''.join(seqs))) | |
| # make model |
| from __future__ import print_function | |
| import torch | |
| import torch.nn as nn | |
| import torch.nn.functional as F | |
| from torch.autograd import Variable | |
| def sample_gumbel(shape, eps=1e-20): | |
| U = torch.rand(shape).cuda() | |
| return -Variable(torch.log(-torch.log(U + eps) + eps)) |
| #!/bin/bash | |
| fileid="FILEIDENTIFIER" | |
| filename="FILENAME" | |
| curl -c ./cookie -s -L "https://drive.google.com/uc?export=download&id=${fileid}" > /dev/null | |
| curl -Lb ./cookie "https://drive.google.com/uc?export=download&confirm=`awk '/download/ {print $NF}' ./cookie`&id=${fileid}" -o ${filename} |
| # | |
| # @author: Allan | |
| # | |
| def convert(input, output): | |
| from gensim.models.keyedvectors import KeyedVectors | |
| embedding = KeyedVectors.load_word2vec_format(input, binary=True) | |
| f= open(output, 'w', encoding='utf-8') |
| """ | |
| IOB1: O I I B I | |
| IOB2: O B I B I | |
| """ | |
| from typing import List | |
| def iob2(tags: List[str]): | |
| """ | |
| Check that tags have a valid IOB format. |
