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@paduvi
paduvi / FlatCnnLayer.py
Last active May 10, 2024 16:59
Hierarchical Softmax CNN Classification
import torch
import torch.nn as nn
import torch.nn.init as init
dropout_prob = 0.5
class FlatCnnLayer(nn.Module):
def __init__(self, embedding_size, sequence_length, filter_sizes=[3, 4, 5], out_channels=128):
super(FlatCnnLayer, self).__init__()
@bartolsthoorn
bartolsthoorn / multilabel_example.py
Created April 29, 2017 12:13
Simple multi-laber classification example with Pytorch and MultiLabelSoftMarginLoss (https://en.wikipedia.org/wiki/Multi-label_classification)
import torch
import torch.nn as nn
import numpy as np
import torch.optim as optim
from torch.autograd import Variable
# (1, 0) => target labels 0+2
# (0, 1) => target labels 1
# (1, 1) => target labels 3
train = []
@ryerh
ryerh / tmux-cheatsheet.markdown
Last active September 10, 2024 02:31 — forked from MohamedAlaa/tmux-cheatsheet.markdown
Tmux 快捷键 & 速查表 & 简明教程

注意：本文内容适用于 Tmux 2.3 及以上的版本，但是绝大部分的特性低版本也都适用，鼠标支持、VI 模式、插件管理在低版本可能会与本文不兼容。

Tmux 快捷键 & 速查表 & 简明教程

启动新会话：

tmux [new -s 会话名 -n 窗口名]

恢复会话：

@bgshih
bgshih / tps-demo.py
Created October 21, 2015 09:48
A simple example of Thin Plate Spline (TPS) transformation in Numpy.
import ipdb
import numpy as np
import numpy.linalg as nl
import matplotlib.pyplot as plt
from scipy.spatial.distance import pdist, cdist, squareform
def makeT(cp):
# cp: [K x 2] control points
# T: [(K+3) x (K+3)]
K = cp.shape[0]
@alexbowe
alexbowe / nltk-intro.py
Created March 21, 2011 12:59
Demonstration of extracting key phrases with NLTK in Python
import nltk
text = """The Buddha, the Godhead, resides quite as comfortably in the circuits of a digital
computer or the gears of a cycle transmission as he does at the top of a mountain
or in the petals of a flower. To think otherwise is to demean the Buddha...which is
to demean oneself."""
# Used when tokenizing words
sentence_re = r'''(?x) # set flag to allow verbose regexps
([A-Z])(\.[A-Z])+\.? # abbreviations, e.g. U.S.A.