Skip to content

Instantly share code, notes, and snippets.

View acuros's full-sized avatar

Seungyeon Kim(Acuros Kim) acuros

View GitHub Profile
class AutoBrAdmin(admin.ModelAdmin):
br_attrs = tuple()
def get_object(self, request, object_id):
obj = super(AutoBrAdmin, self).get_object(request, object_id)
for attr in self.br_attrs:
value = getattr(obj, attr)
setattr(obj, attr, value.replace('\r\n', '').replace('<br>', '\r\n'))
return obj
@acuros
acuros / min-char-rnn.py
Created March 13, 2016 14:55 — forked from karpathy/min-char-rnn.py
Minimal character-level language model with a Vanilla Recurrent Neural Network, in Python/numpy
"""
Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy)
BSD License
"""
import numpy as np
# data I/O
data = open('input.txt', 'r').read() # should be simple plain text file
chars = list(set(data))
data_size, vocab_size = len(data), len(chars)