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cmake -D BOOST_INCLUDEDIR=/usr/local/include -D BOOST_LIBRARYDIR=/usr/local/lib -D PYTHON_EXECUTABLE=/root/anaconda/bin/python -D PYTHON_INCLUDE_DIR=/root/anaconda/include/python2.7 -D PYTHON_LIBRARY=/root/anaconda/lib/libpython2.7.so -D PYTHON_PACKAGES_PATH=/root/anaconda/lib/python2.7/site-packages/ -D PYTHON_NUMPY_INCLUDE_DIR=/root/anaconda/lib/python2.7/dist-packages/numpy/core/include -D CMAKE_BUILD_TYPE=RELEASE -D CMAKE_INSTALL_PREFIX=/usr/local -D WITH_TBB=ON -D WITH_EIGEN=ON BUILD_TESTS=OFF -D BUILD_PERF_TESTS=OFF -D BUILD_EXAMPLES=OFF -D WITH_OPENCL=OFF -D WITH_CUDA=OFF -D BUILD_opencv_gpu=OFF -D BUILD_opencv_gpuarithm=OFF -D BUILD_opencv_gpubgsegm=OFF -D BUILD_opencv_gpucodec=OFF -D BUILD_opencv_gpufeatures2d=OFF -D BUILD_opencv_gpufilters=OFF -D BUILD_opencv_gpuimgproc=OFF -D BUILD_opencv_gpulegacy=OFF -D BUILD_opencv_gpuoptflow=OFF -D BUILD_opencv_gpustereo=OFF -D BUILD_opencv_gpuwarping=OFF ..

cmake -D BOOST_INCLUDEDIR=/usr/local/include -D BOOST_LIBRARYDIR=/usr/local/lib -D PYTHON_EXECUTABLE=/r

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#!/usr/bin/env python
# net architecture of http://ccvl.stat.ucla.edu/ccvl/DeepLab/train.prototxt
# format: [kernel, stride]
deep_lab_vgg = [
    # 1
    [3, 1], 
    [3, 1], 
    [2, 2],
    # 2
    [3, 1], 

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"""
This is a batched LSTM forward and backward pass
"""
import numpy as np
import code

class LSTM:
  
  @staticmethod
  def init(input_size, hidden_size, fancy_forget_bias_init = 3):

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All use http.proxy and https.proxy

git

git config --global http.sslVerify false

pip

pip install --trusted-host xxx.com package

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//used for training

def bi_lstm_unroll(seq_len, input_size,num_hidden, num_embed, num_label, dropout=0.):
    embed_weight = mx.sym.Variable("embed_weight")
    cls_weight = mx.sym.Variable("cls_weight")
    cls_bias = mx.sym.Variable("cls_bias")
    last_states = []
    last_states.append(LSTMState(c = mx.sym.Variable("l0_init_c"), h = mx.sym.Variable("l0_init_h")))
    last_states.append(LSTMState(c = mx.sym.Variable("l1_init_c"), h = mx.sym.Variable("l1_init_h")))
    forward_param = LSTMParam(i2h_weight=mx.sym.Variable("l0_i2h_weight"),

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# pylint: disable=C0111,too-many-arguments,too-many-instance-attributes,too-many-locals,redefined-outer-name,fixme
# pylint: disable=superfluous-parens, no-member, invalid-name
import sys
sys.path.insert(0, "../../python")
import mxnet as mx
import numpy as np
import cv2, random

from io import BytesIO
from captcha.image import ImageCaptcha

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nnoremap <F7> :make! test<CR>
augroup MakeRunTestGroup
    autocmd!
    autocmd QuickFixCmdPost make call RunTest()
augroup END

function! RunTest()
    " check quickfix list
    let l:b_ok = 1
    for m in getqflist()

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#!/bin/env python
import requests
from bs4 import BeautifulSoup as Soup 
import cPickle

def getStarers(soup):
    stars = soup.select('#repos .follow-list-item')
    starers = []
    for s in stars:
        starers.append(s.a['href']+'\n')

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cmake -D CMAKE_BUILD_TYPE=RELEASE -D CMAKE_INSTALL_PREFIX=/usr/local -D WITH_TBB=ON -D BUILD_NEW_PYTHON_SUPPORT=ON -D WITH_V4L=ON -D INSTALL_C_EXAMPLES=ON -D INSTALL_PYTHON_EXAMPLES=ON -D BUILD_EXAMPLES=ON -D WITH_QT=ON -D WITH_OPENGL=ON -D CUDA_GENERATION=Auto..

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working tree

• A "working tree" consist of files that you are currently working on.

commits

• a snapshot of
  • a directory tree
  • files within (a)
  • some metadata
    • parents

• commiter