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#!/usr/local/bin/zsh | |
# In a PDF library with associated Skim notes, automatically embed all | |
# skim notes in the PDF files. | |
# I used this to help transition from an OS X + Skim reading environment | |
# to a Linux reading environment. | |
# WARNING: This script deletes the Skim files after embedding their contents | |
# in the PDFs. Make sure you back up your library before using. |
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export VAGRANT_HOME=/om2/user/$USER/vagrant | |
dir=/om2/user/$USER/vms/ibex | |
mkdir -p $VAGRANT_HOME || exit 1 | |
mkdir -p $dir || exit 1 | |
cd $dir | |
# Set up an Ubuntu 16 VM managed by Vagrant. | |
vagrant init ubuntu/xenial64 |
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BEGIN { | |
c["little"]="size"; | |
c["big"]="size"; | |
c["white"]="color"; | |
c["green"]="color"; | |
c["blue"]="color"; | |
c["red"]="color"; | |
c["good"]="char"; | |
c["bad"]="char"; | |
c["first"]="ord"; |
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diff -ruw ./gaps/Makefile ../../SUNCGtoolbox-master/gaps/Makefile | |
--- ./gaps/Makefile 2017-10-01 23:23:17.000000000 +0000 | |
+++ ../../SUNCGtoolbox-master/gaps/Makefile 2017-11-03 14:25:28.760111809 +0000 | |
@@ -31,7 +31,7 @@ | |
target: | |
cd pkgs; $(MAKE) $(TARGET) | |
cd apps; $(MAKE) $(TARGET) | |
- cd vc; $(MAKE) $(TARGET) | |
+ # cd vc; $(MAKE) $(TARGET) | |
# cd docs; $(MAKE) $(TARGET) |
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import theano | |
from theano import gof | |
from theano import tensor as T | |
from theano.sandbox.cuda import GpuOp | |
from theano.sandbox.cuda.basic_ops import (CudaNdarrayType, GpuFromHost, | |
HostFromGpu, | |
as_cuda_ndarray_variable) | |
from theano.tensor.opt import register_specialize_device | |
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from collections import OrderedDict | |
import numpy as np | |
import theano | |
from theano import tensor as T | |
class MyAdvancedSetSubtensor1(T.subtensor.AdvancedIncSubtensor1): | |
def get_inplace(self): |
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from collections import namedtuple | |
import unittest | |
Compose = namedtuple("Compose", ["a", "b"]) | |
class Stack(object): | |
def __init__(self, compose_fn, n): |
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#include <stdlib.h> | |
#include <stdio.h> | |
#include <time.h> | |
#include <cudnn.h> | |
/** | |
* Verified correctness with cuDNN 6.5-R1. | |
* | |
* Author: Jon Gauthier <[email protected]> |
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import numpy as np | |
import theano | |
import theano.tensor as T | |
x = T.bscalar('x') | |
def scan_f(x): | |
# Second argument "until" establishes a stop condition |
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from collections import Counter, defaultdict | |
import itertools | |
import os | |
import random | |
import re | |
import numpy as np | |
EMBEDDING_FILE = "/u/nlp/data/depparser/nn/data/embeddings/en-cw.txt" | |
EMBEDDING_SERIALIZED = "embeddings.npz" |