nsaphra

"""
Because pytorch does not expose the internal activations of a module,
we must instead rerun the same exact function inside that module.
This is written specifically for a 1 layer LSTM with all default settings.
"""

import torch
import torch.nn as nn
from torch.autograd import Variable

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import sys

types = set()
token_count = 0

for i, line in enumerate(sys.stdin):
    if i % 1000 == 0:
        print('.')
    line = line.strip().split()
    types.update(line)

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# -*- coding: utf-8 -*-
import os
from random import shuffle
import argparse

parser = argparse.ArgumentParser(description='shuffle a corpus such that the tags and the original tokenized text still align')
parser.add_argument('--unshuffled_dir', type=str)
parser.add_argument('--shuffled_dir', type=str)
parser.add_argument('--tag_suffix', type=str, default='.tag')
args = parser.parse_args()

nsaphra

Keybase proof

I hereby claim:

• I am nsaphra on github.
• I am nsaphra (https://keybase.io/nsaphra) on keybase.
• I have a public key ASCpyzsqtJYqR6IjSCnoPwSjrInpOg35MPypGR9l_pvTcQo

To claim this, I am signing this object:

nsaphra

def zipf(size, exponent):
    x = np.arange(size, dtype='float')
    pmf = (x ** exponent).reciprocal()
    pmf /= pmf.sum()
    return stats.rv_discrete(values=range(size), pmf)

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class NoughtsAndCrosses:
    NOUGHT = "O"
    CROSS = "X"
    EMPTY = " "

    STALEMATE = "Nobody"

    def __init__(self):
        self.board = [[self.EMPTY] * 3, [self.EMPTY] * 3, [self.EMPTY] * 3]

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#!/bin/bash

if [ "$TERM" != "screen" ]
then
    if type tmux >/dev/null 2>&1
    then
        tmux att || tmux \
            new -s tensorflow -n shell \; \
            neww -n notebook "source activate tensorflow; cd Documents/dynamic_curriculum; jupyter notebook" \; \
            neww -n dir  "cd Documents/dynamic_curriculum"

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type SyntaxNode
    label::AbstractString
    parent::SyntaxNode
    children::Array{SyntaxNode}

    # TODO No error handling when going up a level with undefined parent.
    SyntaxNode() = (
        x = new();
        x.label = "";
        x.children = [];

nsaphra

#!/usr/bin/python
from collections import defaultdict
import json
import os
import argparse
import gzip
import sys
import codecs
from time import asctime

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module SparsePy
# TODO this is only for CSC sparse matrix PyObjects and julia matrices.
#      Add other types when julia releases them?

require("PyCall")
using PyCall

export jlmat2pymat, pymat2jlmat

@pyimport scipy.sparse as pysparse