Mercurial > pylearn

annotate embeddings/one-per-line.py @ 521:2bef0768bc27

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redirect to the good new source.
author Frederic Bastien <bastienf@iro.umontreal.ca>
date Fri, 14 Nov 2008 16:37:51 -0500
parents a07948f780b9
children
rev   line source
456
131e19dfe793 Added sandbox.embeddings
Joseph Turian <turian@iro.umontreal.ca>
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1 #!/usr/bin/python
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2
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Joseph Turian <turian@iro.umontreal.ca>
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3 import string
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4 #import psyco
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5
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Joseph Turian <turian@iro.umontreal.ca>
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6 weightsfile = "lm-weights.txt"
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Joseph Turian <turian@iro.umontreal.ca>
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7 vocabfile = "words.asc"
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Joseph Turian <turian@iro.umontreal.ca>
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8 size = 30000
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9 dimensions = 50
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10
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11 import numpy, math
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12 import sys
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13 from common.str import percent
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14
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Joseph Turian <turian@iro.umontreal.ca>
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15 word_to_vector = {}
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16
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17 f = open(weightsfile)
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18 f.readline()
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19 vals = [float(v) for v in string.split(f.readline())]
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20 assert len(vals) == size * dimensions
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21 vals.reverse()
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22 #for i in range(size):
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23 r = range(size)
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24 r.reverse()
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25 for i in r:
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26 l = vals[dimensions*i:dimensions*(i+1)]
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27 print string.join([`s` for s in l], "\t")