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comparison onehotop.py @ 356:18702ceb2096

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Added more functions
author Joseph Turian <turian@iro.umontreal.ca>
date Thu, 19 Jun 2008 16:18:37 -0400
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355:430c9e92cd23 356:18702ceb2096
1 """
2 One hot Op
3 """
4
5 #from theano import tensor
6 from theano.tensor import as_tensor, Tensor
7 from theano.gof import op
8 from theano.gof.graph import Apply
9
10 import numpy
11
12 class OneHot(op.Op):
13 """
14 Construct a one-hot vector, x out of y.
15
16 @todo: Document inputs and outputs
17 @todo: Use 'bool' as output dtype? Or, at least 'int64' ? Not float64!
18 @todo: Use 'bool' as output dtype, not 'int64' ?
19 @todo: Allow this to operate on column vectors (Tensor)
20 @todo: Describe better.
21 """
22
23 def make_node(self, x, y):
24 """
25 @type x: Vector L{Tensor} of integers
26 @param x: The entries of the one-hot vector to be one.
27 @type y: Integer scalar L{Tensor}
28 @param y: The length (#columns) of the one-hot vectors.
29 @return: A L{Tensor} of one-hot vectors
30
31 @precondition: x < y for all entries of x
32 @todo: Check that x and y are int types
33 """
34 x = as_tensor(x)
35 y = as_tensor(y)
36 #assert x.dtype[0:3] == "int"
37 #assert y.dtype[0:3] == "int"
38 inputs = [x, y]
39 ##outputs = [tensor.Tensor("int64", broadcastable=[False, False])]
40 #outputs = [tensor.Tensor("float64", broadcastable=[False, False])]
41 #outputs = [Tensor("int64", broadcastable=[False, False])]
42 outputs = [Tensor("float64", broadcastable=[False, False]).make_result()]
43 node = Apply(op = self, inputs = inputs, outputs = outputs)
44 return node
45
46 def perform(self, node, (x, y), (out, )):
47 assert x.dtype == "int64" or x.dtype == "int32"
48 assert x.ndim == 1
49 assert y.dtype == "int64" or x.dtype == "int32"
50 assert y.ndim == 0
51 out[0] = numpy.zeros((x.shape[0], y), dtype="float64")
52 for c in range(x.shape[0]):
53 assert x[c] < y
54 out[0][c, x[c]] = 1
55
56 def grad(self, (x, y), (out_gradient, )):
57 return None, None
58 one_hot = OneHot()