def test_tensordot_reshape():
'''Test that the tensordot implementation using dimshuffle, reshape and dot
gives the same results as the default (numpy) version'''
# define some tensors
a = numpy.arange(20, dtype=theano.config.floatX) / 20.0
b = numpy.arange(10, dtype=theano.config.floatX) / 10.0
c = numpy.arange(5, dtype=theano.config.floatX) / 5.0
d = numpy.arange(8, dtype=theano.config.floatX) / 8.0
tensor1 = numpy.tensordot(a, numpy.tensordot(b, numpy.tensordot(c, d, 0), 0), 0)
tensor2 = numpy.tensordot(c, numpy.tensordot(d, a, 0), 0)
tensor3 = tensor2.swapaxes(1, 2).swapaxes(0, 2) # d, a, c
x = T.tensor4('x')
y = T.tensor3('y')
# case 1: number of axes to sum over
default1 = theano.function([x,y], T.tensordot(x, y, 2))(tensor1, tensor2)
reshape1 = theano.function([x,y], B.tensordot(x, y, 2))(tensor1, tensor2)
assert numpy.allclose(default1, reshape1)
# case 2: axis pairs
default2 = theano.function([x,y], T.tensordot(x, y, axes=[(0, 3), (1, 0)]))(tensor1, tensor3)
reshape2 = theano.function([x,y], B.tensordot(x, y, axes=[(0, 3), (1, 0)]))(tensor1, tensor3)
assert numpy.allclose(default2, reshape2)
default3 = theano.function([x,y], T.tensordot(x, y, axes=[(0, 3, 2), (1, 0, 2)]))(tensor1, tensor3)
reshape3 = theano.function([x,y], B.tensordot(x, y, axes=[(0, 3, 2), (1, 0, 2)]))(tensor1, tensor3)
assert numpy.allclose(default3, reshape3)
def test1(self):
# define some tensors
tensor1 = self.rng.rand(20, 10, 5, 8).astype(theano.config.floatX)
tensor2 = self.rng.rand(5, 8, 20).astype(theano.config.floatX)
tensor3 = self.rng.rand(8, 20, 5).astype(theano.config.floatX)
x = T.tensor4("x")
y = T.tensor3("y")
# case 1: number of axes to sum over
default1 = theano.function([x, y], T.tensordot(x, y, 2))(tensor1, tensor2)
reshape1 = theano.function([x, y], B.tensordot(x, y, 2))(tensor1, tensor2)
assert numpy.allclose(default1, reshape1)
# case 2: axis pairs
default2 = theano.function([x, y], T.tensordot(x, y, axes=[(0, 3), (1, 0)]))(tensor1, tensor3)
reshape2 = theano.function([x, y], B.tensordot(x, y, axes=[(0, 3), (1, 0)]))(tensor1, tensor3)
assert numpy.allclose(default2, reshape2)
default3 = theano.function([x, y], T.tensordot(x, y, axes=[(0, 3, 2), (1, 0, 2)]))(tensor1, tensor3)
reshape3 = theano.function([x, y], B.tensordot(x, y, axes=[(0, 3, 2), (1, 0, 2)]))(tensor1, tensor3)
assert numpy.allclose(default3, reshape3)
def test1(self):
# define some tensors
tensor1 = self.rng.rand(20, 10, 5, 8).astype(theano.config.floatX)
tensor2 = self.rng.rand(5, 8, 20).astype(theano.config.floatX)
tensor3 = self.rng.rand(8, 20, 5).astype(theano.config.floatX)
x = T.tensor4('x')
y = T.tensor3('y')
# case 1: number of axes to sum over
default1 = theano.function([x, y], T.tensordot(x, y, 2))(
tensor1, tensor2)
reshape1 = theano.function([x, y], B.tensordot(x, y, 2))(
tensor1, tensor2)
assert numpy.allclose(default1, reshape1)
# case 2: axis pairs
default2 = theano.function(
[x, y],
T.tensordot(x, y, axes=[(0, 3), (1, 0)])
)(tensor1, tensor3)
reshape2 = theano.function(
[x, y],
B.tensordot(x, y, axes=[(0, 3), (1, 0)])
)(tensor1, tensor3)
assert numpy.allclose(default2, reshape2)
default3 = theano.function(
[x, y],
T.tensordot(x, y, axes=[(0, 3, 2), (1, 0, 2)])
)(tensor1, tensor3)
reshape3 = theano.function(
[x, y],
B.tensordot(x, y, axes=[(0, 3, 2), (1, 0, 2)])
)(tensor1, tensor3)
assert numpy.allclose(default3, reshape3)
