In [1]:

    

import numpy as np
import theano
import theano.tensor as T


    

In [3]:

    

x = T.dscalar("x")
y = T.dscalar("y")

f = theano.function([x, y], x ** 2 + y ** 2)

f(0, 0)


    

    
Out[3]:





array(0.0)

In [285]:

    

e = np.array([[0, 0, 0], [1, 1, 1], [1, 0, 1], [1, 0, 0], [0, 1, 0], [0, 0, 1], [0, -1, 1]], dtype=float)
s = 0.05
n_ = np.array([1, 1, 1])
n_ = n_ / np.sqrt((n_ ** n_).sum())
(n_ * n_).sum()

print e


    

    




[[ 0.  0.  0.]
 [ 1.  1.  1.]
 [ 1.  0.  1.]
 [ 1.  0.  0.]
 [ 0.  1.  0.]
 [ 0.  0.  1.]
 [ 0. -1.  1.]]

In [312]:

    

event = theano.shared(e, "event")

theta = T.dvector("theta")
phi = T.dvector("phi")

nx = T.cos(theta)
ny = T.sin(theta) * T.sin(phi)
nz = T.sin(theta) * T.cos(phi)

n = T.stack(nx, ny, nz).T
sigma = theano.shared(0.05, 'sigma')

scalar = T.dot(event, n.T)
project = event - T.tensordot(scalar, n, axes=([], []))
delta_sq = T.sum(project * project, axis=1)
r = T.sum(T.exp(-delta_sq / sigma))

#rr_hess = theano.gradient.hessian(r, [theta, phi])

rr = theano.function([phi, theta], project)


    

In [313]:

    

rr([0.0, 0.1], [0.0, 0.1])


    

    




---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-313-87f74a7df956> in <module>()
----> 1 rr([0.0, 0.1], [0.0, 0.1])

/home/mborisyak/opt/anaconda/lib/python2.7/site-packages/theano/compile/function_module.pyc in __call__(self, *args, **kwargs)
    604                         self.fn.nodes[self.fn.position_of_error],
    605                         self.fn.thunks[self.fn.position_of_error],
--> 606                         storage_map=self.fn.storage_map)
    607                 else:
    608                     # For the c linker We don't have access from

/home/mborisyak/opt/anaconda/lib/python2.7/site-packages/theano/compile/function_module.pyc in __call__(self, *args, **kwargs)
    593         t0_fn = time.time()
    594         try:
--> 595             outputs = self.fn()
    596         except Exception:
    597             if hasattr(self.fn, 'position_of_error'):

ValueError: Input dimension mis-match. (input[0].shape[2] = 7, input[1].shape[2] = 2)
Apply node that caused the error: Elemwise{Sub}[(0, 1)](InplaceDimShuffle{x,x,0,1}.0, Reshape{4}.0)
Inputs types: [TensorType(float64, (True, True, False, False)), TensorType(float64, 4D)]
Inputs shapes: [(1, 1, 7, 3), (7, 2, 2, 3)]
Inputs strides: [(168, 168, 24, 8), (96, 48, 24, 8)]
Inputs values: ['not shown', 'not shown']

HINT: Re-running with most Theano optimization disabled could give you a back-trace of when this node was created. This can be done with by setting the Theano flag 'optimizer=fast_compile'. If that does not work, Theano optimizations can be disabled with 'optimizer=None'.
HINT: Use the Theano flag 'exception_verbosity=high' for a debugprint and storage map footprint of this apply node.

In [255]:

    

s(1, 2)


    

    
Out[255]:





array([[ 1.,  2.]])

In [190]:

    

event.set_value(np.ones((3,2)))


    

In [191]:

    

event.get_value()


    

    
Out[191]:





array([[ 1.,  1.],
       [ 1.,  1.],
       [ 1.,  1.]])

In [217]:

    

x = T.dmatrix("x")
a = theano.shared(1.0, "a")

y = T.sum((x - a) ** 2)

dy = theano.function([x], theano.gradient.hessian(y, x))


    

    




---------------------------------------------------------------------------
AssertionError                            Traceback (most recent call last)
<ipython-input-217-093ca51eb4ee> in <module>()
      4 y = T.sum((x - a) ** 2)
      5 
----> 6 dy = theano.function([x], theano.gradient.hessian(y, x))

/home/mborisyak/opt/anaconda/lib/python2.7/site-packages/theano/gradient.pyc in hessian(cost, wrt, consider_constant, disconnected_inputs)
   1826                 "tensor.hessian expects a (list of) Variable as `wrt`"
   1827         assert input.ndim == 1, \
-> 1828                 "tensor.hessian expects a (list of) 1 dimensional variable "\
   1829                 "as `wrt`"
   1830         expr = grad(cost, input, consider_constant=consider_constant,

AssertionError: tensor.hessian expects a (list of) 1 dimensional variable as `wrt`

In [215]:

    

from theano import pp


    

In [216]:

    

pp(dy.maker.fgraph.outputs[0])


    

    
Out[216]:





'for{cpu,scan_fn}(Shape_i{0}(x), Constant{1}[int64:int64:int8], Shape_i{0}(x), Elemwise{Composite{(i0 * (i1 - i2))}}(TensorConstant{(1,) of 2.0}, x, a), alloc(TensorConstant{(1,) of 0.0}, Shape_i{0}(x)), alloc(TensorConstant{1.0}, Shape_i{0}(x)), alloc(TensorConstant{(1,) of 2.0}, Shape_i{0}(x)))'

In [ ]: