I have two [X,] matrices where X is some number, and I'd like to make a
loss function that will obtain their Pearson correlation.
Code:
def corr(a,b):
c = np.cov(a, b)
d = np.diag(c)
stddev = np.sqrt(d.real)
c /= stddev[:, None]
c /= stddev[None, :]
return c
x= T.matrix() #some input
y= T.matrix() #one of the two matrices
loss = lasagne.layers.get_output([outputlayer], 1) #output from simple mlp
loss = corr(loss,y)[0][1]
loss = loss.mean()
nnparameters = lasagne.layers.get_all_params([outputlayer], trainable=True)
#parameters from simple mlp
grads = T.grad(loss, nnparameters)
I get this error when I try to obtain grads:
Traceback (most recent call last):
File "<ipython-input-232-36dcc0f0d1d5>", line 1, in <module>
grads = T.grad(loss, nnparameters)
File "/usr/local/lib/python2.7/dist-packages/theano/gradient.py", line
549, in grad
grad_dict, wrt, cost_name)
File "/usr/local/lib/python2.7/dist-packages/theano/gradient.py", line
1312, in _populate_grad_dict
rval = [access_grad_cache(elem) for elem in wrt]
File "/usr/local/lib/python2.7/dist-packages/theano/gradient.py", line
1267, in access_grad_cache
term = access_term_cache(node)[idx]
File "/usr/local/lib/python2.7/dist-packages/theano/gradient.py", line
961, in access_term_cache
output_grads = [access_grad_cache(var) for var in node.outputs]
File "/usr/local/lib/python2.7/dist-packages/theano/gradient.py", line
1267, in access_grad_cache
term = access_term_cache(node)[idx]
File "/usr/local/lib/python2.7/dist-packages/theano/gradient.py", line
961, in access_term_cache
output_grads = [access_grad_cache(var) for var in node.outputs]
File "/usr/local/lib/python2.7/dist-packages/theano/gradient.py", line
1267, in access_grad_cache
term = access_term_cache(node)[idx]
File "/usr/local/lib/python2.7/dist-packages/theano/gradient.py", line
961, in access_term_cache
output_grads = [access_grad_cache(var) for var in node.outputs]
File "/usr/local/lib/python2.7/dist-packages/theano/gradient.py", line
1267, in access_grad_cache
term = access_term_cache(node)[idx]
File "/usr/local/lib/python2.7/dist-packages/theano/gradient.py", line
961, in access_term_cache
output_grads = [access_grad_cache(var) for var in node.outputs]
File "/usr/local/lib/python2.7/dist-packages/theano/gradient.py", line
1267, in access_grad_cache
term = access_term_cache(node)[idx]
File "/usr/local/lib/python2.7/dist-packages/theano/gradient.py", line
1101, in access_term_cache
input_grads = node.op.grad(inputs, new_output_grads)
File "/usr/local/lib/python2.7/dist-packages/theano/tensor/elemwise.py",
line 698, in grad
rval = self._bgrad(inputs, ograds)
File "/usr/local/lib/python2.7/dist-packages/theano/tensor/elemwise.py",
line 773, in _bgrad
scalar_igrads = self.scalar_op.grad(scalar_inputs, scalar_ograds)
File "/usr/local/lib/python2.7/dist-packages/theano/scalar/basic.py",
line 908, in grad
self.__class__.__name__)
MethodNotDefined: ('grad', <class 'theano.scalar.basic.Conj'>, 'Conj')
Would anyone know how to solve this error?
Thanks
--
---
You received this message because you are subscribed to the Google Groups
"theano-users" group.
To unsubscribe from this group and stop receiving emails from it, send an email
to [email protected].
For more options, visit https://groups.google.com/d/optout.
