Hi,
I am trying to split an computation over two ops in order to avoid spurious
computations when computing the gradient.
My current attempt uses a first op which returns the desired result for the
forward part and extra intermediate results. The second op just forwards
the desired result, but its grad is overriden to compute the gradient based
on the intermediate results.
In this configuration, Theano complains about unused inputs in the forward
computation because the intermediate results are not used for the forward
method of the second op.
Is this an expected behaviour or a bug?
----
import numpy as np
import theano.tensor as T
import theano
def make_ops():
x_var = T.vector()
m_var = T.bvector()
r = m_var.sum().astype('floatX')
z = x_var * m_var / r
def grad_op1(inputs, output_gradients):
return [
output_gradients[0], # computation delegated to op2
theano.gradient.DisconnectedType()()
]
op1 = theano.OpFromGraph(
inputs=[x_var, m_var],
outputs=[z, r],
grad_overrides=grad_op1)
z_var = T.vector()
r_var = T.scalar()
def grad_op2(inputs, output_gradients):
_, m_, r_ = inputs
return [
m_ * r_,
theano.gradient.DisconnectedType()(),
theano.gradient.DisconnectedType()()
]
op2 = theano.OpFromGraph(
inputs=[z_var, m_var, r_var],
outputs=[z_var],
grad_overrides=grad_op2)
return op1, op2
op1, op2 = make_ops()
x_var = T.vector()
m_var = T.bvector()
z_, r = op1(x_var, m_var)
z = op2(z_, m_var, r)
print(z_.eval({x_var: np.array([1., .3, .0, .2], dtype=np.float32),
m_var: np.array([1, 0, 1, 1], dtype=np.int8)}))
f = theano.function([x_var, m_var], [z], on_unused_input='ignore') #
raises anyway
print(f(np.array([1., .3, .0, .2], dtype=np.float32),
np.array([1, 0, 1, 1], dtype=np.int8)))
# g = theano.grad(T.sum(z), wrt=x_var)
# print(g.eval({x_var: np.array([1., .3, .0, .2], dtype=np.float32),
# m_var: np.array([1, 0, 1, 1], dtype=np.int8)}))
--
---
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.
