Hi,
I would like to use pytensor.scan
to ‘loop’ over two dimensions of a matrix separately. How can this best be done?
I seem to run into errors when I try to do it, but I also don’t fully understand how scan works.
Thank you for your help!
Hi,
I would like to use pytensor.scan
to ‘loop’ over two dimensions of a matrix separately. How can this best be done?
I seem to run into errors when I try to do it, but I also don’t fully understand how scan works.
Thank you for your help!
Can you show what you’ve tried so far?
Yes,
for now I was just trying to loop over a function and store the result in a separate variable:
def function(x,y):
return 2*x + y
def multi_loop():
result_inner, _ = pytensor.scan(fn=function, sequences=[x], non_sequences=[y])
y = result_inner[-1]
return y
result_outer, _ = pytensor.scan(fn=multi_loop, sequences = [pt.arange(10)])
result_final = result_outer
This is a simplified version to show what I am trying to do. When running this I get an error saying TypeError: TensorType does not support iteration. Maybe you are using builtins.sum instead of pytensor.tensor.math.sum? (Maybe .max?)
I think the issue is how I have set up the outer loop. The inner one runs fine on its own.
Any help is highly appreciated
Shouldn’t your outer sequences be 2-dimensional?
Yes, true, but even then I get the same error
Your code as posted doesn’t raise any errors, though I had to make some small changes to your functions:
import pytensor
import pytensor.tensor as pt
def function(x,y):
return 2*x + y
def multi_loop(x, y):
result_inner, _ = pytensor.scan(fn=function, sequences=[x], non_sequences=[y])
y = result_inner[-1]
return y
x,y = pt.matrices('x', 'y')
result_outer, _ = pytensor.scan(fn=multi_loop, non_sequences=[x, y], n_steps=10)
result_outer.eval({x:np.eye(3), y:np.eye(3)})
Can you post a complete example that raises the error you’re encountering?