IfElse vs Switch#

  • Both ops build a condition over symbolic variables.

  • IfElse takes a boolean condition and two variables as inputs.

  • Switch takes a tensor as condition and two variables as inputs. switch is an elementwise operation and is thus more general than ifelse.

  • Whereas switch evaluates both output variables, ifelse is lazy and only evaluates one variable with respect to the condition.


from pytensor import tensor as pt
from pytensor.ifelse import ifelse
import pytensor, time, numpy

a,b = pt.scalars('a', 'b')
x,y = pt.matrices('x', 'y')

z_switch = pt.switch(, b), pt.mean(x), pt.mean(y))
z_lazy = ifelse(, b), pt.mean(x), pt.mean(y))

f_switch = pytensor.function([a, b, x, y], z_switch,
f_lazyifelse = pytensor.function([a, b, x, y], z_lazy,

val1 = 0.
val2 = 1.
big_mat1 = numpy.ones((10000, 1000))
big_mat2 = numpy.ones((10000, 1000))

n_times = 10

tic = time.perf_counter()
for i in range(n_times):
    f_switch(val1, val2, big_mat1, big_mat2)
print('time spent evaluating both values %f sec' % (time.perf_counter() - tic))

tic = time.perf_counter()
for i in range(n_times):
    f_lazyifelse(val1, val2, big_mat1, big_mat2)
print('time spent evaluating one value %f sec' % (time.perf_counter() - tic))

In this example, the IfElse op spends less time (about half as much) than Switch since it computes only one variable out of the two.

$ python
time spent evaluating both values 0.6700 sec
time spent evaluating one value 0.3500 sec

Unless linker='vm' or linker='cvm' are used, ifelse will compute both variables and take the same computation time as switch. Although the linker is not currently set by default to cvm, it will be in the near future.

There is no automatic rewrite replacing a switch with a broadcasted scalar to an ifelse, as this is not always faster. See this ticket.


If you use test values, then all branches of the IfElse will be computed. This is normal, as using test_value means everything will be computed when we build it, due to Python’s greedy evaluation and the semantic of test value. As we build both branches, they will be executed for test values. This doesn’t cause any changes during the execution of the compiled PyTensor function.