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test_constraints.py
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test_constraints.py
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# Copyright Contributors to the Pyro project.
# SPDX-License-Identifier: Apache-2.0
from collections import namedtuple
import pytest
from jax import jit, tree_map, vmap
import jax.numpy as jnp
from numpyro.distributions import constraints
SINGLETON_CONSTRAINTS = {
"boolean": constraints.boolean,
"circular": constraints.circular,
"corr_cholesky": constraints.corr_cholesky,
"corr_matrix": constraints.corr_matrix,
"l1_ball": constraints.l1_ball,
"lower_cholesky": constraints.lower_cholesky,
"scaled_unit_lower_cholesky": constraints.scaled_unit_lower_cholesky,
"nonnegative_integer": constraints.nonnegative_integer,
"ordered_vector": constraints.ordered_vector,
"positive": constraints.positive,
"positive_definite": constraints.positive_definite,
"positive_integer": constraints.positive_integer,
"positive_ordered_vector": constraints.positive_ordered_vector,
"real": constraints.real,
"real_vector": constraints.real_vector,
"real_matrix": constraints.real_matrix,
"simplex": constraints.simplex,
"softplus_lower_cholesky": constraints.softplus_lower_cholesky,
"softplus_positive": constraints.softplus_positive,
"sphere": constraints.sphere,
"unit_interval": constraints.unit_interval,
}
_a = jnp.asarray
class T(namedtuple("TestCase", ["constraint_cls", "params", "kwargs"])):
pass
PARAMETRIZED_CONSTRAINTS = {
"dependent": T(
type(constraints.dependent), (), dict(is_discrete=True, event_dim=2)
),
"greater_than": T(constraints.greater_than, (_a(0.0),), dict()),
"less_than": T(constraints.less_than, (_a(-1.0),), dict()),
"independent": T(
constraints.independent,
(constraints.greater_than(jnp.zeros((2,))),),
dict(reinterpreted_batch_ndims=1),
),
"integer_interval": T(constraints.integer_interval, (_a(-1), _a(1)), dict()),
"integer_greater_than": T(constraints.integer_greater_than, (_a(1),), dict()),
"interval": T(constraints.interval, (_a(-1.0), _a(1.0)), dict()),
"multinomial": T(
constraints.multinomial,
(_a(1.0),),
dict(),
),
"open_interval": T(constraints.open_interval, (_a(-1.0), _a(1.0)), dict()),
}
# TODO: BijectorConstraint
@pytest.mark.parametrize(
"constraint", SINGLETON_CONSTRAINTS.values(), ids=SINGLETON_CONSTRAINTS.keys()
)
def test_singleton_constraint_pytree(constraint):
# test that singleton constraints objects can be used as pytrees
def in_cst(constraint, x):
return x**2
def out_cst(constraint, x):
return constraint
jitted_in_cst = jit(in_cst)
jitted_out_cst = jit(out_cst)
assert jitted_in_cst(constraint, 1.0) == 1.0
assert jitted_out_cst(constraint, 1.0) == constraint
assert jnp.allclose(
vmap(in_cst, in_axes=(None, 0), out_axes=0)(constraint, jnp.ones(3)),
jnp.ones(3),
)
assert (
vmap(out_cst, in_axes=(None, 0), out_axes=None)(constraint, jnp.ones(3))
is constraint
)
@pytest.mark.parametrize(
"cls, cst_args, cst_kwargs",
PARAMETRIZED_CONSTRAINTS.values(),
ids=PARAMETRIZED_CONSTRAINTS.keys(),
)
def test_parametrized_constraint_pytree(cls, cst_args, cst_kwargs):
constraint = cls(*cst_args, **cst_kwargs)
# test that singleton constraints objects can be used as pytrees
def in_cst(constraint, x):
return x**2
def out_cst(constraint, x):
return constraint
jitted_in_cst = jit(in_cst)
jitted_out_cst = jit(out_cst)
assert jitted_in_cst(constraint, 1.0) == 1.0
assert jitted_out_cst(constraint, 1.0) == constraint
assert jnp.allclose(
vmap(in_cst, in_axes=(None, 0), out_axes=0)(constraint, jnp.ones(3)),
jnp.ones(3),
)
assert (
vmap(out_cst, in_axes=(None, 0), out_axes=None)(constraint, jnp.ones(3))
== constraint
)
if len(cst_args) > 0:
# test creating and manipulating vmapped constraints
vmapped_cst_args = tree_map(lambda x: x[None], cst_args)
vmapped_csts = jit(vmap(lambda args: cls(*args, **cst_kwargs), in_axes=(0,)))(
vmapped_cst_args
)
assert vmap(lambda x: x == constraint, in_axes=0)(vmapped_csts).all()
twice_vmapped_cst_args = tree_map(lambda x: x[None], vmapped_cst_args)
vmapped_csts = jit(
vmap(
vmap(lambda args: cls(*args, **cst_kwargs), in_axes=(0,)),
in_axes=(0,),
),
)(twice_vmapped_cst_args)
assert vmap(vmap(lambda x: x == constraint, in_axes=0), in_axes=0)(
vmapped_csts
).all()
@pytest.mark.parametrize(
"cls, cst_args, cst_kwargs",
PARAMETRIZED_CONSTRAINTS.values(),
ids=PARAMETRIZED_CONSTRAINTS.keys(),
)
def test_parametrized_constraint_eq(cls, cst_args, cst_kwargs):
constraint = cls(*cst_args, **cst_kwargs)
constraint2 = cls(*cst_args, **cst_kwargs)
assert constraint == constraint2
assert constraint != 1
# check that equality checks are robust to constraints parametrized
# by abstract values
@jit
def check_constraints(c1, c2):
return c1 == c2
assert check_constraints(constraint, constraint2)
@pytest.mark.parametrize(
"constraint", SINGLETON_CONSTRAINTS.values(), ids=SINGLETON_CONSTRAINTS.keys()
)
def test_singleton_constraint_eq(constraint):
assert constraint == constraint
assert constraint != 1
# check that equality checks are robust to constraints parametrized
# by abstract values
@jit
def check_constraints(c1, c2):
return c1 == c2
assert check_constraints(constraint, constraint)