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Fix pfft gradients #34

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Dec 22, 2024
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2 changes: 1 addition & 1 deletion pyproject.toml
Original file line number Diff line number Diff line change
Expand Up @@ -11,7 +11,7 @@ readme = "README.md"
requires-python = ">=3.9"
license = { file = "LICENSE" }
urls = { "Homepage" = "https://github.com/DifferentiableUniverseInitiative/JaxPM" }
dependencies = ["jax_cosmo", "jax>=0.4.30", "jaxdecomp>=0.2.2"]
dependencies = ["jax_cosmo", "jax>=0.4.35", "jaxdecomp>=0.2.3"]

[tool.setuptools]
packages = ["jaxpm"]
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87 changes: 87 additions & 0 deletions tests/test_gradients.py
Original file line number Diff line number Diff line change
@@ -0,0 +1,87 @@
import jax
import pytest
from diffrax import (BacksolveAdjoint, Dopri5, ODETerm, PIDController,
RecursiveCheckpointAdjoint, SaveAt, diffeqsolve)
from helpers import MSE
from jax import numpy as jnp

from jaxpm.distributed import uniform_particles
from jaxpm.painting import cic_paint, cic_paint_dx
from jaxpm.pm import lpt, make_diffrax_ode


@pytest.mark.single_device
@pytest.mark.parametrize("order", [1, 2])
@pytest.mark.parametrize("absolute_painting", [True, False])
@pytest.mark.parametrize("adjoint", ['DTO', 'OTD'])
def test_nbody_grad(simulation_config, initial_conditions, lpt_scale_factor,
nbody_from_lpt1, nbody_from_lpt2, cosmo, order,
absolute_painting, adjoint):

mesh_shape, _ = simulation_config
cosmo._workspace = {}

if adjoint == 'OTD':
pytest.skip("OTD adjoint not implemented yet (needs PFFT3D JVP)")

adjoint = RecursiveCheckpointAdjoint(
) if adjoint == 'DTO' else BacksolveAdjoint(solver=Dopri5())

@jax.jit
@jax.grad
def forward_model(initial_conditions, cosmo):

# Initial displacement
if absolute_painting:
particles = uniform_particles(mesh_shape)
dx, p, _ = lpt(cosmo,
initial_conditions,
particles,
a=lpt_scale_factor,
order=order)
ode_fn = ODETerm(make_diffrax_ode(cosmo, mesh_shape))
y0 = jnp.stack([particles + dx, p])

else:
dx, p, _ = lpt(cosmo,
initial_conditions,
a=lpt_scale_factor,
order=order)
ode_fn = ODETerm(
make_diffrax_ode(cosmo, mesh_shape, paint_absolute_pos=False))
y0 = jnp.stack([dx, p])

solver = Dopri5()
controller = PIDController(rtol=1e-7,
atol=1e-7,
pcoeff=0.4,
icoeff=1,
dcoeff=0)

saveat = SaveAt(t1=True)

solutions = diffeqsolve(ode_fn,
solver,
t0=lpt_scale_factor,
t1=1.0,
dt0=None,
y0=y0,
adjoint=adjoint,
stepsize_controller=controller,
saveat=saveat)

if absolute_painting:
final_field = cic_paint(jnp.zeros(mesh_shape), solutions.ys[-1, 0])
else:
final_field = cic_paint_dx(solutions.ys[-1, 0])

return MSE(final_field,
nbody_from_lpt1 if order == 1 else nbody_from_lpt2)

bad_initial_conditions = initial_conditions + jax.random.normal(
jax.random.PRNGKey(0), initial_conditions.shape) * 0.5
best_ic = forward_model(initial_conditions, cosmo)
bad_ic = forward_model(bad_initial_conditions, cosmo)

assert jnp.max(best_ic) < 1e-5
assert jnp.max(bad_ic) > 1e-5
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