Some minor fixes
This commit is contained in:
Deaglan Bartlett
parent
42be9de326
commit
2016ef0599
11 changed files with 460 additions and 31 deletions
|
|
@ -1,2 +1,3 @@
|
|||
# mgborg_emulator
|
||||
|
||||
bash build.sh --c-compiler icx --cxx-compiler icpx --python=/home/bartlett//anaconda3/envs/borg_env/bin/python3 --hades-python --with-mpi --install-system-python --build-dir /data101/bartlett/build_borg
|
||||
|
|
@ -37,6 +37,7 @@ mixing = 1
|
|||
[model]
|
||||
gravity = lpt
|
||||
logfR0 = -5.0
|
||||
gauss_sigma = 0.05
|
||||
af = 1.0
|
||||
ai = 0.05
|
||||
|
||||
|
|
@ -65,11 +66,14 @@ z0 = 0
|
|||
|
||||
[emulator]
|
||||
use_emulator = True
|
||||
model_weights_path = /home/bartlett/mgborg_emulator/weights/emulator_weights.file_type
|
||||
model_weights_path = /home/bartlett/mgborg_emulator/weights/d2d_borg.pt
|
||||
architecture = StyledVNet
|
||||
use_float64 = False
|
||||
use_pad_and_NN = True
|
||||
requires_grad = False
|
||||
style_size = 1
|
||||
in_chan = 3
|
||||
out_chan = 3
|
||||
|
||||
[run]
|
||||
run_type = mock
|
||||
|
|
|
|||
|
|
@ -4,7 +4,8 @@ import numpy as np
|
|||
|
||||
# Emulator imports
|
||||
import torch
|
||||
# from .model_architecture.cosmology import *
|
||||
torch.cuda.empty_cache()
|
||||
|
||||
from networks import StyledVNet, StyledVNet_distill
|
||||
|
||||
# JAX set-up
|
||||
|
|
@ -16,6 +17,7 @@ from jax.config import config as jax_config
|
|||
jax_config.update("jax_enable_x64", True)
|
||||
|
||||
from utils import myprint
|
||||
import utils
|
||||
|
||||
class Emulator(borg.forward.BaseForwardModel):
|
||||
|
||||
|
|
@ -85,7 +87,7 @@ class Emulator(borg.forward.BaseForwardModel):
|
|||
# Step 2 - correct for particles that moved over the periodic boundary
|
||||
if self.debug:
|
||||
start_time = time.time()
|
||||
disp_temp = correct_displacement_over_periodic_boundaries(disp,L=self.box.L[0],max_disp_1d=self.box.L[0]//2)
|
||||
disp_temp = utils.correct_displacement_over_periodic_boundaries(disp,L=self.box.L[0],max_disp_1d=self.box.L[0]//2)
|
||||
if self.debug:
|
||||
myprint("Step 2 of forward pass took %s seconds" % (time.time() - start_time))
|
||||
|
||||
|
|
@ -102,7 +104,7 @@ class Emulator(borg.forward.BaseForwardModel):
|
|||
# Step 4 - normalize
|
||||
if self.debug:
|
||||
start_time = time.time()
|
||||
dis(dis_in)
|
||||
utils.dis(dis_in)
|
||||
if self.debug:
|
||||
myprint("Step 4 of forward pass took %s seconds" % (time.time() - start_time))
|
||||
|
||||
|
|
@ -162,7 +164,7 @@ class Emulator(borg.forward.BaseForwardModel):
|
|||
# Step 9 - undo the normalization
|
||||
if self.debug:
|
||||
start_time = time.time()
|
||||
dis(dis_out,undo=True)
|
||||
utils.dis(dis_out,undo=True)
|
||||
if self.debug:
|
||||
self.dis_out = dis_out
|
||||
myprint("Step 9 of forward pass took %s seconds" % (time.time() - start_time))
|
||||
|
|
@ -227,7 +229,7 @@ class Emulator(borg.forward.BaseForwardModel):
|
|||
# reverse step 9
|
||||
if self.debug:
|
||||
start_time = time.time()
|
||||
dis(ag,undo=False)
|
||||
utils.dis(ag,undo=False)
|
||||
if self.debug:
|
||||
myprint("Reverse step 9 took %s seconds" % (time.time() - start_time))
|
||||
|
||||
|
|
@ -274,7 +276,7 @@ class Emulator(borg.forward.BaseForwardModel):
|
|||
# reverse step 4
|
||||
if self.debug:
|
||||
start_time = time.time()
|
||||
dis(ag,undo=True)
|
||||
utils.dis(ag,undo=True)
|
||||
if self.debug:
|
||||
myprint("Reverse step 4 took %s seconds" % (time.time() - start_time))
|
||||
|
||||
|
|
@ -314,9 +316,9 @@ class Emulator(borg.forward.BaseForwardModel):
|
|||
y = y * Ny / Ly
|
||||
z = z * Nz / Lz
|
||||
|
||||
qx, ix = get_cell_coord(x)
|
||||
qy, iy = get_cell_coord(y)
|
||||
qz, iz = get_cell_coord(z)
|
||||
qx, ix = utils.get_cell_coord(x)
|
||||
qy, iy = utils.get_cell_coord(y)
|
||||
qz, iz = utils.get_cell_coord(z)
|
||||
|
||||
ix = ix.astype(int)
|
||||
iy = iy.astype(int)
|
||||
|
|
@ -352,9 +354,9 @@ class Emulator(borg.forward.BaseForwardModel):
|
|||
y = y * Ny / Ly
|
||||
z = z * Nz / Lz
|
||||
|
||||
qx, ix = get_cell_coord(x)
|
||||
qy, iy = get_cell_coord(y)
|
||||
qz, iz = get_cell_coord(z)
|
||||
qx, ix = utils.get_cell_coord(x)
|
||||
qy, iy = utils.get_cell_coord(y)
|
||||
qz, iz = utils.get_cell_coord(z)
|
||||
|
||||
ix = ix.astype(int)
|
||||
iy = iy.astype(int)
|
||||
|
|
|
|||
|
|
@ -7,9 +7,10 @@ import symbolic_pofk.linear
|
|||
import jax
|
||||
from functools import partial
|
||||
import ast
|
||||
import torch
|
||||
|
||||
import utils as utils
|
||||
from utils import myprint
|
||||
from utils import myprint, initial_pos
|
||||
import forwards
|
||||
import networks
|
||||
|
||||
|
|
@ -56,7 +57,7 @@ class GaussianLikelihood(borg.likelihood.BaseLikelihood):
|
|||
|
||||
# Initialise model parameters
|
||||
model_params = {
|
||||
'logfR0':float(config['model']['logfr0'])
|
||||
'logfR0':float(config['model']['logfr0']),
|
||||
'gauss_sigma':float(config['model']['gauss_sigma'])
|
||||
}
|
||||
self.fwd_param.setModelParams(model_params)
|
||||
|
|
@ -134,7 +135,12 @@ class GaussianLikelihood(borg.likelihood.BaseLikelihood):
|
|||
if self.run_type == 'data':
|
||||
raise NotImplementedError
|
||||
elif self.run_type == 'mock':
|
||||
raise NotImplementedError
|
||||
output_density = np.zeros(self.fwd.getOutputBoxModel().N)
|
||||
self.fwd.forwardModel_v2(s_hat)
|
||||
self.fwd.getDensityFinal(output_density)
|
||||
state["BORG_final_density"][:] = output_density
|
||||
output_density += np.random.normal(size=self.fwd.getOutputBoxModel().N) * self.getModelParam('nullforward', 'gauss_sigma')
|
||||
state["mock"][:] = output_density
|
||||
else:
|
||||
raise NotImplementedError
|
||||
|
||||
|
|
@ -179,9 +185,6 @@ class GaussianLikelihood(borg.likelihood.BaseLikelihood):
|
|||
output_density = np.zeros((N,N,N))
|
||||
self.fwd.forwardModel_v2(s_hat)
|
||||
self.fwd.getDensityFinal(output_density)
|
||||
|
||||
# Get velocity field
|
||||
output_velocity = self.fwd_vel.getVelocityField()
|
||||
|
||||
self.delta = output_density
|
||||
self.vel = output_velocity
|
||||
|
|
@ -219,7 +222,7 @@ class GaussianLikelihood(borg.likelihood.BaseLikelihood):
|
|||
self.fwd.adjointModel_v2(mygradient)
|
||||
mygrad_hat = np.zeros(s_hat.shape, dtype=np.complex128)
|
||||
self.fwd.getAdjointModel(mygrad_hat)
|
||||
elf.fwd.clearAdjointGradient()
|
||||
self.fwd.clearAdjointGradient()
|
||||
|
||||
return mygrad_hat
|
||||
|
||||
|
|
@ -263,6 +266,10 @@ def build_gravity_model(state: borg.likelihood.MarkovState, box: borg.forward.Bo
|
|||
config.read(ini_file)
|
||||
ai = float(config['model']['ai'])
|
||||
af = float(config['model']['af'])
|
||||
|
||||
# Setup forward model
|
||||
chain = borg.forward.ChainForwardModel(box)
|
||||
chain.addModel(borg.forward.models.HermiticEnforcer(box))
|
||||
|
||||
# Cosmological parameters
|
||||
if ini_file is None:
|
||||
|
|
@ -270,10 +277,6 @@ def build_gravity_model(state: borg.likelihood.MarkovState, box: borg.forward.Bo
|
|||
else:
|
||||
cpar = utils.get_cosmopar(ini_file)
|
||||
chain.setCosmoParams(cpar)
|
||||
|
||||
# Setup forward model
|
||||
chain = borg.forward.ChainForwardModel(box)
|
||||
chain.addModel(borg.forward.models.HermiticEnforcer(box))
|
||||
|
||||
# CLASS transfer function
|
||||
chain @= borg.forward.model_lib.M_PRIMORDIAL_AS(box)
|
||||
|
|
@ -322,10 +325,7 @@ def build_gravity_model(state: borg.likelihood.MarkovState, box: borg.forward.Bo
|
|||
|
||||
# Initialize model
|
||||
model = getattr(networks, config['emulator']['architecture'])
|
||||
# if use_distilled:
|
||||
# model = networks.StyledVNet_distill(1,3,3,num_filt=num_filt)
|
||||
# else:
|
||||
# model = networks.StyledVNet(1,3,3)
|
||||
model = model(int(config['emulator']['style_size']), int(config['emulator']['in_chan']), int(config['emulator']['out_chan']))
|
||||
model.load_state_dict(emu_weights['model'])
|
||||
|
||||
use_float64 = config['emulator']['use_float64'].lower().strip() == 'true'
|
||||
|
|
@ -505,7 +505,7 @@ def build_likelihood(state: borg.likelihood.MarkovState, info: borg.likelihood.L
|
|||
myprint("Building likelihood")
|
||||
myprint(chain.getCosmoParams())
|
||||
boxm = chain.getBoxModel()
|
||||
likelihood = VelocityBORGLikelihood(chain, fwd_param, fwd_vel, borg.getIniConfigurationFilename())
|
||||
likelihood = VelocityBORGLikelihood(chain, fwd_param, borg.getIniConfigurationFilename())
|
||||
return likelihood
|
||||
|
||||
|
||||
|
|
@ -1,8 +1,8 @@
|
|||
import torch
|
||||
import torch.nn as nn
|
||||
|
||||
from .styled_conv import ConvStyledBlock, ResStyledBlock
|
||||
from .narrow import narrow_by
|
||||
from map2map_tools.styled_conv import ConvStyledBlock, ResStyledBlock
|
||||
from map2map_tools.narrow import narrow_by
|
||||
|
||||
class StyledVNet(nn.Module):
|
||||
def __init__(self, style_size, in_chan, out_chan, bypass=None, **kwargs):
|
||||
|
|
|
|||
|
|
@ -1,5 +1,9 @@
|
|||
import aquila_borg as borg
|
||||
import configparser
|
||||
import numpy as np
|
||||
import jax.numpy as jnp
|
||||
from scipy.special import hyp2f1
|
||||
import symbolic_pofk.linear
|
||||
|
||||
cons = borg.console()
|
||||
myprint = lambda x: cons.print_std(x) if type(x) == str else cons.print_std(repr(x))
|
||||
|
|
@ -34,3 +38,83 @@ def get_cosmopar(ini_file):
|
|||
cpar.sigma8, cpar.omega_m, cpar.omega_b, cpar.h, cpar.n_s)
|
||||
|
||||
return cpar
|
||||
|
||||
def initial_pos(L,N,order="F"):
|
||||
values = np.linspace(0,L,N+1)[:-1] #ensure LLC
|
||||
xx,yy,zz = np.meshgrid(values,values,values)
|
||||
|
||||
if order=="F":
|
||||
pos_mesh = np.vstack((yy.flatten(),xx.flatten(),zz.flatten())).T
|
||||
if order=="C":
|
||||
pos_mesh = np.vstack((zz.flatten(),xx.flatten(),yy.flatten())).T
|
||||
|
||||
return pos_mesh
|
||||
|
||||
|
||||
def correct_displacement_over_periodic_boundaries(disp,L,max_disp_1d=125):
|
||||
# Need to correct for positions moving over the periodic boundary
|
||||
|
||||
moved_over_bound = L - max_disp_1d
|
||||
axis = ['x','y','z']
|
||||
|
||||
for i in [0,1,2]:
|
||||
idx_sup, idx_sub = check(disp,L,moved_over_bound,max_disp_1d,i,axis)
|
||||
|
||||
# Correct positions
|
||||
disp[:,i][idx_sup] -= L
|
||||
disp[:,i][idx_sub] += L
|
||||
|
||||
check(disp,L,moved_over_bound,max_disp_1d,i,axis)
|
||||
|
||||
assert np.amin(disp[:,i]) >= -max_disp_1d and np.amax(disp[:,i]) <= max_disp_1d, "Particles outside allowed region"
|
||||
|
||||
return disp
|
||||
|
||||
|
||||
def check(disp,L,moved_over_bound,max_disp_1d,i,axis):
|
||||
idxsup = disp[:,i]>moved_over_bound
|
||||
idx = np.abs(disp[:,i])<=max_disp_1d
|
||||
idxsub = disp[:,i]<-moved_over_bound
|
||||
|
||||
sup = len(disp[:,i][idxsup])
|
||||
did_not_cross_boundary = len(disp[:,i][idx])
|
||||
sub = len(disp[:,i][idxsub])
|
||||
|
||||
if not sub+did_not_cross_boundary+sup == len(disp[:,i]):
|
||||
myprint(f'Disp in {axis[i]} direction under -{moved_over_bound} Mpc/h is = '+str(sub))
|
||||
myprint(f'|Disp| in {axis[i]} direction under {max_disp_1d} Mpc/h is = '+str(did_not_cross_boundary))
|
||||
myprint(f'Disp in {axis[i]} direction over {moved_over_bound} Mpc/h is = '+str(sup))
|
||||
myprint('These add up to: '+str(sub+did_not_cross_boundary+sup))
|
||||
myprint(f"Should add up to: len(disp[:,i]) {len(disp[:,i])}")
|
||||
myprint('\n')
|
||||
|
||||
assert sub+did_not_cross_boundary+sup == len(disp[:,i]), "Incorrect summation" # cannot lose/gain particles
|
||||
|
||||
return idxsup, idxsub
|
||||
|
||||
|
||||
def dis(x, undo=False, z=0.0, dis_std=6.0, **kwargs):
|
||||
dis_norm = dis_std * linear_D(z) # [Mpc/h]
|
||||
|
||||
if not undo:
|
||||
dis_norm = 1 / dis_norm
|
||||
|
||||
x *= dis_norm
|
||||
|
||||
|
||||
def linear_D(z, Om=0.31):
|
||||
"""linear growth function for flat LambdaCDM, normalized to 1 at redshift zero
|
||||
"""
|
||||
OL = 1 - Om
|
||||
a = 1 / (1+z)
|
||||
return a * hyp2f1(1, 1/3, 11/6, - OL * a**3 / Om) \
|
||||
/ hyp2f1(1, 1/3, 11/6, - OL / Om)
|
||||
|
||||
|
||||
def get_cell_coord(x):
|
||||
ix = jnp.floor(x)
|
||||
return x - ix, ix
|
||||
|
||||
def get_cell_coord_np(x):
|
||||
ix = np.floor(x)
|
||||
return x - ix, ix
|
||||
19
tests/allocation_stats_0.txt
Normal file
19
tests/allocation_stats_0.txt
Normal file
|
|
@ -0,0 +1,19 @@
|
|||
Memory still allocated at the end: 479.03 MB
|
||||
|
||||
Statistics per context (name, allocated, freed, peak)
|
||||
======================
|
||||
|
||||
*none* 64.0001 122.07 312.32
|
||||
BORG LPT MODEL 113.12 0 553.44
|
||||
BORGForwardModel::setup 0.000205994 0 216.82
|
||||
BorgLptModel::BorgLptModel 144 0 216.82
|
||||
[/home/bartlett/borg/libLSS/physics/chain_forward_model.cpp]virtual void LibLSS::ChainForwardModel::forwardModel_v2(ModelInput<3>) 160 16.25 617.35
|
||||
[/home/bartlett/borg/libLSS/physics/forward_model.cpp]void LibLSS::BORGForwardModel::setupDefault() 64 0 72.8201
|
||||
[/home/bartlett/borg/libLSS/physics/forwards/borg_lpt.cpp]std::shared_ptr<BORGForwardModel> build_borg_lpt(std::shared_ptr<MPI_Communication>, const BoxModel &, const PropertyProxy &) [Grid = LibLSS::ClassicCloudInCell<double, false, true>] 0 0 8.82007
|
||||
[/home/bartlett/borg/libLSS/physics/forwards/particle_balancer/balanceinfo.hpp]void LibLSS::BalanceInfo::allocate(MPI_Communication *, size_t) 16.16 0 569.6
|
||||
[/home/bartlett/borg/libLSS/physics/forwards/primordial_as.cpp]std::shared_ptr<BORGForwardModel> build_primordial_as(std::shared_ptr<MPI_Communication>, const BoxModel &, const PropertyProxy &) 4.41 7.62939e-06 4.41006
|
||||
[/home/bartlett/borg/libLSS/physics/forwards/transfer_class.cpp]std::shared_ptr<BORGForwardModel> build_class(std::shared_ptr<MPI_Communication>, const BoxModel &, const PropertyProxy &) 4.41 7.62939e-06 8.82008
|
||||
[/home/bartlett/borg/libLSS/samplers/core/gridLikelihoodBase.cpp]LibLSS::GridDensityLikelihoodBase<3>::GridDensityLikelihoodBase(MPI_Communication *, const GridSizes &, const GridLengths &) [Dims = 3] 64 32.5 280.82
|
||||
[/home/bartlett/borg/libLSS/tools/mpi/ghost_planes.hpp]void LibLSS::GhostPlanes<std::complex<double>, 2>::setup(MPI_Communication *, PlaneList &&, PlaneSet &&, DimList &&, size_t) [T = std::complex<double>, Nd = 2, PlaneList = std::set<long> &, PlaneSet = std::set<long> &, DimList = std::array<long, 2> &] 7.62939e-06 0.000495911 5.34058e-05
|
||||
dispatch_plane_map 0.000988007 0.000499725 0.00104141
|
||||
lpt_ic 32 16.25 601.6
|
||||
63
tests/fft_wisdom
Normal file
63
tests/fft_wisdom
Normal file
|
|
@ -0,0 +1,63 @@
|
|||
(fftw-3.3.10 fftw_wisdom #x029d284e #xc5dfc84e #xce4ac490 #x98c4e7bb
|
||||
(fftw_dft_thr_vrank_geq1_register 0 #x10bdd #x10bdd #x0 #x8c3bd361 #x74c82e49 #xd9d08cec #x490fb3c3)
|
||||
(fftw_dft_vrank_geq1_register 0 #x10bdd #x10bdd #x0 #xa79e8a60 #xe87bfd8a #x902920f9 #x2ec9719b)
|
||||
(fftw_mpi_rdft2_serial_register 0 #x10bdd #x10bdd #x0 #x4ee85eaa #x68518300 #x99d7298f #x8e84c365)
|
||||
(fftw_dft_r2hc_register 0 #x10bdd #x10bdd #x0 #xbe8bb67c #x0147d50a #xd6a7d883 #xaba02422)
|
||||
(fftw_rdft2_thr_vrank_geq1_register 0 #x10bdd #x10bdd #x0 #x851f9a4b #x19b2c27b #xed08cfa9 #x4bb3370b)
|
||||
(fftw_rdft2_rank_geq2_register 0 #x10bdd #x10bdd #x0 #x658ee741 #x13268820 #x59089f57 #x487d6156)
|
||||
(fftw_codelet_t1_16 0 #x10bdd #x10bdd #x0 #x8d3a0404 #x4ced2878 #xd7b0010b #x343f82db)
|
||||
(fftw_rdft_rank0_register 3 #x10bdd #x10bdd #x0 #xb076fe66 #xe428602a #xff6bd3c3 #xf198ea92)
|
||||
(fftw_dft_vrank_geq1_register 0 #x10bdd #x10bdd #x0 #xb26542a9 #x6f11da3d #xcc2f3b11 #xf58ffaf3)
|
||||
(fftw_dft_r2hc_register 0 #x10bdd #x10bdd #x0 #x19986bf9 #x1b1c9f9a #xbfa313e4 #x8089c52d)
|
||||
(fftw_codelet_n1_8 0 #x10bdd #x10bdd #x0 #xd47121ba #x8509d296 #xda71f68f #x32819f4c)
|
||||
(fftw_dft_thr_vrank_geq1_register 0 #x10bdd #x10bdd #x0 #x676d367b #x9d081048 #x84d35015 #xadb7f14f)
|
||||
(fftw_codelet_n1_8 0 #x10bdd #x10bdd #x0 #x96b8529e #xb560f141 #x58923d7d #x29e83836)
|
||||
(fftw_rdft2_rank_geq2_register 0 #x10bdd #x10bdd #x0 #xafd851da #x99c0aebd #x0230e6a1 #x4dc1a835)
|
||||
(fftw_dft_vrank_geq1_register 0 #x10bdd #x10bdd #x0 #x9d85b3d1 #x9fe51a73 #x90554ee0 #xae9d884a)
|
||||
(fftw_rdft2_rank_geq2_register 0 #x10bdd #x10bdd #x0 #x432cb311 #x3851b42e #xe2a123c6 #xe40063b1)
|
||||
(fftw_dft_thr_vrank_geq1_register 0 #x10bdd #x10bdd #x0 #x3b11e766 #xcac44a9a #xebe02560 #xf4741891)
|
||||
(fftw_rdft2_thr_vrank_geq1_register 0 #x10bdd #x10bdd #x0 #x1e5b754b #xc1ee385c #x32bb8ea2 #x03c0f524)
|
||||
(fftw_codelet_r2cb_128 2 #x10bdd #x10bdd #x0 #x3537951e #x3fde8ce2 #x944269f6 #xe658bdf2)
|
||||
(fftw_rdft2_rank_geq2_register 0 #x10bdd #x10bdd #x0 #x87a70733 #x168e4628 #x5985aa94 #x15260cc8)
|
||||
(fftw_codelet_n1_8 0 #x10bdd #x10bdd #x0 #x808c2c0b #xbc5616e2 #xc7cd6770 #x7d6b57c8)
|
||||
(fftw_dft_thr_vrank_geq1_register 0 #x10bdd #x10bdd #x0 #xc5735095 #x158eb2be #x520352f6 #x7c5ad18a)
|
||||
(fftw_dft_buffered_register 1 #x10bdd #x10bdd #x0 #x1bb138e5 #x126b4895 #x84639765 #xc6e16ed2)
|
||||
(fftw_mpi_rdft2_serial_register 0 #x10bdd #x10bdd #x0 #xb92bad75 #xe367ef0e #x7081a83c #x6bca5b81)
|
||||
(fftw_rdft2_thr_vrank_geq1_register 0 #x10bdd #x10bdd #x0 #x85be544a #x6ec428e5 #x464a9e59 #x2d009947)
|
||||
(fftw_rdft2_rank_geq2_register 0 #x10bdd #x10bdd #x0 #xd82cc4f0 #x264fda99 #x5da09515 #xaf7ad82a)
|
||||
(fftw_codelet_r2cf_8 2 #x10bdd #x10bdd #x0 #x2b8efd4b #xf9271562 #x58810e69 #x2a843b48)
|
||||
(fftw_mpi_rdft2_serial_register 0 #x10bdd #x10bdd #x0 #x64e50173 #xb27777d0 #xab348092 #xbcf5cef7)
|
||||
(fftw_dft_thr_vrank_geq1_register 0 #x10bdd #x10bdd #x0 #xdfbe0f99 #x9b0e292d #x4a5c0b38 #x807ed5d9)
|
||||
(fftw_codelet_n1_8 0 #x10bdd #x10bdd #x0 #x786bb47e #xf1901331 #x7f050641 #xf40ac495)
|
||||
(fftw_dft_thr_vrank_geq1_register 0 #x10bdd #x10bdd #x0 #xe414074e #xb5f6c556 #x331a5df5 #x42b72bfe)
|
||||
(fftw_dft_vrank_geq1_register 0 #x10bdd #x10bdd #x0 #x1c43a133 #x3a02cc9a #x06061ea2 #x8bd59400)
|
||||
(fftw_codelet_n1_8 0 #x10bdd #x10bdd #x0 #x8780ffa9 #x5043b17e #xf6b31f7c #x09308bf3)
|
||||
(fftw_rdft_rank0_register 3 #x10bdd #x10bdd #x0 #x0a7949d7 #x8e617643 #x1dc37829 #xb9c99559)
|
||||
(fftw_codelet_n1_8 0 #x10bdd #x10bdd #x0 #x6cd039b7 #x416fd217 #x9a1f1005 #xae8b516f)
|
||||
(fftw_codelet_r2cf_128 2 #x10bdd #x10bdd #x0 #x01ed1f43 #x9eb2a8be #x54a463f4 #x4065bd8c)
|
||||
(fftw_dft_buffered_register 1 #x10bdd #x10bdd #x0 #x8cb4c207 #xbbe7f9d8 #x6142bd03 #x1fef6cbd)
|
||||
(fftw_codelet_t1_16 0 #x10bdd #x10bdd #x0 #x07493f2d #xdbff69bf #xc99ae69c #x99aebe87)
|
||||
(fftw_mpi_rdft2_serial_register 0 #x10bdd #x10bdd #x0 #x12333882 #x58ed4c26 #x2573fe73 #x58166349)
|
||||
(fftw_dft_vrank_geq1_register 0 #x10bdd #x10bdd #x0 #x55dc834f #xe6778f48 #x5fb9338e #xb26105c2)
|
||||
(fftw_codelet_n1_16 0 #x10bdd #x10bdd #x0 #x31243853 #xcd3ffac1 #x216a5369 #xbed877e1)
|
||||
(fftw_codelet_n1_8 0 #x10bdd #x10bdd #x0 #x07538465 #x05c872d2 #x2e3a8015 #x2c1d6fb3)
|
||||
(fftw_codelet_t1_8 0 #x10bdd #x10bdd #x0 #xe1c49a16 #x6e50ae21 #x6a60b5f7 #x922c9861)
|
||||
(fftw_rdft2_rank_geq2_register 0 #x10bdd #x10bdd #x0 #xd747290f #x47e022d8 #x5f66ed62 #x0703deff)
|
||||
(fftw_rdft2_thr_vrank_geq1_register 0 #x10bdd #x10bdd #x0 #x6e5782da #xff8f0cb7 #xb7b3553d #xff227114)
|
||||
(fftw_dft_nop_register 0 #x10bdd #x10bdd #x0 #x54333caa #x860f0b6a #xeeb1b4b0 #xbc1bf503)
|
||||
(fftw_dft_nop_register 0 #x10bdd #x10bdd #x0 #x329f88d1 #x8b794130 #x1d6cd482 #x226d9d8c)
|
||||
(fftw_dft_nop_register 0 #x10bdd #x10bdd #x0 #xcaa1aff4 #x76b5ab1f #xa1c4e63a #x795533ee)
|
||||
(fftw_dft_r2hc_register 0 #x10bdd #x10bdd #x0 #xed14e8ff #x6a3fa4af #xcf6bc976 #x9ed6862b)
|
||||
(fftw_rdft2_rank_geq2_register 0 #x10bdd #x10bdd #x0 #xf68eeb4b #x9707c500 #xea967ca2 #x94317695)
|
||||
(fftw_dft_thr_vrank_geq1_register 0 #x10bdd #x10bdd #x0 #x8e7540ba #xdf13a27a #xc5dfd29d #xcc18c450)
|
||||
(fftw_dft_thr_vrank_geq1_register 0 #x10bdd #x10bdd #x0 #x4d5128a3 #x2c886ce4 #xae533803 #xd036a3e3)
|
||||
(fftw_codelet_t1_16 0 #x10bdd #x10bdd #x0 #xec8d8b00 #x73468233 #xfd711f80 #x8216811f)
|
||||
(fftw_rdft2_rank_geq2_register 0 #x10bdd #x10bdd #x0 #x69620706 #x1630ea0a #x7845ac91 #x107c1ea6)
|
||||
(fftw_dft_vrank_geq1_register 0 #x10bdd #x10bdd #x0 #xfa2f8f06 #x1e602e94 #x45491c98 #xb72edccf)
|
||||
(fftw_dft_buffered_register 1 #x10bdd #x10bdd #x0 #x9d8339bb #x21e617a3 #x19bcf6ec #x843e58c6)
|
||||
(fftw_dft_r2hc_register 0 #x10bdd #x10bdd #x0 #x2b1407ee #x9181dd05 #x70f5ba55 #x9d03e54b)
|
||||
(fftw_dft_buffered_register 1 #x10bdd #x10bdd #x0 #xb5a35887 #x56e26ed1 #x50fc7926 #x21aa2465)
|
||||
(fftw_rdft2_thr_vrank_geq1_register 0 #x10bdd #x10bdd #x0 #xde80c147 #x2f2b1766 #x646a051f #xbce0e7ea)
|
||||
(fftw_dft_nop_register 0 #x10bdd #x10bdd #x0 #xa211000f #x16096f47 #x8977fda7 #x5859feab)
|
||||
(fftw_codelet_r2cb_8 2 #x10bdd #x10bdd #x0 #xcc33ac01 #x3a093b70 #xce721838 #xe388f482)
|
||||
)
|
||||
198
tests/test_gradient.py
Normal file
198
tests/test_gradient.py
Normal file
|
|
@ -0,0 +1,198 @@
|
|||
import aquila_borg as borg
|
||||
import configparser
|
||||
import numpy as np
|
||||
import matplotlib.pyplot as plt
|
||||
import matplotlib
|
||||
import itertools
|
||||
import h5py as h5
|
||||
import os
|
||||
import sys
|
||||
import contextlib
|
||||
from tqdm import tqdm
|
||||
|
||||
sys.path.insert(0, '../mgborg_emulator/')
|
||||
import likelihood
|
||||
import forwards
|
||||
import utils
|
||||
|
||||
run_test = True
|
||||
# run_test = False
|
||||
epsilon = 1e-2
|
||||
|
||||
|
||||
# Create a context manager to suppress stdout
|
||||
@contextlib.contextmanager
|
||||
def suppress_stdout():
|
||||
with open(os.devnull, 'w') as devnull:
|
||||
old_stdout = sys.stdout
|
||||
sys.stdout = devnull
|
||||
try:
|
||||
yield
|
||||
finally:
|
||||
sys.stdout = old_stdout
|
||||
|
||||
def compare_gradients(
|
||||
ag_lh_auto_real: np.ndarray,
|
||||
ag_lh_auto_imag: np.ndarray,
|
||||
ag_lh_num_real: np.ndarray,
|
||||
ag_lh_num_imag: np.ndarray,
|
||||
plot_step: int,
|
||||
filename: str="gradients.png",
|
||||
) -> None:
|
||||
"""
|
||||
Comparison of an autodiff adjoint gradient of the likelihood against a
|
||||
numerical one evaluated with finite differences.
|
||||
|
||||
Args:
|
||||
- ag_lh_auto_real (np.ndarray): Real part of the adjoint gradient (autodiff)
|
||||
- ag_lh_auto_imag (np.ndarray): Imaginary part of the adjoint gradient (autodiff)
|
||||
- ag_lh_num_real (np.ndarray): Real part of the adjoint gradient (numerical)
|
||||
- ag_lh_num_imag (np.ndarray): Imaginary part of the adjoint gradient (numerical)
|
||||
- plot_step (int): How frequently to sample the arrays
|
||||
- filename (str): Name of the file to save the figure
|
||||
|
||||
"""
|
||||
# Plot colors
|
||||
colors = {
|
||||
"red": "#ba3d3b",
|
||||
"blue": "#3d5792",
|
||||
}
|
||||
|
||||
fig, axs = plt.subplots(2, 2, figsize=(10, 7))
|
||||
|
||||
# Real part
|
||||
axs[0,0].axhline(0.0, color="black", linestyle=":")
|
||||
axs[0,0].plot(ag_lh_num_real[::plot_step], c=colors["blue"], label="Finite differences")
|
||||
axs[0,0].plot(ag_lh_auto_real[::plot_step], "o", c=colors["red"], ms=3, label="Autodiff")
|
||||
axs[0,0].yaxis.get_major_formatter().set_powerlimits((-2, 2))
|
||||
axs[0,0].set_ylabel("Real part")
|
||||
axs[0,0].legend()
|
||||
axs[0,1].plot(ag_lh_num_real[::plot_step],
|
||||
ag_lh_auto_real[::plot_step] - ag_lh_num_real[::plot_step],
|
||||
"o",
|
||||
c=colors["red"],
|
||||
ms=3
|
||||
)
|
||||
x = axs[0,1].get_xlim()
|
||||
axs[0,1].axhline(y=0, color='k')
|
||||
axs[0,1].set_xlabel("Numerical")
|
||||
axs[0,1].set_ylabel("Autodiff - Numerical (real)")
|
||||
|
||||
# Imaginary part
|
||||
axs[1,0].axhline(0.0, color="black", linestyle=":")
|
||||
axs[1,0].plot(ag_lh_num_imag[::plot_step][4:], c=colors["blue"], label="Finite differences")
|
||||
axs[1,0].plot(ag_lh_auto_imag[::plot_step][4:], "o", c=colors["red"], ms=3, label="Autodiff")
|
||||
axs[1,0].yaxis.get_major_formatter().set_powerlimits((-2, 2))
|
||||
axs[1,0].set_ylabel("Imaginary part")
|
||||
axs[1,0].set_xlabel("Voxel ID")
|
||||
axs[1,1].plot(ag_lh_num_imag[::plot_step],
|
||||
ag_lh_auto_imag[::plot_step] - ag_lh_num_imag[::plot_step],
|
||||
".",
|
||||
c=colors["red"]
|
||||
)
|
||||
x = axs[1,1].get_xlim()
|
||||
axs[1,1].axhline(y=0, color='k')
|
||||
axs[1,1].set_xlabel("Numerical")
|
||||
axs[1,1].set_ylabel("Autodiff - Numerical (imag)")
|
||||
|
||||
fig.suptitle("Adjoint gradient of the likelihood w.r.t. initial conditions")
|
||||
fig.tight_layout()
|
||||
fig.subplots_adjust(hspace=0.)
|
||||
|
||||
path = "../figs/"
|
||||
fig.savefig(path + filename, bbox_inches="tight")
|
||||
|
||||
|
||||
ini_file = '../conf/basic_ini.ini'
|
||||
|
||||
# Input box
|
||||
box_in = borg.forward.BoxModel()
|
||||
config = configparser.ConfigParser()
|
||||
config.read(ini_file)
|
||||
box_in.L = (float(config['system']['L0']), float(config['system']['L1']), float(config['system']['L2']))
|
||||
box_in.N = (int(config['system']['N0']), int(config['system']['N1']), int(config['system']['N2']))
|
||||
box_in.xmin = (float(config['system']['corner0']), float(config['system']['corner1']), float(config['system']['corner2']))
|
||||
|
||||
# Setup BORG forward model and likelihood
|
||||
model = likelihood.build_gravity_model(None, box_in, ini_file=ini_file)
|
||||
cosmo = utils.get_cosmopar(ini_file)
|
||||
model.setCosmoParams(cosmo)
|
||||
fwd_param = forwards.NullForward(box_in)
|
||||
mylike = likelihood.GaussianLikelihood(model, fwd_param, ini_file)
|
||||
|
||||
# Create mock data
|
||||
state = borg.likelihood.MarkovState()
|
||||
mylike.initializeLikelihood(state)
|
||||
mylike.updateCosmology(cosmo)
|
||||
s_hat = np.fft.rfftn(np.random.randn(*box_in.N)) / box_in.Ntot ** (0.5)
|
||||
mylike.generateMockData(s_hat, state)
|
||||
|
||||
# Compute density field
|
||||
output_density = np.zeros(box_in.N)
|
||||
mylike.fwd.forwardModel_v2(s_hat)
|
||||
print('SUM START', output_density.sum())
|
||||
mylike.fwd.getDensityFinal(output_density)
|
||||
print('SUM NOW', output_density.sum())
|
||||
L = mylike.logLikelihoodComplex(s_hat, None)
|
||||
print(L)
|
||||
quit()
|
||||
|
||||
# Autodiff
|
||||
autodiff_gradient = mylike.gradientLikelihoodComplex(s_hat)
|
||||
print(autodiff_gradient.min(), autodiff_gradient.max(), np.sum(np.isfinite(autodiff_gradient)), np.prod(autodiff_gradient.shape))
|
||||
|
||||
# Finite differences
|
||||
if run_test:
|
||||
s_hat_epsilon = s_hat.copy()
|
||||
num_gradient = np.zeros(s_hat.shape, dtype=np.complex128)
|
||||
for i, j, k in tqdm(
|
||||
itertools.product(*map(range, [box_in.N[0], box_in.N[1], box_in.N[2] // 2 + 1])),
|
||||
total=box_in.N[0] * box_in.N[1] * (box_in.N[2] // 2 + 1),
|
||||
mininterval=1,
|
||||
):
|
||||
|
||||
# +/- epsilon
|
||||
s_hat_epsilon[i, j, k] = s_hat[i, j, k] + epsilon
|
||||
with suppress_stdout():
|
||||
L = mylike.logLikelihoodComplex(s_hat_epsilon, None)
|
||||
s_hat_epsilon[i, j, k] = s_hat[i, j, k] - epsilon
|
||||
with suppress_stdout():
|
||||
L -= mylike.logLikelihoodComplex(s_hat_epsilon, None)
|
||||
QQ = L / (2.0 * epsilon)
|
||||
|
||||
# +/- i * epsilon
|
||||
s_hat_epsilon[i, j, k] = s_hat[i, j, k] + 1j * epsilon
|
||||
with suppress_stdout():
|
||||
L = mylike.logLikelihoodComplex(s_hat_epsilon, None)
|
||||
s_hat_epsilon[i, j, k] = s_hat[i, j, k] - 1j * epsilon
|
||||
with suppress_stdout():
|
||||
L -= mylike.logLikelihoodComplex(s_hat_epsilon, None)
|
||||
QQ = QQ + L * 1j / (2.0 * epsilon)
|
||||
|
||||
s_hat_epsilon[i, j, k] = s_hat[i, j, k]
|
||||
num_gradient[i, j, k] = QQ
|
||||
|
||||
|
||||
with h5.File(f"gradients_{box_in.N}.h5", mode="w") as ff:
|
||||
ff["scalars/gradient_array_lh"] = autodiff_gradient
|
||||
ff["scalars/gradient_array_lh_ref"] = num_gradient
|
||||
ff["scalars/gradient_array_prior"] = np.zeros_like(autodiff_gradient)
|
||||
ff["scalars/gradient_array_prior_ref"] = np.zeros_like(autodiff_gradient)
|
||||
|
||||
slice_step = 2
|
||||
plot_step = 2
|
||||
|
||||
with h5.File(f'gradients_{box_in.N}.h5', 'r') as f:
|
||||
ag_lh_auto_real = f["scalars"]["gradient_array_lh"][::slice_step, :, :].flatten().real
|
||||
ag_lh_auto_imag = f["scalars"]["gradient_array_lh"][::slice_step, :, :].flatten().imag
|
||||
ag_lh_num_real = f["scalars"]["gradient_array_lh_ref"][::slice_step, :, :].flatten().real
|
||||
ag_lh_num_imag = f["scalars"]["gradient_array_lh_ref"][::slice_step, :, :].flatten().imag
|
||||
|
||||
compare_gradients(
|
||||
ag_lh_auto_real,
|
||||
ag_lh_auto_imag,
|
||||
ag_lh_num_real,
|
||||
ag_lh_num_imag,
|
||||
plot_step,
|
||||
f'gradient_test_{box_in.N[0]}.png',
|
||||
)
|
||||
58
tests/timing_stats_0.txt
Normal file
58
tests/timing_stats_0.txt
Normal file
|
|
@ -0,0 +1,58 @@
|
|||
ARES version a9c88f3e8f91e04ec7c84eaea3b11ac5546aa6a5 modules
|
||||
|
||||
Cumulative timing spent in different context
|
||||
--------------------------------------------
|
||||
Context, Total time (seconds)
|
||||
|
||||
[/home/bartlett/borg/libLSS/physics/forward_model.cpp]void LibLSS::ForwardModel::setCosmoParams(const CosmologicalParameters &) 39 2.96271
|
||||
[/home/bartlett/borg/libLSS/physics/chain_forward_model.cpp]virtual void LibLSS::ChainForwardModel::forwardModel_v2(ModelInput<3>) 1 2.54629
|
||||
[/home/bartlett/borg/libLSS/physics/forwards/borg_lpt.cpp]virtual void LibLSS::BorgLptModel<>::updateCosmo() [CIC = LibLSS::ClassicCloudInCell<double, false, true>] 4 0.882557
|
||||
lightcone computation 1 0.878502
|
||||
[/home/bartlett/borg/libLSS/physics/cosmo.cpp]void LibLSS::Cosmology::precompute_com2a() 1 0.678918
|
||||
[/home/bartlett/borg/libLSS/physics/forwards/transfer_class.cpp]virtual void LibLSS::ForwardClass::updateCosmo() 4 0.593989
|
||||
[/home/bartlett/borg/libLSS/physics/class_cosmo.cpp]LibLSS::ClassCosmo::ClassCosmo(const CosmologicalParameters &, unsigned int, double, std::string, unsigned int, const std::map<std::string, std::string> &) 1 0.482735
|
||||
[/home/bartlett/borg/libLSS/physics/forwards/primordial_as.cpp]std::shared_ptr<BORGForwardModel> build_primordial_as(std::shared_ptr<MPI_Communication>, const BoxModel &, const PropertyProxy &) 1 0.222871
|
||||
[/home/bartlett/borg/libLSS/physics/forwards/transfer_class.cpp]std::shared_ptr<BORGForwardModel> build_class(std::shared_ptr<MPI_Communication>, const BoxModel &, const PropertyProxy &) 1 0.202131
|
||||
BORG LPT MODEL 1 0.193024
|
||||
BORG forward model 1 0.191335
|
||||
lpt_ic 1 0.186872
|
||||
[/home/bartlett/borg/libLSS/physics/cosmo.cpp]void LibLSS::Cosmology::precompute_d_plus() 1 0.174369
|
||||
[/home/bartlett/borg/libLSS/physics/forwards/lpt/borg_fwd_lpt.cpp]virtual void LibLSS::BorgLptModel<>::getDensityFinal(ModelOutput<3>) [CIC = LibLSS::ClassicCloudInCell<double, false, true>] 1 0.0468955
|
||||
Classic CIC projection 1 0.0429608
|
||||
FFTW_Manager::execute_c2r 3 0.0177956
|
||||
[/home/bartlett/borg/libLSS/physics/forwards/borg_lpt.cpp]std::shared_ptr<BORGForwardModel> build_borg_lpt(std::shared_ptr<MPI_Communication>, const BoxModel &, const PropertyProxy &) [Grid = LibLSS::ClassicCloudInCell<double, false, true>] 1 0.0122158
|
||||
BorgLptModel::BorgLptModel 1 0.0117337
|
||||
[/home/bartlett/borg/libLSS/tools/hermiticity_fixup.cpp]LibLSS::Hermiticity_fixer<double, 3>::Hermiticity_fixer(Mgr_p) [T = double, Nd = 3] 1 0.00922349
|
||||
[/home/bartlett/borg/libLSS/tools/mpi/ghost_planes.hpp]void LibLSS::GhostPlanes<std::complex<double>, 2>::setup(MPI_Communication *, PlaneList &&, PlaneSet &&, DimList &&, size_t) [T = std::complex<double>, Nd = 2, PlaneList = std::set<long> &, PlaneSet = std::set<long> &, DimList = std::array<long, 2> &] 1 0.00915645
|
||||
FFTW_Manager::create_r2c_plan 3 0.00870736
|
||||
[/home/bartlett/borg/python/pyforward.cpp]void transfer_in(std::shared_ptr<BORGForwardModel::DFT_Manager> &, T &, U &, bool) [T = boost::multi_array_ref<std::complex<double>, 3>, U = pybind11::detail::unchecked_reference<std::complex<double>, 3>] 1 0.00718587
|
||||
dispatch_plane_map 1 0.00579799
|
||||
FFTW_Manager::create_c2r_plan 2 0.00561102
|
||||
[/home/bartlett/borg/libLSS/physics/forward_model.cpp]void LibLSS::BORGForwardModel::setupDefault() 1 0.00491136
|
||||
[/home/bartlett/borg/libLSS/physics/forwards/primordial_as.cpp]virtual void LibLSS::ForwardPrimordial_As::updateCosmo() 8 0.00461581
|
||||
[/home/bartlett/borg/libLSS/physics/forwards/primordial_as.cpp]void LibLSS::ForwardPrimordial_As::updatePower() 4 0.00431693
|
||||
[/home/bartlett/borg/libLSS/samplers/core/gridLikelihoodBase.cpp]LibLSS::GridDensityLikelihoodBase<3>::GridDensityLikelihoodBase(MPI_Communication *, const GridSizes &, const GridLengths &) [Dims = 3] 1 0.0029058
|
||||
[/home/bartlett/borg/libLSS/physics/hermitic.hpp]virtual void LibLSS::ForwardHermiticOperation::getDensityFinal(ModelOutput<3>) 1 0.00258788
|
||||
[/home/bartlett/borg/libLSS/physics/forwards/particle_balancer/balanceinfo.hpp]void LibLSS::BalanceInfo::allocate(MPI_Communication *, size_t) 1 0.00160495
|
||||
BORGForwardModel::setup 9 0.00148339
|
||||
Initializing peer system 15 0.00125319
|
||||
[/home/bartlett/borg/libLSS/physics/forwards/adapt_generic_bias.cpp]void (anonymous namespace)::bias_registrator() 1 0.0011465
|
||||
[/home/bartlett/borg/libLSS/physics/class_cosmo.cpp]void LibLSS::ClassCosmo::retrieve_Tk(const double) 2 0.00064302
|
||||
[/home/bartlett/borg/libLSS/physics/class_cosmo.cpp]void LibLSS::ClassCosmo::reinterpolate(const array_ref_1d &, const array_ref_1d &, LibLSS::auto_interpolator<double> &) 6 0.000562291
|
||||
[/home/bartlett/borg/libLSS/tools/hermiticity_fixup.cpp]void LibLSS::Hermiticity_fixer<double, 3>::forward(CArrayRef &) [T = double, Nd = 3] 1 0.00051675
|
||||
[/home/bartlett/borg/libLSS/physics/model_io.cpp]virtual LibLSS::detail_output::ModelOutputBase<3>::~ModelOutputBase() [Nd = 3, Super = LibLSS::detail_model::ModelIO<3>] 14 0.000265913
|
||||
[/home/bartlett/borg/libLSS/tools/hermiticity_fixup.cpp]typename std::enable_if<Dim != 1, void>::type fix_plane(Mgr &, Ghosts &&, CArray &&, size_t *) [rank = 0UL, Mgr = LibLSS::FFTW_Manager<double, 3>, Ghosts = (lambda at /home/bartlett/borg/libLSS/tools/hermiticity_fixup.cpp:212:7), CArray = boost::detail::multi_array::multi_array_view<std::complex<double>, 2>, Dim = 2UL] 1 0.000250649
|
||||
gather_peer_by_plane 1 0.00023947
|
||||
[/home/bartlett/borg/libLSS/tools/hermiticity_fixup.cpp]typename std::enable_if<Dim != 1, void>::type fix_plane(Mgr &, Ghosts &&, CArray &&, size_t *) [rank = 0UL, Mgr = LibLSS::FFTW_Manager<double, 3>, Ghosts = (lambda at /home/bartlett/borg/libLSS/tools/hermiticity_fixup.cpp:218:7), CArray = boost::detail::multi_array::multi_array_view<std::complex<double>, 2>, Dim = 2UL] 1 0.000165529
|
||||
[/home/bartlett/borg/libLSS/physics/model_io.cpp]void LibLSS::detail_output::ModelOutputBase<3>::transfer(ModelOutputBase<Nd, Super> &&) [Nd = 3, Super = LibLSS::detail_model::ModelIO<3>] 9 7.3155e-05
|
||||
ghost synchronize 1 3.1071e-05
|
||||
[/home/bartlett/borg/libLSS/physics/model_io/base.hpp]void LibLSS::detail_model::ModelIO<3>::transfer(ModelIO<Nd> &&) [Nd = 3] 30 2.4868e-05
|
||||
[/home/bartlett/borg/libLSS/physics/forwards/transfer_class.cpp]virtual void LibLSS::ForwardClass::forwardModel_v2(ModelInput<3>) 1 1.2496e-05
|
||||
[/home/bartlett/borg/libLSS/physics/model_io.cpp]virtual void LibLSS::detail_output::ModelOutputBase<3>::close() [Nd = 3, Super = LibLSS::detail_model::ModelIO<3>] 14 1.2394e-05
|
||||
[/home/bartlett/borg/libLSS/physics/forwards/primordial_as.cpp]virtual void LibLSS::ForwardPrimordial_As::forwardModel_v2(ModelInput<3>) 1 1.231e-05
|
||||
[/home/bartlett/borg/libLSS/physics/forwards/transfer_class.cpp]virtual void LibLSS::ForwardClass::setModelParams(const ModelDictionnary &) 1 9.429e-06
|
||||
[/home/bartlett/borg/libLSS/physics/model_io.cpp]void LibLSS::detail_input::ModelInputBase<3>::setRequestedIO(PreferredIO) [Nd = 3, Super = LibLSS::detail_model::ModelIO<3>] 5 3.766e-06
|
||||
[/home/bartlett/borg/libLSS/physics/model_io.cpp]void LibLSS::detail_output::ModelOutputBase<3>::setRequestedIO(PreferredIO) [Nd = 3, Super = LibLSS::detail_model::ModelIO<3>] 4 3.162e-06
|
||||
[/home/bartlett/borg/libLSS/physics/model_io.cpp]void LibLSS::detail_input::ModelInputBase<3>::needDestroyInput() [Nd = 3, Super = LibLSS::detail_model::ModelIO<3>] 1 2.173e-06
|
||||
particle distribution 1 1.5e-06
|
||||
[/home/bartlett/borg/libLSS/physics/forward_model.cpp]virtual void LibLSS::ForwardModel::setModelParams(const ModelDictionnary &) 1 1.258e-06
|
||||
BIN
weights/d2d_borg.pt
Normal file
BIN
weights/d2d_borg.pt
Normal file
Binary file not shown.
Loading…
Reference in a new issue