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test_examples.py
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test_examples.py
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# Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import logging
import os
import sys
from subprocess import check_call
import pytest
import torch
from tests.common import (
EXAMPLES_DIR,
requires_cuda,
requires_funsor,
requires_horovod,
requires_lightning,
xfail_param,
)
logger = logging.getLogger(__name__)
pytestmark = pytest.mark.stage("test_examples")
CPU_EXAMPLES = [
"air/main.py --num-steps=1",
"air/main.py --num-steps=1 --no-baseline",
"baseball.py --num-samples=200 --warmup-steps=100 --num-chains=2",
"lkj.py --n=50 --num-chains=1 --warmup-steps=100 --num-samples=200",
"capture_recapture/cjs.py --num-steps=1 -m 1",
"capture_recapture/cjs.py --num-steps=1 -m 2",
"capture_recapture/cjs.py --num-steps=1 -m 3",
"capture_recapture/cjs.py --num-steps=1 -m 4",
"capture_recapture/cjs.py --num-steps=1 -m 5",
"capture_recapture/cjs.py --num-steps=1 -m 1 --tmc --tmc-num-samples=2",
"capture_recapture/cjs.py --num-steps=1 -m 2 --tmc --tmc-num-samples=2",
"capture_recapture/cjs.py --num-steps=1 -m 3 --tmc --tmc-num-samples=2",
"capture_recapture/cjs.py --num-steps=1 -m 4 --tmc --tmc-num-samples=2",
"capture_recapture/cjs.py --num-steps=1 -m 5 --tmc --tmc-num-samples=2",
"contrib/autoname/scoping_mixture.py --num-epochs=1",
"contrib/autoname/mixture.py --num-epochs=1",
"contrib/autoname/tree_data.py --num-epochs=1",
"contrib/cevae/synthetic.py --num-epochs=1",
"contrib/epidemiology/sir.py --nojit -np=128 -t=2 -w=2 -n=4 -d=20 -p=1000 -f 2",
"contrib/epidemiology/sir.py --nojit -np=128 -t=2 -w=2 -n=4 -d=20 -p=1000 -f 2 -c=2",
"contrib/epidemiology/sir.py --nojit -np=128 -t=2 -w=2 -n=4 -d=20 -p=1000 -f 2 -e=2",
"contrib/epidemiology/sir.py --nojit -np=128 -t=2 -w=2 -n=4 -d=20 -p=1000 -f 2 -k=1",
"contrib/epidemiology/sir.py --nojit -np=128 -t=2 -w=2 -n=4 -d=20 -p=1000 -f 2 -e=2 -k=1",
"contrib/epidemiology/sir.py --nojit -np=128 -t=2 -w=2 -n=4 -d=20 -p=1000 -f 2 --haar",
"contrib/epidemiology/sir.py --nojit -np=128 -t=2 -w=2 -n=4 -d=20 -p=1000 -f 2 -nb=4",
"contrib/epidemiology/sir.py --nojit -np=128 -t=2 -w=2 -n=4 -d=20 -p=1000 -f 2 -hfm=3",
"contrib/epidemiology/sir.py --nojit -np=128 -t=2 -w=2 -n=4 -d=20 -p=1000 -f 2 -a",
"contrib/epidemiology/sir.py --nojit -np=128 -t=2 -w=2 -n=4 -d=20 -p=1000 -f 2 -o=0.2",
"contrib/epidemiology/sir.py --nojit -np=128 -ss=2 -n=4 -d=20 -p=1000 -f 2 --svi",
"contrib/epidemiology/regional.py --nojit -t=2 -w=2 -n=4 -r=3 -d=20 -p=1000 -f 2",
"contrib/epidemiology/regional.py --nojit -t=2 -w=2 -n=4 -r=3 -d=20 -p=1000 -f 2 --haar",
"contrib/epidemiology/regional.py --nojit -t=2 -w=2 -n=4 -r=3 -d=20 -p=1000 -f 2 -hfm=3",
"contrib/epidemiology/regional.py --nojit -t=2 -w=2 -n=4 -r=3 -d=20 -p=1000 -f 2 -nb=4",
"contrib/epidemiology/regional.py --nojit -ss=2 -n=4 -r=3 -d=20 -p=1000 -f 2 --svi",
"contrib/forecast/bart.py --num-steps=2 --stride=99999",
"contrib/gp/sv-dkl.py --epochs=1 --num-inducing=4 --batch-size=1000",
"contrib/gp/sv-dkl.py --binary --epochs=1 --num-inducing=4 --batch-size=1000",
"contrib/mue/FactorMuE.py --test --small --include-stop --no-plots --no-save",
"contrib/mue/FactorMuE.py --test --small -ard -idfac --no-substitution-matrix --no-plots --no-save",
"contrib/mue/ProfileHMM.py --test --small --no-plots --no-save",
"contrib/mue/ProfileHMM.py --test --small --include-stop --no-plots --no-save",
"contrib/oed/ab_test.py --num-vi-steps=10 --num-bo-steps=2",
"contrib/timeseries/gp_models.py -m imgp --test --num-steps=2",
"contrib/timeseries/gp_models.py -m lcmgp --test --num-steps=2",
"dmm.py --num-epochs=1",
"dmm.py --num-epochs=1 --tmcelbo --tmc-num-samples=2",
"dmm.py --num-epochs=1 --num-iafs=1",
"dmm.py --num-epochs=1 --tmc --tmc-num-samples=2",
"dmm.py --num-epochs=1 --tmcelbo --tmc-num-samples=2",
"eight_schools/mcmc.py --num-samples=500 --warmup-steps=100",
"eight_schools/svi.py --num-epochs=1",
"einsum.py",
"hmm.py --num-steps=1 --truncate=10 --model=0",
"hmm.py --num-steps=1 --truncate=10 --model=1",
"hmm.py --num-steps=1 --truncate=10 --model=2",
"hmm.py --num-steps=1 --truncate=10 --model=3",
"hmm.py --num-steps=1 --truncate=10 --model=4",
"hmm.py --num-steps=1 --truncate=10 --model=5",
"hmm.py --num-steps=1 --truncate=10 --model=6",
"hmm.py --num-steps=1 --truncate=10 --model=6 --raftery-parameterization",
"hmm.py --num-steps=1 --truncate=10 --model=7",
"hmm.py --num-steps=1 --truncate=10 --model=0 --tmc --tmc-num-samples=2",
"hmm.py --num-steps=1 --truncate=10 --model=1 --tmc --tmc-num-samples=2",
"hmm.py --num-steps=1 --truncate=10 --model=2 --tmc --tmc-num-samples=2",
"hmm.py --num-steps=1 --truncate=10 --model=3 --tmc --tmc-num-samples=2",
"hmm.py --num-steps=1 --truncate=10 --model=4 --tmc --tmc-num-samples=2",
"hmm.py --num-steps=1 --truncate=10 --model=5 --tmc --tmc-num-samples=2",
"hmm.py --num-steps=1 --truncate=10 --model=6 --tmc --tmc-num-samples=2",
"inclined_plane.py --num-samples=1",
"lda.py --num-steps=2 --num-words=100 --num-docs=100 --num-words-per-doc=8",
"minipyro.py --backend=pyro",
"minipyro.py",
"mixed_hmm/experiment.py --timesteps=1",
"neutra.py -n 10 --num-warmup 10 --num-samples 10",
"rsa/generics.py --num-samples=10",
"rsa/hyperbole.py --price=10000",
"rsa/schelling.py --num-samples=10",
"rsa/schelling_false.py --num-samples=10",
"rsa/semantic_parsing.py --num-samples=10",
"scanvi/scanvi.py --num-epochs 1 --dataset mock",
"sir_hmc.py -t=2 -w=2 -n=4 -d=2 -m=1 --enum",
"sir_hmc.py -t=2 -w=2 -n=4 -d=2 -p=10000 --sequential",
"sir_hmc.py -t=2 -w=2 -n=4 -d=100 -p=10000 -f 2",
"smcfilter.py --num-timesteps=3 --num-particles=10",
"sparse_gamma_def.py --num-epochs=2 --eval-particles=2 --eval-frequency=1 --guide custom",
"sparse_gamma_def.py --num-epochs=2 --eval-particles=2 --eval-frequency=1 --guide auto",
"sparse_gamma_def.py --num-epochs=2 --eval-particles=2 --eval-frequency=1 --guide easy",
"svi_torch.py --num-epochs=2 --size=400",
"svi_horovod.py --num-epochs=2 --size=400 --no-horovod",
pytest.param(
"svi_lightning.py --max_epochs=2 --size=400 --accelerator cpu --devices 1",
marks=[requires_lightning],
),
"toy_mixture_model_discrete_enumeration.py --num-steps=1",
"sparse_regression.py --num-steps=100 --num-data=100 --num-dimensions 11",
"vae/ss_vae_M2.py --num-epochs=1",
"vae/ss_vae_M2.py --num-epochs=1 --aux-loss",
"vae/ss_vae_M2.py --num-epochs=1 --enum-discrete=parallel",
"vae/ss_vae_M2.py --num-epochs=1 --enum-discrete=sequential",
"vae/vae.py --num-epochs=1",
"vae/vae_comparison.py --num-epochs=1",
"cvae/main.py --num-quadrant-inputs=1 --num-epochs=1",
"contrib/funsor/hmm.py --num-steps=1 --truncate=10 --model=0 ",
"contrib/funsor/hmm.py --num-steps=1 --truncate=10 --model=1 ",
"contrib/funsor/hmm.py --num-steps=1 --truncate=10 --model=2 ",
"contrib/funsor/hmm.py --num-steps=1 --truncate=10 --model=3 ",
"contrib/funsor/hmm.py --num-steps=1 --truncate=10 --model=4 ",
"contrib/funsor/hmm.py --num-steps=1 --truncate=10 --model=5 ",
"contrib/funsor/hmm.py --num-steps=1 --truncate=10 --model=6 ",
"contrib/funsor/hmm.py --num-steps=1 --truncate=10 --model=6 --raftery-parameterization ",
"contrib/funsor/hmm.py --num-steps=1 --truncate=10 --model=1 --tmc --tmc-num-samples=2 ",
"contrib/funsor/hmm.py --num-steps=1 --truncate=10 --model=2 --tmc --tmc-num-samples=2 ",
"contrib/funsor/hmm.py --num-steps=1 --truncate=10 --model=3 --tmc --tmc-num-samples=2 ",
"contrib/funsor/hmm.py --num-steps=1 --truncate=10 --model=4 --tmc --tmc-num-samples=2 ",
"contrib/funsor/hmm.py --num-steps=1 --truncate=10 --model=5 --tmc --tmc-num-samples=2 ",
"contrib/funsor/hmm.py --num-steps=1 --truncate=10 --model=6 --tmc --tmc-num-samples=2 ",
"contrib/funsor/hmm.py --num-steps=1 --truncate=10 --model=6 --tmc --tmc-num-samples=2 -rp",
]
CUDA_EXAMPLES = [
"air/main.py --num-steps=1 --cuda",
"baseball.py --num-samples=200 --warmup-steps=100 --num-chains=2 --cuda",
"contrib/cevae/synthetic.py --num-epochs=1 --cuda",
"contrib/epidemiology/sir.py --nojit -t=2 -w=2 -n=4 -d=20 -p=1000 -f 2 --cuda",
"contrib/epidemiology/sir.py --nojit -t=2 -w=2 -n=4 -d=20 -p=1000 -f 2 -nb=16 --cuda",
"contrib/epidemiology/sir.py --nojit -t=2 -w=2 -n=4 -d=20 -p=1000 -f 2 --haar --cuda",
"contrib/epidemiology/regional.py --nojit -t=2 -w=2 -n=4 -r=3 -d=20 -p=1000 -f 2 --cuda",
"contrib/epidemiology/regional.py --nojit -t=2 -w=2 -n=4 -r=3 -d=20 -p=1000 -f 2 --haar --cuda",
"contrib/gp/sv-dkl.py --epochs=1 --num-inducing=4 --cuda",
"contrib/mue/FactorMuE.py --test --small --include-stop --no-plots --no-save --cuda --cpu-data --pin-mem",
"contrib/mue/FactorMuE.py --test --small -ard -idfac --no-substitution-matrix --no-plots --no-save --cuda",
"contrib/mue/ProfileHMM.py --test --small --no-plots --no-save --cuda --cpu-data --pin-mem",
"contrib/mue/ProfileHMM.py --test --small --include-stop --no-plots --no-save --cuda",
"lkj.py --n=50 --num-chains=1 --warmup-steps=100 --num-samples=200 --cuda",
"dmm.py --num-epochs=1 --cuda",
"dmm.py --num-epochs=1 --num-iafs=1 --cuda",
"dmm.py --num-epochs=1 --tmc --tmc-num-samples=2 --cuda",
"dmm.py --num-epochs=1 --tmcelbo --tmc-num-samples=2 --cuda",
"einsum.py --cuda",
"hmm.py --num-steps=1 --truncate=10 --model=0 --cuda",
"hmm.py --num-steps=1 --truncate=10 --model=1 --cuda",
"hmm.py --num-steps=1 --truncate=10 --model=2 --cuda",
"hmm.py --num-steps=1 --truncate=10 --model=3 --cuda",
"hmm.py --num-steps=1 --truncate=10 --model=4 --cuda",
"hmm.py --num-steps=1 --truncate=10 --model=5 --cuda",
"hmm.py --num-steps=1 --truncate=10 --model=6 --cuda",
"hmm.py --num-steps=1 --truncate=10 --model=6 --cuda --raftery-parameterization",
"hmm.py --num-steps=1 --truncate=10 --model=7 --cuda",
"hmm.py --num-steps=1 --truncate=10 --model=0 --tmc --tmc-num-samples=2 --cuda",
"hmm.py --num-steps=1 --truncate=10 --model=1 --tmc --tmc-num-samples=2 --cuda",
"hmm.py --num-steps=1 --truncate=10 --model=2 --tmc --tmc-num-samples=2 --cuda",
"hmm.py --num-steps=1 --truncate=10 --model=3 --tmc --tmc-num-samples=2 --cuda",
"hmm.py --num-steps=1 --truncate=10 --model=4 --tmc --tmc-num-samples=2 --cuda",
"hmm.py --num-steps=1 --truncate=10 --model=5 --tmc --tmc-num-samples=2 --cuda",
"hmm.py --num-steps=1 --truncate=10 --model=6 --tmc --tmc-num-samples=2 --cuda",
"scanvi/scanvi.py --num-epochs 1 --dataset mock --cuda",
"sir_hmc.py -t=2 -w=2 -n=4 -d=2 -m=1 --enum --cuda",
"sir_hmc.py -t=2 -w=2 -n=4 -d=2 -p=10000 --sequential --cuda",
"sir_hmc.py -t=2 -w=2 -n=4 -d=100 -p=10000 --cuda",
"svi_torch.py --num-epochs=2 --size=400 --cuda",
"svi_horovod.py --num-epochs=2 --size=400 --cuda --no-horovod",
pytest.param(
"svi_lightning.py --max_epochs=2 --size=400 --accelerator gpu --devices 1",
marks=[requires_lightning],
),
"vae/vae.py --num-epochs=1 --cuda",
"vae/ss_vae_M2.py --num-epochs=1 --cuda",
"vae/ss_vae_M2.py --num-epochs=1 --aux-loss --cuda",
"vae/ss_vae_M2.py --num-epochs=1 --enum-discrete=parallel --cuda",
"vae/ss_vae_M2.py --num-epochs=1 --enum-discrete=sequential --cuda",
"cvae/main.py --num-quadrant-inputs=1 --num-epochs=1 --cuda",
"contrib/funsor/hmm.py --num-steps=1 --truncate=10 --model=0 --cuda",
"contrib/funsor/hmm.py --num-steps=1 --truncate=10 --model=1 --cuda",
"contrib/funsor/hmm.py --num-steps=1 --truncate=10 --model=2 --cuda",
"contrib/funsor/hmm.py --num-steps=1 --truncate=10 --model=3 --cuda",
"contrib/funsor/hmm.py --num-steps=1 --truncate=10 --model=4 --cuda",
"contrib/funsor/hmm.py --num-steps=1 --truncate=10 --model=5 --cuda",
"contrib/funsor/hmm.py --num-steps=1 --truncate=10 --model=6 --cuda",
"contrib/funsor/hmm.py --num-steps=1 --truncate=10 --model=6 --cuda --raftery-parameterization ",
"contrib/funsor/hmm.py --num-steps=1 --truncate=10 --model=1 --cuda--tmc --tmc-num-samples=2 ",
"contrib/funsor/hmm.py --num-steps=1 --truncate=10 --model=2 --cuda--tmc --tmc-num-samples=2 ",
"contrib/funsor/hmm.py --num-steps=1 --truncate=10 --model=3 --cuda--tmc --tmc-num-samples=2 ",
"contrib/funsor/hmm.py --num-steps=1 --truncate=10 --model=4 --cuda--tmc --tmc-num-samples=2 ",
"contrib/funsor/hmm.py --num-steps=1 --truncate=10 --model=5 --cuda--tmc --tmc-num-samples=2 ",
"contrib/funsor/hmm.py --num-steps=1 --truncate=10 --model=6 --cuda--tmc --tmc-num-samples=2 ",
"contrib/funsor/hmm.py --num-steps=1 --truncate=10 --model=6 --cuda--tmc --tmc-num-samples=2 -rp",
]
def xfail_jit(*args, **kwargs):
reason = kwargs.pop("reason", "not jittable")
return pytest.param(
*args,
marks=[
pytest.mark.xfail(reason=reason),
pytest.mark.skipif("CI" in os.environ, reason="slow test"),
]
)
JIT_EXAMPLES = [
"air/main.py --num-steps=1 --jit",
xfail_jit(
"baseball.py --num-samples=200 --warmup-steps=100 --jit",
reason="unreproducible RuntimeError on CI",
),
"contrib/autoname/mixture.py --num-epochs=1 --jit",
"contrib/cevae/synthetic.py --num-epochs=1 --jit",
"contrib/epidemiology/sir.py --jit -np=128 -t=2 -w=2 -n=4 -d=20 -p=1000 -f 2",
"contrib/epidemiology/sir.py --jit -np=128 -ss=2 -n=4 -d=20 -p=1000 -f 2 --svi",
"contrib/epidemiology/regional.py --jit -t=2 -w=2 -n=4 -r=3 -d=20 -p=1000 -f 2",
"contrib/epidemiology/regional.py --jit -ss=2 -n=4 -r=3 -d=20 -p=1000 -f 2 --svi",
xfail_jit("contrib/gp/sv-dkl.py --epochs=1 --num-inducing=4 --jit"),
"contrib/mue/FactorMuE.py --test --small --include-stop --no-plots --no-save --jit",
"contrib/mue/FactorMuE.py --test --small -ard -idfac --no-substitution-matrix --no-plots --no-save --jit",
"contrib/mue/ProfileHMM.py --test --small --no-plots --no-save --jit",
"contrib/mue/ProfileHMM.py --test --small --include-stop --no-plots --no-save --jit",
xfail_jit("dmm.py --num-epochs=1 --jit"),
xfail_jit("dmm.py --num-epochs=1 --num-iafs=1 --jit"),
"eight_schools/mcmc.py --num-samples=500 --warmup-steps=100 --jit",
"eight_schools/svi.py --num-epochs=1 --jit",
"hmm.py --num-steps=1 --truncate=10 --model=1 --jit",
"hmm.py --num-steps=1 --truncate=10 --model=2 --jit",
"hmm.py --num-steps=1 --truncate=10 --model=3 --jit",
"hmm.py --num-steps=1 --truncate=10 --model=4 --jit",
"hmm.py --num-steps=1 --truncate=10 --model=5 --jit",
"hmm.py --num-steps=1 --truncate=10 --model=7 --jit",
xfail_jit(
"hmm.py --num-steps=1 --truncate=10 --model=1 --tmc --tmc-num-samples=2 --jit"
),
xfail_jit(
"hmm.py --num-steps=1 --truncate=10 --model=2 --tmc --tmc-num-samples=2 --jit"
),
xfail_jit(
"hmm.py --num-steps=1 --truncate=10 --model=3 --tmc --tmc-num-samples=2 --jit"
),
xfail_jit(
"hmm.py --num-steps=1 --truncate=10 --model=4 --tmc --tmc-num-samples=2 --jit"
),
"lda.py --num-steps=2 --num-words=100 --num-docs=100 --num-words-per-doc=8 --jit",
"minipyro.py --backend=pyro --jit",
"minipyro.py --jit",
"sir_hmc.py -t=2 -w=2 -n=4 -d=2 -m=1 --enum --jit",
"sir_hmc.py -t=2 -w=2 -n=4 -d=2 -p=10000 --sequential --jit",
xfail_jit("sir_hmc.py -t=2 -w=2 -n=4 -p=10000 --jit"),
xfail_jit("vae/ss_vae_M2.py --num-epochs=1 --aux-loss --jit"),
"vae/ss_vae_M2.py --num-epochs=1 --enum-discrete=parallel --jit",
"vae/ss_vae_M2.py --num-epochs=1 --enum-discrete=sequential --jit",
"vae/ss_vae_M2.py --num-epochs=1 --jit",
"vae/vae.py --num-epochs=1 --jit",
"vae/vae_comparison.py --num-epochs=1 --jit",
"contrib/funsor/hmm.py --num-steps=1 --truncate=10 --model=1 --jit",
"contrib/funsor/hmm.py --num-steps=1 --truncate=10 --model=2 --jit",
"contrib/funsor/hmm.py --num-steps=1 --truncate=10 --model=3 --jit",
"contrib/funsor/hmm.py --num-steps=1 --truncate=10 --model=4 --jit",
"contrib/funsor/hmm.py --num-steps=1 --truncate=10 --model=5 --jit",
"contrib/funsor/hmm.py --num-steps=1 --truncate=10 --model=6 --jit",
"contrib/funsor/hmm.py --num-steps=1 --truncate=10 --model=6 --jit --raftery-parameterization ",
]
HOROVOD_EXAMPLES = [
"svi_horovod.py --num-epochs=2 --size=400",
pytest.param(
"svi_horovod.py --num-epochs=2 --size=400 --cuda", marks=[requires_cuda]
),
]
FUNSOR_EXAMPLES = [
xfail_param(
"contrib/funsor/hmm.py --num-steps=1 --truncate=10 --model=0 --funsor",
reason="unreproducible recursion error on travis?",
),
"contrib/funsor/hmm.py --num-steps=1 --truncate=10 --model=1 --funsor",
"contrib/funsor/hmm.py --num-steps=1 --truncate=10 --model=2 --funsor",
"contrib/funsor/hmm.py --num-steps=1 --truncate=10 --model=3 --funsor",
"contrib/funsor/hmm.py --num-steps=1 --truncate=10 --model=4 --funsor",
xfail_param(
"contrib/funsor/hmm.py --num-steps=1 --truncate=10 --model=5 --funsor",
reason="https://github.com/pyro-ppl/pyro/issues/3046",
run=False,
),
"contrib/funsor/hmm.py --num-steps=1 --truncate=10 --model=6 --funsor",
"contrib/funsor/hmm.py --num-steps=1 --truncate=10 --model=6 --raftery-parameterization --funsor",
"contrib/funsor/hmm.py --num-steps=1 --truncate=10 --model=6 --jit --funsor",
"contrib/funsor/hmm.py --num-steps=1 --truncate=10 --model=6 --jit --raftery-parameterization --funsor",
xfail_param(
"contrib/funsor/hmm.py --num-steps=1 --truncate=10 --model=0 --tmc --tmc-num-samples=2 --funsor",
reason="unreproducible recursion error on travis?",
),
"contrib/funsor/hmm.py --num-steps=1 --truncate=10 --model=1 --tmc --tmc-num-samples=2 --funsor",
"contrib/funsor/hmm.py --num-steps=1 --truncate=10 --model=2 --tmc --tmc-num-samples=2 --funsor",
"contrib/funsor/hmm.py --num-steps=1 --truncate=10 --model=3 --tmc --tmc-num-samples=2 --funsor",
"contrib/funsor/hmm.py --num-steps=1 --truncate=10 --model=4 --tmc --tmc-num-samples=2 --funsor",
"contrib/funsor/hmm.py --num-steps=1 --truncate=10 --model=5 --tmc --tmc-num-samples=2 --funsor",
"contrib/funsor/hmm.py --num-steps=1 --truncate=10 --model=6 --tmc --tmc-num-samples=2 --funsor",
"contrib/funsor/hmm.py --num-steps=1 --truncate=10 --model=6 --tmc --tmc-num-samples=2 --funsor -rp",
"contrib/funsor/hmm.py --num-steps=1 --truncate=10 --model=6 --jit --tmc --tmc-num-samples=2 --funsor",
"contrib/funsor/hmm.py --num-steps=1 --truncate=10 --model=6 --jit --tmc --tmc-num-samples=2 --funsor -rp",
]
def test_coverage():
cpu_tests = set(
(e if isinstance(e, str) else e.values[0]).split()[0] for e in CPU_EXAMPLES
)
cuda_tests = set(
(e if isinstance(e, str) else e.values[0]).split()[0] for e in CUDA_EXAMPLES
)
jit_tests = set(
(e if isinstance(e, str) else e.values[0]).split()[0] for e in JIT_EXAMPLES
)
for root, dirs, files in os.walk(EXAMPLES_DIR):
for basename in files:
if not basename.endswith(".py"):
continue
path = os.path.join(root, basename)
with open(path) as f:
text = f.read()
example = os.path.relpath(path, EXAMPLES_DIR)
if "__main__" in text:
if example not in cpu_tests:
pytest.fail(
"Example: {} not covered in CPU_EXAMPLES.".format(example)
)
if "--cuda" in text and example not in cuda_tests:
pytest.fail(
"Example: {} not covered by CUDA_EXAMPLES.".format(example)
)
if "--jit" in text and example not in jit_tests:
pytest.fail(
"Example: {} not covered by JIT_EXAMPLES.".format(example)
)
@pytest.mark.parametrize("example", CPU_EXAMPLES)
def test_cpu(example):
logger.info("Running:\npython examples/{}".format(example))
example = example.split()
filename, args = example[0], example[1:]
filename = os.path.join(EXAMPLES_DIR, filename)
check_call([sys.executable, filename] + args)
@requires_cuda
@pytest.mark.parametrize("example", CUDA_EXAMPLES)
def test_cuda(example):
logger.info("Running:\npython examples/{}".format(example))
example = example.split()
filename, args = example[0], example[1:]
filename = os.path.join(EXAMPLES_DIR, filename)
check_call([sys.executable, filename] + args)
@pytest.mark.parametrize("example", JIT_EXAMPLES)
def test_jit(example):
logger.info("Running:\npython examples/{}".format(example))
example = example.split()
filename, args = example[0], example[1:]
filename = os.path.join(EXAMPLES_DIR, filename)
check_call([sys.executable, filename] + args)
@requires_horovod
@pytest.mark.parametrize("np", [1, 2])
@pytest.mark.parametrize("example", HOROVOD_EXAMPLES)
def test_horovod(np, example):
if "cuda" in example and np > torch.cuda.device_count():
pytest.skip()
horovodrun = "horovodrun -np {} --mpi-args=--oversubscribe".format(np)
logger.info("Running:\n{} python examples/{}".format(horovodrun, example))
example = example.split()
filename, args = example[0], example[1:]
filename = os.path.join(EXAMPLES_DIR, filename)
check_call(horovodrun.split() + [sys.executable, filename] + args)
@requires_funsor
@pytest.mark.parametrize("example", FUNSOR_EXAMPLES)
def test_funsor(example):
logger.info("Running:\npython examples/{}".format(example))
example = example.split()
filename, args = example[0], example[1:]
filename = os.path.join(EXAMPLES_DIR, filename)
check_call([sys.executable, filename] + args)