repo stringclasses 454
values | file_path stringlengths 5 201 | extension stringclasses 1
value | content stringlengths 8 509k | num_lines int64 3 16.9k | size_bytes int64 8 511k |
|---|---|---|---|---|---|
pyro | tests/infer/mcmc/test_nuts.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import logging
import os
from collections import namedtuple
import pytest
import torch
import pyro
import pyro.distributions as dist
import pyro.optim as optim
import pyro.poutine as poutine
from pyro.contrib.conjugate.infer impo... | 566 | 20,409 |
pyro | tests/infer/mcmc/test_valid_models.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import io
import logging
import pytest
import torch
import pyro
import pyro.distributions as dist
import pyro.poutine as poutine
from pyro.infer import config_enumerate
from pyro.infer.mcmc import HMC, NUTS
from pyro.infer.mcmc.a... | 495 | 17,116 |
pyro | tests/infer/mcmc/test_mcmc_util.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
from functools import partial
import pytest
import torch
import pyro
import pyro.distributions as dist
from pyro.infer import Predictive
from pyro.infer.autoguide import (
init_to_feasible,
init_to_generated,
init_to_... | 139 | 4,106 |
pyro | tests/infer/mcmc/test_adaptation.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import pytest
import torch
from pyro.infer.mcmc.adaptation import (
ArrowheadMassMatrix,
BlockMassMatrix,
WarmupAdapter,
adapt_window,
)
from tests.common import assert_close, assert_equal
@pytest.mark.parametriz... | 73 | 2,472 |
pyro | tests/integration_tests/test_conjugate_gaussian_models.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import logging
import os
import time
from unittest import TestCase
import numpy as np
import pytest
import torch
import pyro
import pyro.distributions as dist
import pyro.optim as optim
from pyro.distributions.testing import fake... | 653 | 25,477 |
pyro | tests/integration_tests/test_tracegraph_elbo.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import logging
from unittest import TestCase
import numpy as np
import pytest
import torch
from torch import nn as nn
import pyro
import pyro.distributions as dist
import pyro.optim as optim
from pyro.distributions.testing import... | 633 | 25,003 |
pyro | tests/integration_tests/conftest.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import pytest
def pytest_collection_modifyitems(items):
for item in items:
if item.nodeid.startswith("tests/integration_tests"):
if "stage" not in item.keywords:
item.add_marker(pytest.mark... | 14 | 451 |
pyro | tests/ops/test_streaming.py | .py | # Copyright Contributors to the Pyro project.
# SPDX-License-Identifier: Apache-2.0
import functools
import pytest
import torch
from pyro.ops.streaming import (
CountMeanStats,
CountMeanVarianceStats,
CountStats,
StackStats,
StatsOfDict,
)
from tests.common import assert_close
def generate_data... | 110 | 3,172 |
pyro | tests/ops/test_provenance.py | .py | # Copyright Contributors to the Pyro project.
# SPDX-License-Identifier: Apache-2.0
import pytest
import torch
from pyro.ops.provenance import ProvenanceTensor, get_provenance, track_provenance
from tests.common import assert_equal, requires_cuda
@requires_cuda
@pytest.mark.parametrize(
"dtype1",
[
... | 69 | 1,855 |
pyro | tests/ops/test_integrator.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import logging
from collections import namedtuple
import pytest
import torch
from pyro.ops.integrator import velocity_verlet
from tests.common import assert_equal
logger = logging.getLogger(__name__)
TEST_EXAMPLES = []
EXAMPLE... | 181 | 4,558 |
pyro | tests/ops/test_stats.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import warnings
import pytest
import torch
from pyro.ops.stats import (
_cummin,
autocorrelation,
autocovariance,
crps_empirical,
effective_sample_size,
energy_score_empirical,
fit_generalized_pareto,
... | 376 | 11,712 |
pyro | tests/ops/test_indexing.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import itertools
import pytest
import torch
import pyro.distributions as dist
from pyro.distributions.util import broadcast_shape
from pyro.ops.indexing import Index, Vindex
from tests.common import assert_equal
class TensorMoc... | 170 | 6,117 |
pyro | tests/ops/test_arrowhead.py | .py | # Copyright Contributors to the Pyro project.
# SPDX-License-Identifier: Apache-2.0
import pytest
import torch
from pyro.ops.arrowhead import (
SymmArrowhead,
sqrt,
triu_gram,
triu_inverse,
triu_matvecmul,
)
from tests.common import assert_close
@pytest.mark.parametrize("head_size", [0, 2, 5])
d... | 59 | 1,733 |
pyro | tests/ops/test_newton.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import itertools
import logging
import pytest
import torch
from torch.autograd import grad
from pyro.ops.newton import newton_step
from tests.common import assert_equal
logger = logging.getLogger(__name__)
def random_inside_un... | 142 | 5,028 |
pyro | tests/ops/test_packed.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import itertools
import random
import pytest
import torch
from torch.distributions.utils import broadcast_all
from pyro.ops import packed
from tests.common import assert_equal
EXAMPLE_DIMS = [
"".join(dims)
for num_dims ... | 75 | 2,259 |
pyro | tests/ops/test_gaussian.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import math
from collections import OrderedDict
import pytest
import torch
from torch.distributions import constraints, transform_to
from torch.nn.functional import pad
import pyro.distributions as dist
from pyro.distributions.ut... | 613 | 23,038 |
pyro | tests/ops/test_gamma_gaussian.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import math
import pytest
import torch
from torch.nn.functional import pad
import pyro.distributions as dist
from pyro.distributions.util import broadcast_shape
from pyro.ops.gamma_gaussian import (
GammaGaussian,
gamma_a... | 359 | 12,357 |
pyro | tests/ops/gaussian.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import torch
import pyro.distributions as dist
from pyro.ops.gaussian import Gaussian
from tests.common import assert_close
def random_gaussian(batch_shape, dim, rank=None, *, requires_grad=False):
"""
Generate a random ... | 48 | 1,675 |
pyro | tests/ops/test_welford.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import numpy as np
import pytest
import torch
from pyro.ops.welford import WelfordArrowheadCovariance, WelfordCovariance
from pyro.util import optional
from tests.common import assert_equal
@pytest.mark.filterwarnings("ignore:.*... | 83 | 3,133 |
pyro | tests/ops/test_contract.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import itertools
import numbers
from collections import OrderedDict
import opt_einsum
import pytest
import torch
import pyro.ops.jit
from pyro.distributions.util import logsumexp
from pyro.ops.contract import (
_partition_ter... | 836 | 26,142 |
pyro | tests/ops/test_linalg.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import pytest
import torch
from pyro.ops.linalg import rinverse
from tests.common import assert_equal
@pytest.mark.parametrize(
"A",
[
torch.tensor([[17.0]]),
torch.tensor([[1.0, 2.0], [2.0, -3.0]]),
... | 38 | 1,204 |
pyro | tests/ops/test_tensor_utils.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import math
import numpy as np
import pytest
import scipy.fftpack as fftpack
import torch
import pyro
from pyro.ops.tensor_utils import (
block_diag_embed,
block_diagonal,
convolve,
dct,
idct,
next_fast_le... | 197 | 6,592 |
pyro | tests/ops/test_ssm_gp.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import pytest
import torch
from pyro.ops.ssm_gp import MaternKernel
from tests.common import assert_equal
@pytest.mark.parametrize("num_gps", [1, 2, 3])
@pytest.mark.parametrize("nu", [0.5, 1.5, 2.5])
def test_matern_kernel(num_... | 36 | 1,153 |
pyro | tests/ops/gamma_gaussian.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import torch
import pyro.distributions as dist
from pyro.ops.gamma_gaussian import GammaGaussian
from tests.common import assert_close
def random_gamma_gaussian(batch_shape, dim, rank=None):
"""
Generate a random Gaussia... | 52 | 1,763 |
pyro | tests/ops/test_jit.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import torch
import pyro.ops.jit
from tests.common import assert_equal
def test_varying_len_args():
def fn(*args):
return sum(args)
jit_fn = pyro.ops.jit.trace(fn)
examples = [
[torch.tensor(1.0)],
... | 43 | 1,077 |
pyro | tests/ops/conftest.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import pytest
def pytest_collection_modifyitems(items):
for item in items:
if item.nodeid.startswith("tests/ops"):
if "stage" not in item.keywords:
item.add_marker(pytest.mark.stage("unit")... | 14 | 430 |
pyro | tests/ops/test_special.py | .py | # Copyright Contributors to the Pyro project.
# SPDX-License-Identifier: Apache-2.0
import pytest
import torch
from scipy.special import iv
from torch import tensor
from torch.autograd import grad
from pyro.ops.special import get_quad_rule, log_beta, log_binomial, log_I1, safe_log
from tests.common import assert_equa... | 104 | 2,760 |
pyro | tests/ops/einsum/test_torch_log.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import itertools
import pytest
import torch
from pyro.infer.util import torch_exp
from pyro.ops.einsum import contract
from tests.common import assert_equal
@pytest.mark.parametrize("min_size", [1, 2])
@pytest.mark.parametrize(... | 58 | 1,562 |
pyro | tests/ops/einsum/test_adjoint.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import gc
import itertools
import pytest
import torch
from pyro.ops.einsum import contract
from pyro.ops.einsum.adjoint import require_backward
from tests.common import assert_equal
EQUATIONS = [
"->",
"w->",
",w->",... | 144 | 4,420 |
pyro | tests/ops/einsum/conftest.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import pytest
def pytest_collection_modifyitems(items):
for item in items:
if item.nodeid.startswith("tests/ops/einsum"):
if "stage" not in item.keywords:
item.add_marker(pytest.mark.stage(... | 14 | 437 |
pyro | tests/contrib/test_zuko.py | .py | # Copyright Contributors to the Pyro project.
# SPDX-License-Identifier: Apache-2.0
import pytest
import torch
import pyro
from pyro.contrib.zuko import ZukoToPyro
from pyro.infer import SVI, Trace_ELBO
from pyro.optim import Adam
@pytest.mark.parametrize("multivariate", [True, False])
@pytest.mark.parametrize("rs... | 66 | 1,671 |
pyro | tests/contrib/test_util.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
from collections import OrderedDict
import pytest
import torch
from pyro.contrib.util import (
get_indices,
lexpand,
rdiag,
rexpand,
rmv,
rtril,
rvv,
tensor_to_dict,
)
from tests.common import asse... | 99 | 3,036 |
pyro | tests/contrib/test_minipyro.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import warnings
import pytest
import torch
from pytest import approx
from torch.distributions import constraints
from pyro.generic import distributions as dist
from pyro.generic import infer, ops, optim, pyro, pyro_backend
from t... | 261 | 8,701 |
pyro | tests/contrib/test_hessian.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import torch
import pyro.distributions as dist
from pyro.ops.hessian import hessian
from tests.common import assert_equal
def test_hessian_mvn():
tmp = torch.randn(3, 10)
cov = torch.matmul(tmp, tmp.t())
mvn = dist.M... | 32 | 853 |
pyro | tests/contrib/conftest.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import pytest
def pytest_collection_modifyitems(items):
for item in items:
if item.nodeid.startswith("tests/contrib"):
if "stage" not in item.keywords:
item.add_marker(pytest.mark.stage("in... | 14 | 449 |
pyro | tests/contrib/cevae/test_cevae.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import io
import warnings
import pytest
import torch
import pyro
import pyro.distributions as dist
from pyro.contrib.cevae import CEVAE, DistributionNet
from tests.common import assert_close
DIST_NETS = [cls.__name__.lower()[:-3... | 72 | 2,388 |
pyro | tests/contrib/funsor/test_pyroapi_funsor.py | .py | # Copyright Contributors to the Pyro project.
# SPDX-License-Identifier: Apache-2.0
import pytest
try:
# triggers backend registration
import funsor
import pyro.contrib.funsor # noqa: F401
funsor.set_backend("torch")
except ImportError:
pytestmark = pytest.mark.skip()
from pyroapi import pyro_... | 24 | 488 |
pyro | tests/contrib/funsor/test_infer_discrete.py | .py | # Copyright Contributors to the Pyro project.
# SPDX-License-Identifier: Apache-2.0
import logging
import os
import pyroapi
import pytest
import torch
from pyro.infer.autoguide import AutoNormal
from tests.common import assert_equal
# put all funsor-related imports here, so test collection works without funsor
try:... | 457 | 16,722 |
pyro | tests/contrib/funsor/test_enum_funsor.py | .py | # Copyright Contributors to the Pyro project.
# SPDX-License-Identifier: Apache-2.0
import logging
import os
import pyroapi
import pytest
import torch
from torch.autograd import grad
from torch.distributions import constraints
from pyro.ops.indexing import Vindex
from pyro.util import torch_isnan
from tests.common i... | 1,946 | 71,964 |
pyro | tests/contrib/funsor/test_valid_models_sequential_plate.py | .py | # Copyright Contributors to the Pyro project.
# SPDX-License-Identifier: Apache-2.0
import logging
import pytest
import torch
from pyro.ops.indexing import Vindex
# put all funsor-related imports here, so test collection works without funsor
try:
import funsor
import pyro.contrib.funsor
funsor.set_bac... | 127 | 4,418 |
pyro | tests/contrib/funsor/test_named_handlers.py | .py | # Copyright Contributors to the Pyro project.
# SPDX-License-Identifier: Apache-2.0
import logging
from collections import OrderedDict
import pytest
import torch
# put all funsor-related imports here, so test collection works without funsor
try:
import funsor
from funsor.tensor import Tensor
import pyro... | 159 | 5,329 |
pyro | tests/contrib/funsor/test_valid_models_enum.py | .py | # Copyright Contributors to the Pyro project.
# SPDX-License-Identifier: Apache-2.0
import contextlib
import logging
import os
from collections import defaultdict
from queue import LifoQueue
import pytest
import torch
from pyro.infer.enum import iter_discrete_escape, iter_discrete_extend
from pyro.ops.indexing impor... | 504 | 17,970 |
pyro | tests/contrib/funsor/test_tmc.py | .py | # Copyright Contributors to the Pyro project.
# SPDX-License-Identifier: Apache-2.0
import logging
import math
import pytest
import torch
from torch.autograd import grad
from torch.distributions import constraints
from tests.common import assert_equal
# put all funsor-related imports here, so test collection works ... | 213 | 7,191 |
pyro | tests/contrib/funsor/test_vectorized_markov.py | .py | # Copyright Contributors to the Pyro project.
# SPDX-License-Identifier: Apache-2.0
import pytest
import torch
from pyroapi import pyro_backend
from torch.distributions import constraints
from pyro.ops.indexing import Vindex
# put all funsor-related imports here, so test collection works without funsor
try:
impo... | 850 | 30,783 |
pyro | tests/contrib/funsor/test_valid_models_plate.py | .py | # Copyright Contributors to the Pyro project.
# SPDX-License-Identifier: Apache-2.0
import logging
import pytest
import torch
from pyro.ops.indexing import Vindex
from tests.common import xfail_param
# put all funsor-related imports here, so test collection works without funsor
try:
import funsor
import py... | 201 | 7,546 |
pyro | tests/contrib/funsor/conftest.py | .py | # Copyright Contributors to the Pyro project.
# SPDX-License-Identifier: Apache-2.0
import pytest
def pytest_collection_modifyitems(items):
for item in items:
if item.nodeid.startswith("tests/contrib/funsor"):
if "stage" not in item.keywords:
item.add_marker(pytest.mark.stage(... | 16 | 602 |
pyro | tests/contrib/epidemiology/test_util.py | .py | # Copyright Contributors to the Pyro project.
# SPDX-License-Identifier: Apache-2.0
import pytest
import torch
from pyro.contrib.epidemiology.util import cat2, clamp
from tests.common import assert_equal
@pytest.mark.parametrize("min", [None, 0.0, (), (2,)], ids=str)
@pytest.mark.parametrize("max", [None, 1.0, (), ... | 45 | 1,492 |
pyro | tests/contrib/epidemiology/test_models.py | .py | # Copyright Contributors to the Pyro project.
# SPDX-License-Identifier: Apache-2.0
import logging
import math
import pytest
import torch
import pyro
import pyro.distributions as dist
from pyro.contrib.epidemiology.models import (
HeterogeneousRegionalSIRModel,
HeterogeneousSIRModel,
OverdispersedSEIRMod... | 683 | 22,313 |
pyro | tests/contrib/epidemiology/test_distributions.py | .py | # Copyright Contributors to the Pyro project.
# SPDX-License-Identifier: Apache-2.0
import math
import pytest
import torch
from torch.distributions.transforms import SigmoidTransform
import pyro.distributions as dist
from pyro.contrib.epidemiology import beta_binomial_dist, binomial_dist, infection_dist
from pyro.co... | 280 | 9,012 |
pyro | tests/contrib/epidemiology/test_quant.py | .py | # Copyright Contributors to the Pyro project.
# SPDX-License-Identifier: Apache-2.0
import pytest
import torch
from pyro.contrib.epidemiology.util import compute_bin_probs
@pytest.mark.parametrize("num_quant_bins", [2, 4, 8, 12, 16])
def test_quantization_scheme(num_quant_bins, num_samples=1000 * 1000):
min, ma... | 30 | 925 |
pyro | tests/contrib/bnn/test_hidden_layer.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import pytest
import torch
import torch.nn.functional as F
from torch.distributions import Normal
from pyro.contrib.bnn import HiddenLayer
from tests.common import assert_equal
@pytest.mark.parametrize("non_linearity", [F.relu])... | 68 | 2,100 |
pyro | tests/contrib/autoname/test_named.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import torch
import pyro
import pyro.distributions as dist
from pyro import poutine
from pyro.contrib.autoname import named
def get_sample_names(tr):
return set(
[
name
for name, site in tr.no... | 117 | 3,676 |
pyro | tests/contrib/autoname/test_scoping.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import logging
import torch
import pyro
import pyro.distributions.torch as dist
import pyro.poutine as poutine
from pyro.contrib.autoname import name_count, scope
logger = logging.getLogger(__name__)
def test_multi_nested():
... | 187 | 4,628 |
pyro | tests/contrib/autoname/test_autoname.py | .py | # Copyright Contributors to the Pyro project.
# SPDX-License-Identifier: Apache-2.0
import torch
import pyro
import pyro.distributions.torch as dist
import pyro.poutine as poutine
from pyro.contrib.autoname import autoname, sample
def test_basic_scope():
@autoname
def f1():
sample(dist.Normal(0, 1))... | 373 | 9,663 |
pyro | tests/contrib/oed/test_xexpx.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import pytest
import torch
from pyro.contrib.oed.eig import xexpx
@pytest.mark.parametrize(
"argument,output",
[
(torch.tensor([float("-inf")]), torch.tensor([0.0])),
(torch.tensor([0.0]), torch.tensor([0... | 20 | 470 |
pyro | tests/contrib/oed/test_finite_spaces_eig.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
from contextlib import ExitStack
import pytest
import torch
import pyro
import pyro.distributions as dist
import pyro.optim as optim
from pyro.contrib.oed.eig import (
donsker_varadhan_eig,
lfire_eig,
marginal_eig,
... | 273 | 7,851 |
pyro | tests/contrib/oed/test_ewma.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import math
import pytest
import torch
from pyro.contrib.oed.eig import EwmaLog
from tests.common import assert_equal
@pytest.mark.parametrize("alpha", [0.5, 0.9, 0.99])
def test_ewma(alpha, NS=10000, D=1):
ewma_log = EwmaL... | 51 | 1,464 |
pyro | tests/contrib/oed/test_glmm.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import pytest
import torch
from torch.distributions.transforms import AffineTransform, SigmoidTransform
import pyro
import pyro.distributions as dist
import pyro.poutine as poutine
from pyro.contrib.oed.glmm import (
group_lin... | 178 | 5,729 |
pyro | tests/contrib/oed/test_linear_models_eig.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import pytest
import torch
import pyro
import pyro.distributions as dist
import pyro.optim as optim
from pyro.contrib.oed.eig import (
donsker_varadhan_eig,
laplace_eig,
lfire_eig,
marginal_eig,
marginal_likeli... | 314 | 9,466 |
pyro | tests/contrib/randomvariable/test_random_variable.py | .py | # Copyright Contributors to the Pyro project.
# SPDX-License-Identifier: Apache-2.0
import math
import torch
from pyro.distributions import Uniform
N_SAMPLES = 100
def test_add():
X = Uniform(0, 1).rv # (0, 1)
X = X + 1 # (1, 2)
X = 1 + X # (2, 3)
X += 1 # (3, 4)
x = X.dist.sample([N_SAMPL... | 84 | 1,893 |
pyro | tests/contrib/forecast/test_forecaster.py | .py | # Copyright Contributors to the Pyro project.
# SPDX-License-Identifier: Apache-2.0
import pytest
import torch
import pyro
import pyro.distributions as dist
import pyro.poutine as poutine
from pyro.contrib.forecast import Forecaster, ForecastingModel, HMCForecaster
from pyro.infer.autoguide import AutoDelta
from pyro... | 331 | 11,591 |
pyro | tests/contrib/forecast/test_evaluate.py | .py | # Copyright Contributors to the Pyro project.
# SPDX-License-Identifier: Apache-2.0
import math
import pytest
import torch
import pyro
import pyro.distributions as dist
from pyro.contrib.forecast import Forecaster, ForecastingModel, HMCForecaster, backtest
from pyro.contrib.forecast.evaluate import DEFAULT_METRICS
f... | 150 | 4,477 |
pyro | tests/contrib/forecast/test_util.py | .py | # Copyright Contributors to the Pyro project.
# SPDX-License-Identifier: Apache-2.0
import pytest
import torch
from torch.distributions import transform_to
import pyro.distributions as dist
from pyro.contrib.forecast.util import (
UNIVARIATE_DISTS,
UNIVARIATE_TRANSFORMS,
prefix_condition,
reshape_batc... | 157 | 5,539 |
pyro | tests/contrib/timeseries/test_lgssm.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import pytest
import torch
from pyro.contrib.timeseries import GenericLGSSM, GenericLGSSMWithGPNoiseModel
from tests.common import assert_equal
@pytest.mark.parametrize("model_class", ["lgssm", "lgssmgp"])
@pytest.mark.parametri... | 99 | 3,905 |
pyro | tests/contrib/timeseries/test_gp.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import math
import pytest
import torch
import pyro
from pyro.contrib.timeseries import (
DependentMaternGP,
GenericLGSSM,
GenericLGSSMWithGPNoiseModel,
IndependentMaternGP,
LinearlyCoupledMaternGP,
)
from pyro... | 172 | 5,986 |
pyro | tests/contrib/gp/test_models.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import logging
from collections import namedtuple
import pytest
import torch
import pyro.distributions as dist
from pyro.contrib.gp.kernels import RBF, Cosine, Matern32, WhiteNoise
from pyro.contrib.gp.likelihoods import Gaussian... | 456 | 15,052 |
pyro | tests/contrib/gp/test_kernels.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
from collections import namedtuple
import pytest
import torch
from pyro.contrib.gp.kernels import (
RBF,
Brownian,
Constant,
Coregionalize,
Cosine,
Exponent,
Exponential,
Linear,
Matern32,
... | 153 | 4,744 |
pyro | tests/contrib/gp/test_parameterized.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import torch
from torch.distributions import constraints
from torch.nn import Parameter
import pyro
import pyro.distributions as dist
from pyro.contrib.gp.parameterized import Parameterized
from pyro.nn.module import PyroParam, Py... | 156 | 4,723 |
pyro | tests/contrib/gp/test_conditional.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
from collections import namedtuple
import pytest
import torch
import pyro
from pyro.contrib.gp.kernels import Matern52, WhiteNoise
from pyro.contrib.gp.util import conditional
from tests.common import assert_equal
T = namedtuple... | 88 | 2,750 |
pyro | tests/contrib/gp/test_likelihoods.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
from collections import namedtuple
import pytest
import torch
from pyro.contrib.gp.kernels import RBF
from pyro.contrib.gp.likelihoods import Binary, MultiClass, Poisson
from pyro.contrib.gp.models import VariationalGP, Variation... | 124 | 4,731 |
pyro | tests/contrib/tracking/test_em.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import logging
import math
import pytest
import torch
from torch.distributions import constraints
import pyro
import pyro.distributions as dist
import pyro.poutine as poutine
from pyro.contrib.tracking.assignment import MarginalA... | 228 | 8,636 |
pyro | tests/contrib/tracking/test_measurements.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import torch
from pyro.contrib.tracking.measurements import PositionMeasurement
def test_PositionMeasurement():
dimension = 3
time = 0.232
frame_num = 5
measurement = PositionMeasurement(
mean=torch.rand(... | 30 | 934 |
pyro | tests/contrib/tracking/test_ekf.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import torch
from pyro.contrib.tracking.dynamic_models import NcpContinuous, NcvContinuous
from pyro.contrib.tracking.extended_kalman_filter import EKFState
from pyro.contrib.tracking.measurements import PositionMeasurement
from t... | 74 | 2,792 |
pyro | tests/contrib/tracking/test_hashing.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import logging
import pytest
import torch
from pyro.contrib.tracking.hashing import LSH, ApproxSet, merge_points
from tests.common import assert_equal
logger = logging.getLogger(__name__)
@pytest.mark.parametrize("scale", [-1.... | 159 | 4,601 |
pyro | tests/contrib/tracking/test_assignment.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import logging
import pytest
import torch
from torch.autograd import grad
import pyro
import pyro.distributions as dist
from pyro.contrib.tracking.assignment import (
MarginalAssignment,
MarginalAssignmentPersistent,
... | 358 | 14,126 |
pyro | tests/contrib/tracking/test_dynamic_models.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import torch
from pyro.contrib.tracking.dynamic_models import (
NcpContinuous,
NcpDiscrete,
NcvContinuous,
NcvDiscrete,
)
from tests.common import assert_equal, assert_not_equal
def assert_cov_validity(cov, eigen... | 189 | 5,020 |
pyro | tests/contrib/tracking/test_distributions.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import pytest
import torch
from pyro.contrib.tracking.distributions import EKFDistribution
from pyro.contrib.tracking.dynamic_models import NcpContinuous, NcvContinuous
@pytest.mark.parametrize("Model", [NcpContinuous, NcvContin... | 26 | 890 |
pyro | tests/contrib/mue/test_dataloaders.py | .py | # Copyright Contributors to the Pyro project.
# SPDX-License-Identifier: Apache-2.0
import pytest
import torch
from pyro.contrib.mue.dataloaders import BiosequenceDataset, alphabets, write
@pytest.mark.parametrize("source_type", ["list", "fasta"])
@pytest.mark.parametrize("alphabet", ["amino-acid", "dna", "ATC"])
@... | 117 | 3,607 |
pyro | tests/contrib/mue/test_models.py | .py | # Copyright Contributors to the Pyro project.
# SPDX-License-Identifier: Apache-2.0
import numpy as np
import pytest
import torch
from torch.optim import Adam
import pyro
from pyro.contrib.mue.dataloaders import BiosequenceDataset
from pyro.contrib.mue.models import FactorMuE, ProfileHMM
from pyro.optim import MultiS... | 108 | 3,213 |
pyro | tests/contrib/mue/test_missingdatahmm.py | .py | # Copyright Contributors to the Pyro project.
# SPDX-License-Identifier: Apache-2.0
import pytest
import torch
from pyro.contrib.mue.missingdatahmm import MissingDataDiscreteHMM
from pyro.distributions import Categorical, DiscreteHMM
def test_hmm_log_prob():
a0 = torch.tensor([0.9, 0.08, 0.02])
a = torch.te... | 557 | 18,642 |
pyro | tests/contrib/mue/test_statearrangers.py | .py | # Copyright Contributors to the Pyro project.
# SPDX-License-Identifier: Apache-2.0
import pytest
import torch
from pyro.contrib.mue.statearrangers import Profile, mg2k
def simpleprod(lst):
# Product of list of scalar tensors, as numpy would do it.
if len(lst) == 0:
return torch.tensor(1.0)
else... | 272 | 10,625 |
pyro | tests/contrib/easyguide/test_easyguide.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import io
import warnings
import pytest
import torch
from torch.distributions import constraints
import pyro
import pyro.distributions as dist
from pyro.contrib.easyguide import EasyGuide, easy_guide
from pyro.infer import SVI, T... | 256 | 8,618 |
pyro | tests/optim/test_multi.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import pytest
import torch
from torch.distributions import constraints
import pyro
import pyro.distributions as dist
import pyro.optim
import pyro.poutine as poutine
from pyro.optim.multi import (
MixedMultiOptimizer,
Newt... | 90 | 2,637 |
pyro | tests/optim/test_optim.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import os
from tempfile import TemporaryDirectory
from unittest import TestCase
import pytest
import torch
from torch.distributions import constraints
import pyro
import pyro.distributions as dist
import pyro.optim as optim
from ... | 561 | 19,397 |
pyro | tests/optim/conftest.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import pytest
def pytest_collection_modifyitems(items):
for item in items:
if item.nodeid.startswith("tests/optim"):
if "stage" not in item.keywords:
item.add_marker(pytest.mark.stage("unit... | 24 | 747 |
pyro | scripts/update_headers.py | .py | # Copyright Contributors to the Pyro project.
# SPDX-License-Identifier: Apache-2.0
import argparse
import glob
import os
import sys
root = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
blacklist = ["/build/", "/dist/", "/pyro/_version.py"]
file_types = [
("*.py", "# {}"),
("*.cpp", "// {}"),
]
... | 78 | 2,276 |
pyro | scripts/update_version.py | .py | # Copyright Contributors to the Pyro project.
# SPDX-License-Identifier: Apache-2.0
import glob
import os
import re
root = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
# Get new version.
with open(os.path.join(root, "pyro", "__init__.py")) as f:
for line in f:
if line.startswith("version_p... | 37 | 1,188 |
pyro | examples/hmm.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
"""
This example shows how to marginalize out discrete model variables in Pyro.
This combines Stochastic Variational Inference (SVI) with a
variable elimination algorithm, where we use enumeration to exactly
marginalize out some v... | 776 | 32,365 |
pyro | examples/sparse_gamma_def.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
# This is an implementation of the sparse gamma deep exponential family model described in
# Ranganath, Rajesh, Tang, Linpeng, Charlin, Laurent, and Blei, David. Deep exponential families.
#
# To do inference we use one of the foll... | 298 | 12,106 |
pyro | examples/neutra.py | .py | # Copyright Contributors to the Pyro project.
# SPDX-License-Identifier: Apache-2.0
"""
This example illustrates the use of `NeuTraReparam` to run neural transport HMC [1]
on a toy model that draws from a banana-shaped bivariate distribution [2]. We first
train an autoguide by using `AutoNormalizingFlow` that learns a... | 283 | 9,381 |
pyro | examples/einsum.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
"""
This example demonstrates how to use plated ``einsum`` with different backends
to compute logprob, gradients, MAP estimates, posterior samples, and marginals.
The interface for adjoint algorithms requires four steps:
1. Call ... | 227 | 7,580 |
pyro | examples/toy_mixture_model_discrete_enumeration.py | .py | # Copyright Contributors to the Pyro project.
# SPDX-License-Identifier: Apache-2.0
"""
A toy mixture model to provide a simple example for implementing discrete enumeration.
(A) -> [B] -> (C)
A is an observed Bernoulli variable with Beta prior.
B is a hidden variable which is a mixture of two Bernoulli distribution... | 142 | 5,184 |
pyro | examples/svi_lightning.py | .py | # Copyright Contributors to the Pyro project.
# SPDX-License-Identifier: Apache-2.0
# Distributed training via Pytorch Lightning.
#
# This tutorial demonstrates how to distribute SVI training across multiple
# machines (or multiple GPUs on one or more machines) using the PyTorch Lightning
# library. PyTorch Lightning ... | 126 | 4,919 |
pyro | examples/baseball.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import argparse
import logging
import math
import pandas as pd
import torch
import pyro
from pyro.distributions import Beta, Binomial, HalfCauchy, Normal, Pareto, Uniform
from pyro.distributions.util import scalar_like
from pyro.... | 422 | 16,321 |
pyro | examples/lkj.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import argparse
import torch
import pyro
import pyro.distributions as dist
from pyro.infer.mcmc import NUTS
from pyro.infer.mcmc.api import MCMC
"""
This simple example is intended to demonstrate how to use an LKJ prior with
a m... | 78 | 2,735 |
pyro | examples/sir_hmc.py | .py | # Copyright Contributors to the Pyro project.
# SPDX-License-Identifier: Apache-2.0
# Introduction
# ============
#
# This advanced Pyro tutorial demonstrates a number of inference and prediction
# tricks in the context of epidemiological models, specifically stochastic
# discrete time compartmental models with large ... | 676 | 24,193 |
pyro | examples/inclined_plane.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import argparse
import numpy as np
import torch
import pyro
from pyro.distributions import Normal, Uniform
from pyro.infer import EmpiricalMarginal, Importance
"""
Samantha really likes physics---but she likes Pyro even more. I... | 153 | 5,455 |
pyro | examples/minipyro.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
"""
This example demonstrates the functionality of `pyro.contrib.minipyro`,
which is a minimal implementation of the Pyro Probabilistic Programming
Language that was created for didactic purposes.
"""
import argparse
import torch... | 76 | 2,971 |
pyro | examples/smcfilter.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import argparse
import logging
import torch
import pyro
import pyro.distributions as dist
from pyro.infer import SMCFilter
logging.basicConfig(format="%(relativeCreated) 9d %(message)s", level=logging.INFO)
"""
This file demons... | 119 | 3,358 |
pyro | examples/svi_horovod.py | .py | # Copyright Contributors to the Pyro project.
# SPDX-License-Identifier: Apache-2.0
# Distributed training via Horovod.
#
# This tutorial demonstrates how to distribute SVI training across multiple
# machines (or multiple GPUs on one or more machines) using the Horovod
# library. Horovod enables data-parallel training... | 170 | 6,668 |
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