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 | examples/svi_torch.py | .py | # Copyright Contributors to the Pyro project.
# SPDX-License-Identifier: Apache-2.0
# Using vanilla PyTorch to perform optimization in SVI.
#
# This tutorial demonstrates how to use standard PyTorch optimizers, dataloaders and training loops
# to perform optimization in SVI. This is useful when you want to use custom ... | 112 | 5,054 |
pyro | examples/sparse_regression.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import argparse
import math
import numpy as np
import torch
from torch.optim import Adam
import pyro
import pyro.distributions as dist
from pyro import poutine
from pyro.infer import Trace_ELBO
from pyro.infer.autoguide import Au... | 380 | 13,618 |
pyro | examples/lda.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
"""
This example implements amortized Latent Dirichlet Allocation [1],
demonstrating how to marginalize out discrete assignment variables in a Pyro
model. This model and inference algorithm treat documents as vectors of
categorical... | 171 | 6,848 |
pyro | examples/dmm.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
"""
An implementation of a Deep Markov Model in Pyro based on reference [1].
This is essentially the DKS variant outlined in the paper. The primary difference
between this implementation and theirs is that in our version any KL div... | 602 | 25,375 |
pyro | examples/mixed_hmm/model.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import torch
from torch.distributions import constraints
import pyro
import pyro.distributions as dist
from pyro import poutine
from pyro.infer import config_enumerate
from pyro.ops.indexing import Vindex
def guide_generic(confi... | 273 | 9,884 |
pyro | examples/mixed_hmm/seal_data.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import os
from urllib.request import urlopen
import pandas as pd
import torch
MISSING = 1e-6
def download_seal_data(filename):
"""download the preprocessed seal data and save it to filename"""
url = "https://github.com/... | 76 | 2,560 |
pyro | examples/mixed_hmm/experiment.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import argparse
import functools
import json
import os
import uuid
import torch
from model import guide_generic, model_generic
from seal_data import prepare_seal
import pyro
import pyro.poutine as poutine
from pyro.infer import T... | 181 | 5,959 |
pyro | examples/rsa/semantic_parsing.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
"""
Combining models of RSA pragmatics and CCG-based compositional semantics.
Taken from: http://dippl.org/examples/zSemanticPragmaticMashup.html
"""
import argparse
import collections
import torch
from search_inference import B... | 358 | 8,669 |
pyro | examples/rsa/hyperbole.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
"""
Interpreting hyperbole with RSA models of pragmatics.
Taken from: https://gscontras.github.io/probLang/chapters/03-nonliteral.html
"""
import argparse
import collections
import torch
from search_inference import HashingMargi... | 225 | 6,737 |
pyro | examples/rsa/generics.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
"""
Interpreting generic statements with RSA models of pragmatics.
Taken from:
[0] http://forestdb.org/models/generics.html
[1] https://gscontras.github.io/probLang/chapters/07-generics.html
"""
import argparse
import collections... | 185 | 5,389 |
pyro | examples/rsa/search_inference.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
"""
Inference algorithms and utilities used in the RSA example models.
Adapted from: http://dippl.org/chapters/03-enumeration.html
"""
import collections
import functools
import queue
import torch
import pyro.distributions as d... | 224 | 7,562 |
pyro | examples/rsa/schelling_false.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
"""
Schelling coordination game with false belief:
Two spies, Alice and Bob, claim to want to meet.
Bob wants to meet Alice, but Alice actually wants to avoid Bob.
They must choose between two locations without communicating
by re... | 106 | 3,335 |
pyro | examples/rsa/schelling.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
"""
Schelling coordination game:
Two spies, Alice and Bob, want to meet.
They must choose between two locations without communicating
by recursively reasoning about one another.
Taken from: http://forestdb.org/models/schelling.ht... | 90 | 2,840 |
pyro | examples/capture_recapture/cjs.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
"""
We show how to implement several variants of the Cormack-Jolly-Seber (CJS)
[4, 5, 6] model used in ecology to analyze animal capture-recapture data.
For a discussion of these models see reference [1].
We make use of two datase... | 387 | 14,374 |
pyro | examples/eight_schools/mcmc.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import argparse
import logging
import data
import torch
import pyro
import pyro.distributions as dist
import pyro.poutine as poutine
from pyro.infer import MCMC, NUTS
logging.basicConfig(format="%(message)s", level=logging.INFO)... | 70 | 1,818 |
pyro | examples/eight_schools/data.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import torch
J = 8
y = torch.tensor([28, 8, -3, 7, -1, 1, 18, 12]).type(torch.Tensor)
sigma = torch.tensor([15, 10, 16, 11, 9, 11, 10, 18]).type(torch.Tensor)
| 9 | 249 |
pyro | examples/eight_schools/svi.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import argparse
import logging
import torch
from data import J, sigma, y
from torch.distributions import constraints, transforms
import pyro
import pyro.distributions as dist
from pyro.infer import SVI, JitTrace_ELBO, Trace_ELBO
... | 96 | 3,025 |
pyro | examples/air/main.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
"""
AIR applied to the multi-mnist data set [1].
[1] Eslami, SM Ali, et al. "Attend, infer, repeat: Fast scene
understanding with generative models." Advances in Neural Information
Processing Systems. 2016.
"""
import argparse
im... | 454 | 14,656 |
pyro | examples/air/viz.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import math
from collections import namedtuple
import numpy as np
from PIL import Image, ImageDraw
def bounding_box(z_where, x_size):
"""This doesn't take into account interpolation, but it's close
enough to be usable.""... | 77 | 2,528 |
pyro | examples/air/modules.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import torch
import torch.nn as nn
from torch.nn.functional import softplus
# Takes pixel intensities of the attention window to parameters (mean,
# standard deviation) of the distribution over the latent code,
# z_what.
class En... | 91 | 2,991 |
pyro | examples/air/air.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
"""
An implementation of the model described in [1].
[1] Eslami, SM Ali, et al. "Attend, infer, repeat: Fast scene
understanding with generative models." Advances in Neural Information
Processing Systems. 2016.
"""
from collectio... | 410 | 14,031 |
pyro | examples/vae/vae_comparison.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import argparse
import itertools
import os
from abc import ABCMeta, abstractmethod
import torch
import torch.nn as nn
from torch.nn import functional
from torchvision.utils import save_image
from utils.mnist_cached import DATA_DIR... | 276 | 9,094 |
pyro | examples/vae/ss_vae_M2.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import argparse
import torch
import torch.nn as nn
from utils.custom_mlp import MLP, Exp
from utils.mnist_cached import MNISTCached, mkdir_p, setup_data_loaders
from utils.vae_plots import mnist_test_tsne_ssvae, plot_conditional_s... | 542 | 20,433 |
pyro | examples/vae/vae.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import argparse
import numpy as np
import torch
import torch.nn as nn
from utils.mnist_cached import MNISTCached as MNIST
from utils.mnist_cached import setup_data_loaders
from utils.vae_plots import mnist_test_tsne, plot_llk, plo... | 258 | 9,210 |
pyro | examples/vae/utils/mnist_cached.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import errno
import os
from functools import reduce
import numpy as np
import torch
from torch.utils.data import DataLoader
from pyro.contrib.examples.util import MNIST, get_data_directory
# This file contains utilities for cach... | 264 | 8,848 |
pyro | examples/vae/utils/vae_plots.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import torch
def plot_conditional_samples_ssvae(ssvae, visdom_session):
"""
This is a method to do conditional sampling in visdom
"""
vis = visdom_session
ys = {}
for i in range(10):
ys[i] = torch.... | 123 | 3,678 |
pyro | examples/vae/utils/custom_mlp.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
from inspect import isclass
import torch
import torch.nn as nn
from pyro.distributions.util import broadcast_shape
class Exp(nn.Module):
"""
a custom module for exponentiation of tensors
"""
def __init__(self):... | 204 | 6,871 |
pyro | examples/cvae/main.py | .py | # Copyright Contributors to the Pyro project.
# SPDX-License-Identifier: Apache-2.0
import argparse
import baseline
import cvae
import pandas as pd
import torch
from util import generate_table, get_data, visualize
import pyro
def main(args):
device = torch.device(
"cuda:0" if torch.cuda.is_available() ... | 138 | 4,148 |
pyro | examples/cvae/mnist.py | .py | # Copyright Contributors to the Pyro project.
# SPDX-License-Identifier: Apache-2.0
import numpy as np
import torch
from torch.utils.data import DataLoader, Dataset
from torchvision.transforms import Compose, functional
from pyro.contrib.examples.util import MNIST
class CVAEMNIST(Dataset):
def __init__(self, ro... | 95 | 3,204 |
pyro | examples/cvae/util.py | .py | # Copyright Contributors to the Pyro project.
# SPDX-License-Identifier: Apache-2.0
from pathlib import Path
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import torch
from baseline import MaskedBCELoss
from mnist import get_data
from torch.utils.data import DataLoader
from torchvision.utils ... | 158 | 4,845 |
pyro | examples/cvae/baseline.py | .py | # Copyright Contributors to the Pyro project.
# SPDX-License-Identifier: Apache-2.0
import copy
from pathlib import Path
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from tqdm import tqdm
class BaselineNet(nn.Module):
def __init__(self, hidden_1, hidden_2):
super... | 118 | 3,456 |
pyro | examples/cvae/cvae.py | .py | # Copyright Contributors to the Pyro project.
# SPDX-License-Identifier: Apache-2.0
from pathlib import Path
import numpy as np
import torch
import torch.nn as nn
from tqdm import tqdm
import pyro
import pyro.distributions as dist
from pyro.infer import SVI, Trace_ELBO
class Encoder(nn.Module):
def __init__(se... | 190 | 6,899 |
pyro | examples/contrib/cevae/synthetic.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
"""
This example demonstrates how to use the Causal Effect Variational Autoencoder
[1] implemented in pyro.contrib.cevae.CEVAE, documented at
http://docs.pyro.ai/en/latest/contrib.cevae.html
**References**
[1] C. Louizos, U. Shal... | 109 | 3,803 |
pyro | examples/contrib/funsor/hmm.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
"""
This example is largely copied from ``examples/hmm.py``.
It illustrates the use of the experimental ``pyro.contrib.funsor`` Pyro backend
through the ``pyroapi`` package, demonstrating the utility of Funsor [0]
as an intermediat... | 873 | 35,806 |
pyro | examples/contrib/epidemiology/sir.py | .py | # Copyright Contributors to the Pyro project.
# SPDX-License-Identifier: Apache-2.0
# This script aims to replicate the behavior of examples/sir_hmc.py but using
# the high-level components of pyro.contrib.epidemiology. Command line
# arguments and results should be similar.
import argparse
import logging
import math... | 404 | 15,144 |
pyro | examples/contrib/epidemiology/regional.py | .py | # Copyright Contributors to the Pyro project.
# SPDX-License-Identifier: Apache-2.0
import argparse
import logging
import torch
import pyro
from pyro.contrib.epidemiology.models import RegionalSIRModel
logging.basicConfig(format="%(message)s", level=logging.INFO)
def Model(args, data):
assert 0 <= args.coupli... | 218 | 7,900 |
pyro | examples/contrib/autoname/mixture.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import argparse
import torch
from torch.distributions import constraints
import pyro
import pyro.distributions as dist
from pyro.contrib.autoname import named
from pyro.infer import SVI, JitTrace_ELBO, Trace_ELBO
from pyro.optim ... | 83 | 2,572 |
pyro | examples/contrib/autoname/scoping_mixture.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import argparse
import torch
from torch.distributions import constraints
import pyro
import pyro.distributions as dist
import pyro.optim
from pyro.contrib.autoname import scope
from pyro.infer import SVI, TraceEnum_ELBO, config_e... | 79 | 2,239 |
pyro | examples/contrib/autoname/tree_data.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import argparse
import torch
from torch.distributions import constraints
import pyro
import pyro.distributions as dist
from pyro.contrib.autoname import named
from pyro.infer import SVI, Trace_ELBO
from pyro.optim import Adam
# ... | 112 | 3,560 |
pyro | examples/contrib/oed/ab_test.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import argparse
from functools import partial
import numpy as np
import torch
from gp_bayes_opt import GPBayesOptimizer
from torch.distributions import constraints
import pyro
import pyro.contrib.gp as gp
from pyro import optim
f... | 136 | 4,658 |
pyro | examples/contrib/oed/gp_bayes_opt.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import torch
import torch.autograd as autograd
import torch.optim as optim
from torch.distributions import transform_to
import pyro.contrib.gp as gp
import pyro.optim
from pyro.infer import TraceEnum_ELBO
class GPBayesOptimizer(... | 142 | 5,456 |
pyro | examples/contrib/forecast/bart.py | .py | # Copyright Contributors to the Pyro project.
# SPDX-License-Identifier: Apache-2.0
import argparse
import logging
import numpy as np
import torch
import pyro
import pyro.distributions as dist
from pyro.contrib.examples.bart import load_bart_od
from pyro.contrib.forecast import ForecastingModel, backtest
from pyro.o... | 182 | 7,530 |
pyro | examples/contrib/timeseries/gp_models.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import argparse
from os.path import exists
from urllib.request import urlopen
import numpy as np
import torch
import pyro
from pyro.contrib.timeseries import IndependentMaternGP, LinearlyCoupledMaternGP
# download dataset from ... | 204 | 7,165 |
pyro | examples/contrib/gp/sv-dkl.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
"""
An example to use Pyro Gaussian Process module to classify MNIST and binary MNIST.
Follow the idea from reference [1], we will combine a convolutional neural network
(CNN) with a RBF kernel to create a "deep" kernel:
>>> ... | 266 | 8,529 |
pyro | examples/contrib/mue/ProfileHMM.py | .py | # Copyright Contributors to the Pyro project.
# SPDX-License-Identifier: Apache-2.0
"""
A standard profile HMM model [1], which corresponds to a constant (delta
function) distribution with a MuE observation [2]. This is a standard
generative model of variable-length biological sequences (e.g. proteins) which
does not ... | 322 | 10,356 |
pyro | examples/contrib/mue/FactorMuE.py | .py | # Copyright Contributors to the Pyro project.
# SPDX-License-Identifier: Apache-2.0
"""
A probabilistic PCA model with a MuE observation, called a 'FactorMuE' model
[1]. This is a generative model of variable-length biological sequences (e.g.
proteins) which does not require preprocessing the data by building a
multip... | 433 | 13,776 |
pyro | examples/scanvi/scanvi.py | .py | # Copyright Contributors to the Pyro project.
# SPDX-License-Identifier: Apache-2.0
"""
We use a semi-supervised deep generative model of transcriptomics data to propagate labels
from a small set of labeled cells to a larger set of unlabeled cells. In particular we
use a dataset of peripheral blood mononuclear cells (... | 442 | 16,794 |
pyro | pyro/logger.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import logging
default_format = "%(levelname)s \t %(message)s"
log = logging.getLogger("pyro")
log.setLevel(logging.INFO)
if not logging.root.handlers:
default_handler = logging.StreamHandler()
default_handler.setLevel(l... | 17 | 463 |
pyro | pyro/util.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import math
import numbers
import random
import sys
import timeit
import warnings
from collections import defaultdict
from contextlib import contextmanager
from itertools import zip_longest
from typing import (
TYPE_CHECKING,
... | 725 | 24,654 |
pyro | pyro/__init__.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import pyro.poutine as poutine
from pyro.infer.inspect import render_model
from pyro.logger import log
from pyro.poutine import condition, do, markov
from pyro.primitives import (
barrier,
clear_param_store,
determinist... | 67 | 1,308 |
pyro | pyro/settings.py | .py | # Copyright Contributors to the Pyro project.
# SPDX-License-Identifier: Apache-2.0
"""
Example usage::
# Simple getting and setting.
print(pyro.settings.get()) # print all settings
print(pyro.settings.get("cholesky_relative_jitter")) # print one
pyro.settings.set(cholesky_relative_jitter=0.5) # se... | 164 | 5,019 |
pyro | pyro/primitives.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import copy
import warnings
from collections import OrderedDict
from contextlib import ExitStack, contextmanager
from inspect import isclass
from operator import attrgetter
from typing import Callable, Iterator, Optional, Sequence,... | 601 | 24,384 |
pyro | pyro/params/__init__.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
from .param_store import (
module_from_param_with_module_name,
param_with_module_name,
user_param_name,
)
__all__ = [
"module_from_param_with_module_name",
"param_with_module_name",
"user_param_name",
]
| 15 | 317 |
pyro | pyro/params/param_store.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import re
import warnings
import weakref
from contextlib import contextmanager
from typing import (
Callable,
Dict,
ItemsView,
Iterator,
KeysView,
Optional,
Tuple,
Union,
)
import torch
from torch.d... | 396 | 14,527 |
pyro | pyro/nn/__init__.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
from __future__ import absolute_import, division, print_function
from pyro.nn.auto_reg_nn import (
AutoRegressiveNN,
ConditionalAutoRegressiveNN,
MaskedLinear,
)
from pyro.nn.dense_nn import ConditionalDenseNN, DenseNN... | 32 | 665 |
pyro | pyro/nn/module.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
"""
Pyro includes a class :class:`~pyro.nn.module.PyroModule`, a subclass of
:class:`torch.nn.Module`, whose attributes can be modified by Pyro effects. To
create a poutine-aware attribute, use either the :class:`PyroParam` struct... | 977 | 40,779 |
pyro | pyro/nn/dense_nn.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
from typing import List, Sequence, Union
import torch
class ConditionalDenseNN(torch.nn.Module):
"""
An implementation of a simple dense feedforward network taking a context variable, for use in, e.g.,
some condition... | 141 | 5,615 |
pyro | pyro/nn/auto_reg_nn.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import warnings
from typing import List, Optional, Sequence, Tuple, Union
import torch
import torch.nn as nn
from torch.nn import functional as F
def sample_mask_indices(
input_dim: int, hidden_dim: int, simple: bool = True
... | 359 | 14,455 |
pyro | pyro/distributions/zero_inflated.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import torch
from torch.distributions import constraints
from torch.distributions.utils import (
broadcast_all,
lazy_property,
logits_to_probs,
probs_to_logits,
)
from torch.nn.functional import softplus
from pyro.... | 204 | 6,893 |
pyro | pyro/distributions/hmm.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import torch
import torch.nn.functional as F
from pyro.ops.gamma_gaussian import (
GammaGaussian,
gamma_and_mvn_to_gamma_gaussian,
gamma_gaussian_tensordot,
matrix_and_mvn_to_gamma_gaussian,
)
from pyro.ops.gaussia... | 1,318 | 54,265 |
pyro | pyro/distributions/stable.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import math
import torch
from torch.distributions import constraints
from torch.distributions.utils import broadcast_all
from pyro.distributions.stable_log_prob import _stable_log_prob
from pyro.distributions.torch_distribution i... | 247 | 9,997 |
pyro | pyro/distributions/avf_mvn.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import torch
from torch.autograd import Function
from torch.autograd.function import once_differentiable
from torch.distributions import constraints
from pyro.distributions.torch import MultivariateNormal
from pyro.distributions.u... | 107 | 4,062 |
pyro | pyro/distributions/rejector.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import torch
from pyro.distributions.score_parts import ScoreParts
from pyro.distributions.torch_distribution import TorchDistribution
class Rejector(TorchDistribution):
"""
Rejection sampled distribution given an accept... | 74 | 2,933 |
pyro | pyro/distributions/sine_bivariate_von_mises.py | .py | # Copyright Contributors to the Pyro project.
# SPDX-License-Identifier: Apache-2.0
import math
import warnings
from math import pi
import torch
from torch.distributions import VonMises
from torch.distributions.utils import broadcast_all, lazy_property
from pyro.distributions import constraints
from pyro.distributio... | 331 | 12,255 |
pyro | pyro/distributions/folded.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
from torch.distributions import constraints
from torch.distributions.transforms import AbsTransform
from pyro.distributions.torch import TransformedDistribution
class FoldedDistribution(TransformedDistribution):
"""
Equi... | 36 | 1,290 |
pyro | pyro/distributions/distribution.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import functools
import inspect
from abc import ABCMeta, abstractmethod
import torch
from pyro.distributions.score_parts import ScoreParts
COERCIONS = []
class DistributionMeta(ABCMeta):
def __init__(cls, *args, **kwargs):... | 223 | 8,481 |
pyro | pyro/distributions/polya_gamma.py | .py | # Copyright Contributors to the Pyro project.
# SPDX-License-Identifier: Apache-2.0
import math
import torch
from torch.distributions import constraints
from pyro.distributions.torch import Exponential
from pyro.distributions.torch_distribution import TorchDistribution
class TruncatedPolyaGamma(TorchDistribution):... | 81 | 3,090 |
pyro | pyro/distributions/torch_distribution.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import warnings
from collections import OrderedDict
from typing import Callable
import torch
from torch.distributions.kl import kl_divergence, register_kl
import pyro.distributions.torch
from . import constraints
from .distribut... | 546 | 20,843 |
pyro | pyro/distributions/unit.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import torch
from torch.distributions import constraints
from pyro.distributions.torch_distribution import TorchDistribution
from pyro.distributions.util import broadcast_shape
class Unit(TorchDistribution):
"""
Trivial ... | 51 | 1,886 |
pyro | pyro/distributions/one_two_matching.py | .py | # Copyright Contributors to the Pyro project.
# SPDX-License-Identifier: Apache-2.0
import logging
import math
import warnings
import torch
from torch.distributions import constraints
from torch.distributions.utils import lazy_property
from .torch import Categorical
from .torch_distribution import TorchDistribution
... | 213 | 8,193 |
pyro | pyro/distributions/conjugate.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import numbers
import torch
from torch.distributions.utils import broadcast_all
from pyro.ops.special import log_beta, log_binomial
from . import constraints
from .torch import Beta, Binomial, Dirichlet, Gamma, Multinomial, Pois... | 296 | 10,898 |
pyro | pyro/distributions/omt_mvn.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import torch
from torch.autograd import Function
from torch.autograd.function import once_differentiable
from torch.distributions import constraints
from pyro.distributions.torch import MultivariateNormal
from pyro.distributions.u... | 91 | 3,183 |
pyro | pyro/distributions/mixture.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import torch
from torch.distributions import constraints
from torch.distributions.utils import lazy_property
from pyro.distributions.torch_distribution import TorchDistribution
from pyro.distributions.util import broadcast_shape
... | 164 | 6,150 |
pyro | pyro/distributions/diag_normal_mixture_shared_cov.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import math
import torch
from torch.autograd import Function
from torch.autograd.function import once_differentiable
from torch.distributions import Categorical, constraints
from pyro.distributions.torch_distribution import Torch... | 209 | 9,065 |
pyro | pyro/distributions/util.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import copy
import ctypes
import functools
import numbers
import weakref
from contextlib import contextmanager
import torch
import torch.distributions as torch_dist
from torch import logsumexp
from torch.distributions.utils import... | 362 | 11,913 |
pyro | pyro/distributions/empirical.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import torch
from torch.distributions import constraints
from pyro.distributions.torch import Categorical
from pyro.distributions.torch_distribution import TorchDistribution
from pyro.distributions.util import copy_docs_from
@co... | 177 | 6,765 |
pyro | pyro/distributions/__init__.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import pyro.distributions.torch_patch # noqa F403
# Import * to get the latest upstream distributions.
from pyro.distributions.torch import * # noqa F403
# Additionally try to import explicitly to help mypy static analysis.
try... | 264 | 7,555 |
pyro | pyro/distributions/improper_uniform.py | .py | # Copyright Contributors to the Pyro project.
# SPDX-License-Identifier: Apache-2.0
import torch
from torch.distributions import constraints
from .torch_distribution import TorchDistribution
from .util import broadcast_shape
class ImproperUniform(TorchDistribution):
"""
Improper distribution with zero :meth... | 69 | 2,448 |
pyro | pyro/distributions/relaxed_straight_through.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import torch
from torch.distributions.utils import clamp_probs
from pyro.distributions.torch import RelaxedBernoulli, RelaxedOneHotCategorical
from pyro.distributions.util import copy_docs_from
@copy_docs_from(RelaxedOneHotCateg... | 104 | 3,637 |
pyro | pyro/distributions/lkj.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import warnings
import torch
from pyro.distributions.torch import LKJCholesky, TransformedDistribution
from pyro.distributions.transforms.cholesky import CorrMatrixCholeskyTransform
from . import constraints
class LKJCorrChole... | 63 | 2,534 |
pyro | pyro/distributions/gaussian_scale_mixture.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import math
import torch
from torch.autograd import Function
from torch.autograd.function import once_differentiable
from torch.distributions import Categorical, constraints
from pyro.distributions.torch_distribution import Torch... | 212 | 8,374 |
pyro | pyro/distributions/ordered_logistic.py | .py | # Copyright Contributors to the Pyro project.
# SPDX-License-Identifier: Apache-2.0
import torch
from pyro.distributions import constraints
from pyro.distributions.torch import Categorical
class OrderedLogistic(Categorical):
"""
Alternative parametrization of the distribution over a categorical variable.
... | 62 | 2,874 |
pyro | pyro/distributions/spanning_tree.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import itertools
import math
import torch
from torch.distributions import constraints
from torch.distributions.utils import lazy_property
from pyro.distributions.torch_distribution import TorchDistribution
class SpanningTree(To... | 618 | 22,113 |
pyro | pyro/distributions/inverse_gamma.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
from torch.distributions import constraints
from torch.distributions.transforms import PowerTransform
from pyro.distributions.torch import Gamma, TransformedDistribution
# DEPRECATED in favor of torch.distributions.InverseGamma.... | 49 | 1,489 |
pyro | pyro/distributions/softlaplace.py | .py | # Copyright Contributors to the Pyro project.
# SPDX-License-Identifier: Apache-2.0
import math
import torch
from torch.distributions import constraints
from torch.distributions.utils import broadcast_all
from .torch_distribution import TorchDistribution
class SoftLaplace(TorchDistribution):
"""
Smooth dis... | 75 | 2,471 |
pyro | pyro/distributions/conditional.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
from abc import ABC, abstractmethod
import torch
import torch.nn
from .torch import TransformedDistribution
from .torch_transform import ComposeTransformModule
class ConditionalDistribution(ABC):
@abstractmethod
def con... | 151 | 4,895 |
pyro | pyro/distributions/torch_patch.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import functools
import math
import warnings
import weakref
import torch
def patch_dependency(target, root_module=torch):
try:
parts = target.split(".")
assert parts[0] == root_module.__name__
module ... | 90 | 2,859 |
pyro | pyro/distributions/nanmasked.py | .py | # Copyright Contributors to the Pyro project.
# SPDX-License-Identifier: Apache-2.0
import torch
from .torch import MultivariateNormal, Normal
class NanMaskedNormal(Normal):
"""
Wrapper around :class:`~pyro.distributions.Normal` to allow partially
observed data as specified by NAN elements in :meth:`log... | 100 | 3,381 |
pyro | pyro/distributions/von_mises_3d.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import math
import torch
from . import constraints
from .torch_distribution import TorchDistribution
class VonMises3D(TorchDistribution):
"""
Spherical von Mises distribution.
This implementation combines the direc... | 67 | 2,694 |
pyro | pyro/distributions/projected_normal.py | .py | # Copyright Contributors to the Pyro project.
# SPDX-License-Identifier: Apache-2.0
import math
import torch
from pyro.ops.tensor_utils import safe_normalize
from . import constraints
from .torch_distribution import TorchDistribution
class ProjectedNormal(TorchDistribution):
"""
Projected isotropic normal... | 198 | 7,441 |
pyro | pyro/distributions/diag_normal_mixture.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import math
import torch
from torch.autograd import Function
from torch.autograd.function import once_differentiable
from torch.distributions import Categorical, constraints
from pyro.distributions.torch_distribution import Torch... | 247 | 10,445 |
pyro | pyro/distributions/torch.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import math
import re
import textwrap
import torch
from pyro.distributions.torch_distribution import TorchDistributionMixin
from pyro.distributions.util import broadcast_shape, sum_rightmost
from pyro.ops.special import log_binom... | 438 | 15,231 |
pyro | pyro/distributions/sine_skewed.py | .py | # Copyright Contributors to the Pyro project.
# SPDX-License-Identifier: Apache-2.0
import warnings
from math import pi
import torch
from torch import broadcast_shapes
from torch.distributions import Uniform
from pyro.distributions import constraints
from .torch_distribution import TorchDistribution
class SineSke... | 172 | 7,374 |
pyro | pyro/distributions/logistic.py | .py | # Copyright Contributors to the Pyro project.
# SPDX-License-Identifier: Apache-2.0
import math
import torch
from torch.distributions import constraints
from torch.distributions.utils import broadcast_all
from torch.nn.functional import logsigmoid
from .torch_distribution import TorchDistribution
class Logistic(To... | 159 | 5,474 |
pyro | pyro/distributions/affine_beta.py | .py | # Copyright Contributors to the Pyro project.
# SPDX-License-Identifier: Apache-2.0
import torch
from torch.distributions import constraints
from torch.distributions.transforms import AffineTransform
from .torch import Beta, TransformedDistribution
from .util import broadcast_shape
class AffineBeta(TransformedDistr... | 123 | 3,985 |
pyro | pyro/distributions/constraints.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
# Import * to get the latest upstream constraints.
from torch.distributions.constraints import * # noqa F403
# Additionally try to import explicitly to help mypy static analysis.
try:
from torch.distributions.constraints impo... | 235 | 5,739 |
pyro | pyro/distributions/one_one_matching.py | .py | # Copyright Contributors to the Pyro project.
# SPDX-License-Identifier: Apache-2.0
import itertools
import logging
import warnings
import torch
from torch.distributions import constraints
from torch.distributions.utils import lazy_property
from .torch import Categorical
from .torch_distribution import TorchDistribu... | 176 | 6,714 |
pyro | pyro/distributions/asymmetriclaplace.py | .py | # Copyright Contributors to the Pyro project.
# SPDX-License-Identifier: Apache-2.0
import math
import torch
from torch.distributions import constraints
from torch.distributions.utils import broadcast_all, lazy_property
from .torch_distribution import TorchDistribution
class AsymmetricLaplace(TorchDistribution):
... | 211 | 7,369 |
pyro | pyro/distributions/kl.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
import math
from torch.distributions import (
Independent,
MultivariateNormal,
Normal,
kl_divergence,
register_kl,
)
from pyro.distributions.delta import Delta
from pyro.distributions.distribution import Distr... | 57 | 1,661 |
pyro | pyro/distributions/score_parts.py | .py | # Copyright (c) 2017-2019 Uber Technologies, Inc.
# SPDX-License-Identifier: Apache-2.0
from typing import NamedTuple, Optional, Union
import torch
from pyro.distributions.util import scale_and_mask
class ScoreParts(NamedTuple):
"""
This data structure stores terms used in stochastic gradient estimators th... | 39 | 1,282 |
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