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Inference Gym: Move the Stan stuff to the spinoffs directory.
PiperOrigin-RevId: 328403234
1 parent 18d6af3 commit accef4e

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‎spinoffs/inference_gym/README.md

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@@ -109,7 +109,7 @@ models.
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Currently we have a little tooling to help use `cmdstanpy` to generate ground
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truth values (in the correct format) for models without analytic ground truth.
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Using this requires adding a model implementation inside the
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[`tools/inference_gym_ground_truth`][ground_truth_dir]
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[`inference_gym/tools/stan`][ground_truth_dir]
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directory.
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### Adding a new real dataset
@@ -124,11 +124,11 @@ Follow the example of the [`SyntheticItemResponseTheory`][irt] model.
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### Generating ground truth files.
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See [`tools/inference_gym_ground_truth/get_ground_truth.py`][get_ground_truth].
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See [`inference_gym/tools/get_ground_truth.py`][get_ground_truth].
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[model]: https://github.com/tensorflow/probability/tree/master/spinoffs/inference_gym/targets/model.py
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[get_ground_truth]: https://github.com/tensorflow/probability/tree/master/tools/inference_gym_ground_truth/get_ground_truth.py
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[ground_truth_dir]: https://github.com/tensorflow/probability/tree/master/tools/inference_gym_ground_truth
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[get_ground_truth]: https://github.com/tensorflow/probability/tree/master/spinoffs/inference_gym/tools/get_ground_truth.py
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[ground_truth_dir]: https://github.com/tensorflow/probability/tree/master/spinoffs/inference_gym/tools/stan
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[bayesian_model]: https://github.com/tensorflow/probability/tree/master/spinoffs/inference_gym/targets/bayesian_model.py
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[sparse_logistic_regression]: https://github.com/tensorflow/probability/tree/master/spinoffs/inference_gym/targets/sparse_logistic_regression.py
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[logistic_regression]: https://github.com/tensorflow/probability/tree/master/spinoffs/inference_gym/targets/logistic_regression.py

‎spinoffs/inference_gym/internal/BUILD

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package(
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default_visibility = [
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"//tensorflow_probability:__subpackages__",
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"//tools/inference_gym_ground_truth:__subpackages__",
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"//tensorflow_probability/opensource/tools/inference_gym_ground_truth:__subpackages__",
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"//spinoffs/inference_gym:__subpackages__",
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],
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)

‎spinoffs/inference_gym/tools/BUILD

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# Copyright 2020 The TensorFlow Probability Authors.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ============================================================================
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# Ground truth computation.
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package(
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default_visibility = [
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"//tensorflow_probability:__subpackages__",
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"//spinoffs/inference_gym:__subpackages__",
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],
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)
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licenses(["notice"])
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exports_files(["LICENSE"])
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# We can't use strict/pytype because `cmdstanpy` is not available internally.
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py_binary(
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name = "get_ground_truth",
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srcs = ["get_ground_truth.py"],
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python_version = "PY3",
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deps = [
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"//tensorflow_probability",
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"//spinoffs/inference_gym/internal:ground_truth_encoding",
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"//spinoffs/inference_gym/tools/stan:targets",
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],
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)

‎tools/inference_gym_ground_truth/README.md renamed to ‎spinoffs/inference_gym/tools/README.md

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‎tools/inference_gym_ground_truth/get_ground_truth.py renamed to ‎spinoffs/inference_gym/tools/get_ground_truth.py

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# Lint as: python2, python3
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# Lint as: python3
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# Copyright 2020 The TensorFlow Probability Authors.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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- tfds-nightly
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"""
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from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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import functools
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import os
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import sys
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import pandas as pd
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import tensorflow.compat.v2 as tf
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import tensorflow_probability as tfp
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from tools.inference_gym_ground_truth import targets
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from spinoffs.inference_gym.internal import ground_truth_encoding
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from spinoffs.inference_gym.tools.stan import targets
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# Direct import for flatten_with_tuple_paths.
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from tensorflow.python.util import nest # pylint: disable=g-direct-tensorflow-import
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flags.DEFINE_string('output_directory', None,
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'Where to save the ground truth values. By default, this '
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'places it in the appropriate directory in the '
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'TensorFlow Probability source directory.')
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'Inference Gym source directory.')
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FLAGS = flags.FLAGS
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argv_str = '\n'.join([' {} \\'.format(arg) for arg in sys.argv[1:]])
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command_str = (
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"""bazel run //tools/inference_gym_ground_truth:get_ground_truth -- \
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"""bazel run //spinoffs/inference_gym/tools:get_ground_truth -- \
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{argv_str}""".format(argv_str=argv_str))
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file_str = ground_truth_encoding.get_ground_truth_module_source(
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if FLAGS.output_directory is None:
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file_basedir = os.path.dirname(os.path.realpath(__file__))
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output_directory = os.path.join(
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file_basedir, '../../spinoffs/inference_gym/targets/ground_truth')
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file_basedir, '../targets/ground_truth')
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else:
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output_directory = FLAGS.output_directory
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file_path = os.path.join(output_directory, '{}.py'.format(FLAGS.target))

‎tools/inference_gym_ground_truth/BUILD renamed to ‎spinoffs/inference_gym/tools/stan/BUILD

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# limitations under the License.
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# ============================================================================
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# Ground truth computation using Stan.
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licenses(["notice"])
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package(default_visibility = ["//visibility:public"])
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py_binary(
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name = "get_ground_truth",
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srcs = ["get_ground_truth.py"],
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python_version = "PY3",
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tags = ["notap"],
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deps = [
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":targets",
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"//tensorflow_probability",
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"//spinoffs/inference_gym/internal:ground_truth_encoding",
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package(
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default_visibility = [
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"//tensorflow_probability:__subpackages__",
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"//spinoffs/inference_gym:__subpackages__",
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],
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)
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licenses(["notice"])
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exports_files(["LICENSE"])
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# We can't use strict/pytype because `cmdstanpy` is not available internally.
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py_library(
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name = "brownian_motion",
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srcs = ["brownian_motion.py"],

‎tools/inference_gym_ground_truth/brownian_motion.py renamed to ‎spinoffs/inference_gym/tools/stan/brownian_motion.py

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# Lint as: python2, python3
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# Lint as: python3
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# Copyright 2020 The TensorFlow Probability Authors.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# ============================================================================
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"""Brownian Motion model, implemented in Stan."""
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from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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import numpy as np
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from tools.inference_gym_ground_truth import stan_model
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from tools.inference_gym_ground_truth import util
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from spinoffs.inference_gym.tools.stan import stan_model
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from spinoffs.inference_gym.tools.stan import util
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__all__ = [
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'brownian_motion',

‎tools/inference_gym_ground_truth/item_response_theory.py renamed to ‎spinoffs/inference_gym/tools/stan/item_response_theory.py

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# Lint as: python2, python3
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# Lint as: python3
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# Copyright 2020 The TensorFlow Probability Authors.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# ============================================================================
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"""1PL item-response theory model, implemented in Stan."""
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from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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import collections
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from tools.inference_gym_ground_truth import stan_model
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from tools.inference_gym_ground_truth import util
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from spinoffs.inference_gym.tools.stan import stan_model
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from spinoffs.inference_gym.tools.stan import util
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__all__ = [
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'item_response_theory',

‎tools/inference_gym_ground_truth/log_gaussian_cox_process.py renamed to ‎spinoffs/inference_gym/tools/stan/log_gaussian_cox_process.py

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# Lint as: python2, python3
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# Lint as: python3
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# Copyright 2020 The TensorFlow Probability Authors.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# ============================================================================
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"""Log-gaussian Cox Process, implemented in Stan."""
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from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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import collections
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from tools.inference_gym_ground_truth import stan_model
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from tools.inference_gym_ground_truth import util
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from spinoffs.inference_gym.tools.stan import stan_model
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from spinoffs.inference_gym.tools.stan import util
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__all__ = [
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'log_gaussian_cox_process',

‎tools/inference_gym_ground_truth/logistic_regression.py renamed to ‎spinoffs/inference_gym/tools/stan/logistic_regression.py

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# Lint as: python2, python3
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# Lint as: python3
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# Copyright 2020 The TensorFlow Probability Authors.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# ============================================================================
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"""Logistic regression, implemented in Stan."""
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from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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import numpy as np
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from tools.inference_gym_ground_truth import stan_model
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from tools.inference_gym_ground_truth import util
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from spinoffs.inference_gym.tools.stan import stan_model
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from spinoffs.inference_gym.tools.stan import util
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__all__ = [
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'logistic_regression',

‎tools/inference_gym_ground_truth/probit_regression.py renamed to ‎spinoffs/inference_gym/tools/stan/probit_regression.py

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# Lint as: python2, python3
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# Lint as: python3
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# Copyright 2020 The TensorFlow Probability Authors.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# ============================================================================
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"""Probit regression, implemented in Stan."""
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from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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import numpy as np
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from tools.inference_gym_ground_truth import stan_model
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from tools.inference_gym_ground_truth import util
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from spinoffs.inference_gym.tools.stan import stan_model
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from spinoffs.inference_gym.tools.stan import util
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__all__ = [
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'probit_regression',

‎tools/inference_gym_ground_truth/radon_contextual_effects.py renamed to ‎spinoffs/inference_gym/tools/stan/radon_contextual_effects.py

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# Lint as: python2, python3
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# Lint as: python3
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# Copyright 2020 The TensorFlow Probability Authors.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# ============================================================================
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"""Radon model, implemented in Stan."""
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from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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import collections
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import numpy as np
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from tools.inference_gym_ground_truth import stan_model
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from tools.inference_gym_ground_truth import util
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from spinoffs.inference_gym.tools.stan import stan_model
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from spinoffs.inference_gym.tools.stan import util
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__all__ = [
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'radon_contextual_effects',
@@ -115,7 +111,8 @@ def _ext_identity(samples):
115111
samples, r'^county_effect_scale$')[:, 0]
116112
res['county_effect'] = util.get_columns(samples, r'^county_effect\.\d+$')
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res['weight'] = util.get_columns(samples, r'^weight\.\d+$')
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res['log_radon_scale'] = util.get_columns(samples, r'^log_radon_scale$')[:, 0]
114+
res['log_radon_scale'] = (
115+
util.get_columns(samples, r'^log_radon_scale$')[:, 0])
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return res
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121118
extract_fns = {'identity': _ext_identity}

‎tools/inference_gym_ground_truth/sparse_logistic_regression.py renamed to ‎spinoffs/inference_gym/tools/stan/sparse_logistic_regression.py

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# Lint as: python2, python3
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# Lint as: python3
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# Copyright 2020 The TensorFlow Probability Authors.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# ============================================================================
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"""Sparse logistic regression, implemented in Stan."""
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from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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import collections
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import numpy as np
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from tools.inference_gym_ground_truth import stan_model
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from tools.inference_gym_ground_truth import util
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from spinoffs.inference_gym.tools.stan import stan_model
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from spinoffs.inference_gym.tools.stan import util
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__all__ = [
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'sparse_logistic_regression',

‎tools/inference_gym_ground_truth/stan_model.py renamed to ‎spinoffs/inference_gym/tools/stan/stan_model.py

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# Lint as: python2, python3
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# Lint as: python3
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# Copyright 2020 The TensorFlow Probability Authors.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");

‎tools/inference_gym_ground_truth/stochastic_volatility.py renamed to ‎spinoffs/inference_gym/tools/stan/stochastic_volatility.py

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# Lint as: python2, python3
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# Lint as: python3
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# Copyright 2020 The TensorFlow Probability Authors.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# ============================================================================
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"""Stochastic volatility model, implemented in Stan."""
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from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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import collections
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from tools.inference_gym_ground_truth import stan_model
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from tools.inference_gym_ground_truth import util
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from spinoffs.inference_gym.tools.stan import stan_model
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from spinoffs.inference_gym.tools.stan import util
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__all__ = [
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'stochastic_volatility',

‎tools/inference_gym_ground_truth/targets.py renamed to ‎spinoffs/inference_gym/tools/stan/targets.py

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# Lint as: python2, python3
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# Lint as: python3
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# Copyright 2020 The TensorFlow Probability Authors.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# ============================================================================
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"""Stan models, used as a source of ground truth."""
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from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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from tools.inference_gym_ground_truth import brownian_motion
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from tools.inference_gym_ground_truth import item_response_theory
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from tools.inference_gym_ground_truth import log_gaussian_cox_process
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from tools.inference_gym_ground_truth import logistic_regression
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from tools.inference_gym_ground_truth import probit_regression
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from tools.inference_gym_ground_truth import radon_contextual_effects
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from tools.inference_gym_ground_truth import sparse_logistic_regression
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from tools.inference_gym_ground_truth import stochastic_volatility
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from spinoffs.inference_gym.internal import data
19+
from spinoffs.inference_gym.tools.stan import brownian_motion
20+
from spinoffs.inference_gym.tools.stan import item_response_theory
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from spinoffs.inference_gym.tools.stan import log_gaussian_cox_process
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from spinoffs.inference_gym.tools.stan import logistic_regression
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from spinoffs.inference_gym.tools.stan import probit_regression
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from spinoffs.inference_gym.tools.stan import radon_contextual_effects
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from spinoffs.inference_gym.tools.stan import sparse_logistic_regression
26+
from spinoffs.inference_gym.tools.stan import stochastic_volatility
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__all__ = [
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'brownian_motion_missing_middle_observations',

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