# tensorflow-probability 0.24.0

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## Probabilistic modeling and statistical inference in TensorFlow

Contents

Probabilistic modeling and statistical inference in TensorFlow

Stars: 4233, Watchers: 4233, Forks: 1091, Open Issues: 682The `tensorflow/probability`

repo was created 6 years ago and the last code push was 2 weeks ago.

The project is very popular with an impressive 4233 github stars!

## How to Install tensorflow-probability

You can install tensorflow-probability using pip

`pip install tensorflow-probability`

or add it to a project with poetry

`poetry add tensorflow-probability`

## Package Details

- Author
- Google LLC
- License
- Apache 2.0
- Homepage
- http://github.com/tensorflow/probability
- PyPi:
- https://pypi.org/project/tensorflow-probability/
- GitHub Repo:
- https://github.com/tensorflow/probability

## Classifiers

- Scientific/Engineering
- Scientific/Engineering/Artificial Intelligence
- Scientific/Engineering/Mathematics
- Software Development
- Software Development/Libraries
- Software Development/Libraries/Python Modules

## Related Packages

## Errors

A list of common tensorflow-probability errors.

## Code Examples

Here are some `tensorflow-probability`

code examples and snippets.

## GitHub Issues

The tensorflow-probability package has 682 open issues on GitHub

- Please run in eager mode or implement the
`compute_output_shape`

method on your layer (DenseVariational). - Tensorflow Probability Glow has duplicated variable names
- NotImplementedError with tensorflow_probability.layers.IndependentNormal
- Bayesian CNN keeps giving the same output regardless of the input
- Dimensions mismatch error when using
`fit_surrogate_posterior()`

with`sample_size`

> 1 - Optimize
`_kl_matrix_normal_matrix_normal`

for`tfd.MatrixNormalLinearOperator`

- Optimal way to run multiple chains for a bayesian neural network trained with HMC (tfp.mcmc.HamiltonianMonteCarlo)
- Feature request: Allow passing in scope for TransformedVariable, DeferredTensor for distributed programming
- Feature Request: Serialization/deserialization for Distribution class objects
- [Bug] Pivoted cholesky jit error when using jax backend
- generalized gamma distribution
- What would be a good way to get sample mean of joint distribution?
- AttributeError: 'UserRegisteredTypeKerasTensor' object has no attribute 'mean' error raised.
- module 'keras.utils.generic_utils' has no attribute 'populate_dict_with_module_objects'
- Input initial_level_prior inconsistent with initial_state_prior (sts.LocalLevel)