https://github.com/GPflow/GPflow
- HEAD
- refs/heads/0.5.0
- refs/heads/alan/hackathon_docs
- refs/heads/alan/quickfix/multioutput_kernels
- refs/heads/andrewl/fix_GPR_posterior_leading_dim
- refs/heads/avullo-willcowley/working-bee-ef1
- refs/heads/awav/check-det
- refs/heads/awav/develop-2.0/hmc-helper
- refs/heads/awav/develop-2.0/update-parameter-docstring
- refs/heads/awav/different-stuff
- refs/heads/awav/gpflow-2.0-squared_distances
- refs/heads/awav/inference
- refs/heads/awav/kernel-structure
- refs/heads/awav/likelihood-variance
- refs/heads/awav/natural-gradients
- refs/heads/awav/release-pip-package
- refs/heads/awav/release-testing-branch
- refs/heads/awav/sparse-tensors-support
- refs/heads/awav/tensor-functor
- refs/heads/awav/tfp
- refs/heads/awav_documentation
- refs/heads/blockkernel
- refs/heads/cone
- refs/heads/deep
- refs/heads/deep_arccos_kernel
- refs/heads/dependabot/pip/black-24.3.0
- refs/heads/develop
- refs/heads/develop-1.0
- refs/heads/eps_conditionals
- refs/heads/fast-grad
- refs/heads/felix/pathologies_experiment
- refs/heads/fergus/anisotropy
- refs/heads/fergus/het_sgpr
- refs/heads/fergus/linear
- refs/heads/fergus/linear_noise
- refs/heads/fergus/notebook
- refs/heads/fergus/random_init_lin_noise
- refs/heads/fxsm/new_svgp
- refs/heads/gh-pages
- refs/heads/gplvm
- refs/heads/gplvm-fullcov
- refs/heads/gustavocmv/heterocedastic-gaussian-likelihood
- refs/heads/gustavocmv/multiclass-likelihood-quadrature-test
- refs/heads/gustavocmv/ndiagghquadrature-property-setter
- refs/heads/gustavocmv/varying-noise-notebook-comment
- refs/heads/hugh/broadcasting_matched_multi_sample
- refs/heads/hughsalimbeni-broadcasting-conditional
- refs/heads/icouckuy-derivatives
- refs/heads/james-vincent/sgpr
- refs/heads/jax
- refs/heads/jesper/1956/stateless_random
- refs/heads/jesper/dimobjs
- refs/heads/jesper/dimobjswtf
- refs/heads/jesper/fix_gpflux
- refs/heads/jesper/for_hv
- refs/heads/jesper/jn_gps
- refs/heads/jesper/warped_halton
- refs/heads/joelb/type-hint-config
- refs/heads/john-bradshaw/binary-class-GP
- refs/heads/john-bradshaw/derivative-observations
- refs/heads/john-bradshaw/linear-features-for-kernels
- refs/heads/john-bradshaw/linear-features-for-kernels-gpflow1.0
- refs/heads/john/linear
- refs/heads/khurram/scipy_xla
- refs/heads/mark/jitter
- refs/heads/master
- refs/heads/master-1.0
- refs/heads/master_profile_mnist
- refs/heads/merging-masters
- refs/heads/mnist
- refs/heads/mnist_datatypes
- refs/heads/multiclass_slicing
- refs/heads/multioutput
- refs/heads/nbtest
- refs/heads/nested_models_recompilation
- refs/heads/nicolas/sinc_kernel
- refs/heads/parallel_tests
- refs/heads/profiling_mods
- refs/heads/profiling_mods_paper
- refs/heads/pypi
- refs/heads/requirements_fix
- refs/heads/revert-1511-master
- refs/heads/robustmax_epsilon_learnable
- refs/heads/sc336/2.7.0-master-merge-again
- refs/heads/sc336/2.7.0-merge
- refs/heads/sc336/2.7.1-preparation
- refs/heads/sc336/3.8_enum_bug
- refs/heads/sc336/GroupingKey_error
- refs/heads/sc336/categorical_kernel
- refs/heads/sc336/dgp_components
- refs/heads/sc336/fix_conflicts
- refs/heads/sc336/key_rotation
- refs/heads/sc336/mypy-sudden-failure
- refs/heads/sc336/notebook-kernel_link
- refs/heads/sc336/python-3-11
- refs/heads/sc336/sphinx_version_switcher
- refs/heads/sc336/v2.6.4
- refs/heads/sc336/v2.6.5
- refs/heads/sc336/version-numbers
- refs/heads/sergio_pasc/gpflow-2.0/adapt-sgpmc-and-gpmc
- refs/heads/sergio_pasc/gpflow-2.0/adapt-sgpr
- refs/heads/sergio_pasc/gpflow-2.0/move-gplvm-tests
- refs/heads/sergio_pasc/gpflow-2.0/move-multioutput-features-tests
- refs/heads/sergio_pasc/gpflow-2.0/move-quadrature-tests
- refs/heads/sergio_pasc/gpflow-2.0/move-tests-methods
- refs/heads/sergio_pasc/gpflow-2.0/ordinal_regression
- refs/heads/sergio_pasc/gpflow-2.0/parameter_transform
- refs/heads/sergio_pasc/gpflow-2.0/remove_training_loop
- refs/heads/spascual/add-mailmap-file
- refs/heads/st---metaautoflow
- refs/heads/st/clean_up_broadcasting_conditionals
- refs/heads/st/ericpena/natgrad-change
- refs/heads/st/fix_active_dims_2
- refs/heads/st/fix_config_module_docstring
- refs/heads/st/fix_test_method_equivalence
- refs/heads/st/fix_typo
- refs/heads/st/fxsm
- refs/heads/st/fxsm_closure
- refs/heads/st/inv_probit_jitter_arg
- refs/heads/st/new_svgp
- refs/heads/st/posterior
- refs/heads/st/posterior_with_linear_operators
- refs/heads/st/quickfix/dispatch_docs
- refs/heads/st/quickfix/posterior
- refs/heads/st/quickfix_num_latent
- refs/heads/st/rename_slow_multioutput
- refs/heads/st/reorder_covariances
- refs/heads/st/rescue_754
- refs/heads/st/snowflake_kernel
- refs/heads/st/test_cleanup
- refs/heads/st/test_for_shape_check
- refs/heads/st/test_kernel
- refs/heads/st/triangular
- refs/heads/st_FITCvsVFE_2.0
- refs/heads/stef/fxsm
- refs/heads/tf2.0-compatible
- refs/heads/transform_on_sided
- refs/heads/uri/bump_version_to_2_9_1
- refs/heads/uri/clarify_training_loss_ref_in_tutorial
- refs/heads/uri/dont_use_enums_for_default_values
- refs/heads/uri/heteroskedastic_linear_mean
- refs/heads/uri/pickling_scipy_optimizer
- refs/heads/uri/prod_test_environment
- refs/heads/uri/quickfix/dont_round_small_values_in_summary
- refs/heads/uri/quickfix/mypy_fixes
- refs/heads/uri/release_2_8_1
- refs/heads/uri/release_2_9_0
- refs/heads/uri/support_tf_2_12
- refs/heads/uri/test_sgpr_changepoint_issue
- refs/heads/uri/test_tf_2_16
- refs/heads/uri/track_loss_history
- refs/heads/uri/update_max_tf_version
- refs/heads/v1.5.1-docs
- refs/heads/va/additive_models
- refs/heads/va/gpf/conditional_kernel
- refs/heads/va/gpf/seeger_lik
- refs/heads/va/h
- refs/heads/vdutor/multiple-output-gps
- refs/heads/vincent/add-shared-mixed-mok
- refs/heads/vincent/cholesky-to-kl
- refs/heads/vincent/hotfix/preslicing-lmc
- refs/heads/vincent/hotfix/save-keras-model
- refs/heads/vincent/introspect-conditional
- refs/heads/vincent/more-predict-functions
- refs/heads/vincent/nbviewer
- refs/heads/vincent/quickfix/dynamic-shapes-quadrature
- refs/heads/vincent/quickfix/typo
- refs/heads/vincent/shared-mixed-mok
- refs/heads/vincent/st/heteroscedastic
- refs/heads/vincent/st/multi-output-likelihoods
- refs/heads/vincent/update-readme
- refs/heads/whitening
- refs/tags/0.2.1
- refs/tags/0.3.1
- refs/tags/0.3.2
- refs/tags/0.3.3
- refs/tags/0.3.4
- refs/tags/0.3.5
- refs/tags/0.4.0
- refs/tags/0.5.0
- refs/tags/1.0.0
- refs/tags/1.1.0
- refs/tags/1.1.1
- refs/tags/2.0.0-rc1
- refs/tags/v1.4.1
- refs/tags/v1.5.0
- refs/tags/v1.5.1
- refs/tags/v2.0.0
- refs/tags/v2.0.1
- refs/tags/v2.0.2
- refs/tags/v2.0.3
- refs/tags/v2.0.4
- refs/tags/v2.0.5
- refs/tags/v2.1.0
- refs/tags/v2.1.1
- refs/tags/v2.1.2
- refs/tags/v2.1.3
- refs/tags/v2.1.4
- refs/tags/v2.1.5
- refs/tags/v2.2.0
- refs/tags/v2.2.1
- refs/tags/v2.3.0
- refs/tags/v2.3.1
- refs/tags/v2.4.0
- refs/tags/v2.5.0
- refs/tags/v2.5.1
- refs/tags/v2.5.2
- refs/tags/v2.6.0
- refs/tags/v2.6.1
- refs/tags/v2.6.2
- refs/tags/v2.6.3
- refs/tags/v2.6.4
- refs/tags/v2.6.5
- refs/tags/v2.7.0
- refs/tags/v2.7.1
- refs/tags/v2.8.0
- refs/tags/v2.8.1
- refs/tags/v2.9.0
- refs/tags/v2.9.1
Raw File 
Take a new snapshot of a software origin
If the archived software origin currently browsed is not synchronized with its upstream version (for instance when new commits have been issued), you can explicitly request Software Heritage to take a new snapshot of it.
Use the form below to proceed. Once a request has been submitted and accepted, it will be processed as soon as possible. You can then check its processing state by visiting this dedicated page. Processing "take a new snapshot" request ...
Permalinks
To reference or cite the objects present in the Software Heritage archive, permalinks based on SoftWare Hash IDentifiers (SWHIDs) must be used.
Select below a type of object currently browsed in order to display its associated SWHID and permalink.
Tip revision: 6351237537b5a8bde53d837e37eb14820a42e23c authored by ST John on 16 October 2019, 16:04:45 UTC
reactivate SGPR equivalence test
reactivate SGPR equivalence test
Tip revision: 6351237
__init__.py
from .likelihoods import (Bernoulli, Beta, Exponential, Gamma, Gaussian,
GaussianMC, Likelihood, MonteCarloLikelihood,
MultiClass, Ordinal, Poisson, Softmax,
SwitchedLikelihood, StudentT, RobustMax)
