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: 3bba344ff65e112cea1aef3a6087bc7d611a0ad1 authored by Artem Artemev on 26 January 2023, 16:01:40 UTC
Use PyPi token for package uploading (#2043)
Use PyPi token for package uploading (#2043)
Tip revision: 3bba344
__init__.py
from .cglb import CGLB
from .gplvm import GPLVM, BayesianGPLVM
from .gpmc import GPMC
from .gpr import GPR
from .model import BayesianModel, GPModel
from .sgpmc import SGPMC
from .sgpr import GPRFITC, SGPR
from .svgp import SVGP
from .training_mixins import ExternalDataTrainingLossMixin, InternalDataTrainingLossMixin
from .util import maximum_log_likelihood_objective, training_loss, training_loss_closure
from .vgp import VGP, VGPOpperArchambeau
__all__ = [
"BayesianGPLVM",
"BayesianModel",
"CGLB",
"ExternalDataTrainingLossMixin",
"GPLVM",
"GPMC",
"GPModel",
"GPR",
"GPRFITC",
"InternalDataTrainingLossMixin",
"SGPMC",
"SGPR",
"SVGP",
"VGP",
"VGPOpperArchambeau",
"cglb",
"gplvm",
"gpmc",
"gpr",
"maximum_log_likelihood_objective",
"model",
"sgpmc",
"sgpr",
"svgp",
"training_loss",
"training_loss_closure",
"training_mixins",
"util",
"vgp",
]