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: cc1027160395b98ea1aeeeddbb658286e59598a0 authored by Gustavo Carvalho on 05 October 2020, 13:02:59 UTC
testing HeteroskedasticGaussian likelihood from varying_noise notebook
testing HeteroskedasticGaussian likelihood from varying_noise notebook
Tip revision: cc10271
__init__.py
import warnings
import numpy as np
import tensorflow as tf
import gpflow
warnings.filterwarnings("ignore")
gpflow.config.set_default_float(np.float64)
