Wheelodex » Projects » botorch

botorch

View on PyPI — Reverse Dependencies (52)

0.12.0 botorch-0.12.0-py3-none-any.whl

Wheel Details

Project: botorch
Version: 0.12.0
Filename: botorch-0.12.0-py3-none-any.whl
Download: [link]
Size: 644792
MD5: a453b231ec01236d4e02f10fe2db725f
SHA256: 7534566c1722d6997d4f6fd1ad0818f6a97d2975159b02ee94d410b34985347e
Uploaded: 2024-09-17 16:43:01 +0000

dist-info

METADATA · WHEEL · RECORD · top_level.txt

METADATA

Metadata-Version: 2.1
Name: botorch
Version: 0.12.0
Summary: Bayesian Optimization in PyTorch
Author: Meta Platforms, Inc.
Home-Page: https://botorch.org
Project-Url: Documentation, https://botorch.org
Project-Url: Source, https://github.com/pytorch/botorch
Project-Url: conda, https://anaconda.org/pytorch/botorch
License: MIT
Keywords: Bayesian optimization,PyTorch
Classifier: Development Status :: 4 - Beta
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: License :: OSI Approved :: MIT License
Classifier: Topic :: Scientific/Engineering
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Developers
Requires-Python: >=3.10
Requires-Dist: multipledispatch
Requires-Dist: scipy
Requires-Dist: mpmath (<=1.3,>=0.19)
Requires-Dist: torch (>=2.0.1)
Requires-Dist: pyro-ppl (>=1.8.4)
Requires-Dist: typing-extensions
Requires-Dist: gpytorch (==1.13)
Requires-Dist: linear-operator (==0.5.3)
Requires-Dist: pytest; extra == "dev"
Requires-Dist: pytest-cov; extra == "dev"
Requires-Dist: flake8; extra == "dev"
Requires-Dist: ufmt; extra == "dev"
Requires-Dist: flake8-docstrings; extra == "dev"
Requires-Dist: black (==24.4.2); extra == "dev"
Requires-Dist: ruff-api (==0.0.8); extra == "dev"
Requires-Dist: stdlibs (==2024.1.28); extra == "dev"
Requires-Dist: ufmt (==2.7.2); extra == "dev"
Requires-Dist: usort (==1.0.5); extra == "dev"
Requires-Dist: sphinx; extra == "dev"
Requires-Dist: pytest; extra == "test"
Requires-Dist: pytest-cov; extra == "test"
Requires-Dist: ax-platform; extra == "tutorials"
Requires-Dist: cma; extra == "tutorials"
Requires-Dist: jupyter; extra == "tutorials"
Requires-Dist: kaleido; extra == "tutorials"
Requires-Dist: matplotlib; extra == "tutorials"
Requires-Dist: memory-profiler; extra == "tutorials"
Requires-Dist: papermill; extra == "tutorials"
Requires-Dist: pykeops; extra == "tutorials"
Requires-Dist: torchvision; extra == "tutorials"
Provides-Extra: dev
Provides-Extra: test
Provides-Extra: tutorials
Description-Content-Type: text/markdown
License-File: LICENSE
[Description omitted; length: 9339 characters]

WHEEL

Wheel-Version: 1.0
Generator: setuptools (75.1.0)
Root-Is-Purelib: true
Tag: py3-none-any

RECORD

Path Digest Size
botorch/__init__.py sha256=RIsU0Bnyg3HrLxFrGgNRGCA7jjsyXBu6NGga1B-OK0E 2134
botorch/cross_validation.py sha256=ylEz-onEWzVbOdgHaQsw8MqSubE3_9Y5-CDT-8L7OP0 6914
botorch/fit.py sha256=WBpkfZRHu2Zeu5QwEy9bhsguS2n8yda7YI1qt7dBhuA 16519
botorch/logging.py sha256=ZiSmWNLvaALimUGNlhWAG_WrhLmObscj3R3apZ3HXZo 1170
botorch/settings.py sha256=j5kaNyBvTsPmIdWR9hVgpqfH4wpRC_nJNSOhmZx2bRQ 2944
botorch/version.py sha256=HJyq47ePtlF3WPYAhFFp5LPsrHyF6oju_vSEfklwWro 413
botorch/acquisition/__init__.py sha256=sdgBMzCrFqAJVbZWvq3J4CAzu6jnyuzmBVv7CB-U0gw 4391
botorch/acquisition/acquisition.py sha256=F7nPCzbs2WbAyigDlDozZSSsg6yJi8qVMuXwN8scjlY 6052
botorch/acquisition/active_learning.py sha256=IfNCqZdcF0UPMr6EcfAOXwKX_V3nnaNposuN_3Qvt8I 8113
botorch/acquisition/analytic.py sha256=9BW8YoryU8LpMYpLxsJGEuFe5SVAhB997XKm0-FmCs8 52432
botorch/acquisition/bayesian_active_learning.py sha256=tggOaLiXvfRCAInI7WMkSH6rxSLxTSnXSUzws_AmorU 6773
botorch/acquisition/cached_cholesky.py sha256=TXgsfWtVZ_f_qdnKdt_VQYbnafiGs2SbW4vS8Ti9pYU 7625
botorch/acquisition/cost_aware.py sha256=UuUzGwxM93ksEeL1cUCI7f3jaVEcdlc5EmvBqg8Koi4 9789
botorch/acquisition/decoupled.py sha256=OxL2cbIZ_9RBMrTWXm33qg6RHcck7GkUz0TeWQtXOGU 6923
botorch/acquisition/factory.py sha256=HEZtBFXhV2s1P4Jn5TB_mtC0NlaLY6dPYbEEF8J9mFE 9433
botorch/acquisition/fixed_feature.py sha256=kgreAfrA2iuohuELRyNJeZfzHPxNqejRssHXOqfaqiw 8008
botorch/acquisition/input_constructors.py sha256=K4ZjKbm9JsPuTQoRiO78NbCOXk3DONFDnUnm2FKFZW4 70539
botorch/acquisition/joint_entropy_search.py sha256=-tBfQVpY1SlqlFxy4sOFTypnmxR4GD5TPTqCZ71hprA 14981
botorch/acquisition/knowledge_gradient.py sha256=ixxEWqUffAC8yOIE4MFnsxOZF-bihSejEV-RsUBTN6I 26156
botorch/acquisition/logei.py sha256=CvwZ6Gbzb7410yVulyqF_GXvI6GgO8T35qmArXjOpHE 23630
botorch/acquisition/max_value_entropy_search.py sha256=T_vEKwZ8i46QoHTd1QLiLDS4_hM4He72TZWaTkn8_N8 45643
botorch/acquisition/monte_carlo.py sha256=Jhf0t8kxQ7JJDeh-V5dJP5HuElm5UHJFTj_b8LZ4avA 40944
botorch/acquisition/multi_step_lookahead.py sha256=Chsvfm4TvA3YSlmBYKks4hjCRjRQhdcS3d8suGXRJc8 29187
botorch/acquisition/objective.py sha256=945kzLJG_-aQI9Z_1W_rw_TFBrhSnxV4spqBqYyBrhk 22221
botorch/acquisition/penalized.py sha256=brth-v9HsoJ4kJoAdRncwOr7BLdIzYRYLvGgBmn7_ak 14855
botorch/acquisition/predictive_entropy_search.py sha256=UWsdYQ_23wSEudOwF_8xjW3omI3mEFADp3o6FibY5ts 4207
botorch/acquisition/preference.py sha256=_9FlrMlawtCxYziwTd48fzhRZmVMqgZ9d1pxGpYcX_Q 11046
botorch/acquisition/prior_guided.py sha256=dg7VZWabyyfKflV7eDL5lCgWDpNBim6xNKH5AOHfn7M 4235
botorch/acquisition/proximal.py sha256=ztjPEmK4p0fY94vPteKLzmywzK7I-nOY8iN-ju8TTmI 8229
botorch/acquisition/risk_measures.py sha256=ayNbG7RYiPMiDolx9cwE2nn8FwMr9FKO1CtwudvZR_4 12032
botorch/acquisition/thompson_sampling.py sha256=qCeE6QogaIonm-C5GyfD47nBiU7toKtlhIgd6vdYJM0 3167
botorch/acquisition/utils.py sha256=RUr52fTnMUsKR1zPYvucZGJLX5ffn-qXpJwE6YyRaYA 21101
botorch/acquisition/multi_objective/__init__.py sha256=ZXSgml563Khq3QSyROqGlEjxhdiDLpINKrITARSkpzI 2012
botorch/acquisition/multi_objective/analytic.py sha256=vS5xmka2fY_wqpTmpu-52hMLhkc9r3qLtDil3hoeIhQ 8521
botorch/acquisition/multi_objective/base.py sha256=0mTXohVB9UOOTrHSRo5TSI5Y5u_iYm7hoi7VyvGFtRw 6469
botorch/acquisition/multi_objective/hypervolume_knowledge_gradient.py sha256=sFeR7PFgXH4ud_Ami0ayWeTyBAUKBtUMNCRS9aRcbk8 25683
botorch/acquisition/multi_objective/joint_entropy_search.py sha256=THRieQlFp0g2IIbXw2tCFclPhBSobZIlU-_MoY3Is6Y 31237
botorch/acquisition/multi_objective/logei.py sha256=Yj7IEDm5wSDit3f-V0MUmakx48lbcJvGqX5QmG8SOy0 22232
botorch/acquisition/multi_objective/max_value_entropy_search.py sha256=mMgO8Q6zeoXIssEkiHfgtiAkPvlEhIY571kbRT70gq0 15691
botorch/acquisition/multi_objective/monte_carlo.py sha256=zYtTUJ54YL7epSI3k19IlUJICeqFuP71SDVQI2KsYmM 18037
botorch/acquisition/multi_objective/multi_fidelity.py sha256=JOSuer9vn91ZOr3VS8V4prfUqlFKXI4-0M1mynjP8mw 6581
botorch/acquisition/multi_objective/multi_output_risk_measures.py sha256=2YjSWCnMQ-OLjV1vWrbtosksCj-cm4qOBR3Sq_K_eXE 35385
botorch/acquisition/multi_objective/objective.py sha256=zwTG5eqTl0XE80z_WGHoSjIA4F79lW8vmOkQcKxOUBo 8112
botorch/acquisition/multi_objective/parego.py sha256=qzINyEEbY_PPeQ7dU82fpo2oUUelZ4nkLB4G5HTtsQQ 7186
botorch/acquisition/multi_objective/predictive_entropy_search.py sha256=vvBnp0EQ2_6IljUjz5Q8331JA1ze5BqwVkZLd0595NE 48919
botorch/acquisition/multi_objective/utils.py sha256=H20iGU9URJ6BHP527sQzhmUaeV1KGP8lYMx2-vJuJb4 15003
botorch/exceptions/__init__.py sha256=qGbgTLRXQ-31ZKvq67SiO6OvPdyfJMLbdSjLQcuh2c0 1076
botorch/exceptions/errors.py sha256=PHiTNTfRzSdIs8XEFqcDOo5PhL-6u0DgUDO7jc4BFws 2218
botorch/exceptions/warnings.py sha256=9Mr2ngP6eEn3wAfse9pneylTP5F6_AX1fgXKxf7SR8Y 3518
botorch/generation/__init__.py sha256=fxQqKvUex6MUKCBfY01BfHGW42iKE-nRiDynJvC7zmM 552
botorch/generation/gen.py sha256=8lYbbVOKj018UeylcfVFBeWztybLtAaQXGO9d1gxGE0 21081
botorch/generation/sampling.py sha256=bSdBRmlKkBu2hlFy9ig_m6zDuWZpaCbGaPEbOziuWXc 14966
botorch/generation/utils.py sha256=Yo6t9JqCIQJ-jBJoDr738uHKGByoaAHRbrJlYQYlQM0 7578
botorch/models/__init__.py sha256=Ls9j8JHJ9DTvU1BxrSc7xc5bdhrth0JndGNRALbCUBw 1747
botorch/models/approximate_gp.py sha256=pdK6g5_CgLArXZL7VpInAzeRigMSD3IA9bDCkpemfig 21597
botorch/models/contextual.py sha256=HeAILEk0nGSzS8znyL0AL8g261FAtjMYbIvJ6kzx-Ow 6933
botorch/models/contextual_multioutput.py sha256=OK_seXqbGDI_fJay-h6iz9kL7ozsN7IbGFqqq4OP3Qc 11399
botorch/models/converter.py sha256=3KjRjtAKmnhnlPW82ysHKE9rbYdKp1P_1yBeXRuQjeQ 19867
botorch/models/cost.py sha256=8I1_UrX0QzxCFI2uAy43oQe0dDid7pONkevKdOzGHfY 4287
botorch/models/deterministic.py sha256=coyayyLN_Hh1jIGVispqzcU4xdns17a8dBNB5nT88VU 7511
botorch/models/ensemble.py sha256=_0pLLalE_iZllhP4ey_-w0_VHGkfGeSkbN1BjsXTYKg 3337
botorch/models/fully_bayesian.py sha256=rDgX2mqay1Ffv6x2bFU_fhjnJo9j-vvJhJFQOWHSq0k 23937
botorch/models/fully_bayesian_multitask.py sha256=6EDl6HgOdiWk5gqCr4DC_UZdHgML-OBWMsSBxX9yi4E 18326
botorch/models/gp_regression.py sha256=qOtipyaGltGcszblEENMJ5mokc1DB2x_JaYBLPx6Z_k 16221
botorch/models/gp_regression_fidelity.py sha256=kZooY-hxsh5XTaNiKlCKrgg3eOFF1CEqlsSLgmJloJI 11986
botorch/models/gp_regression_mixed.py sha256=Nk2DsRKL7hcNc16O8O8Dyr0AhpAT78eeQhHHczfG2UM 7907
botorch/models/gpytorch.py sha256=24oC1TfnuQ7mhkbr75qKaiGeKIxTwfgukN-pf6tl2Z8 42776
botorch/models/higher_order_gp.py sha256=MOFy2O_PBsgSJQwYHEA2Jb_0ZxiNJwBhgPCF55eMUu8 24479
botorch/models/model.py sha256=P6DRlJRfUP7ucOqqrAWK-SeW2Pw-HkcdoTTsbDsNl5M 29121
botorch/models/model_list_gp_regression.py sha256=JGYvD9SydoXC94huMhI5rP3TnIVKs1OxlECaDHQHiz8 5979
botorch/models/multitask.py sha256=p197lDtiaWCxjQw00E0-cKjsAbTcD880vvlRnftPv3Q 34617
botorch/models/pairwise_gp.py sha256=8g5Cd7FkzX_sejqHjSZ5ZMJYwndwZK_fkXKXLHqFhUE 50196
botorch/models/kernels/__init__.py sha256=zHoaygL-FO9rMsZ5vr68yt2qL_8rZwTAj_gj6fmo6qA 752
botorch/models/kernels/categorical.py sha256=uzA9M4azgeG93aQ-cxsH3pnik5Kqh1OspyCDou2VHio 1180
botorch/models/kernels/contextual_lcea.py sha256=8WZdhVIz-VslFg4mvNY3H6Pf3Zm9aEo2zLYbheSyLu4 17576
botorch/models/kernels/contextual_sac.py sha256=gGOgqayecFUBKof_EWxaZBS0xRV1yRbqqSFgIq1-H9A 4247
botorch/models/kernels/downsampling.py sha256=d70prHF-lPmqolKWKK3n-FdH56fc7Mm1WBmUaMF88Dc 4251
botorch/models/kernels/exponential_decay.py sha256=-udAe5G_bPH3TTAQJgIHVKhYAHng2R6goGsV9c1BgS8 4247
botorch/models/kernels/infinite_width_bnn.py sha256=UocuIjhcJjNLg0-17y6raAzlytmxWFqeNFNwW1ahSlA 6442
botorch/models/kernels/linear_truncated_fidelity.py sha256=fBJEYUWZNtHvZ8_xy-gChjhWWg8pLFgegYgUNvmmR8M 10220
botorch/models/kernels/orthogonal_additive_kernel.py sha256=885RjUPmysJekV-jOv2newHg-jQOzBP_amgqoHwWT08 12155
botorch/models/likelihoods/__init__.py sha256=lec6jjQZqaAGCwEZaYXAVkePsqUc18a_xJFeDdguklg 393
botorch/models/likelihoods/pairwise.py sha256=rrgEfquQAnEDXXBXFSly1pixtTX7kEpIyVB8UzEHa-8 9062
botorch/models/transforms/__init__.py sha256=orl3VMjmgFk1B1mpUXu-e1gpyfZ1imhNHyyYKGRvtJk 726
botorch/models/transforms/factory.py sha256=cE_FGxXC_T1KES_MSPSejh1JrcDqlob4XFphGHkxfcs 4648
botorch/models/transforms/input.py sha256=RqnXYIu2RCV50pD1tj1G3rGs8M74Y3JzJ7WVw_iR7yk 65152
botorch/models/transforms/outcome.py sha256=xIHiHJeazeQSMoRdil1WOkIst2Jj3wzx_SqJ2pPJgcE 30751
botorch/models/transforms/utils.py sha256=y6HRlKR4zWilcVXoe8CbnMhD_HEUvZZFDv5cxXzUQ28 4402
botorch/models/utils/__init__.py sha256=KSHmjJz19OHDB_tX-o02aQvdJUDsC96u4sKtpmJvML0 879
botorch/models/utils/assorted.py sha256=wYZ8tiDSLBn2ZrkT15WuMKZzG5ZAQWyS_10GpAuMuac 15074
botorch/models/utils/gpytorch_modules.py sha256=jwhf-_9nxE1tejA0U8OrMLZM0MsX9UmUciK7b8RneMc 4820
botorch/models/utils/inducing_point_allocators.py sha256=8sRz4S-zClROJgEL0WVDSfYSMsEMnfv3ZbQHOjSJFVU 12753
botorch/optim/__init__.py sha256=NFBY6rHSE5anFjrUZhmLtkybSNBG2JfWUMq-91-ZPtk 1670
botorch/optim/core.py sha256=8B3Ep44msmnKV3-ZoOl1zNB-KqsNIDdbtyIKKK4v-cM 9140
botorch/optim/fit.py sha256=_U3KeO16V0At-CywWtZRzuWjN5xFhCVfDotbFveUpus 7473
botorch/optim/homotopy.py sha256=g7UfO8PrkjPfoWBu1Pm4nbIMmI3MERfnwxnRf4dksrc 5131
botorch/optim/initializers.py sha256=zbPc0Zq3_qihbh7RyzMluOv9AH5VjTG_MBWLI3AMN5Y 53716
botorch/optim/optimize.py sha256=otDcu-k3NyHeiWOpTQxJW9rHE7287gBuGGiuSU-vdvc 56912
botorch/optim/optimize_homotopy.py sha256=NtKThibK9yLq8ZV9wBFHmU6dzMM6fBBBWlWwDyK5yAw 5705
botorch/optim/parameter_constraints.py sha256=U0RE_RHg8wS91PnQuJAIM3snxDj0FGiyN6Tsx7EcsBo 24270
botorch/optim/stopping.py sha256=pxKwu7nN52OrR9j5JHNAx4_b54UdJRoU92q-uKlLb4A 4385
botorch/optim/closures/__init__.py sha256=QpWZOW-1b3EYDcnCr6vE6CsYweHXhQpQINV_oFo7IIk 555
botorch/optim/closures/core.py sha256=0tGYM8fIL45UipDyGQbUr4AR-3CrEYi-gRCWYaNX7XE 7804
botorch/optim/closures/model_closures.py sha256=bBBETRverU4CQC3QkQU5hLbvRbboe_MSl68U66u-HkU 8236
botorch/optim/utils/__init__.py sha256=8oI1l8VG3RHRb9LDFr7j9PwdV92jeb75OoQi51CH9oA 1250
botorch/optim/utils/acquisition_utils.py sha256=pKW_ourCrClNguzh0x7l9cjz4F4yzhfV5zhOqYeMrs4 5138
botorch/optim/utils/common.py sha256=XGBzVFuCDsfnjHWCwk8oL0rG6FHlMNoZ7nmUUHhNAV4 2106
botorch/optim/utils/model_utils.py sha256=Nt56M6J0tYk5HRQqHBqeWJbTLslCp8wcL6FkD0Q4ssE 7061
botorch/optim/utils/numpy_utils.py sha256=Edco8vddekDf6ozBkJZhZ7pdNJOMI7e1glvxMg-zl5k 5904
botorch/optim/utils/timeout.py sha256=VFg5xqFWZ1aqqCOKeLxcWN-zTMpmjPvhpOPbc1QSKBU 3801
botorch/posteriors/__init__.py sha256=LNXw47kidxOQQ21cliYeyL7vJDv22FFnYG_j28Cn-7M 973
botorch/posteriors/base_samples.py sha256=IZGD63HWtHJ-1EqvjuoMN-fbTXdzkpPPM0aps7lpCUA 1581
botorch/posteriors/ensemble.py sha256=Fwi4o2x1gWB8UuQGmuO9zlXU_7GNJE9oTjsjEZ63W_U 5027
botorch/posteriors/fully_bayesian.py sha256=PqOKMZ-yrWH4rO9rnsUHs6SB4EelUfZJ7tBwlVQm8mQ 6557
botorch/posteriors/gpytorch.py sha256=aVngGy1TAG26er88GejbUVgvBNhdfOdGpkIda5mWd8Q 12940
botorch/posteriors/higher_order.py sha256=_AnMuM0T0L3NRMCoDyr1BG4mFKVhVsfxK_d7cl9BkGo 11372
botorch/posteriors/multitask.py sha256=gmzMZawo9NH6m-UIgzXWSoHdz54MNAZI75NhAnWo0f8 12396
botorch/posteriors/posterior.py sha256=18FXef2M7RGiQNhvbyQeK99m8y9S8yLdZZdIGRyxSsY 5121
botorch/posteriors/posterior_list.py sha256=HtWapEbj5Qk0kaLcnlRaQ4WV1wIZKXipba6Oax7XvUk 7074
botorch/posteriors/torch.py sha256=mJa9kXJVphEaT4MphxnCFFgD4ThgYEYJbqUwcCsc3u0 4247
botorch/posteriors/transformed.py sha256=bX1chARnG1C2EmCqiUj6jMJn5arQvt2SAwCt5_RSF7M 5744
botorch/sampling/__init__.py sha256=vTp26Tao0ZJU-4c58DRBgtrBSjLkJIkjS1zsB4g98Gg 1118
botorch/sampling/base.py sha256=mVpT0ognacUhDNCRWixe8WGydZ6RJWe-tyA42EeUe-0 5190
botorch/sampling/get_sampler.py sha256=KAt54NZRDIT8gJAMkMDCuhV944eWIg9BBuGqFRiz7-M 4626
botorch/sampling/index_sampler.py sha256=6GGsr3wP5Z9vnG27hjD4faLPeSJOf0sFpMgU9IytDPM 2289
botorch/sampling/list_sampler.py sha256=RsdBtGydpbq96eQPNcOpBQYhivH6-LHgCSlJH1jgMaI 2657
botorch/sampling/normal.py sha256=g42KW1nRVLpBnZM7ePjWMkwNj2ETIbxqsNft2Y8epf8 8631
botorch/sampling/pairwise_samplers.py sha256=fbUjwR3hjcQuPRrAkDRZH6OD_hwcCKI1VhIhK7vwJGU 4474
botorch/sampling/qmc.py sha256=1iPa6Tbr_PQY3Fua73P0TGvg18OS6diiNBwmhAEGTSY 6712
botorch/sampling/stochastic_samplers.py sha256=s5_Z5xAKJ0dYPLO63lXg25jcJRJtFxBuHHH_WUkxdq0 2232
botorch/sampling/pathwise/__init__.py sha256=1VpKzl2nIKGcAYb5SQNrjdvHuh4DvoWKAe54pG1vfis 1037
botorch/sampling/pathwise/paths.py sha256=pkTwRqykHQjs_AmdKecfOu27602uBuWKx_QTNUcvsrM 6158
botorch/sampling/pathwise/posterior_samplers.py sha256=5HzO-3sNQytLleXMFZB3tcMpqtVq5UaeLUKqEBcGjtg 9453
botorch/sampling/pathwise/prior_samplers.py sha256=-5br8oaCequh-YUan_ZGhMUC3KiX40_ZscNnUtvSrPY 5414
botorch/sampling/pathwise/update_strategies.py sha256=4LnaR3I8lQnvU8-043IaXJ_hLQpGccjhiXUJg2sZiTk 7054
botorch/sampling/pathwise/utils.py sha256=9cF-3weudWqBmCCw_d0jYefnmzxcf9ykeoB8zTxv8Fg 10551
botorch/sampling/pathwise/features/__init__.py sha256=OYkf9Zl9FkrgnSu8JJb1jMSVBkon_Ig9WmrpAmmUquI 512
botorch/sampling/pathwise/features/generators.py sha256=O6kyJLWwETijC7cftBp8mXXvVMlMDZ8bJP-PyrgWuFs 6229
botorch/sampling/pathwise/features/maps.py sha256=M6Z9O7opeDhHayyzAlb2RA--6KquyDrHOcCqx1r8qTg 4458
botorch/test_functions/__init__.py sha256=FF1rTiWE9Pz2ZBtbYVDq34kcdKmsRPndNI0HF5kXDJc 2195
botorch/test_functions/base.py sha256=ZOBFT_v8E8Nhb6ZjRTwEgRw2JPBb85_99laZHylgLEY 7206
botorch/test_functions/multi_fidelity.py sha256=H32NvllwYll1nKEz9XE2-n9SRa7qVFbg3oi_Iqj8ffg 5316
botorch/test_functions/multi_objective.py sha256=It6zMcMQGhOXMlirBd0GJL-SPhLpnTY7GQBZ9nDrAR8 50261
botorch/test_functions/multi_objective_multi_fidelity.py sha256=c72TMPRTutda7mooDeduPrKi9NiCssdpc2XOGLJPHrY 4803
botorch/test_functions/sensitivity_analysis.py sha256=E2NRQX0jqA5dH__tjFiDm1K0e0o6ZlLWT-bVcF5Qyzw 8856
botorch/test_functions/synthetic.py sha256=pcpshmeBG7gr4ire084WjQg9Zy3yFZluAP43_CCFtxU 39399
botorch/test_functions/utils.py sha256=etQxQGcRh7z9ejvpS4keait9uRmA-bPucr8h9EFeE_U 1105
botorch/utils/__init__.py sha256=ueq-ZUX9flpcztpXql4KbCtlxA7B6jNThpRGMeLnuXM 1023
botorch/utils/constants.py sha256=hDD0skOUIyPFweNu3bJ57n0YnsGBAH-NaIsq6okWKYY 1223
botorch/utils/constraints.py sha256=If9mJ7jtwIw2xeFqvJ05r0MP2AlsLp1qUOqFf2qE8YU 3462
botorch/utils/containers.py sha256=0qjaY1Z6HKXk6jU36zbisjGFkPuRTTIsSPad3zXPPnI 4437
botorch/utils/context_managers.py sha256=BVtAWez8BZdEWpabdAgT0B67yxAaU1-LRTz0xy4oBJg 5664
botorch/utils/datasets.py sha256=5uiAZKqMgA3LCGXhEHN1J58VRykRnc0rDG2l28WZVZQ 26084
botorch/utils/dispatcher.py sha256=2ktVv9yr7IjK8WFbUTOx5ASghe8H-F5VyAmQRs6IpiI 5600
botorch/utils/feasible_volume.py sha256=AOM0pm2AHcD8SCQh-hFnJwlg7lB-oEIo5xCFagz5YTg 7839
botorch/utils/gp_sampling.py sha256=FF7Kmxj6wwQz07aOPrrWiOcQ846SSKsi_kiyDOEI27c 20756
botorch/utils/low_rank.py sha256=GjNXQdQK8yriIufnZ6aiZyJQsK0ApU6dqkTtX9v8JTM 6290
botorch/utils/multitask.py sha256=EZ0MPXJIXblFkq2vuYQtlUMOmll2zZlYansVdajTmHE 1698
botorch/utils/objective.py sha256=q9qpn0zFsiExzQhr0E8fwObcwhv9q2y1Grjhnb2N8YI 9170
botorch/utils/rounding.py sha256=FAliaBdQd-J7wBOS1JosZfuukzPcgvTjuBrdBT3gwZ8 3107
botorch/utils/safe_math.py sha256=bO6Gk3aehmyBFr-vjGuv4ZC-ElkZBt7hpgZ5wahh6vk 18136
botorch/utils/sampling.py sha256=OycZGlzuUAryBT4j86_iO9AUL-HgDkvnZCttKnFAZQI 42693
botorch/utils/test_helpers.py sha256=md26I7sWvYT99D6IKYEtHIG5Q-8SUNTKwUL7RucK6wU 12222
botorch/utils/testing.py sha256=k5mwkFUs0LUJqa_X9DJfPLxB4lJNBIm4dXdA8I4gYgI 18857
botorch/utils/torch.py sha256=bTweHr6tpbnggK7IMO-0NGpDl6_zaFmkDs26Xqo7gl4 5641
botorch/utils/transforms.py sha256=XGeEpXtwRtnM0ZDaC4rJE-Fvr8IaTH3NK6A1Ka_u1e4 13517
botorch/utils/types.py sha256=Mtom8SKy9B3RJgQIrXrAwD_v0EAnrN5G4RrTNuAT6HQ 539
botorch/utils/multi_objective/__init__.py sha256=WFuFLnkEhZ_eHLOuRoyEvsxyH-qObpxiv2U0n2ooGM8 565
botorch/utils/multi_objective/hypervolume.py sha256=tM6P2RsxERQiVL9emchlL5Y3_W9z4ogXtM1yOv8KKGQ 33713
botorch/utils/multi_objective/pareto.py sha256=oQybSJzFCqdt79py7YB7srdUDxI-EwaDuy8vOKHLeBE 4733
botorch/utils/multi_objective/scalarization.py sha256=lviJ7LbkOVPe3YDPuAkKOWJZDZ5fTFJl71smbaUAOKc 4451
botorch/utils/multi_objective/box_decompositions/__init__.py sha256=9Io4Sa3XbViCvuZmCF9r2Vbh3g0tGL07gGH5dgF-16o 972
botorch/utils/multi_objective/box_decompositions/box_decomposition.py sha256=8tmh3GXeUC9qaxIjhD0cjyvmIf7Ib3fEHwNF7kpjeMs 13342
botorch/utils/multi_objective/box_decompositions/box_decomposition_list.py sha256=OEFr0Zk1lUp15xJwj8M0O9TymIAM0BLbAD1kJR1OBnw 4473
botorch/utils/multi_objective/box_decompositions/dominated.py sha256=FnZg9U1bkvbC8anQXC8TIyE40R5e1fvtaDfZVixism0 2554
botorch/utils/multi_objective/box_decompositions/non_dominated.py sha256=GbeEZE2CGEqWIgyDbacXrfzJytGOBVKhCmJzFal9jp0 18402
botorch/utils/multi_objective/box_decompositions/utils.py sha256=-yN09AIe5bu5cUfYDDq7kG8sNYQle5gi8wXt-4JvZDQ 12728
botorch/utils/probability/__init__.py sha256=5Bv4XmAEKqhkiGN-buVOBP_JVrcBpe-Oopfeu8feaa4 777
botorch/utils/probability/bvn.py sha256=h-oUgGvMyswFzdSaco_Mnz2XNRRpt6UKe7X265QAFSU 11152
botorch/utils/probability/lin_ess.py sha256=O38KeUscDVQ5KZfMXfkDdWd-cI79FgWG_fSKPTMEjwc 21868
botorch/utils/probability/linalg.py sha256=3gMWUA4D2dUtgPUsVEQbIHop4tvlm0c-RvJNR6O5J2w 7843
botorch/utils/probability/mvnxpb.py sha256=Q8KaQY0Tyv4D1MWKgSQo2nmsiMQom34eHElp_q5ryvY 16553
botorch/utils/probability/truncated_multivariate_normal.py sha256=CmJYQbGqO27aAc3gMsjedXJyaWHbvPK72ff0YPGeTBE 5703
botorch/utils/probability/unified_skew_normal.py sha256=Yb9LvJlMtfgeKgMpkWC3V2sS4kWlay30q7zkl-MzPqU 10755
botorch/utils/probability/utils.py sha256=MrI79K2UAr_KWUzLDxsrIg_KbHCFUgPQS1a2MYsHiFg 11405
botorch_community/__init__.py sha256=D9ECsap08rcUtHyaR111nTjArlKkUjQwP8usXwXAAVQ 179
botorch_community/acquisition/__init__.py sha256=_qz-KCtv30QdQ_IJmWONjLc84--F-WC0SNleYkXtp_A 778
botorch_community/acquisition/augmented_multisource.py sha256=Ys7p7tmtmT3YZ9zc6PHY9BqdlbZt5u2iJRq6d4WOMVE 5860
botorch_community/acquisition/bayesian_active_learning.py sha256=QT2n0h0yCU7K2vU0g1fKpZPAFIkBAnzbdtKM2ofmFkg 5668
botorch_community/acquisition/hentropy_search.py sha256=xv_B5Vbi7Rsgos5GqTWbWMPiISxvVMYUIxVjpHsTkCc 10008
botorch_community/acquisition/input_constructors.py sha256=d3VxRS1HUNk0_JcTr1eqPBaXOcb_rRcQDyqyCnKpBA4 2368
botorch_community/acquisition/scorebo.py sha256=7-qGrbTNRyiFGPGwrDb8jAS12zpgnACo21mdQDWt1UY 7101
botorch_community/models/__init__.py sha256=D9ECsap08rcUtHyaR111nTjArlKkUjQwP8usXwXAAVQ 179
botorch_community/models/example.py sha256=Ag2c0gj1prK7BRKtFPtrD9F092Yd6aXuBR26eobRBt0 1341
botorch_community/models/gp_regression_multisource.py sha256=uqXwSyyIaa0hZ806rVzQsqQMTwAtQWYeY6kt0ELmERQ 10418
test_community/__init__.py sha256=fTYzXiizmsKFSPzKi4M1OUaq7oMyIFpYEuzMp2KAOLw 236
test_community/acquisition/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
test_community/acquisition/test_bayesian_active_learning.py sha256=eHNphhW0hRI-X9Co0GOGBbUAy0XWkODXHgQtDluxUTg 6569
test_community/acquisition/test_hentropy_search.py sha256=gnIvFv8lYS6S26jUz8_WxJNOVr8XfaSLkH5RIX7gf2E 9627
test_community/acquisition/test_input_constructors.py sha256=IjX6as-M-349BkxXGoWsCxqQtwG95f34MEIObnDd_54 6914
test_community/acquisition/test_multi_source.py sha256=oh7NMJRNh9cO6d5z9x9QCJUzwFLKLYzG9NOTqe3jo5Y 7296
test_community/acquisition/test_scorebo.py sha256=mZ7vDbh4Yy6qN8wSCMG4pAOdyYhxV3FLrcZkpyhEXpw 3445
test_community/models/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
test_community/models/test_example.py sha256=UursLsZmcKFdZKYkY7JTccuicRUtHefX3dw1yLx74EY 710
test_community/models/test_gp_regression_multisource.py sha256=ISCz-7oD5CrIDISMtQxYH3_iriQfUlN-rtrDjcXXzV8 15621
botorch-0.12.0.dist-info/LICENSE sha256=2m03A-0Ry-Qr0hLHJZV8mNojy_8ZmMBfpLPZdtGljpM 1088
botorch-0.12.0.dist-info/METADATA sha256=GgRwkZTNrccslT9Jyni12OKEjqGLN0q-S5Iocccr9AQ 11370
botorch-0.12.0.dist-info/WHEEL sha256=GV9aMThwP_4oNCtvEC2ec3qUYutgWeAzklro_0m4WJQ 91
botorch-0.12.0.dist-info/top_level.txt sha256=XAIiN0f5o3hqrFGdA1lUmBo3WchKr8LYTi6y6T1eYm4 41
botorch-0.12.0.dist-info/RECORD — —

top_level.txt

botorch
botorch_community
test_community