torch-timeseries

View on PyPIReverse Dependencies (0)

0.1.3 torch_timeseries-0.1.3-py3-none-any.whl

Wheel Details

Project: torch-timeseries
Version: 0.1.3
Filename: torch_timeseries-0.1.3-py3-none-any.whl
Download: [link]
Size: 114505
MD5: a47f49da119b9028f10f91e02af65da3
SHA256: 0e2f85ebb0c15d0a21db307f1601588d996304b1b1ee03badd1ae8b47fd592e1
Uploaded: 2024-06-24 07:50:34 +0000

dist-info

METADATA

Metadata-Version: 2.1
Name: torch-timeseries
Version: 0.1.3
Summary: Timeseries Learning Library for PyTorch.
Author: Weiwei Ye
Author-Email: Wayne Yip <wwye155[at]gmail.com>
Home-Page: https://github.com/wayne155/pytorch_timeseries
Download-Url: https://github.com/wayne155/pytorch_timeseries/archive/0.1.3.tar.gz
Project-Url: Documentation, https://pytorch-timeseries.readthedocs.io
Project-Url: BugTracker, https://github.com/wayne155/pytorch_timeseries/issues
License: Apache License Version 2.0, January 2004 http://www.apache.org/licenses/ TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION 1. Definitions. "License" shall mean the terms and conditions for use, reproduction, and distribution as defined by Sections 1 through 9 of this document. "Licensor" shall mean the copyright owner or entity authorized by the copyright owner that is granting the License. "Legal Entity" shall mean the union of the acting entity and all other entities that control, are controlled by, or are under common control with that entity. For the purposes of this definition, "control" means (i) the power, direct or indirect, to cause the direction or management of such entity, whether by contract or otherwise, or (ii) ownership of fifty percent (50%) or more of the outstanding shares, or (iii) beneficial ownership of such entity. "You" (or "Your") shall mean an individual or Legal Entity exercising permissions granted by this License. "Source" form shall mean the preferred form for making modifications, including but not limited to software source code, documentation source, and configuration files. "Object" form shall mean any form resulting from mechanical transformation or translation of a Source form, including but not limited to compiled object code, generated documentation, and conversions to other media types. "Work" shall mean the work of authorship, whether in Source or Object form, made available under the License, as indicated by a copyright notice that is included in or attached to the work (an example is provided in the Appendix below). "Derivative Works" shall mean any work, whether in Source or Object form, that is based on (or derived from) the Work and for which the editorial revisions, annotations, elaborations, or other modifications represent, as a whole, an original work of authorship. For the purposes of this License, Derivative Works shall not include works that remain separable from, or merely link (or bind by name) to the interfaces of, the Work and Derivative Works thereof. "Contribution" shall mean any work of authorship, including the original version of the Work and any modifications or additions to that Work or Derivative Works thereof, that is intentionally submitted to Licensor for inclusion in the Work by the copyright owner or by an individual or Legal Entity authorized to submit on behalf of the copyright owner. For the purposes of this definition, "submitted" means any form of electronic, verbal, or written communication sent to the Licensor or its representatives, including but not limited to communication on electronic mailing lists, source code control systems, and issue tracking systems that are managed by, or on behalf of, the Licensor for the purpose of discussing and improving the Work, but excluding communication that is conspicuously marked or otherwise designated in writing by the copyright owner as "Not a Contribution." "Contributor" shall mean Licensor and any individual or Legal Entity on behalf of whom a Contribution has been received by Licensor and subsequently incorporated within the Work. 2. Grant of Copyright License. Subject to the terms and conditions of this License, each Contributor hereby grants to You a perpetual, worldwide, non-exclusive, no-charge, royalty-free, irrevocable copyright license to reproduce, prepare Derivative Works of, publicly display, publicly perform, sublicense, and distribute the Work and such Derivative Works in Source or Object form. 3. Grant of Patent License. Subject to the terms and conditions of this License, each Contributor hereby grants to You a perpetual, worldwide, non-exclusive, no-charge, royalty-free, irrevocable (except as stated in this section) patent license to make, have made, use, offer to sell, sell, import, and otherwise transfer the Work, where such license applies only to those patent claims licensable by such Contributor that are necessarily infringed by their Contribution(s) alone or by combination of their Contribution(s) with the Work to which such Contribution(s) was submitted. If You institute patent litigation against any entity (including a cross-claim or counterclaim in a lawsuit) alleging that the Work or a Contribution incorporated within the Work constitutes direct or contributory patent infringement, then any patent licenses granted to You under this License for that Work shall terminate as of the date such litigation is filed. 4. Redistribution. You may reproduce and distribute copies of the Work or Derivative Works thereof in any medium, with or without modifications, and in Source or Object form, provided that You meet the following conditions: (a) You must give any other recipients of the Work or Derivative Works a copy of this License; and (b) You must cause any modified files to carry prominent notices stating that You changed the files; and (c) You must retain, in the Source form of any Derivative Works that You distribute, all copyright, patent, trademark, and attribution notices from the Source form of the Work, excluding those notices that do not pertain to any part of the Derivative Works; and (d) If the Work includes a "NOTICE" text file as part of its distribution, then any Derivative Works that You distribute must include a readable copy of the attribution notices contained within such NOTICE file, excluding those notices that do not pertain to any part of the Derivative Works, in at least one of the following places: within a NOTICE text file distributed as part of the Derivative Works; within the Source form or documentation, if provided along with the Derivative Works; or, within a display generated by the Derivative Works, if and wherever such third-party notices normally appear. The contents of the NOTICE file are for informational purposes only and do not modify the License. You may add Your own attribution notices within Derivative Works that You distribute, alongside or as an addendum to the NOTICE text from the Work, provided that such additional attribution notices cannot be construed as modifying the License. You may add Your own copyright statement to Your modifications and may provide additional or different license terms and conditions for use, reproduction, or distribution of Your modifications, or for any such Derivative Works as a whole, provided Your use, reproduction, and distribution of the Work otherwise complies with the conditions stated in this License. 5. Submission of Contributions. Unless You explicitly state otherwise, any Contribution intentionally submitted for inclusion in the Work by You to the Licensor shall be under the terms and conditions of this License, without any additional terms or conditions. Notwithstanding the above, nothing herein shall supersede or modify the terms of any separate license agreement you may have executed with Licensor regarding such Contributions. 6. Trademarks. This License does not grant permission to use the trade names, trademarks, service marks, or product names of the Licensor, except as required for reasonable and customary use in describing the origin of the Work and reproducing the content of the NOTICE file. 7. Disclaimer of Warranty. Unless required by applicable law or agreed to in writing, Licensor provides the Work (and each Contributor provides its Contributions) on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied, including, without limitation, any warranties or conditions of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A PARTICULAR PURPOSE. You are solely responsible for determining the appropriateness of using or redistributing the Work and assume any risks associated with Your exercise of permissions under this License. 8. Limitation of Liability. In no event and under no legal theory, whether in tort (including negligence), contract, or otherwise, unless required by applicable law (such as deliberate and grossly negligent acts) or agreed to in writing, shall any Contributor be liable to You for damages, including any direct, indirect, special, incidental, or consequential damages of any character arising as a result of this License or out of the use or inability to use the Work (including but not limited to damages for loss of goodwill, work stoppage, computer failure or malfunction, or any and all other commercial damages or losses), even if such Contributor has been advised of the possibility of such damages. 9. Accepting Warranty or Additional Liability. While redistributing the Work or Derivative Works thereof, You may choose to offer, and charge a fee for, acceptance of support, warranty, indemnity, or other liability obligations and/or rights consistent with this License. However, in accepting such obligations, You may act only on Your own behalf and on Your sole responsibility, not on behalf of any other Contributor, and only if You agree to indemnify, defend, and hold each Contributor harmless for any liability incurred by, or claims asserted against, such Contributor by reason of your accepting any such warranty or additional liability. END OF TERMS AND CONDITIONS APPENDIX: How to apply the Apache License to your work. To apply the Apache License to your work, attach the following boilerplate notice, with the fields enclosed by brackets "[]" replaced with your own identifying information. (Don't include the brackets!) The text should be enclosed in the appropriate comment syntax for the file format. We also recommend that a file or class name and description of purpose be included on the same "printed page" as the copyright notice for easier identification within third-party archives. Copyright [yyyy] [name of copyright owner] Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.
Keywords: deep Learning,time series,pytorch
Requires-Python: >=3.8
Requires-Dist: numpy
Requires-Dist: pandas
Requires-Dist: sktime
Requires-Dist: pandas (>=0.29.0)
Requires-Dist: scikit-learn
Requires-Dist: tqdm
Requires-Dist: prettytable
Requires-Dist: torchmetrics (==1.1.1)
Requires-Dist: fire (>=0.5.0)
Requires-Dist: pytest; extra == "dev"
Requires-Dist: pre-commit; extra == "dev"
Requires-Dist: pyg; extra == "g"
Requires-Dist: pytest; extra == "test"
Provides-Extra: benchmark
Provides-Extra: dev
Provides-Extra: full
Provides-Extra: g
Provides-Extra: test
Description-Content-Type: text/markdown
License-File: LICENSE
[Description omitted; length: 7683 characters]

WHEEL

Wheel-Version: 1.0
Generator: setuptools (70.1.0)
Root-Is-Purelib: true
Tag: py3-none-any

RECORD

Path Digest Size
torch_timeseries/__init__.py sha256=zVTj3DqgZW46iYYlup4XP1FeozzS9YqNYg2IKQDGrgY 122
torch_timeseries/cli/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
torch_timeseries/cli/exp.py sha256=J3KvN-ez9rT6BcD8CULS-jCnokhHNCTpu-HmW3eq0_c 1096
torch_timeseries/core/__init__.py sha256=0CGoyVPRS2Y-0PV0d5p8EIFJ-0qO1p1lVEhmZLrgRFU 209
torch_timeseries/core/scaler.py sha256=apXL8oS7laHi4GbcFD5wZYoXOXaB96W3oh241TiWkPU 1696
torch_timeseries/core/dataset/__init__.py sha256=gnllLHhecBrZn4npkRVYhbeMRruibN2g1NYABZ-kn94 128
torch_timeseries/core/dataset/anomaly.py sha256=QfB6cUh6deKm4fBA71jXOypd12dQCSePvjn-RcA_9LU 245
torch_timeseries/core/dataset/dataset.py sha256=kFVKDz6TJ0Ph6KR60GVr8M57-oH6Tu7W7QUx4DeqnHI 2975
torch_timeseries/core/experiments/__init__.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
torch_timeseries/core/experiments/settings.py sha256=RmqiTHWk8yCRMEL0hQvslvg-AmDgc5x6xfLMA8VkD-8 843
torch_timeseries/dataloader/__init__.py sha256=g_fxPZTYoFBoPEKhSPC2iYKhC6ETeQ_HdT9yKl3kh1U 714
torch_timeseries/dataloader/anomaly.py sha256=3aTQiYd_-i94LI21MT-m_-v5qgis1RBGpTzhKDOEjIE 5792
torch_timeseries/dataloader/maskts.py sha256=2UESs20akWrvbU923JwnhucqvZ2bqEP7Q-RsB4-dd9A 7277
torch_timeseries/dataloader/sliding_window.py sha256=BM3g6BFKpds5IdsjeuTc1VcL9O5RCBWLpsio7o8Ohvw 5452
torch_timeseries/dataloader/sliding_window_ts.py sha256=A3KzNWKAi09wVcX79xCi-618MlxWwlHsR4-vnx4Uc0c 6101
torch_timeseries/dataloader/uea.py sha256=iQFHacN3XPKvL84RWTdXT7LtkQIVqRcFQDTfMkvZoSk 6963
torch_timeseries/dataloader/wrapper.py sha256=DVENgTeJeSHdmnofDR5gvKR2866g6bIox3mXiWFT1yA 7919
torch_timeseries/dataset/ETTh1.py sha256=D4w0Lpzo30AfiqNK9wWj_wktJI_bVn0-AnmHXmjACAU 1757
torch_timeseries/dataset/ETTh2.py sha256=k20gLWPz6HyLvqr2XI15dYT5TdJ0k-eqZyiPni_O96w 1882
torch_timeseries/dataset/ETTm1.py sha256=v1dBEXxtd6ThRBRHUzYxYLgjulyOkpmTN0sHfjZzizY 1817
torch_timeseries/dataset/ETTm2.py sha256=DsKwshvsLmyKZABJmyygO4670zsJ9T0UU79SL3ryvIg 1826
torch_timeseries/dataset/Electricity.py sha256=e5w4qVlY8hQRJZyh9_nmRf23CVrr6m6SMfT-lOkQzvo 1914
torch_timeseries/dataset/ExchangeRate.py sha256=ygyVOsu3xBtaytD4l0zwyknrZ_kMYOGBYJn0wnrbkcg 1755
torch_timeseries/dataset/ILI.py sha256=3PSJT4itSb6aBpsikq_60aNwEaz_UUu9A1iXp-Zmeuc 2120
torch_timeseries/dataset/M4.py sha256=nNtofgF5uE_MtRHH6wHY68vTNA6wAxmv1UE7tTL1Wfc 2724
torch_timeseries/dataset/MSL.py sha256=6O4exenl-QbeFE6uvZOWlJkSeHRCCKw7jWaKzl6o-j8 1256
torch_timeseries/dataset/PSM.py sha256=LLrK13BG4Wkhx3Wy9nvulh7d1PO639eh2Sd18W8P30Y 1439
torch_timeseries/dataset/SMAP.py sha256=9KGpq6w9zx9ee9b7_uIh4DOg7ULHTe1kRjr-ABNCz68 1324
torch_timeseries/dataset/SMD.py sha256=ebojs5GJErkV4nA31ubGNQmuBUvN7I5kcW8WYVIC1Mk 1269
torch_timeseries/dataset/SWaT.py sha256=EknFkMurxHpXCltOo6rihCzPoPEH5ZKdDCkfJut_SB0 1358
torch_timeseries/dataset/SolarEnergy.py sha256=dBky3rKh9-m-sRJ9TGy6CYiU6G61dg2HFdpOhis1lRI 3459
torch_timeseries/dataset/Traffic.py sha256=7E7Dj1SyIQFYrZ344xJmqbnT3sEmW4zptrccBVL1d_k 2008
torch_timeseries/dataset/UEA.py sha256=NI2wWmLPh2OkNac1JugnGBjIamV7bYWrrPYwWe4Srkw 4755
torch_timeseries/dataset/Weather.py sha256=06o4A2TaPqR866NYB8sLLiQLyJay7i9EwoxQGZOghJs 1811
torch_timeseries/dataset/__init__.py sha256=nef4YGDFSnAyrZOFmma4gvo031y_kjYbK_tMNMv4su8 932
torch_timeseries/dataset/dummies/__init__.py sha256=qmB0AJRVbaHZ68cpy1XeAKX0g8s65C_P_h1-AwEdIG4 60
torch_timeseries/dataset/dummies/dummy.py sha256=LfF-Tt6WK0yPZWNza1ajzyneVzr_oHUy8CeQIBAaWg0 1132
torch_timeseries/dataset/dummies/dummy_graph.py sha256=OiC2gcd5YS2jjfZx5Fm7zjQLC9a7UG3-f5FRj0jaM24 1524
torch_timeseries/experiments/Autoformer.py sha256=InLtnBiINNnknzetxsbXJRQTaqc7yG7SbYDV1qFucqs 9324
torch_timeseries/experiments/DLinear.py sha256=9e7Zw74xBjRULEJ1CnJII75rheivuC_UNkE4PrHEbRw 4080
torch_timeseries/experiments/FEDformer.py sha256=TEJe0maq5qeqbbT-tyHLjtkuc_zuY9fjVYXKXXzjpHI 10461
torch_timeseries/experiments/Informer.py sha256=0xgXSw17k6xJMebX6_TFKWD7IYnRqk3TTkAsM23QMUk 9124
torch_timeseries/experiments/PatchTST.py sha256=sxMQzEWrKytgd_ucyZ8yAwvhZpW-k8RX8pyOIGVcBns 5837
torch_timeseries/experiments/__init__.py sha256=SrIvIKRqtCsLsYKQtsX7gbgXQOxPZWWyMNL6EnsSfqU 991
torch_timeseries/experiments/anomaly_detection.py sha256=46yptmbYc81ShPUyC8-sz88AewhiUkvofd3Z4Cgeb8o 18382
torch_timeseries/experiments/base.py sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU 0
torch_timeseries/experiments/forecast.py sha256=voemFCVpIOMdOPX-jHvVNipwKOtu3dJ-c2JNlzF23Is 16401
torch_timeseries/experiments/iTransformer.py sha256=B_XJvcIFWxH9-BeaH2JVZBf4Uy-EjPL1S9EjlTNbI_U 8242
torch_timeseries/experiments/imputation.py sha256=K91KTDY3Vfc6eMj8FTrQ0HDONlkNoMavUGFhaOTw8Vc 16442
torch_timeseries/experiments/uea_classification.py sha256=7_twPs4YguIwf8FIUTo9JCNOflWRwFL9vmLG6CdeKYg 15145
torch_timeseries/model/Autoformer.py sha256=L0Og6jcTRraGQIC3ugF07KmHqbFqRAsJRnDjk6GRuLM 4562
torch_timeseries/model/DLinear.py sha256=tNveqD9gb9Lqwnl5-GJdKA0txDhRUzve0qD1xO32q-k 3685
torch_timeseries/model/FEDformer.py sha256=NbhdeAA6Ry5hXBOdL9lv3v8_23R1GUh4CYWgXcwoelw 8127
torch_timeseries/model/Informer.py sha256=HYa0bZ-6r4mYQFWfR7qiGZi6tH92hZEHCrAPXOMLyyw 8378
torch_timeseries/model/PatchTST.py sha256=JaVy7JtSPfBoPBMYHS5k86dScX5y5Q-lSDtRYyisnTE 8553
torch_timeseries/model/__init__.py sha256=NDl9SD8t-ZYpblGAlBb-_9UjqnQmhyONLCb31ot54wA 197
torch_timeseries/model/iTransformer.py sha256=hE9-gVe-7u9qqa75TfrrzYTA-mfeMq8nLTmBGTfZaR8 3313
torch_timeseries/nn/AutoCorrelation.py sha256=TcrpbjSKTCJCixTHPJxzHCrIo5jHitjO4FYublbPS30 6904
torch_timeseries/nn/Autoformer_EncDec.py sha256=tKIFPqbCixgU3Wah5ht8Jf3GotCzoTdL8g9j8WC2RcU 7593
torch_timeseries/nn/FourierCorrelation.py sha256=F_hfNjHFioPdO_9BeCHi_vZR5o6GaDWUREGGyHA2tZY 5454
torch_timeseries/nn/MultiWaveletCorrelation.py sha256=dY3Qgwgf13gNsXeXDyp4TEW2zo8JRvU8d7kvo61a5mk 26865
torch_timeseries/nn/SelfAttention_Family.py sha256=gXOcRKLOQtUzFxy3sQ57ZOB1nw6u5MvPIQHUTiFd7_s 11705
torch_timeseries/nn/Transformer_EncDec.py sha256=mFwx9K4YewivqpZj3JYKQFRLLsM6tVOJzqs5MO3BzgI 4916
torch_timeseries/nn/__init__.py sha256=oG5gpVsqzrfZWESCmbCrd7RljHAve5aNfwYuxVHxMqA 805
torch_timeseries/nn/attention.py sha256=awDRkQIAmhUPlxmQM7x6j2ZiB2thfnEN5MFRM79auSA 8120
torch_timeseries/nn/decoder.py sha256=7C67gbqNVADAbLfbWuLZO7ld0Esq-8M7XO-ihK-5qd8 1772
torch_timeseries/nn/decomp.py sha256=vsdYp4-mfllsRBJ09AR_UHw_kai_TVwHzmmVY9QBcDI 1164
torch_timeseries/nn/embedding.py sha256=3INMOLqKu5y2aHgOcrwTd5UwLG65KRBtxI2ebnLBZWk 7447
torch_timeseries/nn/encoder.py sha256=v9cqFui_eys2vKtH0Zi4hYY-Sy6_pXB_YZwxB4vIdzc 3555
torch_timeseries/nn/kernels.py sha256=VFidfrMntNw7WdasbLtERxreftu_9AzgaOJpWYwYu9o 739
torch_timeseries/scaler/__init__.py sha256=dsj8II_NtjGkkO0g5zssbzvFT1UU1HdkaPJ0xjK43RQ 179
torch_timeseries/scaler/maxabs.py sha256=PJ_bPTvhMn4EzesylxwXOcE9OPMWaipHXWJN4JHB9NM 1154
torch_timeseries/scaler/standard.py sha256=B-J0SsyJt8tB3UPzvL_JQqml3SPRdzDpYFfOY-7M_j0 1459
torch_timeseries/utils/__init__.py sha256=bZZxbZ9sKqf69LOsaJpOP51TSMRW7eC1qOl0cK-4Vhg 105
torch_timeseries/utils/acc.py sha256=mLxu4idXVOEnziPF-bA9kfl2QisDdSzZhpwRi0cd3rw 395
torch_timeseries/utils/dataclass_ext.py sha256=gF20tTLB33r25KF2RGUgGXrH29FQ9uJFeaQ7cwFrzYA 299
torch_timeseries/utils/early_stop.py sha256=HGkXE8Dl8s9_qiGeQ9m3yLLLavmkYBwp1zugUGDyDqA 2662
torch_timeseries/utils/model_stats.py sha256=5lLdNdVq_h0hYxyVaUUmSZvnTFuTcR7UGvDZEGvVj-o 416
torch_timeseries/utils/parse_type.py sha256=QLDwtKZ2I89bPCTBS01DESCzCVcRjzNy7R3osX1f5Hs 324
torch_timeseries/utils/reproduce.py sha256=4SmnB2TIw3hYSkctJXCpRNFy63p0i6ybhgN_pgDPxz8 510
torch_timeseries/utils/timefeatures.py sha256=LBCWoYvSgt686W3vO8Z_m24wC8HnCDHEAenDJgKaLZA 5686
torch_timeseries-0.1.3.dist-info/LICENSE sha256=xx0jnfkXJvxRnG63LTGOxlggYnIysveWIZ6H3PNdCrQ 11357
torch_timeseries-0.1.3.dist-info/METADATA sha256=xOU9FFKzeRMRv2Js2AifbxDPl3KuuJPpNftFkH3JNNI 21813
torch_timeseries-0.1.3.dist-info/WHEEL sha256=cpQTJ5IWu9CdaPViMhC9YzF8gZuS5-vlfoFihTBC86A 91
torch_timeseries-0.1.3.dist-info/entry_points.txt sha256=47Ptce1yN_uQyQ7mHEEHakefQ5yENjrYupGrN6hxI0A 48
torch_timeseries-0.1.3.dist-info/top_level.txt sha256=jme6adCuaGuQ82aIKquaoowP4E9u8ikbtiVFgoBvdmI 17
torch_timeseries-0.1.3.dist-info/RECORD

top_level.txt

torch_timeseries

entry_points.txt

pytexp = torch_timeseries:exp