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Add xDeepONet family to experimental models #1576
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2c31414
Add xDeepONet family to experimental models
wdyab b95fae3
xdeeponet: address PR #1576 review feedback (Greptile)
wdyab 073af77
Merge branch 'main' into pr/xdeeponet
wdyab 6fc5b4e
Merge branch 'main' into pr/xdeeponet
wdyab 85076f6
xdeeponet: address second Greptile review (PR #1576)
wdyab 101663e
xdeeponet: address third Greptile review (PR #1576)
wdyab f998215
xdeeponet: close out silent-degradation combinations (PR #1576)
wdyab 3c01800
xdeeponet: fix _build_conv_encoder for "sin" activation (PR #1576)
wdyab a1531b7
xdeeponet: address review feedback on PR #1576
wdyab d7010db
xdeeponet: use Literal type aliases for enumerated string parameters
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,48 @@ | ||
| # SPDX-FileCopyrightText: Copyright (c) 2023 - 2026 NVIDIA CORPORATION & AFFILIATES. | ||
| # SPDX-FileCopyrightText: All rights reserved. | ||
| # SPDX-License-Identifier: Apache-2.0 | ||
| # | ||
| # 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. | ||
|
|
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| """xDeepONet — the extended DeepONet family. | ||
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| Config-driven assembly of eight DeepONet-based architectures sharing a | ||
| common branch/trunk/decoder pattern: | ||
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| - ``deeponet``, ``u_deeponet``, ``fourier_deeponet``, ``conv_deeponet``, | ||
| ``hybrid_deeponet`` — single-branch variants. | ||
| - ``mionet``, ``fourier_mionet`` — two-branch multi-input variants. | ||
| - ``tno`` — Temporal Neural Operator (branch2 = previous solution). | ||
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| Both 2D and 3D spatial versions are provided. :class:`DeepONetWrapper` and | ||
| :class:`DeepONet3DWrapper` are the recommended entry points; see their class | ||
| docstrings for usage examples and the branch/trunk configuration schema. | ||
| """ | ||
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| from .branches import MLPBranch, SpatialBranch, SpatialBranch3D, TrunkNet | ||
| from .deeponet import DeepONet, DeepONet3D | ||
| from .wrappers import DeepONet3DWrapper, DeepONetWrapper | ||
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| __all__ = [ | ||
| # Core architectures | ||
| "DeepONet", | ||
| "DeepONet3D", | ||
| # Convenience wrappers (recommended entry points) | ||
| "DeepONetWrapper", | ||
| "DeepONet3DWrapper", | ||
| # Building blocks | ||
| "TrunkNet", | ||
| "MLPBranch", | ||
| "SpatialBranch", | ||
| "SpatialBranch3D", | ||
| ] | ||
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This should export 2 symbols:
DeepONet(unified 2D/3D, with wrapper functionality folded in) andSpatialBranch(unified 2D/3D).TrunkNetandMLPBranchduplicateFullyConnectedand should not be public.DeepONet3D,DeepONet3DWrapper,SpatialBranch3Dshould be unified with their 2D counterparts via adimensionparameter, following theFNOpattern.There was a problem hiding this comment.
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See later comment, but actually I think we can eliminate the Wrapper classes by folding those into DeepONet too