chore: import upstream snapshot with attribution
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# Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from . import (
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loss, # noqa: F401
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utils, # noqa: F401
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)
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from .module import Module # noqa: F401
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# Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from paddle.nn import LayerDict, LayerList
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ModuleList = LayerList
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ModuleDict = LayerDict
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# Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from paddle.nn.layer.loss import ( # noqa: F401
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BCELoss,
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BCEWithLogitsLoss,
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CosineEmbeddingLoss,
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CrossEntropyLoss,
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CTCLoss,
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GaussianNLLLoss,
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HingeEmbeddingLoss,
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KLDivLoss,
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L1Loss,
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MarginRankingLoss,
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MSELoss,
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MultiLabelMarginLoss,
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MultiLabelSoftMarginLoss,
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MultiMarginLoss,
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NLLLoss,
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PoissonNLLLoss,
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SmoothL1Loss,
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SoftMarginLoss,
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TripletMarginLoss,
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TripletMarginWithDistanceLoss,
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_Loss,
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)
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@@ -0,0 +1,18 @@
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# Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from paddle.nn import Layer
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Module = Layer
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@@ -0,0 +1,34 @@
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# Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from __future__ import annotations
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import collections
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from itertools import repeat
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def _ntuple(n, name="parse"):
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def parse(x):
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if isinstance(x, collections.abc.Iterable):
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return tuple(x)
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return tuple(repeat(x, n))
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parse.__name__ = name
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return parse
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_single = _ntuple(1, "_single")
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_pair = _ntuple(2, "_pair")
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_triple = _ntuple(3, "_triple")
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_quadruple = _ntuple(4, "_quadruple")
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