[ET-VK][Ops] aten.embedding #3762
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## The Operator `nn.Module` invocations on the embedding returned by [`torch.nn.Embedding`](https://pytorch.org/docs/stable/generated/torch.nn.Embedding.html) get compiled to `aten.embedding.default` in the Edge Dialect, which carries the following signature. ``` - func: embedding(Tensor weight, Tensor indices, SymInt padding_idx=-1, bool scale_grad_by_freq=False, bool sparse=False) -> Tensor ``` ## Implementation This is a C-packing-only implementation. Interestingly, the 1D-`indices` case is equivalent to the `dim=0` case of the preceding `aten.index_select`: #3744 ``` - func: index_select(Tensor self, int dim, Tensor index) -> Tensor ``` I naïvely thought the rest of the operator would be similarly easy but it wasn't. The 2D and 3D-`indices` cases are more involved to the extent that we require a standalone `cpp`/`glsl` file. ## Codegen We add support for making 2D and 3D index tensors. This requires new generation functions as well as renaming of the `case_name` string to recursively handle list `pylist`s. ``` // 1D Test(weight=[10, 9], indices=[0, 2]), // 2D Test(weight=[10, 9], indices=[[0, 2], [1, 4], [7, 7]]), // 3D Test(weight=[10, 9], indices=[[[3, 1, 4], [1, 5, 9]], [[2, 6, 5], [3, 5, 8]]]), ``` Differential Revision: [D57880520](https://our.internmc.facebook.com/intern/diff/D57880520/) [ghstack-poisoned]
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## The Operator `nn.Module` invocations on the embedding returned by [`torch.nn.Embedding`](https://pytorch.org/docs/stable/generated/torch.nn.Embedding.html) get compiled to `aten.embedding.default` in the Edge Dialect, which carries the following signature. ``` - func: embedding(Tensor weight, Tensor indices, SymInt padding_idx=-1, bool scale_grad_by_freq=False, bool sparse=False) -> Tensor ``` ## Implementation This is a C-packing-only implementation. Interestingly, the 1D-`indices` case is equivalent to the `dim=0` case of the preceding `aten.index_select`: #3744 ``` - func: index_select(Tensor self, int dim, Tensor index) -> Tensor ``` I naïvely thought the rest of the operator would be similarly easy but it wasn't. The 2D and 3D-`indices` cases are more involved to the extent that we require a standalone `cpp`/`glsl` file. ## Codegen We add support for making 2D and 3D index tensors. This requires new generation functions as well as renaming of the `case_name` string to recursively handle list `pylist`s. ``` // 1D Test(weight=[10, 9], indices=[0, 2]), // 2D Test(weight=[10, 9], indices=[[0, 2], [1, 4], [7, 7]]), // 3D Test(weight=[10, 9], indices=[[[3, 1, 4], [1, 5, 9]], [[2, 6, 5], [3, 5, 8]]]), ``` Differential Revision: [D57880520](https://our.internmc.facebook.com/intern/diff/D57880520/) ghstack-source-id: 228038402 Pull Request resolved: #3762
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May 29, 2024
## The Operator `nn.Module` invocations on the embedding returned by [`torch.nn.Embedding`](https://pytorch.org/docs/stable/generated/torch.nn.Embedding.html) get compiled to `aten.embedding.default` in the Edge Dialect, which carries the following signature. ``` - func: embedding(Tensor weight, Tensor indices, SymInt padding_idx=-1, bool scale_grad_by_freq=False, bool sparse=False) -> Tensor ``` ## Implementation This is a C-packing-only implementation. Interestingly, the 1D-`indices` case is equivalent to the `dim=0` case of the preceding `aten.index_select`: #3744 ``` - func: index_select(Tensor self, int dim, Tensor index) -> Tensor ``` I naïvely thought the rest of the operator would be similarly easy but it wasn't. The 2D and 3D-`indices` cases are more involved to the extent that we require a standalone `cpp`/`glsl` file. ## Codegen We add support for making 2D and 3D index tensors. This requires new generation functions as well as renaming of the `case_name` string to recursively handle list `pylist`s. ``` // 1D Test(weight=[10, 9], indices=[0, 2]), // 2D Test(weight=[10, 9], indices=[[0, 2], [1, 4], [7, 7]]), // 3D Test(weight=[10, 9], indices=[[[3, 1, 4], [1, 5, 9]], [[2, 6, 5], [3, 5, 8]]]), ``` Differential Revision: [D57880520](https://our.internmc.facebook.com/intern/diff/D57880520/) [ghstack-poisoned]
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This pull request was exported from Phabricator. Differential Revision: D57880520 |
## The Operator `nn.Module` invocations on the embedding returned by [`torch.nn.Embedding`](https://pytorch.org/docs/stable/generated/torch.nn.Embedding.html) get compiled to `aten.embedding.default` in the Edge Dialect, which carries the following signature. ``` - func: embedding(Tensor weight, Tensor indices, SymInt padding_idx=-1, bool scale_grad_by_freq=False, bool sparse=False) -> Tensor ``` ## Implementation This is a C-packing-only implementation. Interestingly, the 1D-`indices` case is equivalent to the `dim=0` case of the preceding `aten.index_select`: #3744 ``` - func: index_select(Tensor self, int dim, Tensor index) -> Tensor ``` I naïvely thought the rest of the operator would be similarly easy but it wasn't. The 2D and 3D-`indices` cases are more involved to the extent that we require a standalone `cpp`/`glsl` file. ## Codegen We add support for making 2D and 3D index tensors. This requires new generation functions as well as renaming of the `case_name` string to recursively handle list `pylist`s. ``` // 1D Test(weight=[10, 9], indices=[0, 2]), // 2D Test(weight=[10, 9], indices=[[0, 2], [1, 4], [7, 7]]), // 3D Test(weight=[10, 9], indices=[[[3, 1, 4], [1, 5, 9]], [[2, 6, 5], [3, 5, 8]]]), ``` Differential Revision: [D57880520](https://our.internmc.facebook.com/intern/diff/D57880520/) [ghstack-poisoned]
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This pull request was exported from Phabricator. Differential Revision: D57880520 |
## The Operator `nn.Module` invocations on the embedding returned by [`torch.nn.Embedding`](https://pytorch.org/docs/stable/generated/torch.nn.Embedding.html) get compiled to `aten.embedding.default` in the Edge Dialect, which carries the following signature. ``` - func: embedding(Tensor weight, Tensor indices, SymInt padding_idx=-1, bool scale_grad_by_freq=False, bool sparse=False) -> Tensor ``` ## Implementation This is a C-packing-only implementation. Interestingly, the 1D-`indices` case is equivalent to the `dim=0` case of the preceding `aten.index_select`: #3744 ``` - func: index_select(Tensor self, int dim, Tensor index) -> Tensor ``` I naïvely thought the rest of the operator would be similarly easy but it wasn't. The 2D and 3D-`indices` cases are more involved to the extent that we require a standalone `cpp`/`glsl` file. ## Codegen We add support for making 2D and 3D index tensors. This requires new generation functions as well as renaming of the `case_name` string to recursively handle list `pylist`s. ``` // 1D Test(weight=[10, 9], indices=[0, 2]), // 2D Test(weight=[10, 9], indices=[[0, 2], [1, 4], [7, 7]]), // 3D Test(weight=[10, 9], indices=[[[3, 1, 4], [1, 5, 9]], [[2, 6, 5], [3, 5, 8]]]), ``` Differential Revision: [D57880520](https://our.internmc.facebook.com/intern/diff/D57880520/) [ghstack-poisoned]
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This pull request was exported from Phabricator. Differential Revision: D57880520 |
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This pull request has been merged in a36ace7. |
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Jun 25, 2025
Pull Request resolved: pytorch/executorch#3762 ## The Operator `nn.Module` invocations on the embedding returned by [`torch.nn.Embedding`](https://pytorch.org/docs/stable/generated/torch.nn.Embedding.html) get compiled to `aten.embedding.default` in the Edge Dialect, which carries the following signature. ``` - func: embedding(Tensor weight, Tensor indices, SymInt padding_idx=-1, bool scale_grad_by_freq=False, bool sparse=False) -> Tensor ``` ## Implementation This is a C-packing-only implementation. Interestingly, the 1D-`indices` case is equivalent to the `dim=0` case of the preceding `aten.index_select`: pytorch/executorch#3744 ``` - func: index_select(Tensor self, int dim, Tensor index) -> Tensor ``` I naïvely thought the rest of the operator would be similarly easy but it wasn't. The 2D and 3D-`indices` cases are more involved to the extent that we require a standalone `cpp`/`glsl` file. ## Codegen We add support for making 2D and 3D index tensors. This requires new generation functions as well as renaming of the `case_name` string to recursively handle list `pylist`s. ``` // 1D Test(weight=[10, 9], indices=[0, 2]), // 2D Test(weight=[10, 9], indices=[[0, 2], [1, 4], [7, 7]]), // 3D Test(weight=[10, 9], indices=[[[3, 1, 4], [1, 5, 9]], [[2, 6, 5], [3, 5, 8]]]), ``` ghstack-source-id: 228201965 Differential Revision: [D57880520](https://our.internmc.facebook.com/intern/diff/D57880520/)
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Stack from ghstack (oldest at bottom):
The Operator
nn.Moduleinvocations on the embedding returned bytorch.nn.Embeddingget compiled toaten.embedding.defaultin the Edge Dialect, which carries the following signature.Implementation
This is a C-packing-only implementation.
Interestingly, the 1D-
indicescase is equivalent to thedim=0case of the precedingaten.index_select: #3744I naïvely thought the rest of the operator would be similarly easy but it wasn't. The 2D and 3D-
indicescases are more involved to the extent that we require a standalonecpp/glslfile.Codegen
We add support for making 2D and 3D index tensors. This requires new generation functions as well as renaming of the
case_namestring to recursively handle listpylists.Differential Revision: D57880520