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Tensors and Dynamic neural networks in Python with strong GPU acceleration

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This is an automated pull request to update the first-party submodule for [pytorch/FBGEMM](https://github.com/pytorch/FBGEMM). New submodule commit: https://github.com/pytorch/FBGEMM/commit/f99e1616630e3b78e3bccd0ceb9e50e8e82409f1 Test Plan: Ensure that CI jobs succeed on GitHub before landing.

triaged
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Summary: Check that fastpath is taken, which type (sparsity fastpath or normal) for mask that is aligned and one that is not. Test Plan: buck test caffe2/test:test_transformers Differential Revision: D38259928

fb-exported
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with-ssh

Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom): * __->__ #83136 Changes: - Move namespace handling from `_new_node` to `_graph_op` for clarity - Always require the `aten` namespace when creating aten ops....

module: onnx
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## Summary To better enable users to write triton kernels on nested nested tensors having empty_like support is helpful. This will be used to create a nested_tensor output buffer to...

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Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom): * __->__ #81930 land after #83122 This PR explores solutions for 2 issues: 1. Collective comm ops are inplace ops, and does not return...

oncall: distributed
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fx

Summary: add 3 operators ops (max_pool2d, linear, conv2d) test functions in xnnPack test Test Plan: buck test //xplat/caffe2:pt_xnnpack_test Reviewed By: kirklandsign Differential Revision: D38548757

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Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom): * __->__ #83134

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fx

Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom): * __->__ #82841 * #82839 * #82837 * #82836

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Stack from [ghstack](https://github.com/ezyang/ghstack) (oldest at bottom): * #82841 * #82839 * __->__ #82837 * #82836

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Fixes #82899 TODO: - [ ] python test for the breakage.

oncall: jit
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