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Propagate sparsity metadata from sparse tensors of torch.sparse into the traced graph representation (with would be useful for a JIT backend that supports a "sparse compiler"). This is a first careful attempt, since the actual "meta" feature seem still incomplete for coo and completely lacking for csr/csc/bsr/bsc. For background see forum postings (with examples): https://discuss.pytorch.org/t/connecting-pytorch-sparse-tensors-with-mlir/195145 https://dev-discuss.pytorch.org/t/connecting-pytorch-sparse-tensors-with-mlir/1803 And feature request: https://github.com/pytorch/pytorch/issues/117188 Pull Request resolved: https://github.com/pytorch/pytorch/pull/117907 Approved by: https://github.com/pearu, https://github.com/ezyang |
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| .. | ||
| __init__.py | ||
| opinfo_schema.py | ||
| test_converter.py | ||
| test_db.py | ||
| test_experimental.py | ||
| test_export.py | ||
| test_export_nonstrict.py | ||
| test_functionalized_assertions.py | ||
| test_hop.py | ||
| test_lift_unlift.py | ||
| test_pass_infra.py | ||
| test_passes.py | ||
| test_retraceability.py | ||
| test_schema.py | ||
| test_serdes.py | ||
| test_serialize.py | ||
| test_sparse.py | ||
| test_tools.py | ||
| test_torchbind.py | ||
| test_tree_utils.py | ||
| test_unflatten.py | ||
| test_verifier.py | ||
| testing.py | ||